Diabetes

Statins raise the risks for increased glucose levels and the development of type 2 diabetes among people who don’t have it at baseline, but those risks are outweighed by the cardiovascular benefit, new data suggested.

The findings come from an analysis of individual participant data from a total of 23 randomized trials of statin therapy involving 154,664 individuals. In people without diabetes at baseline, statin therapy produces a dose-dependent increase in the risk for diabetes diagnosis, particularly among those whose glycemia marker levels are already at the diagnostic threshold.

Statins also tend to raise glucose levels in people who already have diabetes, but “the diabetes-related risks arising from the small changes in glycemia resulting from statin therapy are greatly outweighed by the benefits of statins on major vascular events when the direct clinical consequences of these outcomes are taken into consideration,” wrote the authors of the Cholesterol Treatment Trialists’ (CTT) Collaboration in their paper, published online in The Lancet Diabetes & Endocrinology.

Moreover, they say, “since the effect of statin therapy on measures of glycemia within an individual is small, there is likely to be little clinical benefit in measuring glucose concentrations and A1c values routinely after starting statin therapy with the aim of making comparisons to values taken before the initiation of a statin. However, people should continue to be screened for diabetes and associated risk factors and have their glycemic control monitored in accordance with current clinical guidelines.”

The CTT is co-led by Christina Reith, MBChB, PhD, and David Preiss, PhD, FRCPath, MRCP, both of the Nuffield Department of Population Health, University of Oxford, England.

In an accompanying editorial, Hertzel C. Gerstein, MD, and Marie Pigeyre, MD, PhD, both of McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada, noted that the decreased absolute annual incidence of life-threatening cardiovascular outcomes with statins in people at high risk for type 2 diabetes “clearly exceeds the 0.1%-1.3% per year increased absolute incidence of type 2 diabetes.”

Dr. Gerstein and Dr. Pigeyre also said “these findings emphasize the importance of holistic care. As people at risk for cardiovascular outcomes are also at risk for type 2 diabetes, any prescription of a statin should be accompanied by promoting proven strategies to prevent or delay diabetes, such as modest weight reduction and increased physical activity. Finally, these findings emphasize the importance of always being alert for harmful adverse effects, even with the most beneficial and successful preventive therapies.”
 

Statins Raise Diabetes Risk, Glucose Levels Slightly

The meta-analysis of trials in the CTT Collaboration included individual participant data from 19 double-blind randomized, controlled trials with a median follow-up of 4.3 years comparing statins with placebo in a total of 123,940 participants, including 18% who had known type 2 diabetes at randomization. Also analyzed were another four double-blind trials of lower- vs higher-intensity statins involving a total of 30,724 participants followed for a median of 4.9 years, with 15% having diabetes at baseline.

In the 19 trials of low- or moderate-intensity statins vs placebo, statins resulted in a significant 10% increase in new-onset diabetes compared with placebo (rate ratio, 1.10), while high-intensity statins raised the risk by an also significant 36% (1.36). This translated to a mean absolute excess of 0.12% per year of treatment.

Compared with less intensive statin therapy, more intensive statin therapy resulted in a significant 10% proportional increase in new-onset diabetes (1.10), giving an absolute annual excess of 0.22%.

In the statin vs placebo trials, differences in A1c values from placebo were 0.06 percentage points higher for low- or moderate-intensity statins and 0.08 points greater for high-intensity statins.

Nearly two thirds (62%) of the excess cases of new-onset diabetes occurred among participants in the highest quarter of the baseline glycemia distribution for both low-intensity or moderate-intensity and high-intensity statin therapy.

And among participants who already had diabetes at baseline, there was a significant 10% relative increase in worsening glycemia (defined by adverse glycemic event, A1c increase of ≥ 0.5 percentage points, or medication escalation) with low- or moderate-intensity statins compared with placebo and a 24% relative increase in the high-intensity trials.

The Nuffield Department of Population Health has an explicit policy of not accepting any personal honoraria payments directly or indirectly from the pharmaceutical and food industries. It seeks reimbursement to the University of Oxford for the costs of travel and accommodation to participate in scientific meetings. Dr. Reith reported receiving funding to the University of Oxford from the UK National Institute for Health and Care Research Health Technology Assessment Programme and holding unpaid roles on the Clinical Data Interchange Standards Consortium as a board member and WHO as a scientific advisor. Dr. Preiss reported receiving funding to his research institution (but no personal funding) from Novartis for the ORION 4 trial of inclisiran, Novo Nordisk for the ASCEND PLUS trial of semaglutide, and Boehringer Ingelheim and Eli Lilly for the EMPA-KIDNEY trial and being a committee member for a National Institute for Health and Care Excellence guideline.

Dr. Gerstein holds the McMaster-Sanofi Population Health Institute Chair in Diabetes Research and Care. He reported research grants from Eli Lilly, AstraZeneca, Novo Nordisk, Hanmi, and Merck; continuing medical education grants to McMaster University from Eli Lilly, Abbott, Sanofi, Novo Nordisk, and Boehringer Ingelheim; honoraria for speaking from AstraZeneca, Eli Lilly, Novo Nordisk, DKSH, Zuellig Pharma, Sanofi, and Jiangsu Hanson; and consulting fees from Abbott, Eli Lilly, Novo Nordisk, Pfizer, Carbon Brand, Sanofi, Kowa, and Hanmi. Pigeyre had no disclosures.
 

A version of this article appeared on Medscape.com.

Statins raise the risks for increased glucose levels and the development of type 2 diabetes among people who don’t have it at baseline, but those risks are outweighed by the cardiovascular benefit, new data suggested.

The findings come from an analysis of individual participant data from a total of 23 randomized trials of statin therapy involving 154,664 individuals. In people without diabetes at baseline, statin therapy produces a dose-dependent increase in the risk for diabetes diagnosis, particularly among those whose glycemia marker levels are already at the diagnostic threshold.

Statins also tend to raise glucose levels in people who already have diabetes, but “the diabetes-related risks arising from the small changes in glycemia resulting from statin therapy are greatly outweighed by the benefits of statins on major vascular events when the direct clinical consequences of these outcomes are taken into consideration,” wrote the authors of the Cholesterol Treatment Trialists’ (CTT) Collaboration in their paper, published online in The Lancet Diabetes & Endocrinology.

Moreover, they say, “since the effect of statin therapy on measures of glycemia within an individual is small, there is likely to be little clinical benefit in measuring glucose concentrations and A1c values routinely after starting statin therapy with the aim of making comparisons to values taken before the initiation of a statin. However, people should continue to be screened for diabetes and associated risk factors and have their glycemic control monitored in accordance with current clinical guidelines.”

The CTT is co-led by Christina Reith, MBChB, PhD, and David Preiss, PhD, FRCPath, MRCP, both of the Nuffield Department of Population Health, University of Oxford, England.

In an accompanying editorial, Hertzel C. Gerstein, MD, and Marie Pigeyre, MD, PhD, both of McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada, noted that the decreased absolute annual incidence of life-threatening cardiovascular outcomes with statins in people at high risk for type 2 diabetes “clearly exceeds the 0.1%-1.3% per year increased absolute incidence of type 2 diabetes.”

Dr. Gerstein and Dr. Pigeyre also said “these findings emphasize the importance of holistic care. As people at risk for cardiovascular outcomes are also at risk for type 2 diabetes, any prescription of a statin should be accompanied by promoting proven strategies to prevent or delay diabetes, such as modest weight reduction and increased physical activity. Finally, these findings emphasize the importance of always being alert for harmful adverse effects, even with the most beneficial and successful preventive therapies.”
 

Statins Raise Diabetes Risk, Glucose Levels Slightly

The meta-analysis of trials in the CTT Collaboration included individual participant data from 19 double-blind randomized, controlled trials with a median follow-up of 4.3 years comparing statins with placebo in a total of 123,940 participants, including 18% who had known type 2 diabetes at randomization. Also analyzed were another four double-blind trials of lower- vs higher-intensity statins involving a total of 30,724 participants followed for a median of 4.9 years, with 15% having diabetes at baseline.

In the 19 trials of low- or moderate-intensity statins vs placebo, statins resulted in a significant 10% increase in new-onset diabetes compared with placebo (rate ratio, 1.10), while high-intensity statins raised the risk by an also significant 36% (1.36). This translated to a mean absolute excess of 0.12% per year of treatment.

Compared with less intensive statin therapy, more intensive statin therapy resulted in a significant 10% proportional increase in new-onset diabetes (1.10), giving an absolute annual excess of 0.22%.

In the statin vs placebo trials, differences in A1c values from placebo were 0.06 percentage points higher for low- or moderate-intensity statins and 0.08 points greater for high-intensity statins.

Nearly two thirds (62%) of the excess cases of new-onset diabetes occurred among participants in the highest quarter of the baseline glycemia distribution for both low-intensity or moderate-intensity and high-intensity statin therapy.

And among participants who already had diabetes at baseline, there was a significant 10% relative increase in worsening glycemia (defined by adverse glycemic event, A1c increase of ≥ 0.5 percentage points, or medication escalation) with low- or moderate-intensity statins compared with placebo and a 24% relative increase in the high-intensity trials.

The Nuffield Department of Population Health has an explicit policy of not accepting any personal honoraria payments directly or indirectly from the pharmaceutical and food industries. It seeks reimbursement to the University of Oxford for the costs of travel and accommodation to participate in scientific meetings. Dr. Reith reported receiving funding to the University of Oxford from the UK National Institute for Health and Care Research Health Technology Assessment Programme and holding unpaid roles on the Clinical Data Interchange Standards Consortium as a board member and WHO as a scientific advisor. Dr. Preiss reported receiving funding to his research institution (but no personal funding) from Novartis for the ORION 4 trial of inclisiran, Novo Nordisk for the ASCEND PLUS trial of semaglutide, and Boehringer Ingelheim and Eli Lilly for the EMPA-KIDNEY trial and being a committee member for a National Institute for Health and Care Excellence guideline.

Dr. Gerstein holds the McMaster-Sanofi Population Health Institute Chair in Diabetes Research and Care. He reported research grants from Eli Lilly, AstraZeneca, Novo Nordisk, Hanmi, and Merck; continuing medical education grants to McMaster University from Eli Lilly, Abbott, Sanofi, Novo Nordisk, and Boehringer Ingelheim; honoraria for speaking from AstraZeneca, Eli Lilly, Novo Nordisk, DKSH, Zuellig Pharma, Sanofi, and Jiangsu Hanson; and consulting fees from Abbott, Eli Lilly, Novo Nordisk, Pfizer, Carbon Brand, Sanofi, Kowa, and Hanmi. Pigeyre had no disclosures.
 

A version of this article appeared on Medscape.com.

Statins raise the risks for increased glucose levels and the development of type 2 diabetes among people who don’t have it at baseline, but those risks are outweighed by the cardiovascular benefit, new data suggested.

The findings come from an analysis of individual participant data from a total of 23 randomized trials of statin therapy involving 154,664 individuals. In people without diabetes at baseline, statin therapy produces a dose-dependent increase in the risk for diabetes diagnosis, particularly among those whose glycemia marker levels are already at the diagnostic threshold.

Statins also tend to raise glucose levels in people who already have diabetes, but “the diabetes-related risks arising from the small changes in glycemia resulting from statin therapy are greatly outweighed by the benefits of statins on major vascular events when the direct clinical consequences of these outcomes are taken into consideration,” wrote the authors of the Cholesterol Treatment Trialists’ (CTT) Collaboration in their paper, published online in The Lancet Diabetes & Endocrinology.

Moreover, they say, “since the effect of statin therapy on measures of glycemia within an individual is small, there is likely to be little clinical benefit in measuring glucose concentrations and A1c values routinely after starting statin therapy with the aim of making comparisons to values taken before the initiation of a statin. However, people should continue to be screened for diabetes and associated risk factors and have their glycemic control monitored in accordance with current clinical guidelines.”

The CTT is co-led by Christina Reith, MBChB, PhD, and David Preiss, PhD, FRCPath, MRCP, both of the Nuffield Department of Population Health, University of Oxford, England.

In an accompanying editorial, Hertzel C. Gerstein, MD, and Marie Pigeyre, MD, PhD, both of McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada, noted that the decreased absolute annual incidence of life-threatening cardiovascular outcomes with statins in people at high risk for type 2 diabetes “clearly exceeds the 0.1%-1.3% per year increased absolute incidence of type 2 diabetes.”

Dr. Gerstein and Dr. Pigeyre also said “these findings emphasize the importance of holistic care. As people at risk for cardiovascular outcomes are also at risk for type 2 diabetes, any prescription of a statin should be accompanied by promoting proven strategies to prevent or delay diabetes, such as modest weight reduction and increased physical activity. Finally, these findings emphasize the importance of always being alert for harmful adverse effects, even with the most beneficial and successful preventive therapies.”
 

Statins Raise Diabetes Risk, Glucose Levels Slightly

The meta-analysis of trials in the CTT Collaboration included individual participant data from 19 double-blind randomized, controlled trials with a median follow-up of 4.3 years comparing statins with placebo in a total of 123,940 participants, including 18% who had known type 2 diabetes at randomization. Also analyzed were another four double-blind trials of lower- vs higher-intensity statins involving a total of 30,724 participants followed for a median of 4.9 years, with 15% having diabetes at baseline.

In the 19 trials of low- or moderate-intensity statins vs placebo, statins resulted in a significant 10% increase in new-onset diabetes compared with placebo (rate ratio, 1.10), while high-intensity statins raised the risk by an also significant 36% (1.36). This translated to a mean absolute excess of 0.12% per year of treatment.

Compared with less intensive statin therapy, more intensive statin therapy resulted in a significant 10% proportional increase in new-onset diabetes (1.10), giving an absolute annual excess of 0.22%.

In the statin vs placebo trials, differences in A1c values from placebo were 0.06 percentage points higher for low- or moderate-intensity statins and 0.08 points greater for high-intensity statins.

Nearly two thirds (62%) of the excess cases of new-onset diabetes occurred among participants in the highest quarter of the baseline glycemia distribution for both low-intensity or moderate-intensity and high-intensity statin therapy.

And among participants who already had diabetes at baseline, there was a significant 10% relative increase in worsening glycemia (defined by adverse glycemic event, A1c increase of ≥ 0.5 percentage points, or medication escalation) with low- or moderate-intensity statins compared with placebo and a 24% relative increase in the high-intensity trials.

The Nuffield Department of Population Health has an explicit policy of not accepting any personal honoraria payments directly or indirectly from the pharmaceutical and food industries. It seeks reimbursement to the University of Oxford for the costs of travel and accommodation to participate in scientific meetings. Dr. Reith reported receiving funding to the University of Oxford from the UK National Institute for Health and Care Research Health Technology Assessment Programme and holding unpaid roles on the Clinical Data Interchange Standards Consortium as a board member and WHO as a scientific advisor. Dr. Preiss reported receiving funding to his research institution (but no personal funding) from Novartis for the ORION 4 trial of inclisiran, Novo Nordisk for the ASCEND PLUS trial of semaglutide, and Boehringer Ingelheim and Eli Lilly for the EMPA-KIDNEY trial and being a committee member for a National Institute for Health and Care Excellence guideline.

Dr. Gerstein holds the McMaster-Sanofi Population Health Institute Chair in Diabetes Research and Care. He reported research grants from Eli Lilly, AstraZeneca, Novo Nordisk, Hanmi, and Merck; continuing medical education grants to McMaster University from Eli Lilly, Abbott, Sanofi, Novo Nordisk, and Boehringer Ingelheim; honoraria for speaking from AstraZeneca, Eli Lilly, Novo Nordisk, DKSH, Zuellig Pharma, Sanofi, and Jiangsu Hanson; and consulting fees from Abbott, Eli Lilly, Novo Nordisk, Pfizer, Carbon Brand, Sanofi, Kowa, and Hanmi. Pigeyre had no disclosures.
 

A version of this article appeared on Medscape.com.

TOPLINE:

In people with type 2 diabetes (T2D), higher levels of arm and trunk fat are associated with an increased risk for cardiovascular disease (CVD) and mortality, while higher levels of leg fat are associated with a reduced risk for these conditions.

METHODOLOGY:

• People with T2D have a twofold to fourfold higher risk for CVD and mortality, and evidence shows obesity management helps delay complications and premature death, but an elevated body mass index (BMI) may be insufficient to measure obesity.
• In the “obesity paradox,” people with elevated BMI may have a lower CVD risk than people of normal weight.
• Researchers prospectively investigated how regional body fat accumulation was associated with CVD risk in 21,472 people with T2D (mean age, 58.9 years; 60.7% men; BMI about 29-33) from the UK Biobank (2006-2010), followed up for a median of 7.7 years.
• The regional body fat distribution in arms, trunk, and legs was assessed using bioelectrical impedance analysis.
• The primary outcomes were the incidence of CVD, all-cause mortality, and CVD mortality.

TAKEAWAY:

• Participants in the highest quartile of arm fat percentage (multivariate-adjusted hazard ratio [HR], 1.63; 95% CI, 1.29-2.05) and trunk fat percentage (HR, 1.27; 95% CI, 1.06-1.52) were at a higher risk for CVD than those in the lowest quartile.
• However, participants in the highest quartile of leg fat percentage had a lower risk for CVD than those in the lowest quartile (HR, 0.72; 95% CI, 0.58-0.90).
• A nonlinear relationship was observed between higher leg fat percentage and lower CVD risk and between higher trunk fat percentage and higher CVD risk, whereas a linear relationship was noted between higher arm fat percentage and higher CVD risk.
• The patterns of association were similar for both all-cause mortality and CVD mortality. Overall patterns were similar for men and women.

IN PRACTICE:

“Our findings add to the understanding of body fat distribution in patients with T2D, which highlights the importance of considering both the amount and the location of body fat when assessing CVD and mortality risk among patients with T2D,” wrote the authors.

SOURCE:

The study led by Zixin Qiu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, was published online in The Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

As body fat was measured only once at the beginning of the study, its changing association over time could not be assessed. Moreover, the findings were primarily based on predominantly White UK adults, potentially restricting their generalizability to other population groups. Furthermore, diabetes was diagnosed using self-reported medical history, medication, and hemoglobin A1c levels, implying that some cases may have gone undetected at baseline. 

DISCLOSURES:

This study was funded by grants from the National Natural Science Foundation of China, Hubei Province Science Fund for Distinguished Young Scholars, and Fundamental Research Funds for the Central Universities. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

In people with type 2 diabetes (T2D), higher levels of arm and trunk fat are associated with an increased risk for cardiovascular disease (CVD) and mortality, while higher levels of leg fat are associated with a reduced risk for these conditions.

METHODOLOGY:

• People with T2D have a twofold to fourfold higher risk for CVD and mortality, and evidence shows obesity management helps delay complications and premature death, but an elevated body mass index (BMI) may be insufficient to measure obesity.
• In the “obesity paradox,” people with elevated BMI may have a lower CVD risk than people of normal weight.
• Researchers prospectively investigated how regional body fat accumulation was associated with CVD risk in 21,472 people with T2D (mean age, 58.9 years; 60.7% men; BMI about 29-33) from the UK Biobank (2006-2010), followed up for a median of 7.7 years.
• The regional body fat distribution in arms, trunk, and legs was assessed using bioelectrical impedance analysis.
• The primary outcomes were the incidence of CVD, all-cause mortality, and CVD mortality.

TAKEAWAY:

• Participants in the highest quartile of arm fat percentage (multivariate-adjusted hazard ratio [HR], 1.63; 95% CI, 1.29-2.05) and trunk fat percentage (HR, 1.27; 95% CI, 1.06-1.52) were at a higher risk for CVD than those in the lowest quartile.
• However, participants in the highest quartile of leg fat percentage had a lower risk for CVD than those in the lowest quartile (HR, 0.72; 95% CI, 0.58-0.90).
• A nonlinear relationship was observed between higher leg fat percentage and lower CVD risk and between higher trunk fat percentage and higher CVD risk, whereas a linear relationship was noted between higher arm fat percentage and higher CVD risk.
• The patterns of association were similar for both all-cause mortality and CVD mortality. Overall patterns were similar for men and women.

IN PRACTICE:

“Our findings add to the understanding of body fat distribution in patients with T2D, which highlights the importance of considering both the amount and the location of body fat when assessing CVD and mortality risk among patients with T2D,” wrote the authors.

SOURCE:

The study led by Zixin Qiu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, was published online in The Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

As body fat was measured only once at the beginning of the study, its changing association over time could not be assessed. Moreover, the findings were primarily based on predominantly White UK adults, potentially restricting their generalizability to other population groups. Furthermore, diabetes was diagnosed using self-reported medical history, medication, and hemoglobin A1c levels, implying that some cases may have gone undetected at baseline. 

DISCLOSURES:

This study was funded by grants from the National Natural Science Foundation of China, Hubei Province Science Fund for Distinguished Young Scholars, and Fundamental Research Funds for the Central Universities. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

In people with type 2 diabetes (T2D), higher levels of arm and trunk fat are associated with an increased risk for cardiovascular disease (CVD) and mortality, while higher levels of leg fat are associated with a reduced risk for these conditions.

METHODOLOGY:

• People with T2D have a twofold to fourfold higher risk for CVD and mortality, and evidence shows obesity management helps delay complications and premature death, but an elevated body mass index (BMI) may be insufficient to measure obesity.
• In the “obesity paradox,” people with elevated BMI may have a lower CVD risk than people of normal weight.
• Researchers prospectively investigated how regional body fat accumulation was associated with CVD risk in 21,472 people with T2D (mean age, 58.9 years; 60.7% men; BMI about 29-33) from the UK Biobank (2006-2010), followed up for a median of 7.7 years.
• The regional body fat distribution in arms, trunk, and legs was assessed using bioelectrical impedance analysis.
• The primary outcomes were the incidence of CVD, all-cause mortality, and CVD mortality.

TAKEAWAY:

• Participants in the highest quartile of arm fat percentage (multivariate-adjusted hazard ratio [HR], 1.63; 95% CI, 1.29-2.05) and trunk fat percentage (HR, 1.27; 95% CI, 1.06-1.52) were at a higher risk for CVD than those in the lowest quartile.
• However, participants in the highest quartile of leg fat percentage had a lower risk for CVD than those in the lowest quartile (HR, 0.72; 95% CI, 0.58-0.90).
• A nonlinear relationship was observed between higher leg fat percentage and lower CVD risk and between higher trunk fat percentage and higher CVD risk, whereas a linear relationship was noted between higher arm fat percentage and higher CVD risk.
• The patterns of association were similar for both all-cause mortality and CVD mortality. Overall patterns were similar for men and women.

IN PRACTICE:

“Our findings add to the understanding of body fat distribution in patients with T2D, which highlights the importance of considering both the amount and the location of body fat when assessing CVD and mortality risk among patients with T2D,” wrote the authors.

SOURCE:

The study led by Zixin Qiu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, was published online in The Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

As body fat was measured only once at the beginning of the study, its changing association over time could not be assessed. Moreover, the findings were primarily based on predominantly White UK adults, potentially restricting their generalizability to other population groups. Furthermore, diabetes was diagnosed using self-reported medical history, medication, and hemoglobin A1c levels, implying that some cases may have gone undetected at baseline. 

DISCLOSURES:

This study was funded by grants from the National Natural Science Foundation of China, Hubei Province Science Fund for Distinguished Young Scholars, and Fundamental Research Funds for the Central Universities. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Monthly cycles of a fasting-mimicking diet (FMD) may slow metabolic and immune system aging and reduce the risk for metabolic disease.

METHODOLOGY:

• In two clinical trials, monthly 5-day cycles of an FMD (a proprietary line of plant-based, low-calorie, and low-protein food products) showed lower body weight, body fat, and blood pressure at 3 months.
• Researchers assessed secondary outcomes for the impact of the diet on risk factors for metabolic syndrome and biomarkers associated with aging and age-related diseases.
• This study looked at data from nearly half of the original 184 participants (aged 18-70 years) from the two clinical trials who went through three to four monthly cycles, adhering to 5 days of an FMD in either a crossover design compared with a normal diet or an intervention group compared with people following a Mediterranean diet.
• Abdominal fat and hepatic fat were measured using an MRI in a subset of representative participants. The study also assessed metabolic blood markers and lipids and lymphoid-to-myeloid ratios (for immune aging).
• Biological age estimation was calculated from seven clinical chemistry measures, and life expectancy and mortality risk estimates and a simulation of continued FMD cycles were based on the National Health and Nutrition Examination Survey.

TAKEAWAY:

• In 15 volunteers measured by MRI, the body mass index (P = .0002), total body fat (P = .002), subcutaneous adipose tissue (P = .008), visceral adipose tissue (P = .002), and hepatic fat fraction (P = .049) reduced after the third FMD cycle, with a 50% reduction in liver fat for the five people with hepatic steatosis.
• In 11 participants with prediabetes, insulin resistance (measured by homeostatic model assessment) reduced from 1.473 to 1.209 (P = .046), while A1c levels dropped from 5.8 to 5.43 (P = .032) after the third FMD cycle.

• The lymphoid-to-myeloid ratio improved (P = .005) in all study participants receiving three FMD cycles, indicating an immune aging reversal.
• The estimated median biological age of the 86 participants who completed three FMD cycles in both trials decreased by nearly 2.5 years, independent of weight loss.

IN PRACTICE:

“Together our findings indicate that the FMD is a feasible periodic dietary intervention that reduces disease risk factors and biological age,” the authors wrote.

SOURCE:

The study, led by Sebastian Brandhorst, PhD, Leonard Davis School of Gerontology, University of Southern California (USC), Los Angeles, and Morgan E. Levine, PhD, Department of Pathology, Yale School of Medicine, New Haven, Connecticut, was published in Nature Communications.

LIMITATIONS:

The study estimated the effects of monthly FMD cycles based on results from two clinical trials and included a small subset of trial volunteers. By study measures, the cohort was healthier and biologically younger than average people of similar chronological age. Of the 86 participants, 24 who underwent FMD cycles exhibited increased biological age. The simulation did not consider compliance, dropout, mortality, or the bias that may arise owing to enthusiastic volunteers. Estimated risk reductions assume an effect of change in biological age, which hasn’t been proven. Projections from extending the effects of FMD to a lifelong intervention may require cautious interpretation.

DISCLOSURES:

The study was supported by the USC Edna Jones chair fund and funds from NIH/NIA and the Yale PEPPER Center. The experimental diet was provided by L-Nutra Inc. Some authors declared an equity interest in L-Nutra, with one author’s equity to be assigned to the nonprofit foundation Create Cures. Others disclosed no conflicts of interest.
 

A version of this article appeared on Medscape.com.

TOPLINE:

Monthly cycles of a fasting-mimicking diet (FMD) may slow metabolic and immune system aging and reduce the risk for metabolic disease.

METHODOLOGY:

• In two clinical trials, monthly 5-day cycles of an FMD (a proprietary line of plant-based, low-calorie, and low-protein food products) showed lower body weight, body fat, and blood pressure at 3 months.
• Researchers assessed secondary outcomes for the impact of the diet on risk factors for metabolic syndrome and biomarkers associated with aging and age-related diseases.
• This study looked at data from nearly half of the original 184 participants (aged 18-70 years) from the two clinical trials who went through three to four monthly cycles, adhering to 5 days of an FMD in either a crossover design compared with a normal diet or an intervention group compared with people following a Mediterranean diet.
• Abdominal fat and hepatic fat were measured using an MRI in a subset of representative participants. The study also assessed metabolic blood markers and lipids and lymphoid-to-myeloid ratios (for immune aging).
• Biological age estimation was calculated from seven clinical chemistry measures, and life expectancy and mortality risk estimates and a simulation of continued FMD cycles were based on the National Health and Nutrition Examination Survey.

TAKEAWAY:

• In 15 volunteers measured by MRI, the body mass index (P = .0002), total body fat (P = .002), subcutaneous adipose tissue (P = .008), visceral adipose tissue (P = .002), and hepatic fat fraction (P = .049) reduced after the third FMD cycle, with a 50% reduction in liver fat for the five people with hepatic steatosis.
• In 11 participants with prediabetes, insulin resistance (measured by homeostatic model assessment) reduced from 1.473 to 1.209 (P = .046), while A1c levels dropped from 5.8 to 5.43 (P = .032) after the third FMD cycle.

• The lymphoid-to-myeloid ratio improved (P = .005) in all study participants receiving three FMD cycles, indicating an immune aging reversal.
• The estimated median biological age of the 86 participants who completed three FMD cycles in both trials decreased by nearly 2.5 years, independent of weight loss.

IN PRACTICE:

“Together our findings indicate that the FMD is a feasible periodic dietary intervention that reduces disease risk factors and biological age,” the authors wrote.

SOURCE:

The study, led by Sebastian Brandhorst, PhD, Leonard Davis School of Gerontology, University of Southern California (USC), Los Angeles, and Morgan E. Levine, PhD, Department of Pathology, Yale School of Medicine, New Haven, Connecticut, was published in Nature Communications.

LIMITATIONS:

The study estimated the effects of monthly FMD cycles based on results from two clinical trials and included a small subset of trial volunteers. By study measures, the cohort was healthier and biologically younger than average people of similar chronological age. Of the 86 participants, 24 who underwent FMD cycles exhibited increased biological age. The simulation did not consider compliance, dropout, mortality, or the bias that may arise owing to enthusiastic volunteers. Estimated risk reductions assume an effect of change in biological age, which hasn’t been proven. Projections from extending the effects of FMD to a lifelong intervention may require cautious interpretation.

DISCLOSURES:

The study was supported by the USC Edna Jones chair fund and funds from NIH/NIA and the Yale PEPPER Center. The experimental diet was provided by L-Nutra Inc. Some authors declared an equity interest in L-Nutra, with one author’s equity to be assigned to the nonprofit foundation Create Cures. Others disclosed no conflicts of interest.
 

A version of this article appeared on Medscape.com.

TOPLINE:

Monthly cycles of a fasting-mimicking diet (FMD) may slow metabolic and immune system aging and reduce the risk for metabolic disease.

METHODOLOGY:

• In two clinical trials, monthly 5-day cycles of an FMD (a proprietary line of plant-based, low-calorie, and low-protein food products) showed lower body weight, body fat, and blood pressure at 3 months.
• Researchers assessed secondary outcomes for the impact of the diet on risk factors for metabolic syndrome and biomarkers associated with aging and age-related diseases.
• This study looked at data from nearly half of the original 184 participants (aged 18-70 years) from the two clinical trials who went through three to four monthly cycles, adhering to 5 days of an FMD in either a crossover design compared with a normal diet or an intervention group compared with people following a Mediterranean diet.
• Abdominal fat and hepatic fat were measured using an MRI in a subset of representative participants. The study also assessed metabolic blood markers and lipids and lymphoid-to-myeloid ratios (for immune aging).
• Biological age estimation was calculated from seven clinical chemistry measures, and life expectancy and mortality risk estimates and a simulation of continued FMD cycles were based on the National Health and Nutrition Examination Survey.

TAKEAWAY:

• In 15 volunteers measured by MRI, the body mass index (P = .0002), total body fat (P = .002), subcutaneous adipose tissue (P = .008), visceral adipose tissue (P = .002), and hepatic fat fraction (P = .049) reduced after the third FMD cycle, with a 50% reduction in liver fat for the five people with hepatic steatosis.
• In 11 participants with prediabetes, insulin resistance (measured by homeostatic model assessment) reduced from 1.473 to 1.209 (P = .046), while A1c levels dropped from 5.8 to 5.43 (P = .032) after the third FMD cycle.

• The lymphoid-to-myeloid ratio improved (P = .005) in all study participants receiving three FMD cycles, indicating an immune aging reversal.
• The estimated median biological age of the 86 participants who completed three FMD cycles in both trials decreased by nearly 2.5 years, independent of weight loss.

IN PRACTICE:

“Together our findings indicate that the FMD is a feasible periodic dietary intervention that reduces disease risk factors and biological age,” the authors wrote.

SOURCE:

The study, led by Sebastian Brandhorst, PhD, Leonard Davis School of Gerontology, University of Southern California (USC), Los Angeles, and Morgan E. Levine, PhD, Department of Pathology, Yale School of Medicine, New Haven, Connecticut, was published in Nature Communications.

LIMITATIONS:

The study estimated the effects of monthly FMD cycles based on results from two clinical trials and included a small subset of trial volunteers. By study measures, the cohort was healthier and biologically younger than average people of similar chronological age. Of the 86 participants, 24 who underwent FMD cycles exhibited increased biological age. The simulation did not consider compliance, dropout, mortality, or the bias that may arise owing to enthusiastic volunteers. Estimated risk reductions assume an effect of change in biological age, which hasn’t been proven. Projections from extending the effects of FMD to a lifelong intervention may require cautious interpretation.

DISCLOSURES:

The study was supported by the USC Edna Jones chair fund and funds from NIH/NIA and the Yale PEPPER Center. The experimental diet was provided by L-Nutra Inc. Some authors declared an equity interest in L-Nutra, with one author’s equity to be assigned to the nonprofit foundation Create Cures. Others disclosed no conflicts of interest.
 

A version of this article appeared on Medscape.com.

Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the risk for amputation.

Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.

Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic wound management. These models use deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.

AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately detect signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated “foot selfie” to predict and prevent problems before they start.

AI’s predictive capabilities are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.

Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.

As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.

Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.

A version of this article first appeared on Medscape.com.

Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the risk for amputation.

Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.

Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic wound management. These models use deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.

AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately detect signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated “foot selfie” to predict and prevent problems before they start.

AI’s predictive capabilities are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.

Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.

As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.

Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.

A version of this article first appeared on Medscape.com.

Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the risk for amputation.

Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.

Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic wound management. These models use deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.

AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately detect signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated “foot selfie” to predict and prevent problems before they start.

AI’s predictive capabilities are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.

Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.

As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.

Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.

A version of this article first appeared on Medscape.com.

Among adults with type 2 diabetes (T2D) older than 65 years, a body mass index (BMI) in the moderate overweight category (26-28) appears to offer better protection from cardiovascular death than does a BMI in the “normal” range, new data suggested.

On the other hand, the study findings also suggest that the “normal” range of 23-25 is optimal for middle-aged adults with T2D.

The findings reflect a previously demonstrated phenomenon called the “obesity paradox,” in which older people with overweight may have better outcomes than leaner people due to factors such as bone loss, frailty, and nutritional deficits, study lead author Shaoyong Xu, of Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China, told this news organization.

“In this era of population growth and aging, the question arises as to whether obesity or overweight can be beneficial in improving survival rates for older individuals with diabetes. This topic holds significant relevance due to the potential implications it has on weight management strategies for older adults. If overweight does not pose an increased risk of cardiovascular mortality, it may suggest that older individuals are not necessarily required to strive for weight loss to achieve so-called normal values.”

Moreover, Dr. Xu added, “inappropriate weight loss and being underweight could potentially elevate the risk of cardiovascular events, myocardial infarction, cerebral infarction, and all-cause mortality.”

Thus, he said, “while there are general guidelines recommending a BMI below 25, our findings suggest that personalized BMI targets may be more beneficial, particularly for different age groups and individuals with specific health conditions.”

Asked to comment, Ian J. Neeland, MD, director of cardiovascular prevention, University Hospitals Harrington Heart & Vascular Institute, Case Western Reserve University, Cleveland, Ohio, pointed out that older people who are underweight or in lower weight categories may be more likely to smoke or have undiagnosed cancer, or that “their BMI is not so much reflective of fat mass as of low muscle mass, or sarcopenia, and that is definitely a risk factor for adverse outcomes and risks. ... And those who have slightly higher BMIs may be maintaining muscle mass, even though they’re older, and therefore they have less risk.”

However, Dr. Neeland disagreed with the authors’ conclusions regarding “optimal” BMI. “Just because you have different risk categories based on BMI doesn’t mean that’s ‘optimal’ BMI. The way I would interpret this paper is that there’s an association of mildly overweight with better outcomes in adults who are over 65 with type 2 diabetes. We need to try to understand the mechanisms underlying that observation.”

Dr. Neeland advised that for an older person with T2D who has low muscle mass and frailty, “I wouldn’t recommend necessarily targeted weight loss in that person. But I would potentially recommend weight loss in addition to resistance training, muscle building, and endurance training, and therefore reducing fat mass. The goal would be not so much weight loss but reduction of body fat and maintaining and improving muscle health.”
 

U-Shaped Relationship Found Between Age, BMI, and Cardiovascular Disease (CVD) Risk

The data come from the UK Biobank, a population-based prospective cohort study of adults in the United Kingdom. A total of 22,874 participants with baseline T2D were included in the current study. Baseline surveys were conducted between 2006 and 2010, and follow-up was a median of 12.52 years. During that time, 891 people died of CVD.

Hazard ratios were adjusted for baseline variables including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of CVDs.

Compared with people with BMI a < 25 in the group who were aged 65 years or younger, those with a BMI of 25.0-29.9 had a 13% higher risk for cardiovascular death. However, among those older than 65 years, a BMI between 25.0 and 29.9 was associated with an 18% lower risk.

A U-shaped relationship was found between BMI and the risk for cardiovascular death, with an optimal BMI cutoff of 24.0 in the under-65 group and a 27.0 cutoff in the older group. Ranges of 23.0-25.0 in the under-65 group and 26.0-28 in the older group were associated with the lowest cardiovascular risk.

In contrast, there was a linear relationship between both waist circumference and waist-to-height ratio and the risk for cardiovascular death, making those more direct measures of adiposity, Dr. Xu told this news organization.

“For clinicians, our data underscores the importance of considering age when assessing BMI targets for cardiovascular health. Personalized treatment plans that account for age-specific BMI cutoffs and other risk factors may enhance patient outcomes and reduce CVD mortality,” Dr. Xu said.

However, he added, “while these findings suggest an optimal BMI range, it is crucial to acknowledge that these cutoff points may vary based on gender, race, and other factors. Our future studies will validate these findings in different populations and attempt to explain the mechanism by which the optimal nodal values exist in people with diabetes at different ages.”

Dr. Neeland cautioned, “I think more work needs to be done in terms of not just identifying the risk differences but understanding why and how to better risk stratify individuals and do personalized medicine. I think that’s important, but you have to have good data to support the strategies you’re going to use. These data are observational, and they’re a good start, but they wouldn’t directly impact practice at this point.”

The data will be presented at the European Congress on Obesity taking place May 12-15 in Venice, Italy.

The authors declared no competing interests. Study funding came from several sources, including the Young Talents Project of Hubei Provincial Health Commission, China, Hubei Provincial Natural Science Foundation of China, the Science and Technology Research Key Project of the Education Department of Hubei Province China, and the Sanuo Diabetes Charity Foundation, China, and the Xiangyang Science and Technology Plan Project, China. Dr. Neeland is a speaker and/or consultant for Boehringer Ingelheim, Novo Nordisk, Bayer, and Eli Lilly and Company.
 

A version of this article appeared on Medscape.com.

Among adults with type 2 diabetes (T2D) older than 65 years, a body mass index (BMI) in the moderate overweight category (26-28) appears to offer better protection from cardiovascular death than does a BMI in the “normal” range, new data suggested.

On the other hand, the study findings also suggest that the “normal” range of 23-25 is optimal for middle-aged adults with T2D.

The findings reflect a previously demonstrated phenomenon called the “obesity paradox,” in which older people with overweight may have better outcomes than leaner people due to factors such as bone loss, frailty, and nutritional deficits, study lead author Shaoyong Xu, of Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China, told this news organization.

“In this era of population growth and aging, the question arises as to whether obesity or overweight can be beneficial in improving survival rates for older individuals with diabetes. This topic holds significant relevance due to the potential implications it has on weight management strategies for older adults. If overweight does not pose an increased risk of cardiovascular mortality, it may suggest that older individuals are not necessarily required to strive for weight loss to achieve so-called normal values.”

Moreover, Dr. Xu added, “inappropriate weight loss and being underweight could potentially elevate the risk of cardiovascular events, myocardial infarction, cerebral infarction, and all-cause mortality.”

Thus, he said, “while there are general guidelines recommending a BMI below 25, our findings suggest that personalized BMI targets may be more beneficial, particularly for different age groups and individuals with specific health conditions.”

Asked to comment, Ian J. Neeland, MD, director of cardiovascular prevention, University Hospitals Harrington Heart & Vascular Institute, Case Western Reserve University, Cleveland, Ohio, pointed out that older people who are underweight or in lower weight categories may be more likely to smoke or have undiagnosed cancer, or that “their BMI is not so much reflective of fat mass as of low muscle mass, or sarcopenia, and that is definitely a risk factor for adverse outcomes and risks. ... And those who have slightly higher BMIs may be maintaining muscle mass, even though they’re older, and therefore they have less risk.”

However, Dr. Neeland disagreed with the authors’ conclusions regarding “optimal” BMI. “Just because you have different risk categories based on BMI doesn’t mean that’s ‘optimal’ BMI. The way I would interpret this paper is that there’s an association of mildly overweight with better outcomes in adults who are over 65 with type 2 diabetes. We need to try to understand the mechanisms underlying that observation.”

Dr. Neeland advised that for an older person with T2D who has low muscle mass and frailty, “I wouldn’t recommend necessarily targeted weight loss in that person. But I would potentially recommend weight loss in addition to resistance training, muscle building, and endurance training, and therefore reducing fat mass. The goal would be not so much weight loss but reduction of body fat and maintaining and improving muscle health.”
 

U-Shaped Relationship Found Between Age, BMI, and Cardiovascular Disease (CVD) Risk

The data come from the UK Biobank, a population-based prospective cohort study of adults in the United Kingdom. A total of 22,874 participants with baseline T2D were included in the current study. Baseline surveys were conducted between 2006 and 2010, and follow-up was a median of 12.52 years. During that time, 891 people died of CVD.

Hazard ratios were adjusted for baseline variables including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of CVDs.

Compared with people with BMI a < 25 in the group who were aged 65 years or younger, those with a BMI of 25.0-29.9 had a 13% higher risk for cardiovascular death. However, among those older than 65 years, a BMI between 25.0 and 29.9 was associated with an 18% lower risk.

A U-shaped relationship was found between BMI and the risk for cardiovascular death, with an optimal BMI cutoff of 24.0 in the under-65 group and a 27.0 cutoff in the older group. Ranges of 23.0-25.0 in the under-65 group and 26.0-28 in the older group were associated with the lowest cardiovascular risk.

In contrast, there was a linear relationship between both waist circumference and waist-to-height ratio and the risk for cardiovascular death, making those more direct measures of adiposity, Dr. Xu told this news organization.

“For clinicians, our data underscores the importance of considering age when assessing BMI targets for cardiovascular health. Personalized treatment plans that account for age-specific BMI cutoffs and other risk factors may enhance patient outcomes and reduce CVD mortality,” Dr. Xu said.

However, he added, “while these findings suggest an optimal BMI range, it is crucial to acknowledge that these cutoff points may vary based on gender, race, and other factors. Our future studies will validate these findings in different populations and attempt to explain the mechanism by which the optimal nodal values exist in people with diabetes at different ages.”

Dr. Neeland cautioned, “I think more work needs to be done in terms of not just identifying the risk differences but understanding why and how to better risk stratify individuals and do personalized medicine. I think that’s important, but you have to have good data to support the strategies you’re going to use. These data are observational, and they’re a good start, but they wouldn’t directly impact practice at this point.”

The data will be presented at the European Congress on Obesity taking place May 12-15 in Venice, Italy.

The authors declared no competing interests. Study funding came from several sources, including the Young Talents Project of Hubei Provincial Health Commission, China, Hubei Provincial Natural Science Foundation of China, the Science and Technology Research Key Project of the Education Department of Hubei Province China, and the Sanuo Diabetes Charity Foundation, China, and the Xiangyang Science and Technology Plan Project, China. Dr. Neeland is a speaker and/or consultant for Boehringer Ingelheim, Novo Nordisk, Bayer, and Eli Lilly and Company.
 

A version of this article appeared on Medscape.com.

Among adults with type 2 diabetes (T2D) older than 65 years, a body mass index (BMI) in the moderate overweight category (26-28) appears to offer better protection from cardiovascular death than does a BMI in the “normal” range, new data suggested.

On the other hand, the study findings also suggest that the “normal” range of 23-25 is optimal for middle-aged adults with T2D.

The findings reflect a previously demonstrated phenomenon called the “obesity paradox,” in which older people with overweight may have better outcomes than leaner people due to factors such as bone loss, frailty, and nutritional deficits, study lead author Shaoyong Xu, of Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China, told this news organization.

“In this era of population growth and aging, the question arises as to whether obesity or overweight can be beneficial in improving survival rates for older individuals with diabetes. This topic holds significant relevance due to the potential implications it has on weight management strategies for older adults. If overweight does not pose an increased risk of cardiovascular mortality, it may suggest that older individuals are not necessarily required to strive for weight loss to achieve so-called normal values.”

Moreover, Dr. Xu added, “inappropriate weight loss and being underweight could potentially elevate the risk of cardiovascular events, myocardial infarction, cerebral infarction, and all-cause mortality.”

Thus, he said, “while there are general guidelines recommending a BMI below 25, our findings suggest that personalized BMI targets may be more beneficial, particularly for different age groups and individuals with specific health conditions.”

Asked to comment, Ian J. Neeland, MD, director of cardiovascular prevention, University Hospitals Harrington Heart & Vascular Institute, Case Western Reserve University, Cleveland, Ohio, pointed out that older people who are underweight or in lower weight categories may be more likely to smoke or have undiagnosed cancer, or that “their BMI is not so much reflective of fat mass as of low muscle mass, or sarcopenia, and that is definitely a risk factor for adverse outcomes and risks. ... And those who have slightly higher BMIs may be maintaining muscle mass, even though they’re older, and therefore they have less risk.”

However, Dr. Neeland disagreed with the authors’ conclusions regarding “optimal” BMI. “Just because you have different risk categories based on BMI doesn’t mean that’s ‘optimal’ BMI. The way I would interpret this paper is that there’s an association of mildly overweight with better outcomes in adults who are over 65 with type 2 diabetes. We need to try to understand the mechanisms underlying that observation.”

Dr. Neeland advised that for an older person with T2D who has low muscle mass and frailty, “I wouldn’t recommend necessarily targeted weight loss in that person. But I would potentially recommend weight loss in addition to resistance training, muscle building, and endurance training, and therefore reducing fat mass. The goal would be not so much weight loss but reduction of body fat and maintaining and improving muscle health.”
 

U-Shaped Relationship Found Between Age, BMI, and Cardiovascular Disease (CVD) Risk

The data come from the UK Biobank, a population-based prospective cohort study of adults in the United Kingdom. A total of 22,874 participants with baseline T2D were included in the current study. Baseline surveys were conducted between 2006 and 2010, and follow-up was a median of 12.52 years. During that time, 891 people died of CVD.

Hazard ratios were adjusted for baseline variables including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of CVDs.

Compared with people with BMI a < 25 in the group who were aged 65 years or younger, those with a BMI of 25.0-29.9 had a 13% higher risk for cardiovascular death. However, among those older than 65 years, a BMI between 25.0 and 29.9 was associated with an 18% lower risk.

A U-shaped relationship was found between BMI and the risk for cardiovascular death, with an optimal BMI cutoff of 24.0 in the under-65 group and a 27.0 cutoff in the older group. Ranges of 23.0-25.0 in the under-65 group and 26.0-28 in the older group were associated with the lowest cardiovascular risk.

In contrast, there was a linear relationship between both waist circumference and waist-to-height ratio and the risk for cardiovascular death, making those more direct measures of adiposity, Dr. Xu told this news organization.

“For clinicians, our data underscores the importance of considering age when assessing BMI targets for cardiovascular health. Personalized treatment plans that account for age-specific BMI cutoffs and other risk factors may enhance patient outcomes and reduce CVD mortality,” Dr. Xu said.

However, he added, “while these findings suggest an optimal BMI range, it is crucial to acknowledge that these cutoff points may vary based on gender, race, and other factors. Our future studies will validate these findings in different populations and attempt to explain the mechanism by which the optimal nodal values exist in people with diabetes at different ages.”

Dr. Neeland cautioned, “I think more work needs to be done in terms of not just identifying the risk differences but understanding why and how to better risk stratify individuals and do personalized medicine. I think that’s important, but you have to have good data to support the strategies you’re going to use. These data are observational, and they’re a good start, but they wouldn’t directly impact practice at this point.”

The data will be presented at the European Congress on Obesity taking place May 12-15 in Venice, Italy.

The authors declared no competing interests. Study funding came from several sources, including the Young Talents Project of Hubei Provincial Health Commission, China, Hubei Provincial Natural Science Foundation of China, the Science and Technology Research Key Project of the Education Department of Hubei Province China, and the Sanuo Diabetes Charity Foundation, China, and the Xiangyang Science and Technology Plan Project, China. Dr. Neeland is a speaker and/or consultant for Boehringer Ingelheim, Novo Nordisk, Bayer, and Eli Lilly and Company.
 

A version of this article appeared on Medscape.com.

This case is a little out of the ordinary, but we would love to find out how readers would handle it.

Diana is a 51-year-old woman with a history of depression, obesity, hypertension, type 2 diabetes, and coronary artery disease. She has come in for a routine visit for her chronic illnesses. She seems very distant and has a flat affect during the initial interview. When you ask about any recent stressful events, she begins crying and explains that her daughter was just deported, leaving behind a child and boyfriend.

Their country of origin suffers from chronic instability and violence. Diana’s father was murdered there, and Diana was the victim of sexual assault. “I escaped when I was 18, and I tried to never look back. Until now.” Diana is very worried about her daughter’s return to that country. “I don’t want her to have to endure what I have endured.”

You spend some time discussing the patient’s mental health burden and identify a counselor and online resources that might help. You wonder if Diana’s adverse childhood experiences (ACEs) might have contributed to some of her physical illnesses.

ACEs and Adult Health

The effects of trauma run long and deep. ACEs have been associated with higher risks for multiple chronic conditions, even among adults aged 60 years or older. Therefore, clinicians should consider a patient’s history of ACEs as part of their evaluation of risk for chronic illness.

One of the most pronounced and straightforward links is that between ACEs and depression. In the Southern Community Cohort Study of more than 38,200 US adults, the highest odds ratio between ACEs and chronic disease was for depression. Persons who reported more than three ACEs had about a twofold increase in the risk for depression compared with persons without ACEs. There was a monotonic increase in the risk for depression and other chronic illnesses as the burden of ACEs increased.

In another study from the United Kingdom, each additional ACE was associated with a significant 11% increase in the risk for incident diabetes during adulthood. Researchers found that both depression symptoms and cardiometabolic dysfunction mediated the effects of ACEs in promoting higher rates of diabetes.

Depression and diabetes are significant risk factors for coronary artery disease, so it is not surprising that ACEs are also associated with a higher risk for coronary events. A review by Godoy and colleagues described how ACEs promote neuroendocrine, autonomic, and inflammatory dysfunction, which in turn leads to higher rates of traditional cardiovascular risk factors such as diabetes and obesity. Ultimately, the presence of four or more ACEs is associated with more than a twofold higher risk for cardiovascular disease compared with no ACEs.

Many of the pathologic processes that promote cardiovascular disease also increase the risk for dementia. Could the reach of ACEs span decades to promote a higher risk for dementia among older adults? A study by Yuan and colleagues of 7222 Chinese adults suggests that the answer is yes. This study divided the cohort into persons with a history of no ACEs, household dysfunction during childhood, or mistreatment during childhood. Child mistreatment was associated with higher rates of diabetes, depression, and cardiovascular disease, as well as an odds ratio of 1.37 (95% CI, 1.12 to 1.68) for cognitive impairment.

The magnitude of the effects ACEs can have on well-being is reinforced by epidemiologic data surrounding ACEs. According to the US Centers for Disease Control and Prevention (CDC), 64% of US adults report at least one ACE and 17% experienced at least four ACEs. Risk factors for ACEs include being female, American Indian or Alaska Native, or unemployed.

How do we reduce the impact of ACEs? Prevention is key. The CDC estimates that nearly 2 million cases of adult heart disease and more than 20 million cases of adult depression could be avoided if ACEs were eliminated.

But what is the best means to pragmatically reduce ACEs in our current practice models? How do we discover a history of ACEs in patients, and what are the best practices in managing persons with a positive history? We will cover these critical subjects in a future article, but for now, please provide your own comments and pearls regarding the prevention and management of ACEs.

Dr. Vega, health sciences clinical professor, family medicine, University of California, Irvine, disclosed ties with GlaxoSmithKline and Johnson and Johnson. Ms. Hurtado, MD candidate, University of California, Irvine School of Medicine, has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

This case is a little out of the ordinary, but we would love to find out how readers would handle it.

Diana is a 51-year-old woman with a history of depression, obesity, hypertension, type 2 diabetes, and coronary artery disease. She has come in for a routine visit for her chronic illnesses. She seems very distant and has a flat affect during the initial interview. When you ask about any recent stressful events, she begins crying and explains that her daughter was just deported, leaving behind a child and boyfriend.

Their country of origin suffers from chronic instability and violence. Diana’s father was murdered there, and Diana was the victim of sexual assault. “I escaped when I was 18, and I tried to never look back. Until now.” Diana is very worried about her daughter’s return to that country. “I don’t want her to have to endure what I have endured.”

You spend some time discussing the patient’s mental health burden and identify a counselor and online resources that might help. You wonder if Diana’s adverse childhood experiences (ACEs) might have contributed to some of her physical illnesses.

ACEs and Adult Health

The effects of trauma run long and deep. ACEs have been associated with higher risks for multiple chronic conditions, even among adults aged 60 years or older. Therefore, clinicians should consider a patient’s history of ACEs as part of their evaluation of risk for chronic illness.

One of the most pronounced and straightforward links is that between ACEs and depression. In the Southern Community Cohort Study of more than 38,200 US adults, the highest odds ratio between ACEs and chronic disease was for depression. Persons who reported more than three ACEs had about a twofold increase in the risk for depression compared with persons without ACEs. There was a monotonic increase in the risk for depression and other chronic illnesses as the burden of ACEs increased.

In another study from the United Kingdom, each additional ACE was associated with a significant 11% increase in the risk for incident diabetes during adulthood. Researchers found that both depression symptoms and cardiometabolic dysfunction mediated the effects of ACEs in promoting higher rates of diabetes.

Depression and diabetes are significant risk factors for coronary artery disease, so it is not surprising that ACEs are also associated with a higher risk for coronary events. A review by Godoy and colleagues described how ACEs promote neuroendocrine, autonomic, and inflammatory dysfunction, which in turn leads to higher rates of traditional cardiovascular risk factors such as diabetes and obesity. Ultimately, the presence of four or more ACEs is associated with more than a twofold higher risk for cardiovascular disease compared with no ACEs.

Many of the pathologic processes that promote cardiovascular disease also increase the risk for dementia. Could the reach of ACEs span decades to promote a higher risk for dementia among older adults? A study by Yuan and colleagues of 7222 Chinese adults suggests that the answer is yes. This study divided the cohort into persons with a history of no ACEs, household dysfunction during childhood, or mistreatment during childhood. Child mistreatment was associated with higher rates of diabetes, depression, and cardiovascular disease, as well as an odds ratio of 1.37 (95% CI, 1.12 to 1.68) for cognitive impairment.

The magnitude of the effects ACEs can have on well-being is reinforced by epidemiologic data surrounding ACEs. According to the US Centers for Disease Control and Prevention (CDC), 64% of US adults report at least one ACE and 17% experienced at least four ACEs. Risk factors for ACEs include being female, American Indian or Alaska Native, or unemployed.

How do we reduce the impact of ACEs? Prevention is key. The CDC estimates that nearly 2 million cases of adult heart disease and more than 20 million cases of adult depression could be avoided if ACEs were eliminated.

But what is the best means to pragmatically reduce ACEs in our current practice models? How do we discover a history of ACEs in patients, and what are the best practices in managing persons with a positive history? We will cover these critical subjects in a future article, but for now, please provide your own comments and pearls regarding the prevention and management of ACEs.

Dr. Vega, health sciences clinical professor, family medicine, University of California, Irvine, disclosed ties with GlaxoSmithKline and Johnson and Johnson. Ms. Hurtado, MD candidate, University of California, Irvine School of Medicine, has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

This case is a little out of the ordinary, but we would love to find out how readers would handle it.

Diana is a 51-year-old woman with a history of depression, obesity, hypertension, type 2 diabetes, and coronary artery disease. She has come in for a routine visit for her chronic illnesses. She seems very distant and has a flat affect during the initial interview. When you ask about any recent stressful events, she begins crying and explains that her daughter was just deported, leaving behind a child and boyfriend.

Their country of origin suffers from chronic instability and violence. Diana’s father was murdered there, and Diana was the victim of sexual assault. “I escaped when I was 18, and I tried to never look back. Until now.” Diana is very worried about her daughter’s return to that country. “I don’t want her to have to endure what I have endured.”

You spend some time discussing the patient’s mental health burden and identify a counselor and online resources that might help. You wonder if Diana’s adverse childhood experiences (ACEs) might have contributed to some of her physical illnesses.

ACEs and Adult Health

The effects of trauma run long and deep. ACEs have been associated with higher risks for multiple chronic conditions, even among adults aged 60 years or older. Therefore, clinicians should consider a patient’s history of ACEs as part of their evaluation of risk for chronic illness.

One of the most pronounced and straightforward links is that between ACEs and depression. In the Southern Community Cohort Study of more than 38,200 US adults, the highest odds ratio between ACEs and chronic disease was for depression. Persons who reported more than three ACEs had about a twofold increase in the risk for depression compared with persons without ACEs. There was a monotonic increase in the risk for depression and other chronic illnesses as the burden of ACEs increased.

In another study from the United Kingdom, each additional ACE was associated with a significant 11% increase in the risk for incident diabetes during adulthood. Researchers found that both depression symptoms and cardiometabolic dysfunction mediated the effects of ACEs in promoting higher rates of diabetes.

Depression and diabetes are significant risk factors for coronary artery disease, so it is not surprising that ACEs are also associated with a higher risk for coronary events. A review by Godoy and colleagues described how ACEs promote neuroendocrine, autonomic, and inflammatory dysfunction, which in turn leads to higher rates of traditional cardiovascular risk factors such as diabetes and obesity. Ultimately, the presence of four or more ACEs is associated with more than a twofold higher risk for cardiovascular disease compared with no ACEs.

Many of the pathologic processes that promote cardiovascular disease also increase the risk for dementia. Could the reach of ACEs span decades to promote a higher risk for dementia among older adults? A study by Yuan and colleagues of 7222 Chinese adults suggests that the answer is yes. This study divided the cohort into persons with a history of no ACEs, household dysfunction during childhood, or mistreatment during childhood. Child mistreatment was associated with higher rates of diabetes, depression, and cardiovascular disease, as well as an odds ratio of 1.37 (95% CI, 1.12 to 1.68) for cognitive impairment.

The magnitude of the effects ACEs can have on well-being is reinforced by epidemiologic data surrounding ACEs. According to the US Centers for Disease Control and Prevention (CDC), 64% of US adults report at least one ACE and 17% experienced at least four ACEs. Risk factors for ACEs include being female, American Indian or Alaska Native, or unemployed.

How do we reduce the impact of ACEs? Prevention is key. The CDC estimates that nearly 2 million cases of adult heart disease and more than 20 million cases of adult depression could be avoided if ACEs were eliminated.

But what is the best means to pragmatically reduce ACEs in our current practice models? How do we discover a history of ACEs in patients, and what are the best practices in managing persons with a positive history? We will cover these critical subjects in a future article, but for now, please provide your own comments and pearls regarding the prevention and management of ACEs.

Dr. Vega, health sciences clinical professor, family medicine, University of California, Irvine, disclosed ties with GlaxoSmithKline and Johnson and Johnson. Ms. Hurtado, MD candidate, University of California, Irvine School of Medicine, has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

TOPLINE:

A review of 22 articles found a higher incidence of “altered skin sensations” and alopecia in individuals receiving oral semaglutide than in those receiving placebo.

METHODOLOGY:

• The Food and Drug Administration’s  has not received reports of semaglutide-related safety events, and few studies have characterized skin findings associated with oral or subcutaneous semaglutide, a glucagon-like peptide 1 agonist used to treat obesity and type 2 diabetes.
• In this scoping review, researchers included 22 articles (15 clinical trials, six case reports, and one retrospective cohort study), published through January 2024, of patients receiving either semaglutide or a placebo or comparator, which included reports of semaglutide-associated adverse dermatologic events in 255 participants.

TAKEAWAY:

• Patients who received 50 mg oral semaglutide weekly reported a higher incidence of altered skin sensations, such as dysesthesia (1.8% vs 0%), hyperesthesia (1.2% vs 0%), skin pain (2.4% vs 0%), paresthesia (2.7% vs 0%), and sensitive skin (2.7% vs 0%), than those receiving placebo or comparator.
• Reports of alopecia (6.9% vs 0.3%) were higher in patients who received 50 mg oral semaglutide weekly than in those on placebo, but only 0.2% of patients on 2.4 mg of subcutaneous semaglutide reported alopecia vs 0.5% of those on placebo.
• Unspecified dermatologic reactions (4.1% vs 1.5%) were reported in more patients on subcutaneous semaglutide than those on a placebo or comparator. Several case reports described isolated cases of severe skin-related adverse effects, such as bullous pemphigoid, eosinophilic fasciitis, and leukocytoclastic vasculitis.
• On the contrary, injection site reactions (3.5% vs 6.7%) were less common in patients on subcutaneous semaglutide compared with in those on a placebo or comparator.

IN PRACTICE:

“Variations in dosage and administration routes could influence the types and severity of skin findings, underscoring the need for additional research,” the authors wrote.

SOURCE:

Megan M. Tran, BS, from the Warren Alpert Medical School, Brown University, Providence, Rhode Island, led this study, which was published online in the Journal of the American Academy of Dermatology.

LIMITATIONS:

This study could not adjust for confounding factors and could not establish a direct causal association between semaglutide and the adverse reactions reported.

DISCLOSURES:

This study did not report any funding sources. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

A review of 22 articles found a higher incidence of “altered skin sensations” and alopecia in individuals receiving oral semaglutide than in those receiving placebo.

METHODOLOGY:

• The Food and Drug Administration’s  has not received reports of semaglutide-related safety events, and few studies have characterized skin findings associated with oral or subcutaneous semaglutide, a glucagon-like peptide 1 agonist used to treat obesity and type 2 diabetes.
• In this scoping review, researchers included 22 articles (15 clinical trials, six case reports, and one retrospective cohort study), published through January 2024, of patients receiving either semaglutide or a placebo or comparator, which included reports of semaglutide-associated adverse dermatologic events in 255 participants.

TAKEAWAY:

• Patients who received 50 mg oral semaglutide weekly reported a higher incidence of altered skin sensations, such as dysesthesia (1.8% vs 0%), hyperesthesia (1.2% vs 0%), skin pain (2.4% vs 0%), paresthesia (2.7% vs 0%), and sensitive skin (2.7% vs 0%), than those receiving placebo or comparator.
• Reports of alopecia (6.9% vs 0.3%) were higher in patients who received 50 mg oral semaglutide weekly than in those on placebo, but only 0.2% of patients on 2.4 mg of subcutaneous semaglutide reported alopecia vs 0.5% of those on placebo.
• Unspecified dermatologic reactions (4.1% vs 1.5%) were reported in more patients on subcutaneous semaglutide than those on a placebo or comparator. Several case reports described isolated cases of severe skin-related adverse effects, such as bullous pemphigoid, eosinophilic fasciitis, and leukocytoclastic vasculitis.
• On the contrary, injection site reactions (3.5% vs 6.7%) were less common in patients on subcutaneous semaglutide compared with in those on a placebo or comparator.

IN PRACTICE:

“Variations in dosage and administration routes could influence the types and severity of skin findings, underscoring the need for additional research,” the authors wrote.

SOURCE:

Megan M. Tran, BS, from the Warren Alpert Medical School, Brown University, Providence, Rhode Island, led this study, which was published online in the Journal of the American Academy of Dermatology.

LIMITATIONS:

This study could not adjust for confounding factors and could not establish a direct causal association between semaglutide and the adverse reactions reported.

DISCLOSURES:

This study did not report any funding sources. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

A review of 22 articles found a higher incidence of “altered skin sensations” and alopecia in individuals receiving oral semaglutide than in those receiving placebo.

METHODOLOGY:

• The Food and Drug Administration’s  has not received reports of semaglutide-related safety events, and few studies have characterized skin findings associated with oral or subcutaneous semaglutide, a glucagon-like peptide 1 agonist used to treat obesity and type 2 diabetes.
• In this scoping review, researchers included 22 articles (15 clinical trials, six case reports, and one retrospective cohort study), published through January 2024, of patients receiving either semaglutide or a placebo or comparator, which included reports of semaglutide-associated adverse dermatologic events in 255 participants.

TAKEAWAY:

• Patients who received 50 mg oral semaglutide weekly reported a higher incidence of altered skin sensations, such as dysesthesia (1.8% vs 0%), hyperesthesia (1.2% vs 0%), skin pain (2.4% vs 0%), paresthesia (2.7% vs 0%), and sensitive skin (2.7% vs 0%), than those receiving placebo or comparator.
• Reports of alopecia (6.9% vs 0.3%) were higher in patients who received 50 mg oral semaglutide weekly than in those on placebo, but only 0.2% of patients on 2.4 mg of subcutaneous semaglutide reported alopecia vs 0.5% of those on placebo.
• Unspecified dermatologic reactions (4.1% vs 1.5%) were reported in more patients on subcutaneous semaglutide than those on a placebo or comparator. Several case reports described isolated cases of severe skin-related adverse effects, such as bullous pemphigoid, eosinophilic fasciitis, and leukocytoclastic vasculitis.
• On the contrary, injection site reactions (3.5% vs 6.7%) were less common in patients on subcutaneous semaglutide compared with in those on a placebo or comparator.

IN PRACTICE:

“Variations in dosage and administration routes could influence the types and severity of skin findings, underscoring the need for additional research,” the authors wrote.

SOURCE:

Megan M. Tran, BS, from the Warren Alpert Medical School, Brown University, Providence, Rhode Island, led this study, which was published online in the Journal of the American Academy of Dermatology.

LIMITATIONS:

This study could not adjust for confounding factors and could not establish a direct causal association between semaglutide and the adverse reactions reported.

DISCLOSURES:

This study did not report any funding sources. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Tirzepatide vs basal insulins led to greater improvements in A1c and postprandial glucose (PPG) levels in patients with type 2 diabetes (T2D), regardless of different baseline PPG or fasting serum glucose (FSG) levels.

METHODOLOGY:

• Tirzepatide led to better glycemic control than insulin degludec and insulin glargine in the SURPASS-3 and SURPASS-4 trials, respectively, but the effect on FSG and PPG levels was not evaluated.
• In this post hoc analysis, the researchers assessed changes in various glycemic parameters in 3314 patients with T2D who were randomly assigned to receive tirzepatide (5, 10, or 15 mg), insulin degludec, or insulin glargine.
• Based on the median baseline glucose values, the patients were stratified into four subgroups: Low FSG/low PPG, low FSG/high PPG, high FSG/low PPG, and high FSG/high PPG.
• The outcomes of interest were changes in FSG, PPG, A1c, and body weight from baseline to week 52.

TAKEAWAY:

• Tirzepatide and basal insulins effectively lowered A1c, PPG levels, and FSG levels at 52 weeks across all patient subgroups (all P < .05).
• All three doses of tirzepatide resulted in greater reductions in both A1c and PPG levels than in basal insulins (all P < .05).
• In the high FSG/high PPG subgroup, a greater reduction in FSG levels was observed with tirzepatide 10- and 15-mg doses vs insulin glargine (both P < .05) and insulin degludec vs tirzepatide 5 mg (P < .001).
• Furthermore, at week 52, tirzepatide led to body weight reduction (P < .05), but insulin treatment led to an increase in body weight (P < .05) in all subgroups.

IN PRACTICE:

“Treatment with tirzepatide was consistently associated with more reduced PPG levels compared with insulin treatment across subgroups, including in participants with lower baseline PPG levels, in turn leading to greater A1c reductions,” the authors wrote.

SOURCE:

This study was led by Francesco Giorgino, MD, PhD, of the Section of Internal Medicine, Endocrinology, Andrology, and Metabolic Diseases, University of Bari Aldo Moro, Bari, Italy, and was published online in Diabetes Care.

LIMITATIONS:

The limitations include post hoc nature of the study and the short treatment duration. The trials included only patients with diabetes and overweight or obesity, and therefore, the study findings may not be generalizable to other populations.

DISCLOSURES:

This study and the SURPASS trials were funded by Eli Lilly and Company. Four authors declared being employees and shareholders of Eli Lilly and Company. The other authors declared having several ties with various sources, including Eli Lilly and Company.

A version of this article appeared on Medscape.com.

TOPLINE:

Tirzepatide vs basal insulins led to greater improvements in A1c and postprandial glucose (PPG) levels in patients with type 2 diabetes (T2D), regardless of different baseline PPG or fasting serum glucose (FSG) levels.

METHODOLOGY:

• Tirzepatide led to better glycemic control than insulin degludec and insulin glargine in the SURPASS-3 and SURPASS-4 trials, respectively, but the effect on FSG and PPG levels was not evaluated.
• In this post hoc analysis, the researchers assessed changes in various glycemic parameters in 3314 patients with T2D who were randomly assigned to receive tirzepatide (5, 10, or 15 mg), insulin degludec, or insulin glargine.
• Based on the median baseline glucose values, the patients were stratified into four subgroups: Low FSG/low PPG, low FSG/high PPG, high FSG/low PPG, and high FSG/high PPG.
• The outcomes of interest were changes in FSG, PPG, A1c, and body weight from baseline to week 52.

TAKEAWAY:

• Tirzepatide and basal insulins effectively lowered A1c, PPG levels, and FSG levels at 52 weeks across all patient subgroups (all P < .05).
• All three doses of tirzepatide resulted in greater reductions in both A1c and PPG levels than in basal insulins (all P < .05).
• In the high FSG/high PPG subgroup, a greater reduction in FSG levels was observed with tirzepatide 10- and 15-mg doses vs insulin glargine (both P < .05) and insulin degludec vs tirzepatide 5 mg (P < .001).
• Furthermore, at week 52, tirzepatide led to body weight reduction (P < .05), but insulin treatment led to an increase in body weight (P < .05) in all subgroups.

IN PRACTICE:

“Treatment with tirzepatide was consistently associated with more reduced PPG levels compared with insulin treatment across subgroups, including in participants with lower baseline PPG levels, in turn leading to greater A1c reductions,” the authors wrote.

SOURCE:

This study was led by Francesco Giorgino, MD, PhD, of the Section of Internal Medicine, Endocrinology, Andrology, and Metabolic Diseases, University of Bari Aldo Moro, Bari, Italy, and was published online in Diabetes Care.

LIMITATIONS:

The limitations include post hoc nature of the study and the short treatment duration. The trials included only patients with diabetes and overweight or obesity, and therefore, the study findings may not be generalizable to other populations.

DISCLOSURES:

This study and the SURPASS trials were funded by Eli Lilly and Company. Four authors declared being employees and shareholders of Eli Lilly and Company. The other authors declared having several ties with various sources, including Eli Lilly and Company.

A version of this article appeared on Medscape.com.

TOPLINE:

Tirzepatide vs basal insulins led to greater improvements in A1c and postprandial glucose (PPG) levels in patients with type 2 diabetes (T2D), regardless of different baseline PPG or fasting serum glucose (FSG) levels.

METHODOLOGY:

• Tirzepatide led to better glycemic control than insulin degludec and insulin glargine in the SURPASS-3 and SURPASS-4 trials, respectively, but the effect on FSG and PPG levels was not evaluated.
• In this post hoc analysis, the researchers assessed changes in various glycemic parameters in 3314 patients with T2D who were randomly assigned to receive tirzepatide (5, 10, or 15 mg), insulin degludec, or insulin glargine.
• Based on the median baseline glucose values, the patients were stratified into four subgroups: Low FSG/low PPG, low FSG/high PPG, high FSG/low PPG, and high FSG/high PPG.
• The outcomes of interest were changes in FSG, PPG, A1c, and body weight from baseline to week 52.

TAKEAWAY:

• Tirzepatide and basal insulins effectively lowered A1c, PPG levels, and FSG levels at 52 weeks across all patient subgroups (all P < .05).
• All three doses of tirzepatide resulted in greater reductions in both A1c and PPG levels than in basal insulins (all P < .05).
• In the high FSG/high PPG subgroup, a greater reduction in FSG levels was observed with tirzepatide 10- and 15-mg doses vs insulin glargine (both P < .05) and insulin degludec vs tirzepatide 5 mg (P < .001).
• Furthermore, at week 52, tirzepatide led to body weight reduction (P < .05), but insulin treatment led to an increase in body weight (P < .05) in all subgroups.

IN PRACTICE:

“Treatment with tirzepatide was consistently associated with more reduced PPG levels compared with insulin treatment across subgroups, including in participants with lower baseline PPG levels, in turn leading to greater A1c reductions,” the authors wrote.

SOURCE:

This study was led by Francesco Giorgino, MD, PhD, of the Section of Internal Medicine, Endocrinology, Andrology, and Metabolic Diseases, University of Bari Aldo Moro, Bari, Italy, and was published online in Diabetes Care.

LIMITATIONS:

The limitations include post hoc nature of the study and the short treatment duration. The trials included only patients with diabetes and overweight or obesity, and therefore, the study findings may not be generalizable to other populations.

DISCLOSURES:

This study and the SURPASS trials were funded by Eli Lilly and Company. Four authors declared being employees and shareholders of Eli Lilly and Company. The other authors declared having several ties with various sources, including Eli Lilly and Company.

A version of this article appeared on Medscape.com.

Is lifestyle counseling needed with the more effective second-generation nutrient-stimulated, hormone-based medications like semaglutide and tirzepatide?

If so, how intensive does the counseling need to be, and what components should be emphasized?

These are the clinical practice questions at the top of mind for healthcare professionals and researchers who provide care to patients who have overweight and/or obesity.

This is what we know. Lifestyle management is considered foundational in the care of patients with obesity.

Because obesity is fundamentally a disease of energy dysregulation, counseling has traditionally focused on dietary caloric reduction, increased physical activity, and strategies to adapt new cognitive and lifestyle behaviors.

On the basis of trial results from the Diabetes Prevention Program and the Look AHEAD studies, provision of intensive behavioral therapy (IBT) is recommended for treatment of obesity by the Centers for Medicare & Medicaid Services and by the US Preventive Services Task Force (Moyer VA; US Preventive Services Task Force).

IBT is commonly defined as consisting of 12-26 comprehensive and multicomponent sessions over the course of a year.

Reaffirming the primacy of lifestyle management, all antiobesity medications are approved by the US Food and Drug Administration as an adjunct to a reduced-calorie diet and increased physical activity.

The beneficial effect of combining IBT with earlier-generation medications like naltrexone/bupropion or liraglutide demonstrated that more participants in the trials achieved ≥ 10% weight loss with IBT compared with those taking the medication without IBT: 38.4% vs 20% for naltrexone/bupropion and 46% vs 33% for liraglutide.

Although there aren’t trial data for other first-generation medications like phentermine, orlistat, or phentermine/topiramate, it is assumed that patients taking these medications would also achieve greater weight loss when combined with IBT.

The obesity pharmacotherapy landscape was upended, however, with the approval of semaglutide (Wegovy), a glucagon-like peptide-1 (GLP-1) receptor agonist, in 2021; and tirzepatide (Zepbound), a GLP-1 and glucose-dependent insulinotropic polypeptide dual receptor agonist, in 2023.

These highly effective medications harness the effect of naturally occurring incretin hormones that reduce appetite through direct and indirect effects on the brain. Although the study designs differed between the STEP 1 and STEP 3 trials, the addition of IBT to semaglutide increased mean percent weight loss from 15% to 16% after 68 weeks of treatment (Wilding JPH et al; Wadden TA).

Comparable benefits from the STEP 3 and SURMOUNT-1 trials of adding IBT to tirzepatide at the maximal tolerated dose increased mean percent weight loss from 21% to 24% after 72 weeks (Wadden TA; Jastreboff AM). Though multicomponent IBT appears to provide greater weight loss when used with nutrient-stimulated hormone-based therapeutics, the additional benefit may be less when compared with first-generation medications.

So, how should we view the role and importance of lifestyle management when a patient is taking a second-generation medication? We need to shift the focus from prescribing a calorie-reduced diet to counseling for healthy eating patterns.

Because the second-generation drugs are more biologically effective in suppressing appetite (ie, reducing hunger, food noise, and cravings, and increasing satiation and satiety), it is easier for patients to reduce their food intake without a sense of deprivation. Furthermore, many patients express less desire to consume savory, sweet, and other enticing foods.

Patients should be encouraged to optimize the quality of their diet, prioritizing lean protein sources with meals and snacks; increasing fruits, vegetables, fiber, and complex carbohydrates; and keeping well hydrated. Because of the risk of developing micronutrient deficiencies while consuming a low-calorie diet — most notably calcium, iron, and vitamin D — patients may be advised to take a daily multivitamin supplement. Dietary counseling should be introduced when patients start pharmacotherapy, and if needed, referral to a registered dietitian nutritionist may be helpful in making these changes.

Additional counseling tips to mitigate the gastrointestinal side effects of these drugs that most commonly occur during the early dose-escalation phase include eating slowly; choosing smaller portion sizes; stopping eating when full; not skipping meals; and avoiding fatty, fried, and greasy foods. These dietary changes are particularly important over the first days after patients take the injection.

The increased weight loss achieved also raises concerns about the need to maintain lean body mass and the importance of physical activity and exercise counseling. All weight loss interventions, including dietary restriction, pharmacotherapy, or bariatric surgery, result in loss of fat mass and lean body mass.

The goal of lifestyle counseling is to minimize and preserve muscle mass (a component of lean body mass) which is needed for optimal health, mobility, daily function, and quality of life. Counseling should incorporate both aerobic and resistance training. Aerobic exercise (eg, brisk walking, jogging, dancing, elliptical machine, and cycling) improves cardiovascular fitness, metabolic health, and energy expenditure. Resistance (strength) training (eg, weightlifting, resistance bands, and circuit training) lessens the loss of muscle mass, enhances functional strength and mobility, and improves bone density (Gorgojo-Martinez JJ et al; Oppert JM et al).

Robust physical activity has also been shown to be a predictor of weight loss maintenance. A recently published randomized placebo-controlled trial demonstrated the benefit of supervised exercise in maintaining body weight and lean body mass after discontinuing 52 weeks of liraglutide treatment compared with no exercise.

Rather than minimizing the provision of lifestyle management, using highly effective second-generation therapeutics redirects the focus on how patients with obesity can strive to achieve a healthy and productive life.

A version of this article first appeared on Medscape.com.

Is lifestyle counseling needed with the more effective second-generation nutrient-stimulated, hormone-based medications like semaglutide and tirzepatide?

If so, how intensive does the counseling need to be, and what components should be emphasized?

These are the clinical practice questions at the top of mind for healthcare professionals and researchers who provide care to patients who have overweight and/or obesity.

This is what we know. Lifestyle management is considered foundational in the care of patients with obesity.

Because obesity is fundamentally a disease of energy dysregulation, counseling has traditionally focused on dietary caloric reduction, increased physical activity, and strategies to adapt new cognitive and lifestyle behaviors.

On the basis of trial results from the Diabetes Prevention Program and the Look AHEAD studies, provision of intensive behavioral therapy (IBT) is recommended for treatment of obesity by the Centers for Medicare & Medicaid Services and by the US Preventive Services Task Force (Moyer VA; US Preventive Services Task Force).

IBT is commonly defined as consisting of 12-26 comprehensive and multicomponent sessions over the course of a year.

Reaffirming the primacy of lifestyle management, all antiobesity medications are approved by the US Food and Drug Administration as an adjunct to a reduced-calorie diet and increased physical activity.

The beneficial effect of combining IBT with earlier-generation medications like naltrexone/bupropion or liraglutide demonstrated that more participants in the trials achieved ≥ 10% weight loss with IBT compared with those taking the medication without IBT: 38.4% vs 20% for naltrexone/bupropion and 46% vs 33% for liraglutide.

Although there aren’t trial data for other first-generation medications like phentermine, orlistat, or phentermine/topiramate, it is assumed that patients taking these medications would also achieve greater weight loss when combined with IBT.

The obesity pharmacotherapy landscape was upended, however, with the approval of semaglutide (Wegovy), a glucagon-like peptide-1 (GLP-1) receptor agonist, in 2021; and tirzepatide (Zepbound), a GLP-1 and glucose-dependent insulinotropic polypeptide dual receptor agonist, in 2023.

These highly effective medications harness the effect of naturally occurring incretin hormones that reduce appetite through direct and indirect effects on the brain. Although the study designs differed between the STEP 1 and STEP 3 trials, the addition of IBT to semaglutide increased mean percent weight loss from 15% to 16% after 68 weeks of treatment (Wilding JPH et al; Wadden TA).

Comparable benefits from the STEP 3 and SURMOUNT-1 trials of adding IBT to tirzepatide at the maximal tolerated dose increased mean percent weight loss from 21% to 24% after 72 weeks (Wadden TA; Jastreboff AM). Though multicomponent IBT appears to provide greater weight loss when used with nutrient-stimulated hormone-based therapeutics, the additional benefit may be less when compared with first-generation medications.

So, how should we view the role and importance of lifestyle management when a patient is taking a second-generation medication? We need to shift the focus from prescribing a calorie-reduced diet to counseling for healthy eating patterns.

Because the second-generation drugs are more biologically effective in suppressing appetite (ie, reducing hunger, food noise, and cravings, and increasing satiation and satiety), it is easier for patients to reduce their food intake without a sense of deprivation. Furthermore, many patients express less desire to consume savory, sweet, and other enticing foods.

Patients should be encouraged to optimize the quality of their diet, prioritizing lean protein sources with meals and snacks; increasing fruits, vegetables, fiber, and complex carbohydrates; and keeping well hydrated. Because of the risk of developing micronutrient deficiencies while consuming a low-calorie diet — most notably calcium, iron, and vitamin D — patients may be advised to take a daily multivitamin supplement. Dietary counseling should be introduced when patients start pharmacotherapy, and if needed, referral to a registered dietitian nutritionist may be helpful in making these changes.

Additional counseling tips to mitigate the gastrointestinal side effects of these drugs that most commonly occur during the early dose-escalation phase include eating slowly; choosing smaller portion sizes; stopping eating when full; not skipping meals; and avoiding fatty, fried, and greasy foods. These dietary changes are particularly important over the first days after patients take the injection.

The increased weight loss achieved also raises concerns about the need to maintain lean body mass and the importance of physical activity and exercise counseling. All weight loss interventions, including dietary restriction, pharmacotherapy, or bariatric surgery, result in loss of fat mass and lean body mass.

The goal of lifestyle counseling is to minimize and preserve muscle mass (a component of lean body mass) which is needed for optimal health, mobility, daily function, and quality of life. Counseling should incorporate both aerobic and resistance training. Aerobic exercise (eg, brisk walking, jogging, dancing, elliptical machine, and cycling) improves cardiovascular fitness, metabolic health, and energy expenditure. Resistance (strength) training (eg, weightlifting, resistance bands, and circuit training) lessens the loss of muscle mass, enhances functional strength and mobility, and improves bone density (Gorgojo-Martinez JJ et al; Oppert JM et al).

Robust physical activity has also been shown to be a predictor of weight loss maintenance. A recently published randomized placebo-controlled trial demonstrated the benefit of supervised exercise in maintaining body weight and lean body mass after discontinuing 52 weeks of liraglutide treatment compared with no exercise.

Rather than minimizing the provision of lifestyle management, using highly effective second-generation therapeutics redirects the focus on how patients with obesity can strive to achieve a healthy and productive life.

A version of this article first appeared on Medscape.com.

Is lifestyle counseling needed with the more effective second-generation nutrient-stimulated, hormone-based medications like semaglutide and tirzepatide?

If so, how intensive does the counseling need to be, and what components should be emphasized?

These are the clinical practice questions at the top of mind for healthcare professionals and researchers who provide care to patients who have overweight and/or obesity.

This is what we know. Lifestyle management is considered foundational in the care of patients with obesity.

Because obesity is fundamentally a disease of energy dysregulation, counseling has traditionally focused on dietary caloric reduction, increased physical activity, and strategies to adapt new cognitive and lifestyle behaviors.

On the basis of trial results from the Diabetes Prevention Program and the Look AHEAD studies, provision of intensive behavioral therapy (IBT) is recommended for treatment of obesity by the Centers for Medicare & Medicaid Services and by the US Preventive Services Task Force (Moyer VA; US Preventive Services Task Force).

IBT is commonly defined as consisting of 12-26 comprehensive and multicomponent sessions over the course of a year.

Reaffirming the primacy of lifestyle management, all antiobesity medications are approved by the US Food and Drug Administration as an adjunct to a reduced-calorie diet and increased physical activity.

The beneficial effect of combining IBT with earlier-generation medications like naltrexone/bupropion or liraglutide demonstrated that more participants in the trials achieved ≥ 10% weight loss with IBT compared with those taking the medication without IBT: 38.4% vs 20% for naltrexone/bupropion and 46% vs 33% for liraglutide.

Although there aren’t trial data for other first-generation medications like phentermine, orlistat, or phentermine/topiramate, it is assumed that patients taking these medications would also achieve greater weight loss when combined with IBT.

The obesity pharmacotherapy landscape was upended, however, with the approval of semaglutide (Wegovy), a glucagon-like peptide-1 (GLP-1) receptor agonist, in 2021; and tirzepatide (Zepbound), a GLP-1 and glucose-dependent insulinotropic polypeptide dual receptor agonist, in 2023.

These highly effective medications harness the effect of naturally occurring incretin hormones that reduce appetite through direct and indirect effects on the brain. Although the study designs differed between the STEP 1 and STEP 3 trials, the addition of IBT to semaglutide increased mean percent weight loss from 15% to 16% after 68 weeks of treatment (Wilding JPH et al; Wadden TA).

Comparable benefits from the STEP 3 and SURMOUNT-1 trials of adding IBT to tirzepatide at the maximal tolerated dose increased mean percent weight loss from 21% to 24% after 72 weeks (Wadden TA; Jastreboff AM). Though multicomponent IBT appears to provide greater weight loss when used with nutrient-stimulated hormone-based therapeutics, the additional benefit may be less when compared with first-generation medications.

So, how should we view the role and importance of lifestyle management when a patient is taking a second-generation medication? We need to shift the focus from prescribing a calorie-reduced diet to counseling for healthy eating patterns.

Because the second-generation drugs are more biologically effective in suppressing appetite (ie, reducing hunger, food noise, and cravings, and increasing satiation and satiety), it is easier for patients to reduce their food intake without a sense of deprivation. Furthermore, many patients express less desire to consume savory, sweet, and other enticing foods.

Patients should be encouraged to optimize the quality of their diet, prioritizing lean protein sources with meals and snacks; increasing fruits, vegetables, fiber, and complex carbohydrates; and keeping well hydrated. Because of the risk of developing micronutrient deficiencies while consuming a low-calorie diet — most notably calcium, iron, and vitamin D — patients may be advised to take a daily multivitamin supplement. Dietary counseling should be introduced when patients start pharmacotherapy, and if needed, referral to a registered dietitian nutritionist may be helpful in making these changes.

Additional counseling tips to mitigate the gastrointestinal side effects of these drugs that most commonly occur during the early dose-escalation phase include eating slowly; choosing smaller portion sizes; stopping eating when full; not skipping meals; and avoiding fatty, fried, and greasy foods. These dietary changes are particularly important over the first days after patients take the injection.

The increased weight loss achieved also raises concerns about the need to maintain lean body mass and the importance of physical activity and exercise counseling. All weight loss interventions, including dietary restriction, pharmacotherapy, or bariatric surgery, result in loss of fat mass and lean body mass.

The goal of lifestyle counseling is to minimize and preserve muscle mass (a component of lean body mass) which is needed for optimal health, mobility, daily function, and quality of life. Counseling should incorporate both aerobic and resistance training. Aerobic exercise (eg, brisk walking, jogging, dancing, elliptical machine, and cycling) improves cardiovascular fitness, metabolic health, and energy expenditure. Resistance (strength) training (eg, weightlifting, resistance bands, and circuit training) lessens the loss of muscle mass, enhances functional strength and mobility, and improves bone density (Gorgojo-Martinez JJ et al; Oppert JM et al).

Robust physical activity has also been shown to be a predictor of weight loss maintenance. A recently published randomized placebo-controlled trial demonstrated the benefit of supervised exercise in maintaining body weight and lean body mass after discontinuing 52 weeks of liraglutide treatment compared with no exercise.

Rather than minimizing the provision of lifestyle management, using highly effective second-generation therapeutics redirects the focus on how patients with obesity can strive to achieve a healthy and productive life.

A version of this article first appeared on Medscape.com.

Data derived from continuous glucose monitoring (CGM) devices can help guide nutrition management and insulin dosing in people with type 2 diabetes (T2D) in primary care settings.

At the Advanced Technologies & Treatments for Diabetes meeting, two experts from the International Diabetes Center – HealthPartners Institute, Minneapolis, offered advice for clinicians. Tara Ettestad, RN, LD, CDCES, program manager for care transformation and training at the center, shared tips for helping patients change their diet based on CGM readings. The center’s medical director Thomas Martens, MD, provided a systematic approach to using CGM to guide adjustment of insulin doses and other medications for insulin-treated patients with T2D.
 

CGM-Guided Nutrition: Focus on Sustainable Changes

With CGM, people with diabetes get real-time feedback about the impact of foods on their glucose levels. This can help them learn not just what they can’t eat but what they can eat, Ms. Ettestad pointed out.

“People want to know what to eat. This is the number-one question that people who are newly diagnosed with diabetes ask, and unfortunately, they typically hear what not to eat. No carbohydrates, no sugar, no white foods, no sweets. This can be really disheartening and confusing for many. We should be focusing on sustainable changes to help improve diets,” she said.

She added, “Not everyone can see a dietitian, but all clinicians can help provide evidence-based nutrition guidance.”

When guiding patients, it’s important to focus on the four “core concepts” outlined in the American Diabetes Association’s nutrition consensus report:

• Emphasize nonstarchy vegetables
• Minimize added sugars and refined grains
• Eat more whole foods, less highly processed foods
• Replace sugar-sweetened beverages with water as often as possible

With CGM, patients can see the differences in response to refined carbs (wheat, rice, and potato), sugars (sucrose, fructose, and glucose), and resistant starches (whole grains, fruits, and legumes). Typically, glucose responses are steeper and higher for the first two compared to resistant starches.

CGM can also show the effects of eating fat and protein, in that they can delay glucose responses to meals even with the same carbohydrate content, Ms. Ettestad said.

It’s important to remind patients that although one goal of using CGM is to reduce post-meal glucose spikes, eating a lot of high-saturated fat, high-calorie foods isn’t the healthful way to do it. “What’s really important when we’re using CGM to help guide nutrition is remembering nutrition quality and what can be good for glucose is not always good for our overall health,” Ms. Ettestad stressed.

She provided these further tips:

• Pick one meal at a time to focus on. Collaborate with patients to see what changes they are able and willing to make. For example, rather than entirely giving up rice or noodles at dinner, try eating less of those and adding more vegetables.
• Suggest that patients keep a food log or use a tracking app so that the source of specific glucose patterns can be identified and addressed.
• Show patients how to check their time in range (TIR) on their mobile device or reader each week so they can see big-picture results of their changes. “This can be really motivating for people to see,” she said.
• Remind people that glucose rises with meals. This seems obvious but may not be to those newly diagnosed, she pointed out.
• Educate patients on glucose targets and explain that other factors such as stress and activity can influence glucose levels.
• Focus on the positive. “What have you been learning about how your meals and beverages affect your glucose?”
• Help guide patients toward better diet quality, even when TIR is a goal, using the four core concepts.
• Encourage curiosity, such as by experimenting with portions, timing, or food order. “What if you try eating nonstarchy foods first?”
• Before adjusting a medication dose, consider asking if the patient is willing to make a nutrition change. “Every visit is an opportunity!”

Adjusting Insulin With the Help of CGM: Focus on Four Patient Subgroups

Dr. Martens noted that about a quarter of people with T2D will require insulin treatment, despite increasing use of sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP-1) receptor agonists. And even when insulin is used as a “salvage therapy” in T2D, about two thirds of those individuals still struggle to achieve an A1c below 7% with or without other glucose-lowering medications, he noted.

“So, we have this huge population with type 2 diabetes who have limited access to endocrinology, and advanced insulin delivery devices are not yet available for them. Can better use of CGM drive improvements in care?”

He pointed to MOBILE, a randomized clinical trial, which showed that CGM use resulted in significantly improved A1c at 8 months compared with fingerstick monitoring among adults with T2D taking long-acting insulin alone without premeal insulin. However, TIR was still just 59% (vs 43% with fingerstick testing), suggesting room for improvement.

“This could have been much, much better…Rapid interpretation isn’t really enough. We need to move from interpretation into action,” Dr. Martens said.

His team recently developed a program called “CGM Clinician Guided Management (CCGM)” aimed at primary care that encourages the following principles:

• Appropriate movement toward the safer “high value” noninsulin therapies, that is, GLP-1 agonists and SGLT2 inhibitors.
• Appropriate insulin titration.
• Appropriate cycle time in titration, that is, accelerating more rapidly when one dose isn’t working. “That’s the Achilles heel of primary care,” he noted.
• Quick identification of when the limits of basal insulin therapy have been reached.
• Team-based management for difficult situations and for individuals on multiple daily injections and mealtime insulin regimens. “This is a group that really struggles…in primary care settings,” he noted.

The following three steps are based on published T2D management guidelines:

• Step 1: If the patient has atherosclerotic cardiovascular disease, start with either an SGLT2 inhibitor or GLP-1 agonist. For those with congestive heart failure and/or chronic kidney disease, SGLT2 inhibitors are indicated.
• Step 2: Is the patient on sulfonylurea? Consider eliminating it before moving to CGM-based insulin titration.
• Step 3: Was there a change in therapy based on steps 1 or 2? If not, move to CGM-guided insulin titration. If yes, wait 2-4 weeks to see the impact of therapy change before moving on.

The program categorizes patients into one of four groups based on CGM data, with respective management approaches:

• Category 1: TIR > 70%, time below range (TBR) < 3%: Doing well, keep on going!
• Category 2: TIR > 70%, TBR ≥ 3%: Too much hypoglycemia, need to decrease therapy. Stop sulfonylureas, and if TBR > 10%, also decrease basal insulin dose.
• Category 3: TIR < 70%, TBR < 3%: Too much hyperglycemia — increase therapy.
• Category 4: TIR < 70%, TBR ≥ 3%: This is the toughest category. Fix or advance therapy. These patients should be either referred to a diabetes care and education specialist (formerly known as “diabetes educators”) to troubleshoot their regimens or have their therapy advanced to multiple daily injections. The hypoglycemia should be addressed first for safety, then the hyperglycemia.

“We hope that CCGM is going to be the translation of CGM data into action in primary care, where we struggle with action and inaction,” Dr. Martens said. It’s expected to be posted on the IDC website soon.

Ms. Ettestad’s employer received educational grant funds from Abbott Diabetes Care and Sanofi-Aventis Groupe. She also worked as a product trainer with Tandem Diabetes Care. She is employed by nonprofit International Diabetes Center – HealthPartners Institute and received no personal income or honoraria from these activities. Dr. Martens’ employer received funds on his behalf for research and speaking support from Dexcom, Abbott Diabetes Care, Medtronic, Insulet, Tandem, Sanofi, Lilly, and Novo Nordisk and for consulting from Sanofi and Lilly. He is employed by nonprofit HealthPartners Institute – International Diabetes Center and received no personal income or honoraria from these activities.

A version of this article first appeared on Medscape.com.

Data derived from continuous glucose monitoring (CGM) devices can help guide nutrition management and insulin dosing in people with type 2 diabetes (T2D) in primary care settings.

At the Advanced Technologies & Treatments for Diabetes meeting, two experts from the International Diabetes Center – HealthPartners Institute, Minneapolis, offered advice for clinicians. Tara Ettestad, RN, LD, CDCES, program manager for care transformation and training at the center, shared tips for helping patients change their diet based on CGM readings. The center’s medical director Thomas Martens, MD, provided a systematic approach to using CGM to guide adjustment of insulin doses and other medications for insulin-treated patients with T2D.
 

CGM-Guided Nutrition: Focus on Sustainable Changes

With CGM, people with diabetes get real-time feedback about the impact of foods on their glucose levels. This can help them learn not just what they can’t eat but what they can eat, Ms. Ettestad pointed out.

“People want to know what to eat. This is the number-one question that people who are newly diagnosed with diabetes ask, and unfortunately, they typically hear what not to eat. No carbohydrates, no sugar, no white foods, no sweets. This can be really disheartening and confusing for many. We should be focusing on sustainable changes to help improve diets,” she said.

She added, “Not everyone can see a dietitian, but all clinicians can help provide evidence-based nutrition guidance.”

When guiding patients, it’s important to focus on the four “core concepts” outlined in the American Diabetes Association’s nutrition consensus report:

• Emphasize nonstarchy vegetables
• Minimize added sugars and refined grains
• Eat more whole foods, less highly processed foods
• Replace sugar-sweetened beverages with water as often as possible

With CGM, patients can see the differences in response to refined carbs (wheat, rice, and potato), sugars (sucrose, fructose, and glucose), and resistant starches (whole grains, fruits, and legumes). Typically, glucose responses are steeper and higher for the first two compared to resistant starches.

CGM can also show the effects of eating fat and protein, in that they can delay glucose responses to meals even with the same carbohydrate content, Ms. Ettestad said.

It’s important to remind patients that although one goal of using CGM is to reduce post-meal glucose spikes, eating a lot of high-saturated fat, high-calorie foods isn’t the healthful way to do it. “What’s really important when we’re using CGM to help guide nutrition is remembering nutrition quality and what can be good for glucose is not always good for our overall health,” Ms. Ettestad stressed.

She provided these further tips:

• Pick one meal at a time to focus on. Collaborate with patients to see what changes they are able and willing to make. For example, rather than entirely giving up rice or noodles at dinner, try eating less of those and adding more vegetables.
• Suggest that patients keep a food log or use a tracking app so that the source of specific glucose patterns can be identified and addressed.
• Show patients how to check their time in range (TIR) on their mobile device or reader each week so they can see big-picture results of their changes. “This can be really motivating for people to see,” she said.
• Remind people that glucose rises with meals. This seems obvious but may not be to those newly diagnosed, she pointed out.
• Educate patients on glucose targets and explain that other factors such as stress and activity can influence glucose levels.
• Focus on the positive. “What have you been learning about how your meals and beverages affect your glucose?”
• Help guide patients toward better diet quality, even when TIR is a goal, using the four core concepts.
• Encourage curiosity, such as by experimenting with portions, timing, or food order. “What if you try eating nonstarchy foods first?”
• Before adjusting a medication dose, consider asking if the patient is willing to make a nutrition change. “Every visit is an opportunity!”

Adjusting Insulin With the Help of CGM: Focus on Four Patient Subgroups

Dr. Martens noted that about a quarter of people with T2D will require insulin treatment, despite increasing use of sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP-1) receptor agonists. And even when insulin is used as a “salvage therapy” in T2D, about two thirds of those individuals still struggle to achieve an A1c below 7% with or without other glucose-lowering medications, he noted.

“So, we have this huge population with type 2 diabetes who have limited access to endocrinology, and advanced insulin delivery devices are not yet available for them. Can better use of CGM drive improvements in care?”

He pointed to MOBILE, a randomized clinical trial, which showed that CGM use resulted in significantly improved A1c at 8 months compared with fingerstick monitoring among adults with T2D taking long-acting insulin alone without premeal insulin. However, TIR was still just 59% (vs 43% with fingerstick testing), suggesting room for improvement.

“This could have been much, much better…Rapid interpretation isn’t really enough. We need to move from interpretation into action,” Dr. Martens said.

His team recently developed a program called “CGM Clinician Guided Management (CCGM)” aimed at primary care that encourages the following principles:

• Appropriate movement toward the safer “high value” noninsulin therapies, that is, GLP-1 agonists and SGLT2 inhibitors.
• Appropriate insulin titration.
• Appropriate cycle time in titration, that is, accelerating more rapidly when one dose isn’t working. “That’s the Achilles heel of primary care,” he noted.
• Quick identification of when the limits of basal insulin therapy have been reached.
• Team-based management for difficult situations and for individuals on multiple daily injections and mealtime insulin regimens. “This is a group that really struggles…in primary care settings,” he noted.

The following three steps are based on published T2D management guidelines:

• Step 1: If the patient has atherosclerotic cardiovascular disease, start with either an SGLT2 inhibitor or GLP-1 agonist. For those with congestive heart failure and/or chronic kidney disease, SGLT2 inhibitors are indicated.
• Step 2: Is the patient on sulfonylurea? Consider eliminating it before moving to CGM-based insulin titration.
• Step 3: Was there a change in therapy based on steps 1 or 2? If not, move to CGM-guided insulin titration. If yes, wait 2-4 weeks to see the impact of therapy change before moving on.

The program categorizes patients into one of four groups based on CGM data, with respective management approaches:

• Category 1: TIR > 70%, time below range (TBR) < 3%: Doing well, keep on going!
• Category 2: TIR > 70%, TBR ≥ 3%: Too much hypoglycemia, need to decrease therapy. Stop sulfonylureas, and if TBR > 10%, also decrease basal insulin dose.
• Category 3: TIR < 70%, TBR < 3%: Too much hyperglycemia — increase therapy.
• Category 4: TIR < 70%, TBR ≥ 3%: This is the toughest category. Fix or advance therapy. These patients should be either referred to a diabetes care and education specialist (formerly known as “diabetes educators”) to troubleshoot their regimens or have their therapy advanced to multiple daily injections. The hypoglycemia should be addressed first for safety, then the hyperglycemia.

“We hope that CCGM is going to be the translation of CGM data into action in primary care, where we struggle with action and inaction,” Dr. Martens said. It’s expected to be posted on the IDC website soon.

Ms. Ettestad’s employer received educational grant funds from Abbott Diabetes Care and Sanofi-Aventis Groupe. She also worked as a product trainer with Tandem Diabetes Care. She is employed by nonprofit International Diabetes Center – HealthPartners Institute and received no personal income or honoraria from these activities. Dr. Martens’ employer received funds on his behalf for research and speaking support from Dexcom, Abbott Diabetes Care, Medtronic, Insulet, Tandem, Sanofi, Lilly, and Novo Nordisk and for consulting from Sanofi and Lilly. He is employed by nonprofit HealthPartners Institute – International Diabetes Center and received no personal income or honoraria from these activities.

A version of this article first appeared on Medscape.com.

Data derived from continuous glucose monitoring (CGM) devices can help guide nutrition management and insulin dosing in people with type 2 diabetes (T2D) in primary care settings.

At the Advanced Technologies & Treatments for Diabetes meeting, two experts from the International Diabetes Center – HealthPartners Institute, Minneapolis, offered advice for clinicians. Tara Ettestad, RN, LD, CDCES, program manager for care transformation and training at the center, shared tips for helping patients change their diet based on CGM readings. The center’s medical director Thomas Martens, MD, provided a systematic approach to using CGM to guide adjustment of insulin doses and other medications for insulin-treated patients with T2D.
 

CGM-Guided Nutrition: Focus on Sustainable Changes

With CGM, people with diabetes get real-time feedback about the impact of foods on their glucose levels. This can help them learn not just what they can’t eat but what they can eat, Ms. Ettestad pointed out.

“People want to know what to eat. This is the number-one question that people who are newly diagnosed with diabetes ask, and unfortunately, they typically hear what not to eat. No carbohydrates, no sugar, no white foods, no sweets. This can be really disheartening and confusing for many. We should be focusing on sustainable changes to help improve diets,” she said.

She added, “Not everyone can see a dietitian, but all clinicians can help provide evidence-based nutrition guidance.”

When guiding patients, it’s important to focus on the four “core concepts” outlined in the American Diabetes Association’s nutrition consensus report:

• Emphasize nonstarchy vegetables
• Minimize added sugars and refined grains
• Eat more whole foods, less highly processed foods
• Replace sugar-sweetened beverages with water as often as possible

With CGM, patients can see the differences in response to refined carbs (wheat, rice, and potato), sugars (sucrose, fructose, and glucose), and resistant starches (whole grains, fruits, and legumes). Typically, glucose responses are steeper and higher for the first two compared to resistant starches.

CGM can also show the effects of eating fat and protein, in that they can delay glucose responses to meals even with the same carbohydrate content, Ms. Ettestad said.

It’s important to remind patients that although one goal of using CGM is to reduce post-meal glucose spikes, eating a lot of high-saturated fat, high-calorie foods isn’t the healthful way to do it. “What’s really important when we’re using CGM to help guide nutrition is remembering nutrition quality and what can be good for glucose is not always good for our overall health,” Ms. Ettestad stressed.

She provided these further tips:

• Pick one meal at a time to focus on. Collaborate with patients to see what changes they are able and willing to make. For example, rather than entirely giving up rice or noodles at dinner, try eating less of those and adding more vegetables.
• Suggest that patients keep a food log or use a tracking app so that the source of specific glucose patterns can be identified and addressed.
• Show patients how to check their time in range (TIR) on their mobile device or reader each week so they can see big-picture results of their changes. “This can be really motivating for people to see,” she said.
• Remind people that glucose rises with meals. This seems obvious but may not be to those newly diagnosed, she pointed out.
• Educate patients on glucose targets and explain that other factors such as stress and activity can influence glucose levels.
• Focus on the positive. “What have you been learning about how your meals and beverages affect your glucose?”
• Help guide patients toward better diet quality, even when TIR is a goal, using the four core concepts.
• Encourage curiosity, such as by experimenting with portions, timing, or food order. “What if you try eating nonstarchy foods first?”
• Before adjusting a medication dose, consider asking if the patient is willing to make a nutrition change. “Every visit is an opportunity!”

Adjusting Insulin With the Help of CGM: Focus on Four Patient Subgroups

Dr. Martens noted that about a quarter of people with T2D will require insulin treatment, despite increasing use of sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP-1) receptor agonists. And even when insulin is used as a “salvage therapy” in T2D, about two thirds of those individuals still struggle to achieve an A1c below 7% with or without other glucose-lowering medications, he noted.

“So, we have this huge population with type 2 diabetes who have limited access to endocrinology, and advanced insulin delivery devices are not yet available for them. Can better use of CGM drive improvements in care?”

He pointed to MOBILE, a randomized clinical trial, which showed that CGM use resulted in significantly improved A1c at 8 months compared with fingerstick monitoring among adults with T2D taking long-acting insulin alone without premeal insulin. However, TIR was still just 59% (vs 43% with fingerstick testing), suggesting room for improvement.

“This could have been much, much better…Rapid interpretation isn’t really enough. We need to move from interpretation into action,” Dr. Martens said.

His team recently developed a program called “CGM Clinician Guided Management (CCGM)” aimed at primary care that encourages the following principles:

• Appropriate movement toward the safer “high value” noninsulin therapies, that is, GLP-1 agonists and SGLT2 inhibitors.
• Appropriate insulin titration.
• Appropriate cycle time in titration, that is, accelerating more rapidly when one dose isn’t working. “That’s the Achilles heel of primary care,” he noted.
• Quick identification of when the limits of basal insulin therapy have been reached.
• Team-based management for difficult situations and for individuals on multiple daily injections and mealtime insulin regimens. “This is a group that really struggles…in primary care settings,” he noted.

The following three steps are based on published T2D management guidelines:

• Step 1: If the patient has atherosclerotic cardiovascular disease, start with either an SGLT2 inhibitor or GLP-1 agonist. For those with congestive heart failure and/or chronic kidney disease, SGLT2 inhibitors are indicated.
• Step 2: Is the patient on sulfonylurea? Consider eliminating it before moving to CGM-based insulin titration.
• Step 3: Was there a change in therapy based on steps 1 or 2? If not, move to CGM-guided insulin titration. If yes, wait 2-4 weeks to see the impact of therapy change before moving on.

The program categorizes patients into one of four groups based on CGM data, with respective management approaches:

• Category 1: TIR > 70%, time below range (TBR) < 3%: Doing well, keep on going!
• Category 2: TIR > 70%, TBR ≥ 3%: Too much hypoglycemia, need to decrease therapy. Stop sulfonylureas, and if TBR > 10%, also decrease basal insulin dose.
• Category 3: TIR < 70%, TBR < 3%: Too much hyperglycemia — increase therapy.
• Category 4: TIR < 70%, TBR ≥ 3%: This is the toughest category. Fix or advance therapy. These patients should be either referred to a diabetes care and education specialist (formerly known as “diabetes educators”) to troubleshoot their regimens or have their therapy advanced to multiple daily injections. The hypoglycemia should be addressed first for safety, then the hyperglycemia.

“We hope that CCGM is going to be the translation of CGM data into action in primary care, where we struggle with action and inaction,” Dr. Martens said. It’s expected to be posted on the IDC website soon.

Ms. Ettestad’s employer received educational grant funds from Abbott Diabetes Care and Sanofi-Aventis Groupe. She also worked as a product trainer with Tandem Diabetes Care. She is employed by nonprofit International Diabetes Center – HealthPartners Institute and received no personal income or honoraria from these activities. Dr. Martens’ employer received funds on his behalf for research and speaking support from Dexcom, Abbott Diabetes Care, Medtronic, Insulet, Tandem, Sanofi, Lilly, and Novo Nordisk and for consulting from Sanofi and Lilly. He is employed by nonprofit HealthPartners Institute – International Diabetes Center and received no personal income or honoraria from these activities.

A version of this article first appeared on Medscape.com.