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Seize the opportunity to present your research, innovative ideas, and clinical stories to a national audience at HM16. Visit the submission site for full details. To ensure success, SHM strongly recommends that you complete your submission well ahead of the deadline of Wednesday, Dec. 1, 2015, at 11:30 p.m. EST. For details, visit www.hospitalmedicine2016.org.

Seize the opportunity to present your research, innovative ideas, and clinical stories to a national audience at HM16. Visit the submission site for full details. To ensure success, SHM strongly recommends that you complete your submission well ahead of the deadline of Wednesday, Dec. 1, 2015, at 11:30 p.m. EST. For details, visit www.hospitalmedicine2016.org.

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Lupus and diffuse large B-cell lymphoma share genetic risk

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SAN FRANCISCO – Single-nucleotide polymorphisms in genes for interleukin 10 and human leukocyte antigen are significantly associated with both systemic lupus erythematosus (SLE) and diffuse large B-cell lymphoma, according to a meta-analysis of data from three genome-wide association studies.

The findings add to existing data that exonerates immunosuppressive medications as the main causes of lymphoma in patients with SLE, said lead investigator Dr. Sasha Bernatsky of McGill University, Montreal, in an interview. “People with lupus may have a slight increase in risk for lymphoma because of genetic factors, which would be reassuring,” she said. “It may even mean that if you take your baseline risk of lupus and you control the inflammation, perhaps you can modify that small increase in risk of lymphoma and make it more like the risk in the general population.”

 

Amy Karon/Frontline Medical News
Dr. Sasha Bernatsky

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, with an incidence of about one case in 3,000 person-years in the general population and about one case in 1,000 person-years in patients with SLE, Dr. Bernatsky noted. To look for shared genetic risk factors for both diseases, she and her colleagues analyzed pooled data from three genome-wide association studies conducted by the International Lymphoma Epidemiology Consortium. Using data from 3,857 patients with DLBCL and 7,666 controls, the investigators calculated the odds of DLBCL for each of 28 SNPs that are known genetic risk variants for SLE. “If there’s an overlap there, that might be the key,” Dr. Bernatsky said at the annual meeting of the American College of Rheumatology.

In fact, two SLE-related SNPs were clearly linked to an increased risk for DLBCL – rs3024505, a variant allele of the gene for interleukin 10 on chromosome 1 (odds ratio, 1.14; 95% confidence interval, 1.05-1.23; P = .001), and rs1270942, a variant of the gene for human leukocyte antigen on chromosome 6 (OR, 1.2; 95% CI, 1.08-1.33; P = .0007). Both SNPs seem plausible – interleukin 10 induces the bcl-2 protein, which prevents the spontaneous death of germinal center B cells, and some evidence has linked HLA polymorphisms to DLBCL, Dr. Bernatsky said.

The study also linked two other SLE-related SNPs to increased risk for DLBCL, although the associations were not as strong. The first was rs4810485 on the CD40 gene (OR, 1.09; 95% CI, 1.02-1.16; P = .013), and the second was rs2205960 on the TNFSF4 gene, which encodes a cytokine from the tumor necrosis factor–superfamily (OR, 1.08; 95% CI, 1.02-1.15; P = .044). “These findings kind of make sense, because tumor necrosis factor is a very important inflammatory cytokine, and CD40 is a lymphocyte marker,” Dr. Bernatsky said. “It is possible that some genetic factor that controls their expression or function might be associated with lymphoma.”

Rheumatologists have long debated why patients with lupus are at increased risk for lymphoma, and have repeatedly asked whether immunomodulatory drugs are to blame. “We can exercise some caution, but still be aware that most people who use these drugs never end up developing cancer,” Dr. Bernatsky emphasized. In past studies, the absolute risk of lymphoma in patients with SLE remained below 1%, and those patients who did develop lymphoma often had never received drugs such as azathioprine, she noted. The exception was cyclophosphamide, which caused various severe adverse effects, including blood cancers (Ann Rheum Dis. 2013 Jan 8. doi: 10.1136/annrheumdis-2012-202099). “Although we need to use cyclophosphamide for very severe cases of autoimmune disease, it’s clearly a drug that we should use almost as a last resort,” she said.

The study was funded by the Canadian Institutes for Health Research; the Fonds du recherche du Québec; Santé, the Research Institute of the McGill University Health Centre; and the Singer Family Fund for Lupus Research. Dr. Bernatsky and her coinvestigators had no disclosures.

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SAN FRANCISCO – Single-nucleotide polymorphisms in genes for interleukin 10 and human leukocyte antigen are significantly associated with both systemic lupus erythematosus (SLE) and diffuse large B-cell lymphoma, according to a meta-analysis of data from three genome-wide association studies.

The findings add to existing data that exonerates immunosuppressive medications as the main causes of lymphoma in patients with SLE, said lead investigator Dr. Sasha Bernatsky of McGill University, Montreal, in an interview. “People with lupus may have a slight increase in risk for lymphoma because of genetic factors, which would be reassuring,” she said. “It may even mean that if you take your baseline risk of lupus and you control the inflammation, perhaps you can modify that small increase in risk of lymphoma and make it more like the risk in the general population.”

 

Amy Karon/Frontline Medical News
Dr. Sasha Bernatsky

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, with an incidence of about one case in 3,000 person-years in the general population and about one case in 1,000 person-years in patients with SLE, Dr. Bernatsky noted. To look for shared genetic risk factors for both diseases, she and her colleagues analyzed pooled data from three genome-wide association studies conducted by the International Lymphoma Epidemiology Consortium. Using data from 3,857 patients with DLBCL and 7,666 controls, the investigators calculated the odds of DLBCL for each of 28 SNPs that are known genetic risk variants for SLE. “If there’s an overlap there, that might be the key,” Dr. Bernatsky said at the annual meeting of the American College of Rheumatology.

In fact, two SLE-related SNPs were clearly linked to an increased risk for DLBCL – rs3024505, a variant allele of the gene for interleukin 10 on chromosome 1 (odds ratio, 1.14; 95% confidence interval, 1.05-1.23; P = .001), and rs1270942, a variant of the gene for human leukocyte antigen on chromosome 6 (OR, 1.2; 95% CI, 1.08-1.33; P = .0007). Both SNPs seem plausible – interleukin 10 induces the bcl-2 protein, which prevents the spontaneous death of germinal center B cells, and some evidence has linked HLA polymorphisms to DLBCL, Dr. Bernatsky said.

The study also linked two other SLE-related SNPs to increased risk for DLBCL, although the associations were not as strong. The first was rs4810485 on the CD40 gene (OR, 1.09; 95% CI, 1.02-1.16; P = .013), and the second was rs2205960 on the TNFSF4 gene, which encodes a cytokine from the tumor necrosis factor–superfamily (OR, 1.08; 95% CI, 1.02-1.15; P = .044). “These findings kind of make sense, because tumor necrosis factor is a very important inflammatory cytokine, and CD40 is a lymphocyte marker,” Dr. Bernatsky said. “It is possible that some genetic factor that controls their expression or function might be associated with lymphoma.”

Rheumatologists have long debated why patients with lupus are at increased risk for lymphoma, and have repeatedly asked whether immunomodulatory drugs are to blame. “We can exercise some caution, but still be aware that most people who use these drugs never end up developing cancer,” Dr. Bernatsky emphasized. In past studies, the absolute risk of lymphoma in patients with SLE remained below 1%, and those patients who did develop lymphoma often had never received drugs such as azathioprine, she noted. The exception was cyclophosphamide, which caused various severe adverse effects, including blood cancers (Ann Rheum Dis. 2013 Jan 8. doi: 10.1136/annrheumdis-2012-202099). “Although we need to use cyclophosphamide for very severe cases of autoimmune disease, it’s clearly a drug that we should use almost as a last resort,” she said.

The study was funded by the Canadian Institutes for Health Research; the Fonds du recherche du Québec; Santé, the Research Institute of the McGill University Health Centre; and the Singer Family Fund for Lupus Research. Dr. Bernatsky and her coinvestigators had no disclosures.

SAN FRANCISCO – Single-nucleotide polymorphisms in genes for interleukin 10 and human leukocyte antigen are significantly associated with both systemic lupus erythematosus (SLE) and diffuse large B-cell lymphoma, according to a meta-analysis of data from three genome-wide association studies.

The findings add to existing data that exonerates immunosuppressive medications as the main causes of lymphoma in patients with SLE, said lead investigator Dr. Sasha Bernatsky of McGill University, Montreal, in an interview. “People with lupus may have a slight increase in risk for lymphoma because of genetic factors, which would be reassuring,” she said. “It may even mean that if you take your baseline risk of lupus and you control the inflammation, perhaps you can modify that small increase in risk of lymphoma and make it more like the risk in the general population.”

 

Amy Karon/Frontline Medical News
Dr. Sasha Bernatsky

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, with an incidence of about one case in 3,000 person-years in the general population and about one case in 1,000 person-years in patients with SLE, Dr. Bernatsky noted. To look for shared genetic risk factors for both diseases, she and her colleagues analyzed pooled data from three genome-wide association studies conducted by the International Lymphoma Epidemiology Consortium. Using data from 3,857 patients with DLBCL and 7,666 controls, the investigators calculated the odds of DLBCL for each of 28 SNPs that are known genetic risk variants for SLE. “If there’s an overlap there, that might be the key,” Dr. Bernatsky said at the annual meeting of the American College of Rheumatology.

In fact, two SLE-related SNPs were clearly linked to an increased risk for DLBCL – rs3024505, a variant allele of the gene for interleukin 10 on chromosome 1 (odds ratio, 1.14; 95% confidence interval, 1.05-1.23; P = .001), and rs1270942, a variant of the gene for human leukocyte antigen on chromosome 6 (OR, 1.2; 95% CI, 1.08-1.33; P = .0007). Both SNPs seem plausible – interleukin 10 induces the bcl-2 protein, which prevents the spontaneous death of germinal center B cells, and some evidence has linked HLA polymorphisms to DLBCL, Dr. Bernatsky said.

The study also linked two other SLE-related SNPs to increased risk for DLBCL, although the associations were not as strong. The first was rs4810485 on the CD40 gene (OR, 1.09; 95% CI, 1.02-1.16; P = .013), and the second was rs2205960 on the TNFSF4 gene, which encodes a cytokine from the tumor necrosis factor–superfamily (OR, 1.08; 95% CI, 1.02-1.15; P = .044). “These findings kind of make sense, because tumor necrosis factor is a very important inflammatory cytokine, and CD40 is a lymphocyte marker,” Dr. Bernatsky said. “It is possible that some genetic factor that controls their expression or function might be associated with lymphoma.”

Rheumatologists have long debated why patients with lupus are at increased risk for lymphoma, and have repeatedly asked whether immunomodulatory drugs are to blame. “We can exercise some caution, but still be aware that most people who use these drugs never end up developing cancer,” Dr. Bernatsky emphasized. In past studies, the absolute risk of lymphoma in patients with SLE remained below 1%, and those patients who did develop lymphoma often had never received drugs such as azathioprine, she noted. The exception was cyclophosphamide, which caused various severe adverse effects, including blood cancers (Ann Rheum Dis. 2013 Jan 8. doi: 10.1136/annrheumdis-2012-202099). “Although we need to use cyclophosphamide for very severe cases of autoimmune disease, it’s clearly a drug that we should use almost as a last resort,” she said.

The study was funded by the Canadian Institutes for Health Research; the Fonds du recherche du Québec; Santé, the Research Institute of the McGill University Health Centre; and the Singer Family Fund for Lupus Research. Dr. Bernatsky and her coinvestigators had no disclosures.

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Key clinical point: Two genetic risk variants for systemic lupus erythematosus also were clearly linked to risk of diffuse large B-cell lymphoma.

Major finding: The single-nucleotide polymorphisms were rs3024505 on chromosome 1 (OR, 1.14; P = .001), and rs1270942 on chromosome 6 (OR, 1.2; P = .0007).

Data source: A fixed-effect meta-analysis of 28 SLE-related SNPs from 3,857 patients with diffuse large B-cell lymphoma and 7,666 controls.

Disclosures: The study was funded by the Canadian Institutes for Health Research; the Fonds du recherche du Québec; Santé, the Research Institute of the McGill University Health Centre; and the Singer Family Fund for Lupus Research. Dr. Bernatsky and her coinvestigators had no disclosures.

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Sessile Pink Plaque on the Lower Back

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Sessile Pink Plaque on the Lower Back

The Diagnosis: Eccrine Poroma

A shave biopsy of the lesion was performed for definitive diagnosis and demonstrated a well-circumscribed tumor with cords and broad columns composed of uniform basaloid cells extending into the dermis and in areas connecting to the overlying epidermis (Figure). There also were small ducts and cysts admixed in the tumor columns that were embedded in a tumor stroma rich in blood vessels. A diagnosis of eccrine poroma was made based on these characteristic histologic features.

 


 

Biopsy revealed a basaloid tumor originating from the epidermis and extending into the dermis (A)(H&E, original magnification ×4). On higher magnification, ducts were evident amongst the tumor cells and a vascular rich stroma was revealed (B)(H&E, original magnification ×10).

First described by Pinkus et al1 in 1956, eccrine poroma is a benign neoplasm of cells from the intraepidermal ductal portion of the eccrine sweat gland. Eccrine poroma (along with hidroacanthoma simplex, dermal duct tumor, and poroid hidradenoma) is one of the poroid neoplasms, which account for approximately 10% of all primary sweat gland tumors.2 Eccrine poroma usually is seen in patients over 40 years of age without any predilection for race or sex.

Characteristically, eccrine poromas clinically manifest as solitary, firm, sharply demarcated papules or nodules that may be sessile or pedunculated and rarely exceed 2 cm in diameter. This entity classically presents on acral, non–hair-bearing areas (eg, palms and soles). Eccrine poromas have a wide range of clinical appearances that can lead to broad differential diagnoses3 and have been described as flesh-colored,3 pink to red,4 purple,5 and pigmented3,4 papules or nodules depending on features such as blood vessel proliferation and pigment deposition.

Eccrine poromas also have been reported on hair-bearing areas of the body, including the head,3 neck,3,6 chest,4,6 hip,7 and pubic area,8 despite the paucity of eccrine glands in these areas on the body. These findings suggest that these neoplasms may not be purely eccrine in origin. The wide range of clinical presentations of eccrine poromas has prompted investigation into further classification and delineation of this neoplasm.3 The occurrence of eccrine poromas on areas of the skin known to have few eccrine glands suggests that eccrine poromas may not be purely comprised of eccrine ducts and instead may be of apocrine origin.3,9,10 Histologic features of eccrine poromas that suggest apocrine origination include sebaceous and follicular differentiation (eg, folliculocentric distribution), the association with the follicular infundibulum, and the presence of follicular germ cells.3,9,10 Thus, apocrine gland involvement in eccrine poromas may account for their appearance in anatomic areas that do not have high concentrations of eccrine glands, such as the trunk and pubic area.

Based on these findings, eccrine poromas may therefore be of eccrine and/or apocrine origin; however, the nomenclature of this neoplasm remains confusing and possibly misleading, as the term eccrine poroma continues to be accepted even in instances in which the differentiation appears to be largely apocrine. The terms poroma and eccrine poroma often are used interchangeably, which contributes to the confusion by failing to acknowledge the possibility of apocrine influence and possibly causing the clinician to exclude eccrine poromas from the differential diagnosis in areas that do not have high concentrations of eccrine glands.

Because of their high degree of clinical variability, characteristic acral location, and misleading nomenclature, eccrine poromas often are mistakenly confused with a long list of other cutaneous neoplasms, including hemangiomas, pyogenic granulomas, melanocytic nevi, warts, cysts, and other adnexal neoplasms.3 In our case, the lesion was abnormally large and was clinically concerning for an unusual sebaceous nevus. Its location on the lower back is not commonly noted and should remind the clinician of the possibility of apocrine differentiation. Clinicians should be aware of the wide phenotypic diversity of eccrine poromas, and therefore they should consider this diagnosis in their differential diagnosis for solitary papules or nodules occurring in any anatomic area.

References
  1. Pinkus H, Rogin JR, Goldman P. Eccrine poroma: tumors exhibiting features of the epidermal sweat duct unit. Arch Dermatol. 1956;74:511-521.
  2. Pylyser K, Dewolf-Peeters C, Marlen K. The histology of eccrine poromas: a study of 14 cases. Dermatologica. 1983;167:243-249.
  3. Moore TO, Orman HL, Orman SK, et al. Poromas of the head and neck. J Am Acad Dermatol. 2001;44:48-52.
  4. Agarwal S, Kumar B, Sharma N. Nodule on the chest. eccrine poroma. Indian J Dermatol Venereol Leprol. 2009;75:639.
  5. Ackerman AB, Abenoza P. Neoplasms With Eccrine Differentiation. Philadelphia, PA: Lea & Febinger; 1990:113-185.
  6. Okun M, Ansell H. Eccrine poroma. report of three cases, two with an unusual location. Arch Dermatol. 1963;88:561-566.
  7. Sarma DP, Zaman SU, Santos EE, et al. Poroma of the hip and buttock. Dermatol Online J. 2009;15:10.
  8. Altamura D, Piccolo D, Lozzi GP, et al. Eccrine poroma in an unusual site: a clinical and dermoscopic simulator of amelanotic melanoma. J Am Acad Dermatol. 2005;53:539-541.
  9. Groben PA, Hitchcock MG, Leshin B, et al. Apocrine poroma, a distinctive case in a patient with nevoid BCC. Am J Dermatopathol. 1992;21:31-33.
  10. Harvell JD, Kerschmann RL, LeBoit PE. Eccrine or apocrine poroma? six poromas with divergent adnexal differentiation. Am J Dermatopathol. 1996;18:1-9.
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Dr. Marszalek is from Harvard Vanguard Medical Associates, Boston, Massachusetts. Dr. Aung is from the Departments of Pathology and Dermatology, University of Texas MD Anderson Cancer Center, Houston. Dr. Wolpowitz is from Boston Medical Center. Dr. Chen is from the Department of Dermatology, University of Connecticut School of Medicine, Canton.

The authors report no conflict of interest.

Correspondence: Amy Yuntzu-Yen Chen, MD, 117 Albany Turnpike, Canton, CT 06019 ([email protected]).

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Dr. Marszalek is from Harvard Vanguard Medical Associates, Boston, Massachusetts. Dr. Aung is from the Departments of Pathology and Dermatology, University of Texas MD Anderson Cancer Center, Houston. Dr. Wolpowitz is from Boston Medical Center. Dr. Chen is from the Department of Dermatology, University of Connecticut School of Medicine, Canton.

The authors report no conflict of interest.

Correspondence: Amy Yuntzu-Yen Chen, MD, 117 Albany Turnpike, Canton, CT 06019 ([email protected]).

Author and Disclosure Information

Dr. Marszalek is from Harvard Vanguard Medical Associates, Boston, Massachusetts. Dr. Aung is from the Departments of Pathology and Dermatology, University of Texas MD Anderson Cancer Center, Houston. Dr. Wolpowitz is from Boston Medical Center. Dr. Chen is from the Department of Dermatology, University of Connecticut School of Medicine, Canton.

The authors report no conflict of interest.

Correspondence: Amy Yuntzu-Yen Chen, MD, 117 Albany Turnpike, Canton, CT 06019 ([email protected]).

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The Diagnosis: Eccrine Poroma

A shave biopsy of the lesion was performed for definitive diagnosis and demonstrated a well-circumscribed tumor with cords and broad columns composed of uniform basaloid cells extending into the dermis and in areas connecting to the overlying epidermis (Figure). There also were small ducts and cysts admixed in the tumor columns that were embedded in a tumor stroma rich in blood vessels. A diagnosis of eccrine poroma was made based on these characteristic histologic features.

 


 

Biopsy revealed a basaloid tumor originating from the epidermis and extending into the dermis (A)(H&E, original magnification ×4). On higher magnification, ducts were evident amongst the tumor cells and a vascular rich stroma was revealed (B)(H&E, original magnification ×10).

First described by Pinkus et al1 in 1956, eccrine poroma is a benign neoplasm of cells from the intraepidermal ductal portion of the eccrine sweat gland. Eccrine poroma (along with hidroacanthoma simplex, dermal duct tumor, and poroid hidradenoma) is one of the poroid neoplasms, which account for approximately 10% of all primary sweat gland tumors.2 Eccrine poroma usually is seen in patients over 40 years of age without any predilection for race or sex.

Characteristically, eccrine poromas clinically manifest as solitary, firm, sharply demarcated papules or nodules that may be sessile or pedunculated and rarely exceed 2 cm in diameter. This entity classically presents on acral, non–hair-bearing areas (eg, palms and soles). Eccrine poromas have a wide range of clinical appearances that can lead to broad differential diagnoses3 and have been described as flesh-colored,3 pink to red,4 purple,5 and pigmented3,4 papules or nodules depending on features such as blood vessel proliferation and pigment deposition.

Eccrine poromas also have been reported on hair-bearing areas of the body, including the head,3 neck,3,6 chest,4,6 hip,7 and pubic area,8 despite the paucity of eccrine glands in these areas on the body. These findings suggest that these neoplasms may not be purely eccrine in origin. The wide range of clinical presentations of eccrine poromas has prompted investigation into further classification and delineation of this neoplasm.3 The occurrence of eccrine poromas on areas of the skin known to have few eccrine glands suggests that eccrine poromas may not be purely comprised of eccrine ducts and instead may be of apocrine origin.3,9,10 Histologic features of eccrine poromas that suggest apocrine origination include sebaceous and follicular differentiation (eg, folliculocentric distribution), the association with the follicular infundibulum, and the presence of follicular germ cells.3,9,10 Thus, apocrine gland involvement in eccrine poromas may account for their appearance in anatomic areas that do not have high concentrations of eccrine glands, such as the trunk and pubic area.

Based on these findings, eccrine poromas may therefore be of eccrine and/or apocrine origin; however, the nomenclature of this neoplasm remains confusing and possibly misleading, as the term eccrine poroma continues to be accepted even in instances in which the differentiation appears to be largely apocrine. The terms poroma and eccrine poroma often are used interchangeably, which contributes to the confusion by failing to acknowledge the possibility of apocrine influence and possibly causing the clinician to exclude eccrine poromas from the differential diagnosis in areas that do not have high concentrations of eccrine glands.

Because of their high degree of clinical variability, characteristic acral location, and misleading nomenclature, eccrine poromas often are mistakenly confused with a long list of other cutaneous neoplasms, including hemangiomas, pyogenic granulomas, melanocytic nevi, warts, cysts, and other adnexal neoplasms.3 In our case, the lesion was abnormally large and was clinically concerning for an unusual sebaceous nevus. Its location on the lower back is not commonly noted and should remind the clinician of the possibility of apocrine differentiation. Clinicians should be aware of the wide phenotypic diversity of eccrine poromas, and therefore they should consider this diagnosis in their differential diagnosis for solitary papules or nodules occurring in any anatomic area.

The Diagnosis: Eccrine Poroma

A shave biopsy of the lesion was performed for definitive diagnosis and demonstrated a well-circumscribed tumor with cords and broad columns composed of uniform basaloid cells extending into the dermis and in areas connecting to the overlying epidermis (Figure). There also were small ducts and cysts admixed in the tumor columns that were embedded in a tumor stroma rich in blood vessels. A diagnosis of eccrine poroma was made based on these characteristic histologic features.

 


 

Biopsy revealed a basaloid tumor originating from the epidermis and extending into the dermis (A)(H&E, original magnification ×4). On higher magnification, ducts were evident amongst the tumor cells and a vascular rich stroma was revealed (B)(H&E, original magnification ×10).

First described by Pinkus et al1 in 1956, eccrine poroma is a benign neoplasm of cells from the intraepidermal ductal portion of the eccrine sweat gland. Eccrine poroma (along with hidroacanthoma simplex, dermal duct tumor, and poroid hidradenoma) is one of the poroid neoplasms, which account for approximately 10% of all primary sweat gland tumors.2 Eccrine poroma usually is seen in patients over 40 years of age without any predilection for race or sex.

Characteristically, eccrine poromas clinically manifest as solitary, firm, sharply demarcated papules or nodules that may be sessile or pedunculated and rarely exceed 2 cm in diameter. This entity classically presents on acral, non–hair-bearing areas (eg, palms and soles). Eccrine poromas have a wide range of clinical appearances that can lead to broad differential diagnoses3 and have been described as flesh-colored,3 pink to red,4 purple,5 and pigmented3,4 papules or nodules depending on features such as blood vessel proliferation and pigment deposition.

Eccrine poromas also have been reported on hair-bearing areas of the body, including the head,3 neck,3,6 chest,4,6 hip,7 and pubic area,8 despite the paucity of eccrine glands in these areas on the body. These findings suggest that these neoplasms may not be purely eccrine in origin. The wide range of clinical presentations of eccrine poromas has prompted investigation into further classification and delineation of this neoplasm.3 The occurrence of eccrine poromas on areas of the skin known to have few eccrine glands suggests that eccrine poromas may not be purely comprised of eccrine ducts and instead may be of apocrine origin.3,9,10 Histologic features of eccrine poromas that suggest apocrine origination include sebaceous and follicular differentiation (eg, folliculocentric distribution), the association with the follicular infundibulum, and the presence of follicular germ cells.3,9,10 Thus, apocrine gland involvement in eccrine poromas may account for their appearance in anatomic areas that do not have high concentrations of eccrine glands, such as the trunk and pubic area.

Based on these findings, eccrine poromas may therefore be of eccrine and/or apocrine origin; however, the nomenclature of this neoplasm remains confusing and possibly misleading, as the term eccrine poroma continues to be accepted even in instances in which the differentiation appears to be largely apocrine. The terms poroma and eccrine poroma often are used interchangeably, which contributes to the confusion by failing to acknowledge the possibility of apocrine influence and possibly causing the clinician to exclude eccrine poromas from the differential diagnosis in areas that do not have high concentrations of eccrine glands.

Because of their high degree of clinical variability, characteristic acral location, and misleading nomenclature, eccrine poromas often are mistakenly confused with a long list of other cutaneous neoplasms, including hemangiomas, pyogenic granulomas, melanocytic nevi, warts, cysts, and other adnexal neoplasms.3 In our case, the lesion was abnormally large and was clinically concerning for an unusual sebaceous nevus. Its location on the lower back is not commonly noted and should remind the clinician of the possibility of apocrine differentiation. Clinicians should be aware of the wide phenotypic diversity of eccrine poromas, and therefore they should consider this diagnosis in their differential diagnosis for solitary papules or nodules occurring in any anatomic area.

References
  1. Pinkus H, Rogin JR, Goldman P. Eccrine poroma: tumors exhibiting features of the epidermal sweat duct unit. Arch Dermatol. 1956;74:511-521.
  2. Pylyser K, Dewolf-Peeters C, Marlen K. The histology of eccrine poromas: a study of 14 cases. Dermatologica. 1983;167:243-249.
  3. Moore TO, Orman HL, Orman SK, et al. Poromas of the head and neck. J Am Acad Dermatol. 2001;44:48-52.
  4. Agarwal S, Kumar B, Sharma N. Nodule on the chest. eccrine poroma. Indian J Dermatol Venereol Leprol. 2009;75:639.
  5. Ackerman AB, Abenoza P. Neoplasms With Eccrine Differentiation. Philadelphia, PA: Lea & Febinger; 1990:113-185.
  6. Okun M, Ansell H. Eccrine poroma. report of three cases, two with an unusual location. Arch Dermatol. 1963;88:561-566.
  7. Sarma DP, Zaman SU, Santos EE, et al. Poroma of the hip and buttock. Dermatol Online J. 2009;15:10.
  8. Altamura D, Piccolo D, Lozzi GP, et al. Eccrine poroma in an unusual site: a clinical and dermoscopic simulator of amelanotic melanoma. J Am Acad Dermatol. 2005;53:539-541.
  9. Groben PA, Hitchcock MG, Leshin B, et al. Apocrine poroma, a distinctive case in a patient with nevoid BCC. Am J Dermatopathol. 1992;21:31-33.
  10. Harvell JD, Kerschmann RL, LeBoit PE. Eccrine or apocrine poroma? six poromas with divergent adnexal differentiation. Am J Dermatopathol. 1996;18:1-9.
References
  1. Pinkus H, Rogin JR, Goldman P. Eccrine poroma: tumors exhibiting features of the epidermal sweat duct unit. Arch Dermatol. 1956;74:511-521.
  2. Pylyser K, Dewolf-Peeters C, Marlen K. The histology of eccrine poromas: a study of 14 cases. Dermatologica. 1983;167:243-249.
  3. Moore TO, Orman HL, Orman SK, et al. Poromas of the head and neck. J Am Acad Dermatol. 2001;44:48-52.
  4. Agarwal S, Kumar B, Sharma N. Nodule on the chest. eccrine poroma. Indian J Dermatol Venereol Leprol. 2009;75:639.
  5. Ackerman AB, Abenoza P. Neoplasms With Eccrine Differentiation. Philadelphia, PA: Lea & Febinger; 1990:113-185.
  6. Okun M, Ansell H. Eccrine poroma. report of three cases, two with an unusual location. Arch Dermatol. 1963;88:561-566.
  7. Sarma DP, Zaman SU, Santos EE, et al. Poroma of the hip and buttock. Dermatol Online J. 2009;15:10.
  8. Altamura D, Piccolo D, Lozzi GP, et al. Eccrine poroma in an unusual site: a clinical and dermoscopic simulator of amelanotic melanoma. J Am Acad Dermatol. 2005;53:539-541.
  9. Groben PA, Hitchcock MG, Leshin B, et al. Apocrine poroma, a distinctive case in a patient with nevoid BCC. Am J Dermatopathol. 1992;21:31-33.
  10. Harvell JD, Kerschmann RL, LeBoit PE. Eccrine or apocrine poroma? six poromas with divergent adnexal differentiation. Am J Dermatopathol. 1996;18:1-9.
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A 47-year-old man presented with an asymptomatic, 2.5×1.5-cm, sessile pink plaque with a coalescing papular texture on the lower back of 30 years’ duration. The patient reported that 2 papillated papules with peripheral rims of dark crust had developed in the center of the lesion over the past 6 months. His personal and family histories were unremarkable.

 

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AHA: Mixed results for mitral valve replacement vs. repair

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Patients undergoing mitral valve replacement had a lower risk of regurgitation and heart failure–related adverse events at 2 years than those undergoing valve repair, according to the results of a trial presented at the American Heart Association scientific sessions and published simultaneously in the New England Journal of Medicine.

The results of the trial appear to associate mitral valve replacement with clinical advantages over mitral valve repair after 2 years of follow-up. However, replacement held no significant advantages over repair in the primary endpoint of left ventricular end-systolic volume index (LVESVI) or in overall survival, said Dr. Daniel Goldstein of the department of cardiothoracic surgery at Montefiore Medical Center, New York.

In the trial conducted by the Cardiothoracic Surgical Trials Network (CTSN), 251 patients with chronic severe ischemic mitral regurgitation were randomly assigned to undergo surgical repair of the mitral valve or to receive a mitral valve replacement with a prosthetic and procedure selected at the discretion of the surgeon.

In addition to the primary endpoint of LVESVI, the two approaches were also compared for survival, regurgitation recurrence, and heart failure events.

At 2 years, the mean change from baseline in LVESVI, a measure of remodeling, did not differ significantly between the repair and replacement arms (–9.0 vs. –6.5 mL/m2, respectively). In addition, although the 2-year mortality rate was numerically lower in the repair arm relative to the replacement arm (19% vs. 23.2%, respectively), it was also not statistically different (P = .39).

However, the rate of recurrence of moderate or severe mitral regurgitation favored replacement over repair and was significant (3.8% vs. 58.8%, respectively; P less than .001). In addition, the rate of cardiovascular readmissions was significantly lower in the replacement group (P = .01).

For those in the repair group, there were significant trends for more serious adverse events related to heart failure (P = .05) and for a lower quality of life improvement (P = .07) on the Minnesota Living With Heart Failure questionnaire. There were no significant differences in rates of all serious adverse events or overall readmissions.

All of the differences between groups observed at 2 years amplify differences previously reported after 12 months (N Engl J Med. 2014 Jan 2;370[1]:23-32). For example, the difference in the rate of moderate to severe regurgitation favoring replacement over repair was already significant at that time (2.3% vs. 32.6%, respectively; P less than .001), even though the mortality rates were then, as now, numerically lower in the repair group versus the replacement group (14.3% vs. 17.6%, respectively; P = .45).

Dr. Goldstein reported no relevant financial relationships.

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Patients undergoing mitral valve replacement had a lower risk of regurgitation and heart failure–related adverse events at 2 years than those undergoing valve repair, according to the results of a trial presented at the American Heart Association scientific sessions and published simultaneously in the New England Journal of Medicine.

The results of the trial appear to associate mitral valve replacement with clinical advantages over mitral valve repair after 2 years of follow-up. However, replacement held no significant advantages over repair in the primary endpoint of left ventricular end-systolic volume index (LVESVI) or in overall survival, said Dr. Daniel Goldstein of the department of cardiothoracic surgery at Montefiore Medical Center, New York.

In the trial conducted by the Cardiothoracic Surgical Trials Network (CTSN), 251 patients with chronic severe ischemic mitral regurgitation were randomly assigned to undergo surgical repair of the mitral valve or to receive a mitral valve replacement with a prosthetic and procedure selected at the discretion of the surgeon.

In addition to the primary endpoint of LVESVI, the two approaches were also compared for survival, regurgitation recurrence, and heart failure events.

At 2 years, the mean change from baseline in LVESVI, a measure of remodeling, did not differ significantly between the repair and replacement arms (–9.0 vs. –6.5 mL/m2, respectively). In addition, although the 2-year mortality rate was numerically lower in the repair arm relative to the replacement arm (19% vs. 23.2%, respectively), it was also not statistically different (P = .39).

However, the rate of recurrence of moderate or severe mitral regurgitation favored replacement over repair and was significant (3.8% vs. 58.8%, respectively; P less than .001). In addition, the rate of cardiovascular readmissions was significantly lower in the replacement group (P = .01).

For those in the repair group, there were significant trends for more serious adverse events related to heart failure (P = .05) and for a lower quality of life improvement (P = .07) on the Minnesota Living With Heart Failure questionnaire. There were no significant differences in rates of all serious adverse events or overall readmissions.

All of the differences between groups observed at 2 years amplify differences previously reported after 12 months (N Engl J Med. 2014 Jan 2;370[1]:23-32). For example, the difference in the rate of moderate to severe regurgitation favoring replacement over repair was already significant at that time (2.3% vs. 32.6%, respectively; P less than .001), even though the mortality rates were then, as now, numerically lower in the repair group versus the replacement group (14.3% vs. 17.6%, respectively; P = .45).

Dr. Goldstein reported no relevant financial relationships.

Patients undergoing mitral valve replacement had a lower risk of regurgitation and heart failure–related adverse events at 2 years than those undergoing valve repair, according to the results of a trial presented at the American Heart Association scientific sessions and published simultaneously in the New England Journal of Medicine.

The results of the trial appear to associate mitral valve replacement with clinical advantages over mitral valve repair after 2 years of follow-up. However, replacement held no significant advantages over repair in the primary endpoint of left ventricular end-systolic volume index (LVESVI) or in overall survival, said Dr. Daniel Goldstein of the department of cardiothoracic surgery at Montefiore Medical Center, New York.

In the trial conducted by the Cardiothoracic Surgical Trials Network (CTSN), 251 patients with chronic severe ischemic mitral regurgitation were randomly assigned to undergo surgical repair of the mitral valve or to receive a mitral valve replacement with a prosthetic and procedure selected at the discretion of the surgeon.

In addition to the primary endpoint of LVESVI, the two approaches were also compared for survival, regurgitation recurrence, and heart failure events.

At 2 years, the mean change from baseline in LVESVI, a measure of remodeling, did not differ significantly between the repair and replacement arms (–9.0 vs. –6.5 mL/m2, respectively). In addition, although the 2-year mortality rate was numerically lower in the repair arm relative to the replacement arm (19% vs. 23.2%, respectively), it was also not statistically different (P = .39).

However, the rate of recurrence of moderate or severe mitral regurgitation favored replacement over repair and was significant (3.8% vs. 58.8%, respectively; P less than .001). In addition, the rate of cardiovascular readmissions was significantly lower in the replacement group (P = .01).

For those in the repair group, there were significant trends for more serious adverse events related to heart failure (P = .05) and for a lower quality of life improvement (P = .07) on the Minnesota Living With Heart Failure questionnaire. There were no significant differences in rates of all serious adverse events or overall readmissions.

All of the differences between groups observed at 2 years amplify differences previously reported after 12 months (N Engl J Med. 2014 Jan 2;370[1]:23-32). For example, the difference in the rate of moderate to severe regurgitation favoring replacement over repair was already significant at that time (2.3% vs. 32.6%, respectively; P less than .001), even though the mortality rates were then, as now, numerically lower in the repair group versus the replacement group (14.3% vs. 17.6%, respectively; P = .45).

Dr. Goldstein reported no relevant financial relationships.

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FROM THE AHA SCIENTIFIC SESSIONS

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Inside the Article

Vitals

Key clinical point: Mitral valve replacement reduced regurgitation better than valve repair, but it didn’t significantly improve left ventricular function or survival.

Major finding: In patients with severe ischemic mitral regurgitation, regurgitation occurred more frequently after mitral valve repair than after valve replacement (58.8% vs. 3.8%; P less than .001), but left ventricular end-systolic volume indexes and survival rates were not significantly different.

Data source: A randomized, multicenter trial with 251 patients.

Disclosures: Dr. Goldstein reported no relevant financial relationships.

Younger AF Patients at Higher Risk of Dementia

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NEW YORK - Atrial fibrillation (AF) is associated with an increased risk of dementia, especially in younger individuals, according to results from the Rotterdam Study.

"When we started this study, we hypothesized that the hazard of atrial fibrillation would be higher with longer exposure, but to find such a strong exposure-time association in younger participants was striking," said Dr. Frank J. Wolters from Erasmus Medical Center in Rotterdam, the Netherlands.

"It emphasizes that prevention of dementia doesn't start when people report to their physician with mild memory complaints, but years, if not decades before, by identifying those at risk and optimizing preventive strategies," he said by email.

An earlier report from the Rotterdam Study showed that AF is more prevalent in people with dementia, but the cross-sectional design did not allow conclusions regarding a causal relationship.

Dr. Wolters's team investigated the association between AF and dementia during a follow up of 20 years of nearly 6,200 participants in the Rotterdam Study.

About 5% of the participants had AF at baseline, and 15.3% of these individuals developed dementia during more than 81,000 person-years of follow-up.

Another 11.7% developed AF later, and 15.0% developed dementia during more than 79,000 person-years, the researchers report in JAMA Neurology, online September 21.

People who had AF at the start of the study had a 34% increased risk of dementia (compared with those who did not have prevalent AF), and people who developed AF during follow-up had a 23% increased risk of dementia (compared with those who did not have incident AF).

The association between AF and dementia was strongest in persons younger than the median age (67 years), and in these younger participants, the risk of dementia was higher with increasing duration of AF.

"As we found atrial fibrillation to increase the risk of dementia independent of clinical stroke, either chronic hypoperfusion or more acutely silent infarcts or perhaps cortical microinfarcts could account for the increased risk of dementia," Dr. Wolters said.

"A few observational studies have suggested beneficialeffect of treatment of atrial fibrillation on the risk of dementia, but more evidence on treatment efficacy is sorely needed. This includes insight into whether optimal treatment consists of anticoagulation, heart rhythm, or rate control," he noted.

"With regard to treatment of atrial fibrillation, until further evidence on efficacy becomes available, it is worth realizing that optimal adherence to current guidelines may contribute to prevention of cognitive decline in addition to prevention of stroke," Dr. Wolters added. "Although we found the strongest associations between atrial fibrillation and dementia for younger people, the need to determine treatment efficacy is just as profound in the elderly."

Dr. Sanjay Dixit, director of cardiac electrophysiology at Philadelphia VA Medical Center in Pennsylvania, said by email, "Although the association between AF and dementia has been shown, it's difficult to establish cause and effect. As I point out in my previous review, obstructive sleep apnea (OSA) is considered to be a major contributor to the development of neurocognitive decline and dementia. OSA is very common in the AF population and many consider this to be (a) risk factor in the development of AF. So the question remains whether AF is the cause of dementia or other co-morbidities such as OSA that frequently co-exist in the AF population."

"Look for AF in patients with dementia and also caution patients with AF of the possibility of developing this condition in the future," Dr. Dixit advised. "Since catheter ablation therapy has been shown to have better outcomes for long-term control of AF than drugs, physicians should discuss this with patients and consider referring them to cardiac electrophysiologists early in the course of the disease."

Dr. T. Jared Bunch, director of heart rhythm services for Intermountain Healthcare, Murray, Utah, said by email, "It is great to see another confirmatory study that found essentially the same thing we did 5 years ago. These data in aggregate make the likelihood of the association much more compelling."

 

 

"What is interesting in our subsequent work is the patients more sensitive to poor warfarin management (low times in therapeutic range) were at the highest relative risk of dementia compared to older patients," Dr. Bunch explained. "Now we all need to start to unravel the mechanisms behind it and find avenues of preventative treatment. The choice and manner of anticoagulant treatment is one and allowing faster heart rates is another."

Dr. Shih-An Chen and Dr. Tzu-Fan Chao from Taipei Veterans General Hospital, Taipei, Taiwan, who recently reported on the independent association between AF and dementia, struck a more cautious note.

"Only when a lower risk of dementia can be achieved by AF ablation in the prospective and randomized trial can we conclude that AF is the direct cause of dementia," they said in a joint email. "It should also be noted that the development of dementia is multifactorial, and AF only represents one of them."

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NEW YORK - Atrial fibrillation (AF) is associated with an increased risk of dementia, especially in younger individuals, according to results from the Rotterdam Study.

"When we started this study, we hypothesized that the hazard of atrial fibrillation would be higher with longer exposure, but to find such a strong exposure-time association in younger participants was striking," said Dr. Frank J. Wolters from Erasmus Medical Center in Rotterdam, the Netherlands.

"It emphasizes that prevention of dementia doesn't start when people report to their physician with mild memory complaints, but years, if not decades before, by identifying those at risk and optimizing preventive strategies," he said by email.

An earlier report from the Rotterdam Study showed that AF is more prevalent in people with dementia, but the cross-sectional design did not allow conclusions regarding a causal relationship.

Dr. Wolters's team investigated the association between AF and dementia during a follow up of 20 years of nearly 6,200 participants in the Rotterdam Study.

About 5% of the participants had AF at baseline, and 15.3% of these individuals developed dementia during more than 81,000 person-years of follow-up.

Another 11.7% developed AF later, and 15.0% developed dementia during more than 79,000 person-years, the researchers report in JAMA Neurology, online September 21.

People who had AF at the start of the study had a 34% increased risk of dementia (compared with those who did not have prevalent AF), and people who developed AF during follow-up had a 23% increased risk of dementia (compared with those who did not have incident AF).

The association between AF and dementia was strongest in persons younger than the median age (67 years), and in these younger participants, the risk of dementia was higher with increasing duration of AF.

"As we found atrial fibrillation to increase the risk of dementia independent of clinical stroke, either chronic hypoperfusion or more acutely silent infarcts or perhaps cortical microinfarcts could account for the increased risk of dementia," Dr. Wolters said.

"A few observational studies have suggested beneficialeffect of treatment of atrial fibrillation on the risk of dementia, but more evidence on treatment efficacy is sorely needed. This includes insight into whether optimal treatment consists of anticoagulation, heart rhythm, or rate control," he noted.

"With regard to treatment of atrial fibrillation, until further evidence on efficacy becomes available, it is worth realizing that optimal adherence to current guidelines may contribute to prevention of cognitive decline in addition to prevention of stroke," Dr. Wolters added. "Although we found the strongest associations between atrial fibrillation and dementia for younger people, the need to determine treatment efficacy is just as profound in the elderly."

Dr. Sanjay Dixit, director of cardiac electrophysiology at Philadelphia VA Medical Center in Pennsylvania, said by email, "Although the association between AF and dementia has been shown, it's difficult to establish cause and effect. As I point out in my previous review, obstructive sleep apnea (OSA) is considered to be a major contributor to the development of neurocognitive decline and dementia. OSA is very common in the AF population and many consider this to be (a) risk factor in the development of AF. So the question remains whether AF is the cause of dementia or other co-morbidities such as OSA that frequently co-exist in the AF population."

"Look for AF in patients with dementia and also caution patients with AF of the possibility of developing this condition in the future," Dr. Dixit advised. "Since catheter ablation therapy has been shown to have better outcomes for long-term control of AF than drugs, physicians should discuss this with patients and consider referring them to cardiac electrophysiologists early in the course of the disease."

Dr. T. Jared Bunch, director of heart rhythm services for Intermountain Healthcare, Murray, Utah, said by email, "It is great to see another confirmatory study that found essentially the same thing we did 5 years ago. These data in aggregate make the likelihood of the association much more compelling."

 

 

"What is interesting in our subsequent work is the patients more sensitive to poor warfarin management (low times in therapeutic range) were at the highest relative risk of dementia compared to older patients," Dr. Bunch explained. "Now we all need to start to unravel the mechanisms behind it and find avenues of preventative treatment. The choice and manner of anticoagulant treatment is one and allowing faster heart rates is another."

Dr. Shih-An Chen and Dr. Tzu-Fan Chao from Taipei Veterans General Hospital, Taipei, Taiwan, who recently reported on the independent association between AF and dementia, struck a more cautious note.

"Only when a lower risk of dementia can be achieved by AF ablation in the prospective and randomized trial can we conclude that AF is the direct cause of dementia," they said in a joint email. "It should also be noted that the development of dementia is multifactorial, and AF only represents one of them."

NEW YORK - Atrial fibrillation (AF) is associated with an increased risk of dementia, especially in younger individuals, according to results from the Rotterdam Study.

"When we started this study, we hypothesized that the hazard of atrial fibrillation would be higher with longer exposure, but to find such a strong exposure-time association in younger participants was striking," said Dr. Frank J. Wolters from Erasmus Medical Center in Rotterdam, the Netherlands.

"It emphasizes that prevention of dementia doesn't start when people report to their physician with mild memory complaints, but years, if not decades before, by identifying those at risk and optimizing preventive strategies," he said by email.

An earlier report from the Rotterdam Study showed that AF is more prevalent in people with dementia, but the cross-sectional design did not allow conclusions regarding a causal relationship.

Dr. Wolters's team investigated the association between AF and dementia during a follow up of 20 years of nearly 6,200 participants in the Rotterdam Study.

About 5% of the participants had AF at baseline, and 15.3% of these individuals developed dementia during more than 81,000 person-years of follow-up.

Another 11.7% developed AF later, and 15.0% developed dementia during more than 79,000 person-years, the researchers report in JAMA Neurology, online September 21.

People who had AF at the start of the study had a 34% increased risk of dementia (compared with those who did not have prevalent AF), and people who developed AF during follow-up had a 23% increased risk of dementia (compared with those who did not have incident AF).

The association between AF and dementia was strongest in persons younger than the median age (67 years), and in these younger participants, the risk of dementia was higher with increasing duration of AF.

"As we found atrial fibrillation to increase the risk of dementia independent of clinical stroke, either chronic hypoperfusion or more acutely silent infarcts or perhaps cortical microinfarcts could account for the increased risk of dementia," Dr. Wolters said.

"A few observational studies have suggested beneficialeffect of treatment of atrial fibrillation on the risk of dementia, but more evidence on treatment efficacy is sorely needed. This includes insight into whether optimal treatment consists of anticoagulation, heart rhythm, or rate control," he noted.

"With regard to treatment of atrial fibrillation, until further evidence on efficacy becomes available, it is worth realizing that optimal adherence to current guidelines may contribute to prevention of cognitive decline in addition to prevention of stroke," Dr. Wolters added. "Although we found the strongest associations between atrial fibrillation and dementia for younger people, the need to determine treatment efficacy is just as profound in the elderly."

Dr. Sanjay Dixit, director of cardiac electrophysiology at Philadelphia VA Medical Center in Pennsylvania, said by email, "Although the association between AF and dementia has been shown, it's difficult to establish cause and effect. As I point out in my previous review, obstructive sleep apnea (OSA) is considered to be a major contributor to the development of neurocognitive decline and dementia. OSA is very common in the AF population and many consider this to be (a) risk factor in the development of AF. So the question remains whether AF is the cause of dementia or other co-morbidities such as OSA that frequently co-exist in the AF population."

"Look for AF in patients with dementia and also caution patients with AF of the possibility of developing this condition in the future," Dr. Dixit advised. "Since catheter ablation therapy has been shown to have better outcomes for long-term control of AF than drugs, physicians should discuss this with patients and consider referring them to cardiac electrophysiologists early in the course of the disease."

Dr. T. Jared Bunch, director of heart rhythm services for Intermountain Healthcare, Murray, Utah, said by email, "It is great to see another confirmatory study that found essentially the same thing we did 5 years ago. These data in aggregate make the likelihood of the association much more compelling."

 

 

"What is interesting in our subsequent work is the patients more sensitive to poor warfarin management (low times in therapeutic range) were at the highest relative risk of dementia compared to older patients," Dr. Bunch explained. "Now we all need to start to unravel the mechanisms behind it and find avenues of preventative treatment. The choice and manner of anticoagulant treatment is one and allowing faster heart rates is another."

Dr. Shih-An Chen and Dr. Tzu-Fan Chao from Taipei Veterans General Hospital, Taipei, Taiwan, who recently reported on the independent association between AF and dementia, struck a more cautious note.

"Only when a lower risk of dementia can be achieved by AF ablation in the prospective and randomized trial can we conclude that AF is the direct cause of dementia," they said in a joint email. "It should also be noted that the development of dementia is multifactorial, and AF only represents one of them."

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Highlights From the 2015 ECTRIMS Annual Meeting

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Donor CAR T cells treat aggressive ALL in infant

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Donor CAR T cells treat aggressive ALL in infant

Layla Richards, the first

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Photo courtesy of GOSH

A hospital in the UK has reported success with the first-in-human use of an allogeneic chimeric antigen receptor (CAR) T-cell treatment.

The therapy, UCART19, helped treat an aggressive case of acute lymphoblastic leukemia (ALL) in an infant named Layla Richards.

Chemotherapy, a first transplant, and blinatumomab all failed to treat Layla’s disease. But UCART19 provided a bridge to a second transplant, and Layla

is now free of leukemia.

“We have only used this treatment on one very strong little girl, and we have to be cautious about claiming that this will be a suitable treatment option for all children,” said Waseem Qasim, MBBS, PhD, a professor at University College London’s Institute of Child Health and a consultant immunologist at Great Ormond Street Hospital (GOSH) in London, where Layla was treated.

“But this is a landmark in the use of new gene-engineering technology, and the effects for this child have been staggering. If replicated, it could represent a huge step forward in treating leukemia and other cancers.”

Layla’s history

Layla was born in June 2014 and, at 14 weeks old, was diagnosed with CD19+ ALL (t[11;19] rearrangement). Doctors at GOSH described her leukemia as “one of the most aggressive forms of the disease we have ever seen.”

Layla underwent several rounds of chemotherapy at GOSH and then received a transplant from a mismatched, unrelated donor. Seven weeks later, her leukemia had returned.

A second round of chemotherapy wasn’t an option, so Layla went on to receive blinatumomab. This, too, ultimately failed.

Layla’s family was unwilling to accept palliative care, so her doctors mentioned the possibility of using UCART19.

“The approach was looking incredibly successful in laboratory studies, and so when I heard there were no options left for treating this child’s disease, I thought, ‘Why don’t we use the new UCART19 cells?’” Dr Qasim said.

“The treatment was highly experimental, and we had to get special permissions, but she appeared ideally suited for this type of approach.”

UCART19 treatment

Before Layla received UCART19, investigators from GOSH, University College London, and the biotech company Cellectis had been developing off-the-shelf banks of the cells for use in clinical trials.

UCART19 consists of donor T cells modified using transcription activator-like effector nucleases (TALEN). Like some other CAR T-cell products, UCART19 is designed to target CD19+ cancer cells.

But UCART19 cells are also programmed to be insensitive to alemtuzumab. That way, a patient can receive the drug to prevent rejection of HLA-mismatched cells.

Before receiving UCART19, Layla was given vincristine, dexamethasone, and asparaginase, followed by fludarabine, cyclophosphamide, and alemtuzumab. She then received a single dose (4.5 x 106/kg) of UCART19.

After this, Layla spent several months in isolation to protect her from infections while her immune system was extremely weak. Within weeks of receiving UCART19, Layla demonstrated an immune response in the form of a rash.

The rash worsened, but, aside from that, Layla appeared to be well. To date, she has shown no signs of cytokine release syndrome.

She did, however, show signs of molecular and cytogenetic remission. Once she was deemed leukemia-free, Layla underwent a second transplant. One month later, she was well enough to go home. Today, Layla is still free of ALL.

More details on Layla’s story and UCART19 are scheduled to be presented at the 2015 ASH Annual Meeting (abstract 2046). Clinical trials of UCART19 (funded by Cellectis) are set to begin early next year.

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Layla Richards, the first

person treated with UCART19

Photo courtesy of GOSH

A hospital in the UK has reported success with the first-in-human use of an allogeneic chimeric antigen receptor (CAR) T-cell treatment.

The therapy, UCART19, helped treat an aggressive case of acute lymphoblastic leukemia (ALL) in an infant named Layla Richards.

Chemotherapy, a first transplant, and blinatumomab all failed to treat Layla’s disease. But UCART19 provided a bridge to a second transplant, and Layla

is now free of leukemia.

“We have only used this treatment on one very strong little girl, and we have to be cautious about claiming that this will be a suitable treatment option for all children,” said Waseem Qasim, MBBS, PhD, a professor at University College London’s Institute of Child Health and a consultant immunologist at Great Ormond Street Hospital (GOSH) in London, where Layla was treated.

“But this is a landmark in the use of new gene-engineering technology, and the effects for this child have been staggering. If replicated, it could represent a huge step forward in treating leukemia and other cancers.”

Layla’s history

Layla was born in June 2014 and, at 14 weeks old, was diagnosed with CD19+ ALL (t[11;19] rearrangement). Doctors at GOSH described her leukemia as “one of the most aggressive forms of the disease we have ever seen.”

Layla underwent several rounds of chemotherapy at GOSH and then received a transplant from a mismatched, unrelated donor. Seven weeks later, her leukemia had returned.

A second round of chemotherapy wasn’t an option, so Layla went on to receive blinatumomab. This, too, ultimately failed.

Layla’s family was unwilling to accept palliative care, so her doctors mentioned the possibility of using UCART19.

“The approach was looking incredibly successful in laboratory studies, and so when I heard there were no options left for treating this child’s disease, I thought, ‘Why don’t we use the new UCART19 cells?’” Dr Qasim said.

“The treatment was highly experimental, and we had to get special permissions, but she appeared ideally suited for this type of approach.”

UCART19 treatment

Before Layla received UCART19, investigators from GOSH, University College London, and the biotech company Cellectis had been developing off-the-shelf banks of the cells for use in clinical trials.

UCART19 consists of donor T cells modified using transcription activator-like effector nucleases (TALEN). Like some other CAR T-cell products, UCART19 is designed to target CD19+ cancer cells.

But UCART19 cells are also programmed to be insensitive to alemtuzumab. That way, a patient can receive the drug to prevent rejection of HLA-mismatched cells.

Before receiving UCART19, Layla was given vincristine, dexamethasone, and asparaginase, followed by fludarabine, cyclophosphamide, and alemtuzumab. She then received a single dose (4.5 x 106/kg) of UCART19.

After this, Layla spent several months in isolation to protect her from infections while her immune system was extremely weak. Within weeks of receiving UCART19, Layla demonstrated an immune response in the form of a rash.

The rash worsened, but, aside from that, Layla appeared to be well. To date, she has shown no signs of cytokine release syndrome.

She did, however, show signs of molecular and cytogenetic remission. Once she was deemed leukemia-free, Layla underwent a second transplant. One month later, she was well enough to go home. Today, Layla is still free of ALL.

More details on Layla’s story and UCART19 are scheduled to be presented at the 2015 ASH Annual Meeting (abstract 2046). Clinical trials of UCART19 (funded by Cellectis) are set to begin early next year.

Layla Richards, the first

person treated with UCART19

Photo courtesy of GOSH

A hospital in the UK has reported success with the first-in-human use of an allogeneic chimeric antigen receptor (CAR) T-cell treatment.

The therapy, UCART19, helped treat an aggressive case of acute lymphoblastic leukemia (ALL) in an infant named Layla Richards.

Chemotherapy, a first transplant, and blinatumomab all failed to treat Layla’s disease. But UCART19 provided a bridge to a second transplant, and Layla

is now free of leukemia.

“We have only used this treatment on one very strong little girl, and we have to be cautious about claiming that this will be a suitable treatment option for all children,” said Waseem Qasim, MBBS, PhD, a professor at University College London’s Institute of Child Health and a consultant immunologist at Great Ormond Street Hospital (GOSH) in London, where Layla was treated.

“But this is a landmark in the use of new gene-engineering technology, and the effects for this child have been staggering. If replicated, it could represent a huge step forward in treating leukemia and other cancers.”

Layla’s history

Layla was born in June 2014 and, at 14 weeks old, was diagnosed with CD19+ ALL (t[11;19] rearrangement). Doctors at GOSH described her leukemia as “one of the most aggressive forms of the disease we have ever seen.”

Layla underwent several rounds of chemotherapy at GOSH and then received a transplant from a mismatched, unrelated donor. Seven weeks later, her leukemia had returned.

A second round of chemotherapy wasn’t an option, so Layla went on to receive blinatumomab. This, too, ultimately failed.

Layla’s family was unwilling to accept palliative care, so her doctors mentioned the possibility of using UCART19.

“The approach was looking incredibly successful in laboratory studies, and so when I heard there were no options left for treating this child’s disease, I thought, ‘Why don’t we use the new UCART19 cells?’” Dr Qasim said.

“The treatment was highly experimental, and we had to get special permissions, but she appeared ideally suited for this type of approach.”

UCART19 treatment

Before Layla received UCART19, investigators from GOSH, University College London, and the biotech company Cellectis had been developing off-the-shelf banks of the cells for use in clinical trials.

UCART19 consists of donor T cells modified using transcription activator-like effector nucleases (TALEN). Like some other CAR T-cell products, UCART19 is designed to target CD19+ cancer cells.

But UCART19 cells are also programmed to be insensitive to alemtuzumab. That way, a patient can receive the drug to prevent rejection of HLA-mismatched cells.

Before receiving UCART19, Layla was given vincristine, dexamethasone, and asparaginase, followed by fludarabine, cyclophosphamide, and alemtuzumab. She then received a single dose (4.5 x 106/kg) of UCART19.

After this, Layla spent several months in isolation to protect her from infections while her immune system was extremely weak. Within weeks of receiving UCART19, Layla demonstrated an immune response in the form of a rash.

The rash worsened, but, aside from that, Layla appeared to be well. To date, she has shown no signs of cytokine release syndrome.

She did, however, show signs of molecular and cytogenetic remission. Once she was deemed leukemia-free, Layla underwent a second transplant. One month later, she was well enough to go home. Today, Layla is still free of ALL.

More details on Layla’s story and UCART19 are scheduled to be presented at the 2015 ASH Annual Meeting (abstract 2046). Clinical trials of UCART19 (funded by Cellectis) are set to begin early next year.

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Study challenges ‘textbook’ view of hematopoiesis

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Study challenges ‘textbook’ view of hematopoiesis

John Dick, PhD

University Health Network

Results of a study published in Science challenge traditional ideas about how blood is made.

The findings suggest hematopoiesis does not occur through a gradual process consisting of multipotent, oligopotent, and unilineage progenitor stages.

Rather, hematopoietic stem cells (HSCs) mature into different types of blood cells quickly, and the process differs between early human development (fetal liver HSCs) and adulthood (HSCs from bone marrow).

The research indicates “that the whole classic ‘textbook’ view we thought we knew doesn’t actually even exist,” said study investigator John Dick, PhD, of Princess Margaret Cancer Centre in Toronto, Ontario, Canada.

He and his colleagues mapped the lineage potential of nearly 3000 single cells from 33 different populations of HSCs obtained from human blood samples taken at various life stages and ages.

The team’s discoveries build on research published in Science in 2011. In that paper, Dr Dick and his colleagues described isolating an HSC in its purest form—as a single cell capable of regenerating the entire blood system.

“Four years ago, when we isolated the pure stem cell, we realized we had also uncovered populations of stem-cell like ‘daughter’ cells that we thought at the time were other types of stem cells,” Dr Dick said.

“When we burrowed further to study these ‘daughters,’ we discovered they were actually already mature blood lineages. In other words, lineages that had broken off almost immediately from the stem cell compartment and had not developed downstream through the slow, gradual ‘textbook’ process.”

“So in human blood formation, everything begins with the stem cell, which is the executive decision-maker quickly driving the process that replenishes blood at a daily rate that exceeds 300 billion cells.”

The investigators believe this work could help advance the manufacture of blood cells in the lab, and it should aid the study of blood disorders.

“Our discovery means we will be able to understand far better a wide variety of human blood disorders and diseases—from anemia . . . to leukemia,” Dr Dick said. “Think of it as moving from the old world of black-and-white television into the new world of high-definition.”

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John Dick, PhD

University Health Network

Results of a study published in Science challenge traditional ideas about how blood is made.

The findings suggest hematopoiesis does not occur through a gradual process consisting of multipotent, oligopotent, and unilineage progenitor stages.

Rather, hematopoietic stem cells (HSCs) mature into different types of blood cells quickly, and the process differs between early human development (fetal liver HSCs) and adulthood (HSCs from bone marrow).

The research indicates “that the whole classic ‘textbook’ view we thought we knew doesn’t actually even exist,” said study investigator John Dick, PhD, of Princess Margaret Cancer Centre in Toronto, Ontario, Canada.

He and his colleagues mapped the lineage potential of nearly 3000 single cells from 33 different populations of HSCs obtained from human blood samples taken at various life stages and ages.

The team’s discoveries build on research published in Science in 2011. In that paper, Dr Dick and his colleagues described isolating an HSC in its purest form—as a single cell capable of regenerating the entire blood system.

“Four years ago, when we isolated the pure stem cell, we realized we had also uncovered populations of stem-cell like ‘daughter’ cells that we thought at the time were other types of stem cells,” Dr Dick said.

“When we burrowed further to study these ‘daughters,’ we discovered they were actually already mature blood lineages. In other words, lineages that had broken off almost immediately from the stem cell compartment and had not developed downstream through the slow, gradual ‘textbook’ process.”

“So in human blood formation, everything begins with the stem cell, which is the executive decision-maker quickly driving the process that replenishes blood at a daily rate that exceeds 300 billion cells.”

The investigators believe this work could help advance the manufacture of blood cells in the lab, and it should aid the study of blood disorders.

“Our discovery means we will be able to understand far better a wide variety of human blood disorders and diseases—from anemia . . . to leukemia,” Dr Dick said. “Think of it as moving from the old world of black-and-white television into the new world of high-definition.”

John Dick, PhD

University Health Network

Results of a study published in Science challenge traditional ideas about how blood is made.

The findings suggest hematopoiesis does not occur through a gradual process consisting of multipotent, oligopotent, and unilineage progenitor stages.

Rather, hematopoietic stem cells (HSCs) mature into different types of blood cells quickly, and the process differs between early human development (fetal liver HSCs) and adulthood (HSCs from bone marrow).

The research indicates “that the whole classic ‘textbook’ view we thought we knew doesn’t actually even exist,” said study investigator John Dick, PhD, of Princess Margaret Cancer Centre in Toronto, Ontario, Canada.

He and his colleagues mapped the lineage potential of nearly 3000 single cells from 33 different populations of HSCs obtained from human blood samples taken at various life stages and ages.

The team’s discoveries build on research published in Science in 2011. In that paper, Dr Dick and his colleagues described isolating an HSC in its purest form—as a single cell capable of regenerating the entire blood system.

“Four years ago, when we isolated the pure stem cell, we realized we had also uncovered populations of stem-cell like ‘daughter’ cells that we thought at the time were other types of stem cells,” Dr Dick said.

“When we burrowed further to study these ‘daughters,’ we discovered they were actually already mature blood lineages. In other words, lineages that had broken off almost immediately from the stem cell compartment and had not developed downstream through the slow, gradual ‘textbook’ process.”

“So in human blood formation, everything begins with the stem cell, which is the executive decision-maker quickly driving the process that replenishes blood at a daily rate that exceeds 300 billion cells.”

The investigators believe this work could help advance the manufacture of blood cells in the lab, and it should aid the study of blood disorders.

“Our discovery means we will be able to understand far better a wide variety of human blood disorders and diseases—from anemia . . . to leukemia,” Dr Dick said. “Think of it as moving from the old world of black-and-white television into the new world of high-definition.”

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Jury still out on cannabinoid therapy for rheumatic diseases

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Jury still out on cannabinoid therapy for rheumatic diseases

Only four short-term, randomized trials have addressed the safety, efficacy, and tolerability of cannabinoids for treating rheumatic diseases, and all have methodologic weaknesses and a high risk of bias, according to a qualitative review of data published since 1946.

“There is low-quality evidence suggesting that cannabinoids may be associated with improvements in pain and sleep quality in rheumatoid arthritis and fibromyalgia. Clinical positive effects for the studies assessed in this review must be balanced by the reported adverse events,” wrote Dr. Mary-Ann Fitzcharles of McGill University, Montreal, and her colleagues (Arthritis Care Res. 2015 Nov 9. doi: 10.1002/acr.22727).

©Thinkstock.com

The four randomized clinical trials, ranging in duration from 2 to 8 weeks, included one with 58 rheumatoid arthritis patients, two with a total of 71 fibromyalgia patients, and one with 74 osteoarthritis patients. Three trials met their respective primary endpoints and found a statistically significant effect of cannabinoids on pain (in two studies), sleep (in two studies), and improved quality of life (in one study). The investigators noted a high incidence (generally observed in 25%-50% of subjects) of mild to moderate side effects (dizziness, drowsiness, nausea, dry mouth) and many methodologic weaknesses in the evaluated data. The study that tested a fatty acid amide hydrolase inhibitor in osteoarthritis patients was stopped early due to futility. The other three completed studies were associated with an overall high risk of bias.

One of the two fibromyalgia studies was a randomized, double-blind, placebo-controlled trial conducted in 2008 that assessed nabilone in 40 fibromyalgia patients. Nabilone treatment led to significant decreases in the visual analog scale for pain (–2.04, P less than .02) at 4 weeks. A second fibromyalgia trial from 2010 compared amitriptyline to nabilone in 31 subjects and found the latter agent to be superior on the primary endpoint of difference in score on the Insomnia Severity Index (difference = 3.2; 95% confidence interval, 1.2-5.3). A 2006 rheumatoid arthritis trial found that cannabis-based Sativex demonstrated a clinically meaningful advantage over placebo for the primary endpoint of morning pain on movement (difference of –0.95, 95% CI, –1.83 to –0.02; P = .044). No trials assessed herbal cannabis.

“It is not currently possible to recommend this category of treatments as therapy for patients with rheumatic diseases. Any conclusions based on these studies remain tenuous and call for larger, well controlled clinical trials to better understand potential benefits and risks as pertaining to rheumatic conditions,” Dr. Fitzcharles and her coauthors wrote.

No relevant financial disclosures were reported.

[email protected]

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Only four short-term, randomized trials have addressed the safety, efficacy, and tolerability of cannabinoids for treating rheumatic diseases, and all have methodologic weaknesses and a high risk of bias, according to a qualitative review of data published since 1946.

“There is low-quality evidence suggesting that cannabinoids may be associated with improvements in pain and sleep quality in rheumatoid arthritis and fibromyalgia. Clinical positive effects for the studies assessed in this review must be balanced by the reported adverse events,” wrote Dr. Mary-Ann Fitzcharles of McGill University, Montreal, and her colleagues (Arthritis Care Res. 2015 Nov 9. doi: 10.1002/acr.22727).

©Thinkstock.com

The four randomized clinical trials, ranging in duration from 2 to 8 weeks, included one with 58 rheumatoid arthritis patients, two with a total of 71 fibromyalgia patients, and one with 74 osteoarthritis patients. Three trials met their respective primary endpoints and found a statistically significant effect of cannabinoids on pain (in two studies), sleep (in two studies), and improved quality of life (in one study). The investigators noted a high incidence (generally observed in 25%-50% of subjects) of mild to moderate side effects (dizziness, drowsiness, nausea, dry mouth) and many methodologic weaknesses in the evaluated data. The study that tested a fatty acid amide hydrolase inhibitor in osteoarthritis patients was stopped early due to futility. The other three completed studies were associated with an overall high risk of bias.

One of the two fibromyalgia studies was a randomized, double-blind, placebo-controlled trial conducted in 2008 that assessed nabilone in 40 fibromyalgia patients. Nabilone treatment led to significant decreases in the visual analog scale for pain (–2.04, P less than .02) at 4 weeks. A second fibromyalgia trial from 2010 compared amitriptyline to nabilone in 31 subjects and found the latter agent to be superior on the primary endpoint of difference in score on the Insomnia Severity Index (difference = 3.2; 95% confidence interval, 1.2-5.3). A 2006 rheumatoid arthritis trial found that cannabis-based Sativex demonstrated a clinically meaningful advantage over placebo for the primary endpoint of morning pain on movement (difference of –0.95, 95% CI, –1.83 to –0.02; P = .044). No trials assessed herbal cannabis.

“It is not currently possible to recommend this category of treatments as therapy for patients with rheumatic diseases. Any conclusions based on these studies remain tenuous and call for larger, well controlled clinical trials to better understand potential benefits and risks as pertaining to rheumatic conditions,” Dr. Fitzcharles and her coauthors wrote.

No relevant financial disclosures were reported.

[email protected]

Only four short-term, randomized trials have addressed the safety, efficacy, and tolerability of cannabinoids for treating rheumatic diseases, and all have methodologic weaknesses and a high risk of bias, according to a qualitative review of data published since 1946.

“There is low-quality evidence suggesting that cannabinoids may be associated with improvements in pain and sleep quality in rheumatoid arthritis and fibromyalgia. Clinical positive effects for the studies assessed in this review must be balanced by the reported adverse events,” wrote Dr. Mary-Ann Fitzcharles of McGill University, Montreal, and her colleagues (Arthritis Care Res. 2015 Nov 9. doi: 10.1002/acr.22727).

©Thinkstock.com

The four randomized clinical trials, ranging in duration from 2 to 8 weeks, included one with 58 rheumatoid arthritis patients, two with a total of 71 fibromyalgia patients, and one with 74 osteoarthritis patients. Three trials met their respective primary endpoints and found a statistically significant effect of cannabinoids on pain (in two studies), sleep (in two studies), and improved quality of life (in one study). The investigators noted a high incidence (generally observed in 25%-50% of subjects) of mild to moderate side effects (dizziness, drowsiness, nausea, dry mouth) and many methodologic weaknesses in the evaluated data. The study that tested a fatty acid amide hydrolase inhibitor in osteoarthritis patients was stopped early due to futility. The other three completed studies were associated with an overall high risk of bias.

One of the two fibromyalgia studies was a randomized, double-blind, placebo-controlled trial conducted in 2008 that assessed nabilone in 40 fibromyalgia patients. Nabilone treatment led to significant decreases in the visual analog scale for pain (–2.04, P less than .02) at 4 weeks. A second fibromyalgia trial from 2010 compared amitriptyline to nabilone in 31 subjects and found the latter agent to be superior on the primary endpoint of difference in score on the Insomnia Severity Index (difference = 3.2; 95% confidence interval, 1.2-5.3). A 2006 rheumatoid arthritis trial found that cannabis-based Sativex demonstrated a clinically meaningful advantage over placebo for the primary endpoint of morning pain on movement (difference of –0.95, 95% CI, –1.83 to –0.02; P = .044). No trials assessed herbal cannabis.

“It is not currently possible to recommend this category of treatments as therapy for patients with rheumatic diseases. Any conclusions based on these studies remain tenuous and call for larger, well controlled clinical trials to better understand potential benefits and risks as pertaining to rheumatic conditions,” Dr. Fitzcharles and her coauthors wrote.

No relevant financial disclosures were reported.

[email protected]

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Inside the Article

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Key clinical point: Currently, there is insufficient evidence to support cannabinoids as a therapeutic option in rheumatic disease.

Major finding: In two of four reviewed studies, cannabinoids demonstrated a statistically significant effect on pain associated with fibromyalgia and rheumatoid arthritis.

Data source: A qualitative review of four randomized, controlled trials involving 58 patients with rheumatoid arthritis, 71 with fibromyalgia, and 74 with osteoarthritis.

Disclosures: No relevant financial disclosures were reported.

Care Transitions from Hospital to Home

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So many options, where do we start? An overview of the care transitions literature

Transitional care has been defined as a set of actions designed to ensure the coordination and continuity of healthcare as patients transfer between different locations or different levels of care within the same location.[1] Early studies showed that nurse‐led transitional care interventions beginning in the hospital and continuing after discharge had the potential to reduce the rate of hospital readmissions.[2, 3] Since then, the healthcare landscape has been evolving in important ways, with the spread of the electronic medical record, the patient‐centered medical home, and an increased push to health systems integration.[4, 5, 6]

The potential success or failure of transitional care interventions, which are inherently complex and can involve multiple components, may depend on the nature of the interventions themselves, the settings in which they were implemented, and/or the populations included. Health systems are faced with a large array of transitional care interventions and patient populations to whom such activities might apply.

The main aim of this article, culled from a larger report commissioned by the Veterans Health Administration (VHA)[7] was to catalogue which types of transitional care interventions hold promise and which populations have been best studied, to help health systems guide prioritization and adaptation of the most relevant transitional care activities and help focus future research efforts.

METHODS

We conducted a review of systematic reviews published in English, following Preferred Reporting Items for Systematic Reviews and Meta‐analyses reporting guideline for systematic reviews.[8] A protocol describing the review plan was posted to a public website before the study was initiated.[9] From an initial review of the literature, we recognized that most systematic reviews typically either examined different transitional care intervention types in a given patient population, or examined a given intervention type in a variety of patient populations. We use the term intervention type to refer to single‐ or multicomponent interventions that used a similar approach or bundle of care processes (eg, telemonitoring, hospital‐at‐home), or addressed a similar key process of the care transition (eg, medication reconciliation). Patient populations are defined according to clinical condition (eg, congestive heart failure) or demographic characteristics (eg, geriatric). Given that the review was originally commissioned by the VHA, we excluded pediatric and obstetric patient populations.

We identified categories of patient populations and intervention types with input from a panel of content experts, an initial scan of the literature, and with input from our study team to help guide our literature search (see Supporting Information, Appendix A, in the online version of this article). We searched PubMed and Cochrane databases of systematic reviews from database inception through May 2014.

We selected reviews that reported hospital readmissions as an outcome, regardless of whether it was the primary outcome. However, we summarized other outcomes reported by each review. Within each patient population or intervention type of interest, we first identified reviews that fulfilled key quality criteria: (1) clearly reported their search strategy, (2) reported inclusion and exclusion criteria, and (3) conducted an appraisal of the internal validity of the included trials.[10, 11] If there was more than 1 review within each category fulfilling these criteria, we prioritized the most recent review and those with the broadest scope. We discussed the ultimate choice of review as a group and resolved any disagreements through consensus. One author abstracted prespecified data from each review and a second author checked entries for accuracy (see Supporting Information, Appendix B, in the online version of this article).

We qualitatively synthesized the literature, using the categories of intervention type, patient population, and healthcare setting to organize our synthesis. We further identified common themes that cut across different intervention types and patient populations related to the following characteristics (derived from an existing taxonomy):[12] transition type (hospital to home, hospital to nursing facility), intervention target (patient, caregiver), key processes (education, personal health record), key personnel involved (nurse, social worker), method of postdischarge follow‐up (phone, home visits), and intensity and complexity. We developed brief narrative summaries of findings for each review. These narratives were compiled into a single document and reviewed independently by each of the authors of this report, who then compiled a brief list of key cross‐cutting themes in the evidence.

RESULTS

We reviewed 807 titles and abstracts from the electronic search, and identified an additional 94 from reviewing reference lists and performing manual searches for recently published and unpublished or ongoing studies (Figure 1). Eighty‐one systematic reviews met our inclusion criteria and, of these, we selected 17 that were the most recent and broadly scoped: 10 of intervention types (Table 1) and 7 of patient populations (Table 2).

Systematic Reviews of Different Types of Interventions
Systematic Review, Sample Characteristics, Search Dates

N Controlled Trials (N Total Studies), N = Total Patients in RCTs

Summary Estimate for Readmission Risk (95% CI) Summary Estimate for Mortality (95% CI) Other Outcomes (Clinical and Utilization) Quality Assessment Method, Range of Scores
  • NOTE: Abbreviations: AHRQ, Agency for Healthcare Research & Quality; CI, confidence interval; CGA, comprehensive geriatric assessment; DC, discharge; ED, emergency department; EPOC, Cochrane Effective Practice and Organisation of Care Group; ER, emergency room; ERAS, enhanced recovery after surgery; GP, general practice; GRADE, grading of recommendations assessment, development, and evaluation; HF, heart failure; HR, hazard ratio; LOS, length of stay; N, number of (studies/subjects); NR, not reported; OR, odds ratio; PCMH, patient‐centered medical home; QOL, quality of life; RCTs, randomized controlled trials; ROB, risk of bias; RR, relative risk; STS, structured telephone support; STS HH, structured telephone support delivered by human‐to‐human contact; STS HM, structured telephone support delivered by human‐to‐machine interface; TM, telemonitoring; UC, usual care.

Geriatric case management (community dwelling, age 65+ years), Huntley, 2013,[34] 19502010

11 RCTs

(11 studies total), N = 4318

0.71 (0.49 to 1.03)

Combined estimate NR.

Mortality (5 studies) was not significantly different based on case management.

Clinical: NR. Other utilization: ED visits, GP visits, specialist clinic/outpatient visits, and LOS were not improved by case management in all but 1 study. Cochrane ROB. Risk of bias was generally low. Most studies had low or unclear ROB in all categories except 1 study that had high ROB in 3 categories.
Geriatric case assessment (age 65+ years), Ellis, 2011,[26]

19662010

22 RCTs

(22 studies total), N = 10,315

No difference between groups, N = 3822. OR 1.03 (0.89 to 1.18)

Death or functional decline, combined outcome:

0.76 (0.64 to 0.90, P = 0.001) based on data from 5 RCTs, N = 2622

Clinical: significant improvement in cognitive function associated with CGA based on 5 trials. There were nonsignificant differences for dependence. Other utilization: costs were mixed. Few trials accounted for nursing home costs; those that did suggested that CGA might be associated with overall reduced cost. Cochrane ROB. The studies identified were heterogeneous in quality. All used some method of individual patient randomization, though reporting of key issues such as allocation concealment varied. Outcome assessment was seldom blinded though this is less of an issue for hard outcomes such as death or institutionalization. Some trials noted attrition for functional or cognitive outcomes.
Discharge planning (mostly older medical, though some studies included surgery, psych), Shepperd, 2013,[13] 19462012 24 RCTs (24 studies total), N = 8098 Within 3 months of discharge: 0.82 (0.73 to 0.92) for older patients with a medical condition. No difference was found when mixed medical and surgical populations were included.

At 69 months:

0.99 (0.78 to 1.25)

Clinical: QOL outcomes were mixed. Other utilization: lower medical LOS in 10 trials. No change in surgical LOS (2 trials) Cochrane ROB. Low ROB: n = 9, medium ROB: n = 9, high ROB: n = 5, unclear ROB: n = 1
ERAS/fast track (postpancreatic surgery), Kagedan, 2015,[35] 20002013 0 trials or RCTs (10 studies total), N = 0 (no RCTs) Range among studies in % of patients readmitted, ERAS vs UC: (3.515) vs (025)

Range (% of patients), ERAS vs UC:

(04) vs (03)

Clinical: NR. Other utilization: 2/4 studies that examining costs showed reduction, 2/4 no change

GRADE (low, moderate, high).

No high‐quality studies were identified. Cohort studies comparing multiple groups were labelled as being of moderate quality. Single‐group prospective studies were graded as low quality. Moderate quality: n = 7, low quality: n = 3

Hospital at home, Caplan, 2012,[14] database inception through 2012 61 RCTs (61 studies total), N = 6992 0.75 (0.59 to 0.95) 0.81 (0.69 to 0.95)

Clinical: consistent higher satisfaction (21/22 studies reporting patient satisfaction, 6/8 studies reporting CG satisfaction). No difference in caregiver burden (7 studies).

Other utilization: mean cost lower (11 RCTS):

1567.11

(2069.53 to 1064.69, P < 0.001). Average cost savings 26.5%, 32/34 studies concluded HAH was less expensive.

EPOC criteria. Quality ratings not reported. Almost all studies were not blinded. However, many studies used blinded initial assessments before randomisation. Some outcome assessment was blinded.
Medication reconciliation, Kwan, 2013,[15] 19802012 5 RCTs (18 studies total), N = 1075 ER visits and hospitalizations within 30 days of discharge in 3 RCTs, HR: 0.77 (0.63 to 0.95) NR Clinical: NR. Other utilization: NR Cochrane ROB. Low ROB: n = 5 RCTs
PCMH, Jackson, 2013,[36] database inception through June 2012 9 RCTs (19 studies total), N = 54,465 0.96 (0.84 to 1.10) NR Clinical: NR. Other utilization: 3 RCTs reporting ED utilization found no effect. Combined RR: 0.93 (95% CI: 0.72 to 1.20). AHRQ (good, fair, poor quality). All but 1 study were rated as being good or fair quality.
Telemonitoring and structured telephone support (heart failure)

Pandor, 2013,[22] 19992011

21 RCTs (21 studies total), N = 6317

Median HR (credible interval, 2.5% to 97.5%).

All to cause:

STS HH: 0.97 (0.70 to 1.31). TM office hours (transmitted data reviewed by medical staff during office hours): 0.75 (0.49 to 1.10). HF to related:

STS HH: 0.77 (0.62 to 0.96). TM office hours: 0.95 (0.70 to 1.34)

Median HR

(credible interval, 2.5% to 97.5%):

STS HH vs UC: 0.77 (0.55 to 1.08). TM office hours vs UC: 0.76 (0.49 to 1.18)

Clinical: QOL improved in 3 of 4 studies of STS interventions, and 2 of 4 studies of telemonitoring interventions.

Other utilization: HF‐related hospitalizations: no change for STS HM and TM office hours; reduced with STS HH 0.76 (0.61 to 0.94).

Five of 6 studies found no change in LOS, 1 showed reduced.

Study quality not reported individually. The methodological quality of the 21 included studies varied widely and reporting was generally poor on random sequence generation, allocation concealment, blinding of outcome assessment, definition and confirmation of HF diagnosis, and intention‐to‐treat analysis.
Telephone follow‐up, primary‐care based, Crocker 2012,[21] 19482011 3 RCTs (3 studies total), N = 1765 Combined estimate NR. None of the 3 RCTs reported a statistically significant impact of telephone follow‐up on readmission or ER visits. NR Clinical: NR. Other utilization: In all 3 included studies, primary care contact improved with postdischarge telephone follow‐up. Two studies examining ED visits showed no effect. Study quality not reported individually: assessed sequence generation, allocation concealment, blinding, follow‐up and intent to treat analysis, and publication bias. Most studies were high or unclear ROB based on poor reporting of sequence generation, allocation concealment; lack of blinding; and lack of information about attrition.
Telephone follow‐up, hospital‐based (unselected with cardiac and surgical subgroup analyses), Mistiaen, 2006,[20] database inception through July 2003

13 RCTs

(33 studies total), N = 5110

Cardiac (3 RCTs, N = 616): 0.75 (0.41 to 1.36). Surgical (4 RCTs, N = 460): 0.65 (0.28 to 1.55) NR Clinical: No change in anxiety 1 month post‐DC in cardiac surgery patients in pooled effect from 3 studies. No change in depression based on 2 studies. Other utilization: no change in ED visits in surgery patients (pooled from 2 studies) Cochrane ROB. Medium ROB: n = 7. High ROB: n = 26
Systematic Reviews of Care Transition Intervention Studies in Specific Patient Populations
Systematic Review, Sample Characteristics, Search Dates

N Controlled Trials (N Total Studies), N = Total Patients in RCTs

Summary Estimate for Readmission Risk (95% CI)

Summary Estimate for Mortality (95% CI) Other Outcomes (Clinical and Utilization) Quality Assessment Method, Range of Scores
  • NOTE: Abbreviations: ACS, acute coronary syndrome; ADLs, activities of daily living; AHRQ, Agency for Healthcare Research & Quality; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive pulmonary disease; EPOC, Cochrane Effective Practice and Organisation of Care Group; MDS‐HF, multidisciplinary heart failure; MI, myocardial infarction; N, number of (studies/subjects); NR, not reported; RCTs, randomized controlled trials; ROB, risk of bia~s; RR, relative risk.

Acute MI/acute coronary syndrome, Auer, 2008,[25] 19662007

16 controlled trials, including

14 RCTs (26 studies total), N = 1910 from RCTs

612 months: 0.96 (0.79 to 1.17) All causes: 0.94 (0.63 to 1.40). All causes at 1 year: 0.94 (0.63 to 1.44) Clinical: re‐infarction rates: RR 0.51 (95% CI: 0.23 to 1.1). Smoking cessation: RR 1.29 (1.02 to 1.63, I2 = 66%). Other utilization: NR

Modified Jadad score

3 (lowest ROB category): n = 8, 2: n = 5; 1 (highest ROB category): n = 3. Before‐after designs: n = 12 (no formal ROB assessment)

Cancer, Smeenk, 1998,[37] 19851997

5 RCTs (9 studies total)

N = 4249

Range of ratios for readmission (%) in intervention group/ control group: 0.621.12. Combined estimate NR. Timing of readmission assessment NR. NR Clinical: quality of life outcomes were positively associated with home‐care programs in 3 of 7 studies. Other utilization: NR

Weighted methodological quality score (0100 max):

Range: 4868. All considered moderate quality

CHF (moderate‐severe, geriatric), Feltner, 2014,[16] 19902013

47 RCTs (47 studies total)

N = 8693

Combined RR (95% CI) by intervention type; results from single studies per intervention type not included below:

Home‐visiting program, 36 months: 0.75 (0.66 to 0.86). Structured telephone support, 36 months:

0.92 (0.77 to 1.10).

Telemonitoring, 36 months: 1.11 (0.87 to 1.42). Clinic‐based (MDS‐HF), 6 months: 0.70 (0.55 to 0.89)

Combined RR (95% CI) by intervention type; results from single studies per intervention type not included below:

Home‐visiting program,

36 months: 0.77 (0.60 to 0.996). Structured telephone support,

3.6 months: 0.69 (0.51 to 0.92). Clinic‐based (MDS‐HF), 6 months: 0.56 (0.34 to 0.92)

Clinical: NR. Other utilization: NR

AHRQ ROB for trials.

Low ROB: n = 6, medium ROB: n = 27, high ROB: n = 9, unclear ROB: n = 5

COPD, Prieto‐Centurion, 2014,[27] 19662013

5 RCTs (5 studies total)

N = 1393

2 studies found reduced 12‐month readmissions (mean number of hospitalizations per patient, 1.0 vs 1.8; P = 0.01; percent hospitalized, 45% vs 67%; P = 0.028).

Three studies found no significant change in 6‐ or 12‐month readmissions.

4 of 5 studies: no difference. 1 study: increased 12‐month mortality (17% vs 7%, P = 0.003) Clinical: NR. Other utilization: NR EPOC criteria (no. domains with low ROB: 17 max). 6: n = 4, 5: n = 1
General/unselected, Leppin, 2014,[24] 19902013 42 RCTs (42 studies total), N = 17,273 30 days: 0.82 (0.73 to 0.91) NR Clinical: NR. Other utilization: NR EPOC ROB (high, low, unclear). Most studies were at overall low risk of bias. The most common methodological limitation of these trials was the lack of a reliable method for dealing with missing data. Eight of 42 studies were rated as low ROB in all categories; all others were rated as high or unclear ROB in 1 or more categories.
Mental health admissions, Vigod, 2013,[38] database inception through 2012

13 controlled trials, including

8 RCTs (15 studies total)

N = 1007 (RCTs)

Range among studies in % of patients readmitted, intervention group vs control: 3 month: 7%23% vs 13%36%, 624 month: 0%63% vs 4%69% NR Clinical: NR. Other utilization: NR

EPOC criteria. No. of domains with low ROB (19 max): range 38.

Most included studies had small sample sizes, high dropout rates, and/or did not account for baseline differences between groups on key prognostic factors.

Stroke or ACS, Prvu Bettger, 2012,[18] 20002012

24 RCTs stroke, 8 RCTs MI (44 studies total:

27 stroke, 17 MI), N = 4307 stroke, N = 1062 MI

Insufficient evidence for most intervention subtypes in both stroke and MI. Moderate strength evidence that hospital‐initiated support did not reduce readmissions in stroke patients. Timing of readmission assessment NR. Low strength evidence in MI patients: reduced 3 month mortality (1 study), reduced 12 month mortality (2 studies)

Clinical: No significant differences in ADLs.

Inconsistent effects on caregiver strain, quality of life in 5 studies measuring caregiver outcomes. Other utilization: NR

AHRQ (good, fair, poor quality). Good: n = 10, fair: n = 42, poor: n = 10. Strength of evidence insufficient for all intervention/population subgroups except as noted.
Figure 1
Literature flow diagram.

Intervention Types

Among reviews focused on specific intervention types (Table 1), several show promise in reducing readmissions and/or mortality.[13, 14, 15, 16] There is moderate‐strength evidence that structured and individually tailored discharge planning reduces readmissions within 90 days (relative risk [RR]: 0.82, 95% confidence interval [CI]: 0.73 to 0.92) and hospital length of stay (0.91 days, 95% CI: 1.55 to 0.27).[13] However, most of the benefit was seen among studies of robust interventions that included a combination of care processes. In 9 of the interventions, a nurse advocate helped with discharge planning activities and care coordination. Twelve of the interventions included postdischarge follow‐up.

Moderate strength evidence from 61 trials found that hospital‐at‐home interventions were associated with reductions in 30‐day readmissions (RR: 0.75, 95% CI: 0.59 to 0.95) and mortality (RR: 0.81, 95% CI: 0.69 to 0.95).[14] Frequently, specific components of the included interventions were not well described, and periods of observation for outcomes were not specified. Interventions were associated with greater patient and caregiver satisfaction in the vast majority of studies reporting such outcomes.

The impact of medication reconciliation interventions on clinically significant adverse drug events was variable.[15] Readmissions and emergency room visits were reduced (RR: 0.77, 95% CI: 0.0.63 to 0.95) in 3 trials, but this reduction was driven by 1 intervention that included additional care processes such as postdischarge follow‐up.[17] Interventions focused solely on medication reconciliation around the time of discharge were not effective.

One review of patients with stroke or myocardial infarction (MI) described 5 intervention types: hospital‐based discharge preparation, hospital‐based patient and family education, community‐based patient and family education, community‐based models of support interventions, and chronic disease management models of care.[18] They found moderate‐strength evidence that early supported discharge of stroke patients (short hospital stay followed by intensive home care with a multidisciplinary team) shortened length of stay without adversely impacting readmissions or mortality. Specialty care after an MI was associated with reduced mortality, but the strength of evidence was low, being largely based on 1 Veterans Affairs observational study.[19] There was insufficient evidence examining the other types of interventions in this review.

Two reviews examined the effects of postdischarge follow‐up calls in unselected populations. An older Cochrane review from 2006 focused on calls performed by hospital‐based personnel.[20] Though 33 studies including 5110 patients were included in this review, there was inconclusive evidence of the effectiveness of these interventions, largely because of methodological limitations in most included studies. A more recent review similarly concluded there was insufficient evidence of the effects of postdischarge calls on utilization in 3 studies, though they did find that the interventions were associated with higher rates of primary care engagement.[21]

One review focused on postdischarge remote monitoring in patients with congestive heart failure (CHF)[22, 23] via structured telephone support (STS) or telemonitoring. STS interventions typically included periodic scripted telephone calls from nurses to review symptoms, interval physiologic data such as weight, and self‐management skills. Telemonitoring focused on remote transfer of physiologic data, with phone contact when abnormal vital signs or weights occurred. STS interventions reduced long‐term (6 months), but not short‐term (23 months) heart failure readmissions, and were associated with reduced long‐term mortality.[16, 23] Though 1 review noted a trend toward reduced mortality with telemonitoring interventions, both reviews noted the substantial methodological shortcomings of this literature and the inconsistency of results across studies. There was insufficient evidence of the comparative effectiveness between STS and telemonitoring interventions.[16]

One review of CHF patients categorized interventions into 6 types: home‐visiting programs, STS, telemonitoring, outpatient clinic‐based (including multidisciplinary CHF clinics), primarily educational, and other.[16] This review found moderate‐strength evidence that interventions with multidisciplinary heart failure (HF) clinic visits or home visits reduced both all‐cause readmissions and mortality, with number needed to treat below 10 for readmission and 18 to 33 for mortality (for multidisciplinary heart failure clinic and home visiting programs, respectively). STS interventions produced a similar mortality benefit but did not reduce all‐cause readmissions.

Healthcare Setting

We found no evidence directly examining whether intervention effectiveness depends on factors such as the presence of a shared electronic medical record, access to community resources, integration of primary and hospital care, and the presence of a medical home. Moreover, the transitional care literature generally has provided only scant descriptions of the health system context of the interventions.

Patient Population

The relative importance of careful patient selection, as compared to intervening on an unselected group of patients, is unclear. Many studies in these reviews used inclusion criteria that selected patients who were at high risk for readmission because of older age, significant medical comorbidity, and/or a history of high utilization. However, few reviews explicitly examined variation of intervention effects based on patient criteria.

The characteristics and findings of reviews of specific patient populations are shown in Table 2. One review found studies that did and did not use high‐risk patient selection criteria had similar results.[15] A metaregression of trials including general medical or CHF populations did not find significantly different effects between studies without age restrictions and those that included only patients over 65 years of age (interaction P = 0.24).[24] Similarly, a review of hospital‐at‐home studies did not find a clear difference in effects among studies in patients younger than 70 years old, between ages 70 and 73 years, and older than 74 years.[14]

Some of the reviews also speculated that focusing on specific groups of patients allowed disease‐specific customization of interventions and supported expertise development. For example, 1 review found that interventions in acute MI patients, which focused on effective use of disease‐specific medications, were associated with a mortality benefit, though this was largely driven by 1 study.[25] Another review examining comprehensive geriatric assessment interventions found that gains in the combined outcome of mortality and functional decline were only associated with interventions delivered in a geriatric ward setting.[26] The authors speculate that the multidisciplinary team of providers developed more expertise and facility with the patient population.

We found insufficient evidence to determine whether transitional care affects specific patient populations differently. Although there were successful interventions in CHF patients and no consistent evidence of benefit in chronic obstructive pulmonary disease (COPD) patients, it is unclear whether these differences were due to the markedly different types of interventions examined or to the choice of population itself.[16, 27] Populations with chronic medical illnesses were well represented in the literature, although there was a dearth of evidence in mental illness or surgical populations.

Cross‐cutting Themes

Across different intervention types, patient populations, and settings, successful interventions tended to be more comprehensive, involve more aspects of the care transition, and include components before and after hospital discharge. Successful interventions also tended to be flexible enough to accommodate individual patient needs. However, the strength of evidence supporting these overarching conclusions should be considered low because these are indirect, post hoc comparisons across literature that includes many different intervention types, studied in varied populations and clinical settings, and implemented in different ways. We found very few comparative effectiveness studies among the included reviews.

As noted above, the effective discharge planning and medication reconciliation interventions were those that included additional personnel and spanned care settings.[13, 17] In contrast, interventions in COPD populations did not consistently reduce readmissions or mortality, but the interventions began after hospital discharge and frequently omitted some care processes such as discharge planning that are often 1 component of successful interventions in other populations.[27]

One review created a comprehensive support variable that was based on number of patient interactions, number of personnel involved, number of intervention components, and the ability of the intervention to address self‐management needs.[24] A metaregression including 42 trials, the vast majority of which included general medical patients or patients with CHF and were considered to be methodologically sound, found interventions were overall associated with reductions in readmissions (pooled RR: 0.82, 95% CI: 0.73 to 0.91), and interventions with the most comprehensive support accounted for most of the benefit (RR readmission in the 7 studies with highest comprehensive support scores compared to 15 studies with the lowest scores: 0.63, 95% CI: 0.43 to 0.91).[24]

In a review of 47 trials in CHF patients, the key processes of care that seemed to be associated with reduced readmissions included: self‐management education delivered in person, early postdischarge contact, a point of postdischarge contact, and the ability to individually tailor the intervention.[16]

It is unclear whether home visits are a necessary component of transitional care interventions. A meta‐analysis of trials including general medicine or CHF patients did not find that the setting of care delivery influenced outcomes; however, all but 1 of the most comprehensive interventions included home visits in their model.[24] A review of CHF populations found interventions with multidisciplinary HF clinic visits or home visits reduced all‐cause readmissions and mortality, but found insufficient evidence directly comparing interventions with and without home visits.[16]

We found little evidence examining the impact of different transition types (most studies focused on hospital‐to‐home transitions), intervention targets (most studies focused on patients rather than caregivers), or key personnel involved.

DISCUSSION

We examined 17 systematic reviews across different patient populations representing a variety of intervention types to provide a broad overview of the care transitions literature. Variations in population studied, intervention definition, personnel, outcome definition, and setting make it difficult to identify strong evidence in support of a specific intervention type that should be broadly implemented. There were, however, some common themes that emerged across the literature suggesting that successful interventions addressed more aspects of the care transition, included the means to assess and respond to individual peridischarge needs, and included components that spanned care settings. In practical terms, the actualization of these themes has been accomplished in many interventions with the addition of transitional care personnel such as nurses and/or pharmacists. Additionally, interventions have often been tailored to the needs of individual patients with the use of needs assessment and patient‐centered personalized health records.[1]

Because there are many potential steps in the care transition, focusing on only 1 of these steps, such as medication reconciliation, is unlikely to have significant benefit on risk of readmission.[15] The pathways to readmission vary, as suggested both by the inability to accurately anticipate which patients will be readmitted,[28] and by case review studies characterizing underlying factors contributing to preventable readmissions.[29]

The problems with recommending that a specific intervention be broadly implemented include both the lack of evidence supporting such a recommendation and the likelihood that the transitional care gaps are not the same in all settings, or for all populations of patients treated. As health systems rapidly evolve, it may be useful for them to inventory strengths and weaknesses of their current approach to transitional care both to identify critical care gaps and to avoid investment in resource‐intensive transitional care interventions that may be redundant with existing activities.

Indeed, transitional care gaps may have changed over the last decade. Two large reviews showed that more recently published studies were less likely to have found an improvement in outcomes.[14, 24] In the years since some of the most successful and widely cited transitional care interventions were developed and evaluated, many health systems have undertaken major transformations, including the adoption of the patient‐centered medical home model and integration of electronic health records, which may implicitly address some earlier gaps. For instance, foundational qualitative work for the Care Transitions Measure identified discontinuities in information transfer as 1 of 4 major transitional care barriers identified by patients, and the personal health record was created, in part, to address this gap.[30] A shared electronic health record across healthcare settings has the potential to mitigate some of these concerns.

In general, there is an overarching need for better evidence to guide selection and implementation of complex, multicomponent transitional care interventions in different settings. There remain a number of gaps regarding the operationalization of interventions. For instance, the optimal choice of personnel, the comparative effects of home visits and other forms of postdischarge follow‐up, and the best approach to patient selection (whether through use of a formal readmission risk assessment model or a focus on populations with high‐risk comorbidities) are unknown.

One of the major weaknesses of the transitional care literature is the marked variation in intervention definitions, timing of outcome follow‐up, and descriptions of interventions and usual care. Use of taxonomies to guide study design and description may help standardize reporting.

Most of the care transitions literature has been hospital‐focused, and the interventions often extend hospital services beyond hospitalization. Given the growth of medical homes, it will be important to examine the effectiveness of outpatient‐based care transitions models that reach‐in to the hospital. Studies comparing approaches such as home‐visit and telephone‐based interventions, different risk‐prioritization schemes, and the use of different types of personnel are also needed.

There is very little literature examining transitional care interventions in patients with mental health conditions or undergoing surgery. A recent report for the Veterans Health Administration found that 24% of patients with chronic mental health conditions are readmitted within 30 days of discharge.[31] About 1 in 7 Medicare patients admitted to a surgical service is readmitted within 30 days.[32] The transitional care needs of these populations may differ substantially from medical populations and warrant further study.

Our review has a number of important limitations. Our overview of the literature was necessarily broad rather than in‐depth. There are many nuances in the results, internal validity, and generalizability of studies that are not represented in our overview. It was difficult to use established criteria to formally rate the strength of evidence for each of our conclusions, but we indicated strength of evidence ratings when reported in reviews. As we note in the results, our assessment of cross‐cutting themes is based largely on low‐strength evidence, given the indirect comparisons and the many factors that varied among the included studies. Our inclusion criteria specified readmissions as an outcome, but there are care transitions that focus exclusively on other outcomes, such as smoking cessation interventions around the time of discharge.[33] Furthermore, there are many outpatient‐based interventions designed to affect emergency room and hospital utilization that are not captured in our review, but may nevertheless be important to understanding the role of care coordination in the context of the medical home. We did not systematically update the included reviews' searches, and there may be more recent studies not represented here, though we are not aware of newer studies that would substantively change our summary of findings.

CONCLUSIONS

The literature includes many different types of interventions, studied in varied populations and clinical settings, and implemented in different ways. Furthermore, there are very little comparative effectiveness data. It is therefore difficult to conclusively identify specific intervention components and characteristics that are necessary for successful care transitions. Effective interventions are generally more comprehensive, address more aspects of the care transition, extend beyond the hospital stay, and have the flexibility to respond to individual patient needs. Transitional care interventions have not been well studied in integrated health system settings, or in mental health and surgical populations.

Disclosures: The views expressed in this article are those of the authors and do not necessarily represent the views of the US Department of Veterans Affairs or the US government.

The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration (VHA) Project ESP 05‐225, VA#01‐0206. Dr. Jencks' work on this project was supported in part by a grant from the Quality Enhancement Research Initiative (05‐225), Department of Veterans Affairs. Dr. Jencks has reported prior consulting work with the following entities: Inovalon, Care Centrix, Affymax, Curaspan, Reinforced Care, Health Services Advisory Group, Delmarva Foundation, Connecticut Peer Review Organization, Maryland Health Services Cost Review Commission, Institute for Healthcare Improvement, American Association for Respiratory Care, Monaghan Medical, Iowa Society for Respiratory Care.

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  2. Coleman EA, Parry C, Chalmers S, Min S‐J. The care transitions intervention: results of a randomized controlled trial. Arch Intern Med. 2006;166(17):18221828.
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  12. Shepperd S, Lannin NA, Clemson LM, McCluskey A, Cameron ID, Barras SL. Discharge planning from hospital to home. Cochrane Database Syst Rev. 2013;1:CD000313.
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  14. Kwan JL, Lo L, Sampson M, Shojania KG. Medication reconciliation during transitions of care as a patient safety strategy: a systematic review. Ann Intern Med. 2013;158(5 pt 2):397403.
  15. Feltner C, Jones CD, Cene CW, et al. Transitional care interventions to prevent readmissions for persons with heart failure: a systematic review and meta‐analysis. Ann Intern Med. 2014;160(11):774784.
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Transitional care has been defined as a set of actions designed to ensure the coordination and continuity of healthcare as patients transfer between different locations or different levels of care within the same location.[1] Early studies showed that nurse‐led transitional care interventions beginning in the hospital and continuing after discharge had the potential to reduce the rate of hospital readmissions.[2, 3] Since then, the healthcare landscape has been evolving in important ways, with the spread of the electronic medical record, the patient‐centered medical home, and an increased push to health systems integration.[4, 5, 6]

The potential success or failure of transitional care interventions, which are inherently complex and can involve multiple components, may depend on the nature of the interventions themselves, the settings in which they were implemented, and/or the populations included. Health systems are faced with a large array of transitional care interventions and patient populations to whom such activities might apply.

The main aim of this article, culled from a larger report commissioned by the Veterans Health Administration (VHA)[7] was to catalogue which types of transitional care interventions hold promise and which populations have been best studied, to help health systems guide prioritization and adaptation of the most relevant transitional care activities and help focus future research efforts.

METHODS

We conducted a review of systematic reviews published in English, following Preferred Reporting Items for Systematic Reviews and Meta‐analyses reporting guideline for systematic reviews.[8] A protocol describing the review plan was posted to a public website before the study was initiated.[9] From an initial review of the literature, we recognized that most systematic reviews typically either examined different transitional care intervention types in a given patient population, or examined a given intervention type in a variety of patient populations. We use the term intervention type to refer to single‐ or multicomponent interventions that used a similar approach or bundle of care processes (eg, telemonitoring, hospital‐at‐home), or addressed a similar key process of the care transition (eg, medication reconciliation). Patient populations are defined according to clinical condition (eg, congestive heart failure) or demographic characteristics (eg, geriatric). Given that the review was originally commissioned by the VHA, we excluded pediatric and obstetric patient populations.

We identified categories of patient populations and intervention types with input from a panel of content experts, an initial scan of the literature, and with input from our study team to help guide our literature search (see Supporting Information, Appendix A, in the online version of this article). We searched PubMed and Cochrane databases of systematic reviews from database inception through May 2014.

We selected reviews that reported hospital readmissions as an outcome, regardless of whether it was the primary outcome. However, we summarized other outcomes reported by each review. Within each patient population or intervention type of interest, we first identified reviews that fulfilled key quality criteria: (1) clearly reported their search strategy, (2) reported inclusion and exclusion criteria, and (3) conducted an appraisal of the internal validity of the included trials.[10, 11] If there was more than 1 review within each category fulfilling these criteria, we prioritized the most recent review and those with the broadest scope. We discussed the ultimate choice of review as a group and resolved any disagreements through consensus. One author abstracted prespecified data from each review and a second author checked entries for accuracy (see Supporting Information, Appendix B, in the online version of this article).

We qualitatively synthesized the literature, using the categories of intervention type, patient population, and healthcare setting to organize our synthesis. We further identified common themes that cut across different intervention types and patient populations related to the following characteristics (derived from an existing taxonomy):[12] transition type (hospital to home, hospital to nursing facility), intervention target (patient, caregiver), key processes (education, personal health record), key personnel involved (nurse, social worker), method of postdischarge follow‐up (phone, home visits), and intensity and complexity. We developed brief narrative summaries of findings for each review. These narratives were compiled into a single document and reviewed independently by each of the authors of this report, who then compiled a brief list of key cross‐cutting themes in the evidence.

RESULTS

We reviewed 807 titles and abstracts from the electronic search, and identified an additional 94 from reviewing reference lists and performing manual searches for recently published and unpublished or ongoing studies (Figure 1). Eighty‐one systematic reviews met our inclusion criteria and, of these, we selected 17 that were the most recent and broadly scoped: 10 of intervention types (Table 1) and 7 of patient populations (Table 2).

Systematic Reviews of Different Types of Interventions
Systematic Review, Sample Characteristics, Search Dates

N Controlled Trials (N Total Studies), N = Total Patients in RCTs

Summary Estimate for Readmission Risk (95% CI) Summary Estimate for Mortality (95% CI) Other Outcomes (Clinical and Utilization) Quality Assessment Method, Range of Scores
  • NOTE: Abbreviations: AHRQ, Agency for Healthcare Research & Quality; CI, confidence interval; CGA, comprehensive geriatric assessment; DC, discharge; ED, emergency department; EPOC, Cochrane Effective Practice and Organisation of Care Group; ER, emergency room; ERAS, enhanced recovery after surgery; GP, general practice; GRADE, grading of recommendations assessment, development, and evaluation; HF, heart failure; HR, hazard ratio; LOS, length of stay; N, number of (studies/subjects); NR, not reported; OR, odds ratio; PCMH, patient‐centered medical home; QOL, quality of life; RCTs, randomized controlled trials; ROB, risk of bias; RR, relative risk; STS, structured telephone support; STS HH, structured telephone support delivered by human‐to‐human contact; STS HM, structured telephone support delivered by human‐to‐machine interface; TM, telemonitoring; UC, usual care.

Geriatric case management (community dwelling, age 65+ years), Huntley, 2013,[34] 19502010

11 RCTs

(11 studies total), N = 4318

0.71 (0.49 to 1.03)

Combined estimate NR.

Mortality (5 studies) was not significantly different based on case management.

Clinical: NR. Other utilization: ED visits, GP visits, specialist clinic/outpatient visits, and LOS were not improved by case management in all but 1 study. Cochrane ROB. Risk of bias was generally low. Most studies had low or unclear ROB in all categories except 1 study that had high ROB in 3 categories.
Geriatric case assessment (age 65+ years), Ellis, 2011,[26]

19662010

22 RCTs

(22 studies total), N = 10,315

No difference between groups, N = 3822. OR 1.03 (0.89 to 1.18)

Death or functional decline, combined outcome:

0.76 (0.64 to 0.90, P = 0.001) based on data from 5 RCTs, N = 2622

Clinical: significant improvement in cognitive function associated with CGA based on 5 trials. There were nonsignificant differences for dependence. Other utilization: costs were mixed. Few trials accounted for nursing home costs; those that did suggested that CGA might be associated with overall reduced cost. Cochrane ROB. The studies identified were heterogeneous in quality. All used some method of individual patient randomization, though reporting of key issues such as allocation concealment varied. Outcome assessment was seldom blinded though this is less of an issue for hard outcomes such as death or institutionalization. Some trials noted attrition for functional or cognitive outcomes.
Discharge planning (mostly older medical, though some studies included surgery, psych), Shepperd, 2013,[13] 19462012 24 RCTs (24 studies total), N = 8098 Within 3 months of discharge: 0.82 (0.73 to 0.92) for older patients with a medical condition. No difference was found when mixed medical and surgical populations were included.

At 69 months:

0.99 (0.78 to 1.25)

Clinical: QOL outcomes were mixed. Other utilization: lower medical LOS in 10 trials. No change in surgical LOS (2 trials) Cochrane ROB. Low ROB: n = 9, medium ROB: n = 9, high ROB: n = 5, unclear ROB: n = 1
ERAS/fast track (postpancreatic surgery), Kagedan, 2015,[35] 20002013 0 trials or RCTs (10 studies total), N = 0 (no RCTs) Range among studies in % of patients readmitted, ERAS vs UC: (3.515) vs (025)

Range (% of patients), ERAS vs UC:

(04) vs (03)

Clinical: NR. Other utilization: 2/4 studies that examining costs showed reduction, 2/4 no change

GRADE (low, moderate, high).

No high‐quality studies were identified. Cohort studies comparing multiple groups were labelled as being of moderate quality. Single‐group prospective studies were graded as low quality. Moderate quality: n = 7, low quality: n = 3

Hospital at home, Caplan, 2012,[14] database inception through 2012 61 RCTs (61 studies total), N = 6992 0.75 (0.59 to 0.95) 0.81 (0.69 to 0.95)

Clinical: consistent higher satisfaction (21/22 studies reporting patient satisfaction, 6/8 studies reporting CG satisfaction). No difference in caregiver burden (7 studies).

Other utilization: mean cost lower (11 RCTS):

1567.11

(2069.53 to 1064.69, P < 0.001). Average cost savings 26.5%, 32/34 studies concluded HAH was less expensive.

EPOC criteria. Quality ratings not reported. Almost all studies were not blinded. However, many studies used blinded initial assessments before randomisation. Some outcome assessment was blinded.
Medication reconciliation, Kwan, 2013,[15] 19802012 5 RCTs (18 studies total), N = 1075 ER visits and hospitalizations within 30 days of discharge in 3 RCTs, HR: 0.77 (0.63 to 0.95) NR Clinical: NR. Other utilization: NR Cochrane ROB. Low ROB: n = 5 RCTs
PCMH, Jackson, 2013,[36] database inception through June 2012 9 RCTs (19 studies total), N = 54,465 0.96 (0.84 to 1.10) NR Clinical: NR. Other utilization: 3 RCTs reporting ED utilization found no effect. Combined RR: 0.93 (95% CI: 0.72 to 1.20). AHRQ (good, fair, poor quality). All but 1 study were rated as being good or fair quality.
Telemonitoring and structured telephone support (heart failure)

Pandor, 2013,[22] 19992011

21 RCTs (21 studies total), N = 6317

Median HR (credible interval, 2.5% to 97.5%).

All to cause:

STS HH: 0.97 (0.70 to 1.31). TM office hours (transmitted data reviewed by medical staff during office hours): 0.75 (0.49 to 1.10). HF to related:

STS HH: 0.77 (0.62 to 0.96). TM office hours: 0.95 (0.70 to 1.34)

Median HR

(credible interval, 2.5% to 97.5%):

STS HH vs UC: 0.77 (0.55 to 1.08). TM office hours vs UC: 0.76 (0.49 to 1.18)

Clinical: QOL improved in 3 of 4 studies of STS interventions, and 2 of 4 studies of telemonitoring interventions.

Other utilization: HF‐related hospitalizations: no change for STS HM and TM office hours; reduced with STS HH 0.76 (0.61 to 0.94).

Five of 6 studies found no change in LOS, 1 showed reduced.

Study quality not reported individually. The methodological quality of the 21 included studies varied widely and reporting was generally poor on random sequence generation, allocation concealment, blinding of outcome assessment, definition and confirmation of HF diagnosis, and intention‐to‐treat analysis.
Telephone follow‐up, primary‐care based, Crocker 2012,[21] 19482011 3 RCTs (3 studies total), N = 1765 Combined estimate NR. None of the 3 RCTs reported a statistically significant impact of telephone follow‐up on readmission or ER visits. NR Clinical: NR. Other utilization: In all 3 included studies, primary care contact improved with postdischarge telephone follow‐up. Two studies examining ED visits showed no effect. Study quality not reported individually: assessed sequence generation, allocation concealment, blinding, follow‐up and intent to treat analysis, and publication bias. Most studies were high or unclear ROB based on poor reporting of sequence generation, allocation concealment; lack of blinding; and lack of information about attrition.
Telephone follow‐up, hospital‐based (unselected with cardiac and surgical subgroup analyses), Mistiaen, 2006,[20] database inception through July 2003

13 RCTs

(33 studies total), N = 5110

Cardiac (3 RCTs, N = 616): 0.75 (0.41 to 1.36). Surgical (4 RCTs, N = 460): 0.65 (0.28 to 1.55) NR Clinical: No change in anxiety 1 month post‐DC in cardiac surgery patients in pooled effect from 3 studies. No change in depression based on 2 studies. Other utilization: no change in ED visits in surgery patients (pooled from 2 studies) Cochrane ROB. Medium ROB: n = 7. High ROB: n = 26
Systematic Reviews of Care Transition Intervention Studies in Specific Patient Populations
Systematic Review, Sample Characteristics, Search Dates

N Controlled Trials (N Total Studies), N = Total Patients in RCTs

Summary Estimate for Readmission Risk (95% CI)

Summary Estimate for Mortality (95% CI) Other Outcomes (Clinical and Utilization) Quality Assessment Method, Range of Scores
  • NOTE: Abbreviations: ACS, acute coronary syndrome; ADLs, activities of daily living; AHRQ, Agency for Healthcare Research & Quality; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive pulmonary disease; EPOC, Cochrane Effective Practice and Organisation of Care Group; MDS‐HF, multidisciplinary heart failure; MI, myocardial infarction; N, number of (studies/subjects); NR, not reported; RCTs, randomized controlled trials; ROB, risk of bia~s; RR, relative risk.

Acute MI/acute coronary syndrome, Auer, 2008,[25] 19662007

16 controlled trials, including

14 RCTs (26 studies total), N = 1910 from RCTs

612 months: 0.96 (0.79 to 1.17) All causes: 0.94 (0.63 to 1.40). All causes at 1 year: 0.94 (0.63 to 1.44) Clinical: re‐infarction rates: RR 0.51 (95% CI: 0.23 to 1.1). Smoking cessation: RR 1.29 (1.02 to 1.63, I2 = 66%). Other utilization: NR

Modified Jadad score

3 (lowest ROB category): n = 8, 2: n = 5; 1 (highest ROB category): n = 3. Before‐after designs: n = 12 (no formal ROB assessment)

Cancer, Smeenk, 1998,[37] 19851997

5 RCTs (9 studies total)

N = 4249

Range of ratios for readmission (%) in intervention group/ control group: 0.621.12. Combined estimate NR. Timing of readmission assessment NR. NR Clinical: quality of life outcomes were positively associated with home‐care programs in 3 of 7 studies. Other utilization: NR

Weighted methodological quality score (0100 max):

Range: 4868. All considered moderate quality

CHF (moderate‐severe, geriatric), Feltner, 2014,[16] 19902013

47 RCTs (47 studies total)

N = 8693

Combined RR (95% CI) by intervention type; results from single studies per intervention type not included below:

Home‐visiting program, 36 months: 0.75 (0.66 to 0.86). Structured telephone support, 36 months:

0.92 (0.77 to 1.10).

Telemonitoring, 36 months: 1.11 (0.87 to 1.42). Clinic‐based (MDS‐HF), 6 months: 0.70 (0.55 to 0.89)

Combined RR (95% CI) by intervention type; results from single studies per intervention type not included below:

Home‐visiting program,

36 months: 0.77 (0.60 to 0.996). Structured telephone support,

3.6 months: 0.69 (0.51 to 0.92). Clinic‐based (MDS‐HF), 6 months: 0.56 (0.34 to 0.92)

Clinical: NR. Other utilization: NR

AHRQ ROB for trials.

Low ROB: n = 6, medium ROB: n = 27, high ROB: n = 9, unclear ROB: n = 5

COPD, Prieto‐Centurion, 2014,[27] 19662013

5 RCTs (5 studies total)

N = 1393

2 studies found reduced 12‐month readmissions (mean number of hospitalizations per patient, 1.0 vs 1.8; P = 0.01; percent hospitalized, 45% vs 67%; P = 0.028).

Three studies found no significant change in 6‐ or 12‐month readmissions.

4 of 5 studies: no difference. 1 study: increased 12‐month mortality (17% vs 7%, P = 0.003) Clinical: NR. Other utilization: NR EPOC criteria (no. domains with low ROB: 17 max). 6: n = 4, 5: n = 1
General/unselected, Leppin, 2014,[24] 19902013 42 RCTs (42 studies total), N = 17,273 30 days: 0.82 (0.73 to 0.91) NR Clinical: NR. Other utilization: NR EPOC ROB (high, low, unclear). Most studies were at overall low risk of bias. The most common methodological limitation of these trials was the lack of a reliable method for dealing with missing data. Eight of 42 studies were rated as low ROB in all categories; all others were rated as high or unclear ROB in 1 or more categories.
Mental health admissions, Vigod, 2013,[38] database inception through 2012

13 controlled trials, including

8 RCTs (15 studies total)

N = 1007 (RCTs)

Range among studies in % of patients readmitted, intervention group vs control: 3 month: 7%23% vs 13%36%, 624 month: 0%63% vs 4%69% NR Clinical: NR. Other utilization: NR

EPOC criteria. No. of domains with low ROB (19 max): range 38.

Most included studies had small sample sizes, high dropout rates, and/or did not account for baseline differences between groups on key prognostic factors.

Stroke or ACS, Prvu Bettger, 2012,[18] 20002012

24 RCTs stroke, 8 RCTs MI (44 studies total:

27 stroke, 17 MI), N = 4307 stroke, N = 1062 MI

Insufficient evidence for most intervention subtypes in both stroke and MI. Moderate strength evidence that hospital‐initiated support did not reduce readmissions in stroke patients. Timing of readmission assessment NR. Low strength evidence in MI patients: reduced 3 month mortality (1 study), reduced 12 month mortality (2 studies)

Clinical: No significant differences in ADLs.

Inconsistent effects on caregiver strain, quality of life in 5 studies measuring caregiver outcomes. Other utilization: NR

AHRQ (good, fair, poor quality). Good: n = 10, fair: n = 42, poor: n = 10. Strength of evidence insufficient for all intervention/population subgroups except as noted.
Figure 1
Literature flow diagram.

Intervention Types

Among reviews focused on specific intervention types (Table 1), several show promise in reducing readmissions and/or mortality.[13, 14, 15, 16] There is moderate‐strength evidence that structured and individually tailored discharge planning reduces readmissions within 90 days (relative risk [RR]: 0.82, 95% confidence interval [CI]: 0.73 to 0.92) and hospital length of stay (0.91 days, 95% CI: 1.55 to 0.27).[13] However, most of the benefit was seen among studies of robust interventions that included a combination of care processes. In 9 of the interventions, a nurse advocate helped with discharge planning activities and care coordination. Twelve of the interventions included postdischarge follow‐up.

Moderate strength evidence from 61 trials found that hospital‐at‐home interventions were associated with reductions in 30‐day readmissions (RR: 0.75, 95% CI: 0.59 to 0.95) and mortality (RR: 0.81, 95% CI: 0.69 to 0.95).[14] Frequently, specific components of the included interventions were not well described, and periods of observation for outcomes were not specified. Interventions were associated with greater patient and caregiver satisfaction in the vast majority of studies reporting such outcomes.

The impact of medication reconciliation interventions on clinically significant adverse drug events was variable.[15] Readmissions and emergency room visits were reduced (RR: 0.77, 95% CI: 0.0.63 to 0.95) in 3 trials, but this reduction was driven by 1 intervention that included additional care processes such as postdischarge follow‐up.[17] Interventions focused solely on medication reconciliation around the time of discharge were not effective.

One review of patients with stroke or myocardial infarction (MI) described 5 intervention types: hospital‐based discharge preparation, hospital‐based patient and family education, community‐based patient and family education, community‐based models of support interventions, and chronic disease management models of care.[18] They found moderate‐strength evidence that early supported discharge of stroke patients (short hospital stay followed by intensive home care with a multidisciplinary team) shortened length of stay without adversely impacting readmissions or mortality. Specialty care after an MI was associated with reduced mortality, but the strength of evidence was low, being largely based on 1 Veterans Affairs observational study.[19] There was insufficient evidence examining the other types of interventions in this review.

Two reviews examined the effects of postdischarge follow‐up calls in unselected populations. An older Cochrane review from 2006 focused on calls performed by hospital‐based personnel.[20] Though 33 studies including 5110 patients were included in this review, there was inconclusive evidence of the effectiveness of these interventions, largely because of methodological limitations in most included studies. A more recent review similarly concluded there was insufficient evidence of the effects of postdischarge calls on utilization in 3 studies, though they did find that the interventions were associated with higher rates of primary care engagement.[21]

One review focused on postdischarge remote monitoring in patients with congestive heart failure (CHF)[22, 23] via structured telephone support (STS) or telemonitoring. STS interventions typically included periodic scripted telephone calls from nurses to review symptoms, interval physiologic data such as weight, and self‐management skills. Telemonitoring focused on remote transfer of physiologic data, with phone contact when abnormal vital signs or weights occurred. STS interventions reduced long‐term (6 months), but not short‐term (23 months) heart failure readmissions, and were associated with reduced long‐term mortality.[16, 23] Though 1 review noted a trend toward reduced mortality with telemonitoring interventions, both reviews noted the substantial methodological shortcomings of this literature and the inconsistency of results across studies. There was insufficient evidence of the comparative effectiveness between STS and telemonitoring interventions.[16]

One review of CHF patients categorized interventions into 6 types: home‐visiting programs, STS, telemonitoring, outpatient clinic‐based (including multidisciplinary CHF clinics), primarily educational, and other.[16] This review found moderate‐strength evidence that interventions with multidisciplinary heart failure (HF) clinic visits or home visits reduced both all‐cause readmissions and mortality, with number needed to treat below 10 for readmission and 18 to 33 for mortality (for multidisciplinary heart failure clinic and home visiting programs, respectively). STS interventions produced a similar mortality benefit but did not reduce all‐cause readmissions.

Healthcare Setting

We found no evidence directly examining whether intervention effectiveness depends on factors such as the presence of a shared electronic medical record, access to community resources, integration of primary and hospital care, and the presence of a medical home. Moreover, the transitional care literature generally has provided only scant descriptions of the health system context of the interventions.

Patient Population

The relative importance of careful patient selection, as compared to intervening on an unselected group of patients, is unclear. Many studies in these reviews used inclusion criteria that selected patients who were at high risk for readmission because of older age, significant medical comorbidity, and/or a history of high utilization. However, few reviews explicitly examined variation of intervention effects based on patient criteria.

The characteristics and findings of reviews of specific patient populations are shown in Table 2. One review found studies that did and did not use high‐risk patient selection criteria had similar results.[15] A metaregression of trials including general medical or CHF populations did not find significantly different effects between studies without age restrictions and those that included only patients over 65 years of age (interaction P = 0.24).[24] Similarly, a review of hospital‐at‐home studies did not find a clear difference in effects among studies in patients younger than 70 years old, between ages 70 and 73 years, and older than 74 years.[14]

Some of the reviews also speculated that focusing on specific groups of patients allowed disease‐specific customization of interventions and supported expertise development. For example, 1 review found that interventions in acute MI patients, which focused on effective use of disease‐specific medications, were associated with a mortality benefit, though this was largely driven by 1 study.[25] Another review examining comprehensive geriatric assessment interventions found that gains in the combined outcome of mortality and functional decline were only associated with interventions delivered in a geriatric ward setting.[26] The authors speculate that the multidisciplinary team of providers developed more expertise and facility with the patient population.

We found insufficient evidence to determine whether transitional care affects specific patient populations differently. Although there were successful interventions in CHF patients and no consistent evidence of benefit in chronic obstructive pulmonary disease (COPD) patients, it is unclear whether these differences were due to the markedly different types of interventions examined or to the choice of population itself.[16, 27] Populations with chronic medical illnesses were well represented in the literature, although there was a dearth of evidence in mental illness or surgical populations.

Cross‐cutting Themes

Across different intervention types, patient populations, and settings, successful interventions tended to be more comprehensive, involve more aspects of the care transition, and include components before and after hospital discharge. Successful interventions also tended to be flexible enough to accommodate individual patient needs. However, the strength of evidence supporting these overarching conclusions should be considered low because these are indirect, post hoc comparisons across literature that includes many different intervention types, studied in varied populations and clinical settings, and implemented in different ways. We found very few comparative effectiveness studies among the included reviews.

As noted above, the effective discharge planning and medication reconciliation interventions were those that included additional personnel and spanned care settings.[13, 17] In contrast, interventions in COPD populations did not consistently reduce readmissions or mortality, but the interventions began after hospital discharge and frequently omitted some care processes such as discharge planning that are often 1 component of successful interventions in other populations.[27]

One review created a comprehensive support variable that was based on number of patient interactions, number of personnel involved, number of intervention components, and the ability of the intervention to address self‐management needs.[24] A metaregression including 42 trials, the vast majority of which included general medical patients or patients with CHF and were considered to be methodologically sound, found interventions were overall associated with reductions in readmissions (pooled RR: 0.82, 95% CI: 0.73 to 0.91), and interventions with the most comprehensive support accounted for most of the benefit (RR readmission in the 7 studies with highest comprehensive support scores compared to 15 studies with the lowest scores: 0.63, 95% CI: 0.43 to 0.91).[24]

In a review of 47 trials in CHF patients, the key processes of care that seemed to be associated with reduced readmissions included: self‐management education delivered in person, early postdischarge contact, a point of postdischarge contact, and the ability to individually tailor the intervention.[16]

It is unclear whether home visits are a necessary component of transitional care interventions. A meta‐analysis of trials including general medicine or CHF patients did not find that the setting of care delivery influenced outcomes; however, all but 1 of the most comprehensive interventions included home visits in their model.[24] A review of CHF populations found interventions with multidisciplinary HF clinic visits or home visits reduced all‐cause readmissions and mortality, but found insufficient evidence directly comparing interventions with and without home visits.[16]

We found little evidence examining the impact of different transition types (most studies focused on hospital‐to‐home transitions), intervention targets (most studies focused on patients rather than caregivers), or key personnel involved.

DISCUSSION

We examined 17 systematic reviews across different patient populations representing a variety of intervention types to provide a broad overview of the care transitions literature. Variations in population studied, intervention definition, personnel, outcome definition, and setting make it difficult to identify strong evidence in support of a specific intervention type that should be broadly implemented. There were, however, some common themes that emerged across the literature suggesting that successful interventions addressed more aspects of the care transition, included the means to assess and respond to individual peridischarge needs, and included components that spanned care settings. In practical terms, the actualization of these themes has been accomplished in many interventions with the addition of transitional care personnel such as nurses and/or pharmacists. Additionally, interventions have often been tailored to the needs of individual patients with the use of needs assessment and patient‐centered personalized health records.[1]

Because there are many potential steps in the care transition, focusing on only 1 of these steps, such as medication reconciliation, is unlikely to have significant benefit on risk of readmission.[15] The pathways to readmission vary, as suggested both by the inability to accurately anticipate which patients will be readmitted,[28] and by case review studies characterizing underlying factors contributing to preventable readmissions.[29]

The problems with recommending that a specific intervention be broadly implemented include both the lack of evidence supporting such a recommendation and the likelihood that the transitional care gaps are not the same in all settings, or for all populations of patients treated. As health systems rapidly evolve, it may be useful for them to inventory strengths and weaknesses of their current approach to transitional care both to identify critical care gaps and to avoid investment in resource‐intensive transitional care interventions that may be redundant with existing activities.

Indeed, transitional care gaps may have changed over the last decade. Two large reviews showed that more recently published studies were less likely to have found an improvement in outcomes.[14, 24] In the years since some of the most successful and widely cited transitional care interventions were developed and evaluated, many health systems have undertaken major transformations, including the adoption of the patient‐centered medical home model and integration of electronic health records, which may implicitly address some earlier gaps. For instance, foundational qualitative work for the Care Transitions Measure identified discontinuities in information transfer as 1 of 4 major transitional care barriers identified by patients, and the personal health record was created, in part, to address this gap.[30] A shared electronic health record across healthcare settings has the potential to mitigate some of these concerns.

In general, there is an overarching need for better evidence to guide selection and implementation of complex, multicomponent transitional care interventions in different settings. There remain a number of gaps regarding the operationalization of interventions. For instance, the optimal choice of personnel, the comparative effects of home visits and other forms of postdischarge follow‐up, and the best approach to patient selection (whether through use of a formal readmission risk assessment model or a focus on populations with high‐risk comorbidities) are unknown.

One of the major weaknesses of the transitional care literature is the marked variation in intervention definitions, timing of outcome follow‐up, and descriptions of interventions and usual care. Use of taxonomies to guide study design and description may help standardize reporting.

Most of the care transitions literature has been hospital‐focused, and the interventions often extend hospital services beyond hospitalization. Given the growth of medical homes, it will be important to examine the effectiveness of outpatient‐based care transitions models that reach‐in to the hospital. Studies comparing approaches such as home‐visit and telephone‐based interventions, different risk‐prioritization schemes, and the use of different types of personnel are also needed.

There is very little literature examining transitional care interventions in patients with mental health conditions or undergoing surgery. A recent report for the Veterans Health Administration found that 24% of patients with chronic mental health conditions are readmitted within 30 days of discharge.[31] About 1 in 7 Medicare patients admitted to a surgical service is readmitted within 30 days.[32] The transitional care needs of these populations may differ substantially from medical populations and warrant further study.

Our review has a number of important limitations. Our overview of the literature was necessarily broad rather than in‐depth. There are many nuances in the results, internal validity, and generalizability of studies that are not represented in our overview. It was difficult to use established criteria to formally rate the strength of evidence for each of our conclusions, but we indicated strength of evidence ratings when reported in reviews. As we note in the results, our assessment of cross‐cutting themes is based largely on low‐strength evidence, given the indirect comparisons and the many factors that varied among the included studies. Our inclusion criteria specified readmissions as an outcome, but there are care transitions that focus exclusively on other outcomes, such as smoking cessation interventions around the time of discharge.[33] Furthermore, there are many outpatient‐based interventions designed to affect emergency room and hospital utilization that are not captured in our review, but may nevertheless be important to understanding the role of care coordination in the context of the medical home. We did not systematically update the included reviews' searches, and there may be more recent studies not represented here, though we are not aware of newer studies that would substantively change our summary of findings.

CONCLUSIONS

The literature includes many different types of interventions, studied in varied populations and clinical settings, and implemented in different ways. Furthermore, there are very little comparative effectiveness data. It is therefore difficult to conclusively identify specific intervention components and characteristics that are necessary for successful care transitions. Effective interventions are generally more comprehensive, address more aspects of the care transition, extend beyond the hospital stay, and have the flexibility to respond to individual patient needs. Transitional care interventions have not been well studied in integrated health system settings, or in mental health and surgical populations.

Disclosures: The views expressed in this article are those of the authors and do not necessarily represent the views of the US Department of Veterans Affairs or the US government.

The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration (VHA) Project ESP 05‐225, VA#01‐0206. Dr. Jencks' work on this project was supported in part by a grant from the Quality Enhancement Research Initiative (05‐225), Department of Veterans Affairs. Dr. Jencks has reported prior consulting work with the following entities: Inovalon, Care Centrix, Affymax, Curaspan, Reinforced Care, Health Services Advisory Group, Delmarva Foundation, Connecticut Peer Review Organization, Maryland Health Services Cost Review Commission, Institute for Healthcare Improvement, American Association for Respiratory Care, Monaghan Medical, Iowa Society for Respiratory Care.

Transitional care has been defined as a set of actions designed to ensure the coordination and continuity of healthcare as patients transfer between different locations or different levels of care within the same location.[1] Early studies showed that nurse‐led transitional care interventions beginning in the hospital and continuing after discharge had the potential to reduce the rate of hospital readmissions.[2, 3] Since then, the healthcare landscape has been evolving in important ways, with the spread of the electronic medical record, the patient‐centered medical home, and an increased push to health systems integration.[4, 5, 6]

The potential success or failure of transitional care interventions, which are inherently complex and can involve multiple components, may depend on the nature of the interventions themselves, the settings in which they were implemented, and/or the populations included. Health systems are faced with a large array of transitional care interventions and patient populations to whom such activities might apply.

The main aim of this article, culled from a larger report commissioned by the Veterans Health Administration (VHA)[7] was to catalogue which types of transitional care interventions hold promise and which populations have been best studied, to help health systems guide prioritization and adaptation of the most relevant transitional care activities and help focus future research efforts.

METHODS

We conducted a review of systematic reviews published in English, following Preferred Reporting Items for Systematic Reviews and Meta‐analyses reporting guideline for systematic reviews.[8] A protocol describing the review plan was posted to a public website before the study was initiated.[9] From an initial review of the literature, we recognized that most systematic reviews typically either examined different transitional care intervention types in a given patient population, or examined a given intervention type in a variety of patient populations. We use the term intervention type to refer to single‐ or multicomponent interventions that used a similar approach or bundle of care processes (eg, telemonitoring, hospital‐at‐home), or addressed a similar key process of the care transition (eg, medication reconciliation). Patient populations are defined according to clinical condition (eg, congestive heart failure) or demographic characteristics (eg, geriatric). Given that the review was originally commissioned by the VHA, we excluded pediatric and obstetric patient populations.

We identified categories of patient populations and intervention types with input from a panel of content experts, an initial scan of the literature, and with input from our study team to help guide our literature search (see Supporting Information, Appendix A, in the online version of this article). We searched PubMed and Cochrane databases of systematic reviews from database inception through May 2014.

We selected reviews that reported hospital readmissions as an outcome, regardless of whether it was the primary outcome. However, we summarized other outcomes reported by each review. Within each patient population or intervention type of interest, we first identified reviews that fulfilled key quality criteria: (1) clearly reported their search strategy, (2) reported inclusion and exclusion criteria, and (3) conducted an appraisal of the internal validity of the included trials.[10, 11] If there was more than 1 review within each category fulfilling these criteria, we prioritized the most recent review and those with the broadest scope. We discussed the ultimate choice of review as a group and resolved any disagreements through consensus. One author abstracted prespecified data from each review and a second author checked entries for accuracy (see Supporting Information, Appendix B, in the online version of this article).

We qualitatively synthesized the literature, using the categories of intervention type, patient population, and healthcare setting to organize our synthesis. We further identified common themes that cut across different intervention types and patient populations related to the following characteristics (derived from an existing taxonomy):[12] transition type (hospital to home, hospital to nursing facility), intervention target (patient, caregiver), key processes (education, personal health record), key personnel involved (nurse, social worker), method of postdischarge follow‐up (phone, home visits), and intensity and complexity. We developed brief narrative summaries of findings for each review. These narratives were compiled into a single document and reviewed independently by each of the authors of this report, who then compiled a brief list of key cross‐cutting themes in the evidence.

RESULTS

We reviewed 807 titles and abstracts from the electronic search, and identified an additional 94 from reviewing reference lists and performing manual searches for recently published and unpublished or ongoing studies (Figure 1). Eighty‐one systematic reviews met our inclusion criteria and, of these, we selected 17 that were the most recent and broadly scoped: 10 of intervention types (Table 1) and 7 of patient populations (Table 2).

Systematic Reviews of Different Types of Interventions
Systematic Review, Sample Characteristics, Search Dates

N Controlled Trials (N Total Studies), N = Total Patients in RCTs

Summary Estimate for Readmission Risk (95% CI) Summary Estimate for Mortality (95% CI) Other Outcomes (Clinical and Utilization) Quality Assessment Method, Range of Scores
  • NOTE: Abbreviations: AHRQ, Agency for Healthcare Research & Quality; CI, confidence interval; CGA, comprehensive geriatric assessment; DC, discharge; ED, emergency department; EPOC, Cochrane Effective Practice and Organisation of Care Group; ER, emergency room; ERAS, enhanced recovery after surgery; GP, general practice; GRADE, grading of recommendations assessment, development, and evaluation; HF, heart failure; HR, hazard ratio; LOS, length of stay; N, number of (studies/subjects); NR, not reported; OR, odds ratio; PCMH, patient‐centered medical home; QOL, quality of life; RCTs, randomized controlled trials; ROB, risk of bias; RR, relative risk; STS, structured telephone support; STS HH, structured telephone support delivered by human‐to‐human contact; STS HM, structured telephone support delivered by human‐to‐machine interface; TM, telemonitoring; UC, usual care.

Geriatric case management (community dwelling, age 65+ years), Huntley, 2013,[34] 19502010

11 RCTs

(11 studies total), N = 4318

0.71 (0.49 to 1.03)

Combined estimate NR.

Mortality (5 studies) was not significantly different based on case management.

Clinical: NR. Other utilization: ED visits, GP visits, specialist clinic/outpatient visits, and LOS were not improved by case management in all but 1 study. Cochrane ROB. Risk of bias was generally low. Most studies had low or unclear ROB in all categories except 1 study that had high ROB in 3 categories.
Geriatric case assessment (age 65+ years), Ellis, 2011,[26]

19662010

22 RCTs

(22 studies total), N = 10,315

No difference between groups, N = 3822. OR 1.03 (0.89 to 1.18)

Death or functional decline, combined outcome:

0.76 (0.64 to 0.90, P = 0.001) based on data from 5 RCTs, N = 2622

Clinical: significant improvement in cognitive function associated with CGA based on 5 trials. There were nonsignificant differences for dependence. Other utilization: costs were mixed. Few trials accounted for nursing home costs; those that did suggested that CGA might be associated with overall reduced cost. Cochrane ROB. The studies identified were heterogeneous in quality. All used some method of individual patient randomization, though reporting of key issues such as allocation concealment varied. Outcome assessment was seldom blinded though this is less of an issue for hard outcomes such as death or institutionalization. Some trials noted attrition for functional or cognitive outcomes.
Discharge planning (mostly older medical, though some studies included surgery, psych), Shepperd, 2013,[13] 19462012 24 RCTs (24 studies total), N = 8098 Within 3 months of discharge: 0.82 (0.73 to 0.92) for older patients with a medical condition. No difference was found when mixed medical and surgical populations were included.

At 69 months:

0.99 (0.78 to 1.25)

Clinical: QOL outcomes were mixed. Other utilization: lower medical LOS in 10 trials. No change in surgical LOS (2 trials) Cochrane ROB. Low ROB: n = 9, medium ROB: n = 9, high ROB: n = 5, unclear ROB: n = 1
ERAS/fast track (postpancreatic surgery), Kagedan, 2015,[35] 20002013 0 trials or RCTs (10 studies total), N = 0 (no RCTs) Range among studies in % of patients readmitted, ERAS vs UC: (3.515) vs (025)

Range (% of patients), ERAS vs UC:

(04) vs (03)

Clinical: NR. Other utilization: 2/4 studies that examining costs showed reduction, 2/4 no change

GRADE (low, moderate, high).

No high‐quality studies were identified. Cohort studies comparing multiple groups were labelled as being of moderate quality. Single‐group prospective studies were graded as low quality. Moderate quality: n = 7, low quality: n = 3

Hospital at home, Caplan, 2012,[14] database inception through 2012 61 RCTs (61 studies total), N = 6992 0.75 (0.59 to 0.95) 0.81 (0.69 to 0.95)

Clinical: consistent higher satisfaction (21/22 studies reporting patient satisfaction, 6/8 studies reporting CG satisfaction). No difference in caregiver burden (7 studies).

Other utilization: mean cost lower (11 RCTS):

1567.11

(2069.53 to 1064.69, P < 0.001). Average cost savings 26.5%, 32/34 studies concluded HAH was less expensive.

EPOC criteria. Quality ratings not reported. Almost all studies were not blinded. However, many studies used blinded initial assessments before randomisation. Some outcome assessment was blinded.
Medication reconciliation, Kwan, 2013,[15] 19802012 5 RCTs (18 studies total), N = 1075 ER visits and hospitalizations within 30 days of discharge in 3 RCTs, HR: 0.77 (0.63 to 0.95) NR Clinical: NR. Other utilization: NR Cochrane ROB. Low ROB: n = 5 RCTs
PCMH, Jackson, 2013,[36] database inception through June 2012 9 RCTs (19 studies total), N = 54,465 0.96 (0.84 to 1.10) NR Clinical: NR. Other utilization: 3 RCTs reporting ED utilization found no effect. Combined RR: 0.93 (95% CI: 0.72 to 1.20). AHRQ (good, fair, poor quality). All but 1 study were rated as being good or fair quality.
Telemonitoring and structured telephone support (heart failure)

Pandor, 2013,[22] 19992011

21 RCTs (21 studies total), N = 6317

Median HR (credible interval, 2.5% to 97.5%).

All to cause:

STS HH: 0.97 (0.70 to 1.31). TM office hours (transmitted data reviewed by medical staff during office hours): 0.75 (0.49 to 1.10). HF to related:

STS HH: 0.77 (0.62 to 0.96). TM office hours: 0.95 (0.70 to 1.34)

Median HR

(credible interval, 2.5% to 97.5%):

STS HH vs UC: 0.77 (0.55 to 1.08). TM office hours vs UC: 0.76 (0.49 to 1.18)

Clinical: QOL improved in 3 of 4 studies of STS interventions, and 2 of 4 studies of telemonitoring interventions.

Other utilization: HF‐related hospitalizations: no change for STS HM and TM office hours; reduced with STS HH 0.76 (0.61 to 0.94).

Five of 6 studies found no change in LOS, 1 showed reduced.

Study quality not reported individually. The methodological quality of the 21 included studies varied widely and reporting was generally poor on random sequence generation, allocation concealment, blinding of outcome assessment, definition and confirmation of HF diagnosis, and intention‐to‐treat analysis.
Telephone follow‐up, primary‐care based, Crocker 2012,[21] 19482011 3 RCTs (3 studies total), N = 1765 Combined estimate NR. None of the 3 RCTs reported a statistically significant impact of telephone follow‐up on readmission or ER visits. NR Clinical: NR. Other utilization: In all 3 included studies, primary care contact improved with postdischarge telephone follow‐up. Two studies examining ED visits showed no effect. Study quality not reported individually: assessed sequence generation, allocation concealment, blinding, follow‐up and intent to treat analysis, and publication bias. Most studies were high or unclear ROB based on poor reporting of sequence generation, allocation concealment; lack of blinding; and lack of information about attrition.
Telephone follow‐up, hospital‐based (unselected with cardiac and surgical subgroup analyses), Mistiaen, 2006,[20] database inception through July 2003

13 RCTs

(33 studies total), N = 5110

Cardiac (3 RCTs, N = 616): 0.75 (0.41 to 1.36). Surgical (4 RCTs, N = 460): 0.65 (0.28 to 1.55) NR Clinical: No change in anxiety 1 month post‐DC in cardiac surgery patients in pooled effect from 3 studies. No change in depression based on 2 studies. Other utilization: no change in ED visits in surgery patients (pooled from 2 studies) Cochrane ROB. Medium ROB: n = 7. High ROB: n = 26
Systematic Reviews of Care Transition Intervention Studies in Specific Patient Populations
Systematic Review, Sample Characteristics, Search Dates

N Controlled Trials (N Total Studies), N = Total Patients in RCTs

Summary Estimate for Readmission Risk (95% CI)

Summary Estimate for Mortality (95% CI) Other Outcomes (Clinical and Utilization) Quality Assessment Method, Range of Scores
  • NOTE: Abbreviations: ACS, acute coronary syndrome; ADLs, activities of daily living; AHRQ, Agency for Healthcare Research & Quality; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive pulmonary disease; EPOC, Cochrane Effective Practice and Organisation of Care Group; MDS‐HF, multidisciplinary heart failure; MI, myocardial infarction; N, number of (studies/subjects); NR, not reported; RCTs, randomized controlled trials; ROB, risk of bia~s; RR, relative risk.

Acute MI/acute coronary syndrome, Auer, 2008,[25] 19662007

16 controlled trials, including

14 RCTs (26 studies total), N = 1910 from RCTs

612 months: 0.96 (0.79 to 1.17) All causes: 0.94 (0.63 to 1.40). All causes at 1 year: 0.94 (0.63 to 1.44) Clinical: re‐infarction rates: RR 0.51 (95% CI: 0.23 to 1.1). Smoking cessation: RR 1.29 (1.02 to 1.63, I2 = 66%). Other utilization: NR

Modified Jadad score

3 (lowest ROB category): n = 8, 2: n = 5; 1 (highest ROB category): n = 3. Before‐after designs: n = 12 (no formal ROB assessment)

Cancer, Smeenk, 1998,[37] 19851997

5 RCTs (9 studies total)

N = 4249

Range of ratios for readmission (%) in intervention group/ control group: 0.621.12. Combined estimate NR. Timing of readmission assessment NR. NR Clinical: quality of life outcomes were positively associated with home‐care programs in 3 of 7 studies. Other utilization: NR

Weighted methodological quality score (0100 max):

Range: 4868. All considered moderate quality

CHF (moderate‐severe, geriatric), Feltner, 2014,[16] 19902013

47 RCTs (47 studies total)

N = 8693

Combined RR (95% CI) by intervention type; results from single studies per intervention type not included below:

Home‐visiting program, 36 months: 0.75 (0.66 to 0.86). Structured telephone support, 36 months:

0.92 (0.77 to 1.10).

Telemonitoring, 36 months: 1.11 (0.87 to 1.42). Clinic‐based (MDS‐HF), 6 months: 0.70 (0.55 to 0.89)

Combined RR (95% CI) by intervention type; results from single studies per intervention type not included below:

Home‐visiting program,

36 months: 0.77 (0.60 to 0.996). Structured telephone support,

3.6 months: 0.69 (0.51 to 0.92). Clinic‐based (MDS‐HF), 6 months: 0.56 (0.34 to 0.92)

Clinical: NR. Other utilization: NR

AHRQ ROB for trials.

Low ROB: n = 6, medium ROB: n = 27, high ROB: n = 9, unclear ROB: n = 5

COPD, Prieto‐Centurion, 2014,[27] 19662013

5 RCTs (5 studies total)

N = 1393

2 studies found reduced 12‐month readmissions (mean number of hospitalizations per patient, 1.0 vs 1.8; P = 0.01; percent hospitalized, 45% vs 67%; P = 0.028).

Three studies found no significant change in 6‐ or 12‐month readmissions.

4 of 5 studies: no difference. 1 study: increased 12‐month mortality (17% vs 7%, P = 0.003) Clinical: NR. Other utilization: NR EPOC criteria (no. domains with low ROB: 17 max). 6: n = 4, 5: n = 1
General/unselected, Leppin, 2014,[24] 19902013 42 RCTs (42 studies total), N = 17,273 30 days: 0.82 (0.73 to 0.91) NR Clinical: NR. Other utilization: NR EPOC ROB (high, low, unclear). Most studies were at overall low risk of bias. The most common methodological limitation of these trials was the lack of a reliable method for dealing with missing data. Eight of 42 studies were rated as low ROB in all categories; all others were rated as high or unclear ROB in 1 or more categories.
Mental health admissions, Vigod, 2013,[38] database inception through 2012

13 controlled trials, including

8 RCTs (15 studies total)

N = 1007 (RCTs)

Range among studies in % of patients readmitted, intervention group vs control: 3 month: 7%23% vs 13%36%, 624 month: 0%63% vs 4%69% NR Clinical: NR. Other utilization: NR

EPOC criteria. No. of domains with low ROB (19 max): range 38.

Most included studies had small sample sizes, high dropout rates, and/or did not account for baseline differences between groups on key prognostic factors.

Stroke or ACS, Prvu Bettger, 2012,[18] 20002012

24 RCTs stroke, 8 RCTs MI (44 studies total:

27 stroke, 17 MI), N = 4307 stroke, N = 1062 MI

Insufficient evidence for most intervention subtypes in both stroke and MI. Moderate strength evidence that hospital‐initiated support did not reduce readmissions in stroke patients. Timing of readmission assessment NR. Low strength evidence in MI patients: reduced 3 month mortality (1 study), reduced 12 month mortality (2 studies)

Clinical: No significant differences in ADLs.

Inconsistent effects on caregiver strain, quality of life in 5 studies measuring caregiver outcomes. Other utilization: NR

AHRQ (good, fair, poor quality). Good: n = 10, fair: n = 42, poor: n = 10. Strength of evidence insufficient for all intervention/population subgroups except as noted.
Figure 1
Literature flow diagram.

Intervention Types

Among reviews focused on specific intervention types (Table 1), several show promise in reducing readmissions and/or mortality.[13, 14, 15, 16] There is moderate‐strength evidence that structured and individually tailored discharge planning reduces readmissions within 90 days (relative risk [RR]: 0.82, 95% confidence interval [CI]: 0.73 to 0.92) and hospital length of stay (0.91 days, 95% CI: 1.55 to 0.27).[13] However, most of the benefit was seen among studies of robust interventions that included a combination of care processes. In 9 of the interventions, a nurse advocate helped with discharge planning activities and care coordination. Twelve of the interventions included postdischarge follow‐up.

Moderate strength evidence from 61 trials found that hospital‐at‐home interventions were associated with reductions in 30‐day readmissions (RR: 0.75, 95% CI: 0.59 to 0.95) and mortality (RR: 0.81, 95% CI: 0.69 to 0.95).[14] Frequently, specific components of the included interventions were not well described, and periods of observation for outcomes were not specified. Interventions were associated with greater patient and caregiver satisfaction in the vast majority of studies reporting such outcomes.

The impact of medication reconciliation interventions on clinically significant adverse drug events was variable.[15] Readmissions and emergency room visits were reduced (RR: 0.77, 95% CI: 0.0.63 to 0.95) in 3 trials, but this reduction was driven by 1 intervention that included additional care processes such as postdischarge follow‐up.[17] Interventions focused solely on medication reconciliation around the time of discharge were not effective.

One review of patients with stroke or myocardial infarction (MI) described 5 intervention types: hospital‐based discharge preparation, hospital‐based patient and family education, community‐based patient and family education, community‐based models of support interventions, and chronic disease management models of care.[18] They found moderate‐strength evidence that early supported discharge of stroke patients (short hospital stay followed by intensive home care with a multidisciplinary team) shortened length of stay without adversely impacting readmissions or mortality. Specialty care after an MI was associated with reduced mortality, but the strength of evidence was low, being largely based on 1 Veterans Affairs observational study.[19] There was insufficient evidence examining the other types of interventions in this review.

Two reviews examined the effects of postdischarge follow‐up calls in unselected populations. An older Cochrane review from 2006 focused on calls performed by hospital‐based personnel.[20] Though 33 studies including 5110 patients were included in this review, there was inconclusive evidence of the effectiveness of these interventions, largely because of methodological limitations in most included studies. A more recent review similarly concluded there was insufficient evidence of the effects of postdischarge calls on utilization in 3 studies, though they did find that the interventions were associated with higher rates of primary care engagement.[21]

One review focused on postdischarge remote monitoring in patients with congestive heart failure (CHF)[22, 23] via structured telephone support (STS) or telemonitoring. STS interventions typically included periodic scripted telephone calls from nurses to review symptoms, interval physiologic data such as weight, and self‐management skills. Telemonitoring focused on remote transfer of physiologic data, with phone contact when abnormal vital signs or weights occurred. STS interventions reduced long‐term (6 months), but not short‐term (23 months) heart failure readmissions, and were associated with reduced long‐term mortality.[16, 23] Though 1 review noted a trend toward reduced mortality with telemonitoring interventions, both reviews noted the substantial methodological shortcomings of this literature and the inconsistency of results across studies. There was insufficient evidence of the comparative effectiveness between STS and telemonitoring interventions.[16]

One review of CHF patients categorized interventions into 6 types: home‐visiting programs, STS, telemonitoring, outpatient clinic‐based (including multidisciplinary CHF clinics), primarily educational, and other.[16] This review found moderate‐strength evidence that interventions with multidisciplinary heart failure (HF) clinic visits or home visits reduced both all‐cause readmissions and mortality, with number needed to treat below 10 for readmission and 18 to 33 for mortality (for multidisciplinary heart failure clinic and home visiting programs, respectively). STS interventions produced a similar mortality benefit but did not reduce all‐cause readmissions.

Healthcare Setting

We found no evidence directly examining whether intervention effectiveness depends on factors such as the presence of a shared electronic medical record, access to community resources, integration of primary and hospital care, and the presence of a medical home. Moreover, the transitional care literature generally has provided only scant descriptions of the health system context of the interventions.

Patient Population

The relative importance of careful patient selection, as compared to intervening on an unselected group of patients, is unclear. Many studies in these reviews used inclusion criteria that selected patients who were at high risk for readmission because of older age, significant medical comorbidity, and/or a history of high utilization. However, few reviews explicitly examined variation of intervention effects based on patient criteria.

The characteristics and findings of reviews of specific patient populations are shown in Table 2. One review found studies that did and did not use high‐risk patient selection criteria had similar results.[15] A metaregression of trials including general medical or CHF populations did not find significantly different effects between studies without age restrictions and those that included only patients over 65 years of age (interaction P = 0.24).[24] Similarly, a review of hospital‐at‐home studies did not find a clear difference in effects among studies in patients younger than 70 years old, between ages 70 and 73 years, and older than 74 years.[14]

Some of the reviews also speculated that focusing on specific groups of patients allowed disease‐specific customization of interventions and supported expertise development. For example, 1 review found that interventions in acute MI patients, which focused on effective use of disease‐specific medications, were associated with a mortality benefit, though this was largely driven by 1 study.[25] Another review examining comprehensive geriatric assessment interventions found that gains in the combined outcome of mortality and functional decline were only associated with interventions delivered in a geriatric ward setting.[26] The authors speculate that the multidisciplinary team of providers developed more expertise and facility with the patient population.

We found insufficient evidence to determine whether transitional care affects specific patient populations differently. Although there were successful interventions in CHF patients and no consistent evidence of benefit in chronic obstructive pulmonary disease (COPD) patients, it is unclear whether these differences were due to the markedly different types of interventions examined or to the choice of population itself.[16, 27] Populations with chronic medical illnesses were well represented in the literature, although there was a dearth of evidence in mental illness or surgical populations.

Cross‐cutting Themes

Across different intervention types, patient populations, and settings, successful interventions tended to be more comprehensive, involve more aspects of the care transition, and include components before and after hospital discharge. Successful interventions also tended to be flexible enough to accommodate individual patient needs. However, the strength of evidence supporting these overarching conclusions should be considered low because these are indirect, post hoc comparisons across literature that includes many different intervention types, studied in varied populations and clinical settings, and implemented in different ways. We found very few comparative effectiveness studies among the included reviews.

As noted above, the effective discharge planning and medication reconciliation interventions were those that included additional personnel and spanned care settings.[13, 17] In contrast, interventions in COPD populations did not consistently reduce readmissions or mortality, but the interventions began after hospital discharge and frequently omitted some care processes such as discharge planning that are often 1 component of successful interventions in other populations.[27]

One review created a comprehensive support variable that was based on number of patient interactions, number of personnel involved, number of intervention components, and the ability of the intervention to address self‐management needs.[24] A metaregression including 42 trials, the vast majority of which included general medical patients or patients with CHF and were considered to be methodologically sound, found interventions were overall associated with reductions in readmissions (pooled RR: 0.82, 95% CI: 0.73 to 0.91), and interventions with the most comprehensive support accounted for most of the benefit (RR readmission in the 7 studies with highest comprehensive support scores compared to 15 studies with the lowest scores: 0.63, 95% CI: 0.43 to 0.91).[24]

In a review of 47 trials in CHF patients, the key processes of care that seemed to be associated with reduced readmissions included: self‐management education delivered in person, early postdischarge contact, a point of postdischarge contact, and the ability to individually tailor the intervention.[16]

It is unclear whether home visits are a necessary component of transitional care interventions. A meta‐analysis of trials including general medicine or CHF patients did not find that the setting of care delivery influenced outcomes; however, all but 1 of the most comprehensive interventions included home visits in their model.[24] A review of CHF populations found interventions with multidisciplinary HF clinic visits or home visits reduced all‐cause readmissions and mortality, but found insufficient evidence directly comparing interventions with and without home visits.[16]

We found little evidence examining the impact of different transition types (most studies focused on hospital‐to‐home transitions), intervention targets (most studies focused on patients rather than caregivers), or key personnel involved.

DISCUSSION

We examined 17 systematic reviews across different patient populations representing a variety of intervention types to provide a broad overview of the care transitions literature. Variations in population studied, intervention definition, personnel, outcome definition, and setting make it difficult to identify strong evidence in support of a specific intervention type that should be broadly implemented. There were, however, some common themes that emerged across the literature suggesting that successful interventions addressed more aspects of the care transition, included the means to assess and respond to individual peridischarge needs, and included components that spanned care settings. In practical terms, the actualization of these themes has been accomplished in many interventions with the addition of transitional care personnel such as nurses and/or pharmacists. Additionally, interventions have often been tailored to the needs of individual patients with the use of needs assessment and patient‐centered personalized health records.[1]

Because there are many potential steps in the care transition, focusing on only 1 of these steps, such as medication reconciliation, is unlikely to have significant benefit on risk of readmission.[15] The pathways to readmission vary, as suggested both by the inability to accurately anticipate which patients will be readmitted,[28] and by case review studies characterizing underlying factors contributing to preventable readmissions.[29]

The problems with recommending that a specific intervention be broadly implemented include both the lack of evidence supporting such a recommendation and the likelihood that the transitional care gaps are not the same in all settings, or for all populations of patients treated. As health systems rapidly evolve, it may be useful for them to inventory strengths and weaknesses of their current approach to transitional care both to identify critical care gaps and to avoid investment in resource‐intensive transitional care interventions that may be redundant with existing activities.

Indeed, transitional care gaps may have changed over the last decade. Two large reviews showed that more recently published studies were less likely to have found an improvement in outcomes.[14, 24] In the years since some of the most successful and widely cited transitional care interventions were developed and evaluated, many health systems have undertaken major transformations, including the adoption of the patient‐centered medical home model and integration of electronic health records, which may implicitly address some earlier gaps. For instance, foundational qualitative work for the Care Transitions Measure identified discontinuities in information transfer as 1 of 4 major transitional care barriers identified by patients, and the personal health record was created, in part, to address this gap.[30] A shared electronic health record across healthcare settings has the potential to mitigate some of these concerns.

In general, there is an overarching need for better evidence to guide selection and implementation of complex, multicomponent transitional care interventions in different settings. There remain a number of gaps regarding the operationalization of interventions. For instance, the optimal choice of personnel, the comparative effects of home visits and other forms of postdischarge follow‐up, and the best approach to patient selection (whether through use of a formal readmission risk assessment model or a focus on populations with high‐risk comorbidities) are unknown.

One of the major weaknesses of the transitional care literature is the marked variation in intervention definitions, timing of outcome follow‐up, and descriptions of interventions and usual care. Use of taxonomies to guide study design and description may help standardize reporting.

Most of the care transitions literature has been hospital‐focused, and the interventions often extend hospital services beyond hospitalization. Given the growth of medical homes, it will be important to examine the effectiveness of outpatient‐based care transitions models that reach‐in to the hospital. Studies comparing approaches such as home‐visit and telephone‐based interventions, different risk‐prioritization schemes, and the use of different types of personnel are also needed.

There is very little literature examining transitional care interventions in patients with mental health conditions or undergoing surgery. A recent report for the Veterans Health Administration found that 24% of patients with chronic mental health conditions are readmitted within 30 days of discharge.[31] About 1 in 7 Medicare patients admitted to a surgical service is readmitted within 30 days.[32] The transitional care needs of these populations may differ substantially from medical populations and warrant further study.

Our review has a number of important limitations. Our overview of the literature was necessarily broad rather than in‐depth. There are many nuances in the results, internal validity, and generalizability of studies that are not represented in our overview. It was difficult to use established criteria to formally rate the strength of evidence for each of our conclusions, but we indicated strength of evidence ratings when reported in reviews. As we note in the results, our assessment of cross‐cutting themes is based largely on low‐strength evidence, given the indirect comparisons and the many factors that varied among the included studies. Our inclusion criteria specified readmissions as an outcome, but there are care transitions that focus exclusively on other outcomes, such as smoking cessation interventions around the time of discharge.[33] Furthermore, there are many outpatient‐based interventions designed to affect emergency room and hospital utilization that are not captured in our review, but may nevertheless be important to understanding the role of care coordination in the context of the medical home. We did not systematically update the included reviews' searches, and there may be more recent studies not represented here, though we are not aware of newer studies that would substantively change our summary of findings.

CONCLUSIONS

The literature includes many different types of interventions, studied in varied populations and clinical settings, and implemented in different ways. Furthermore, there are very little comparative effectiveness data. It is therefore difficult to conclusively identify specific intervention components and characteristics that are necessary for successful care transitions. Effective interventions are generally more comprehensive, address more aspects of the care transition, extend beyond the hospital stay, and have the flexibility to respond to individual patient needs. Transitional care interventions have not been well studied in integrated health system settings, or in mental health and surgical populations.

Disclosures: The views expressed in this article are those of the authors and do not necessarily represent the views of the US Department of Veterans Affairs or the US government.

The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration (VHA) Project ESP 05‐225, VA#01‐0206. Dr. Jencks' work on this project was supported in part by a grant from the Quality Enhancement Research Initiative (05‐225), Department of Veterans Affairs. Dr. Jencks has reported prior consulting work with the following entities: Inovalon, Care Centrix, Affymax, Curaspan, Reinforced Care, Health Services Advisory Group, Delmarva Foundation, Connecticut Peer Review Organization, Maryland Health Services Cost Review Commission, Institute for Healthcare Improvement, American Association for Respiratory Care, Monaghan Medical, Iowa Society for Respiratory Care.

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  31. Tsai TC, Joynt KE, Orav EJ, Gawande AA, Jha AK. Variation in surgical‐readmission rates and quality of hospital care. N Engl J Med. 2013;369(12):11341142.
  32. Rigotti NA, Regan S, Levy DE, et al. Sustained care intervention and postdischarge smoking cessation among hospitalized adults: a randomized clinical trial. JAMA. 2014;312(7):719728.
  33. Huntley AL, Thomas R, Mann M, et al. Is case management effective in reducing the risk of unplanned hospital admissions for older people? A systematic review and meta‐analysis. Fam Pract. 2013;30(3):266275.
  34. Kagedan DJ, Ahmed M, Devitt KS, Wei AC. Enhanced recovery after pancreatic surgery: a systematic review of the evidence. HPB (Oxford). 2015;17(1):1116.
  35. Jackson GL, Powers BJ, Chatterjee R, et al. Improving patient care. The patient centered medical home. A systematic review. Ann Intern Med. 2013;158(3):169178.
  36. Smeenk FW, Haastregt JC, Witte LP, Crebolder HF. Effectiveness of home care programmes for patients with incurable cancer on their quality of life and time spent in hospital: systematic review. BMJ. 1998;316(7149):19391944.
  37. Vigod SN, Kurdyak PA, Dennis CL, et al. Transitional interventions to reduce early psychiatric readmissions in adults: systematic review. Br J Psychiatry. 2013;202(3):187194.
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  29. Coleman EA, Mahoney E, Parry C. Assessing the quality of preparation for posthospital care from the patient's perspective: the care transitions measure. Med Care. 2005;43(3):246255.
  30. Carey K, Stefos T. An Investigation Into the Cost of VA Hospital Readmissions. Washington DC: US Department of Veterans Affairs, Office of Quality, Safety and Value; 2014.
  31. Tsai TC, Joynt KE, Orav EJ, Gawande AA, Jha AK. Variation in surgical‐readmission rates and quality of hospital care. N Engl J Med. 2013;369(12):11341142.
  32. Rigotti NA, Regan S, Levy DE, et al. Sustained care intervention and postdischarge smoking cessation among hospitalized adults: a randomized clinical trial. JAMA. 2014;312(7):719728.
  33. Huntley AL, Thomas R, Mann M, et al. Is case management effective in reducing the risk of unplanned hospital admissions for older people? A systematic review and meta‐analysis. Fam Pract. 2013;30(3):266275.
  34. Kagedan DJ, Ahmed M, Devitt KS, Wei AC. Enhanced recovery after pancreatic surgery: a systematic review of the evidence. HPB (Oxford). 2015;17(1):1116.
  35. Jackson GL, Powers BJ, Chatterjee R, et al. Improving patient care. The patient centered medical home. A systematic review. Ann Intern Med. 2013;158(3):169178.
  36. Smeenk FW, Haastregt JC, Witte LP, Crebolder HF. Effectiveness of home care programmes for patients with incurable cancer on their quality of life and time spent in hospital: systematic review. BMJ. 1998;316(7149):19391944.
  37. Vigod SN, Kurdyak PA, Dennis CL, et al. Transitional interventions to reduce early psychiatric readmissions in adults: systematic review. Br J Psychiatry. 2013;202(3):187194.
Issue
Journal of Hospital Medicine - 11(3)
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Journal of Hospital Medicine - 11(3)
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221-230
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So many options, where do we start? An overview of the care transitions literature
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So many options, where do we start? An overview of the care transitions literature
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Address for correspondence and reprint requests: Devan Kansagara, MD, Portland Veterans Affairs Medical Center, Mailcode: RD71, 3710 SW US Veterans Hospital Rd., Portland, OR 97239; Telephone: 503‐220‐8262; Fax: 503‐273‐5374; E‐mail: [email protected]
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