Differences in weight-loss outcomes among race-gender subgroups by behavioural intervention delivery mode: An analysis of the POWER trial.

Prior in-person behavioural intervention studies have documented differential weight loss between men and women and by race, with Black women receiving the least benefit. Remotely delivered interventions are now commonplace, but few studies have compared outcomes by race-gender groups and delivery modality. We conducted a secondary analysis of POWER, a randomized trial (NCT00783315) designed to determine the effectiveness of 2 active, lifestyle-based, weight loss interventions (remote vs. in-person) compared to a control group. Participants with obesity and at least one cardiovascular disease risk factor (N = 415) were recruited in the Baltimore, MD area. Data from 233 white and 170 Black individuals were used for this analysis. Following an intention-to-treat approach, we compared the mean percent weight loss at 24 months by race-gender subgroups using repeated-measures, mixed-effects models. Everyone lost weight in the active interventions however, weight loss differed by race and gender. white and Black men had similar results for both interventions (white: in-person (-7.6%) remote (-7.4%); Black: in-person (-4.7%) remote (-4.4%)). In contrast, white women lost more weight with the in-person intervention (in-person (-7.2%) compared to the remote (-4.4%)), whereas Black women lost less weight in the in-person group compared to the remote intervention at 24 months (-2.0% vs. -3.0%, respectively; p for interaction <.001). We found differences between the effectiveness of the 2 weight loss interventions-in-person or remote-in white and Black women at 24 months. Future studies should consider intervention modality when designing weight loss interventions for women.

Sex Specific Associations of Sex hormone With Brain Volumes and Cerebral Blood Flow: A Cross Sectional Observational Study Within the Look AHEAD Type 2 Diabetes Cohort.

Background: Females have greater brain volume and cerebral blood flow than males when controlling for intracranial volume and age. Brain volume decreases after menopause, suggesting a role of sex hormones. We studied the association of sex hormones with brain volume, white matter hyperintensity volumes and cerebral blood flow in people with Type 2 Diabetes and with overweight and obesity conditions that accelerate brain atrophy. Methods: We analyzed data from 215 participants with overweight or obesity and Type 2 Diabetes from the Look AHEAD Brain Magnetic Resonance Imaging ancillary study (mean age 68 years, 73% postmenopausal female). Estradiol and total testosterone levels were measured with electrochemoluminescence assays. The ratio of brain measurements to intracranial volume was analyzed to account for body size. We analyzed sex hormones as quantitative measures in males, whereas in females we grouped those with detectable vs. undetectable hormone levels (Estradiol <73 pmol/L [20 pg/mL]: 79%; Total Testosterone < 0.07 mmol/L [0.02 ng/mL]: 37% undetectable in females). Results: Females with detectable total testosterone levels had higher brain volume to intracranial volume ratio (median [25th, 75th percentile]: 0.85 [0.84, 0.86]) as compared to those with undetectable Total Testosterone levels (0.84 [0.83, 0.86]; rank sum p=0.04). This association was attenuated after age and body mass index adjustment (p=0.08). Neither white matter hyperintensity volumes or cerebral blood flow in females, nor any brain measures in males, were significantly associated with Estradiol or Total Testosterone. Conclusions: In postmenopausal females with Type 2 Diabetes with overweight and obesity, detectable levels of total testosterone were associated greater brain volume relative to intracranial volume, suggesting a protective role for testosterone in female brain health. Our findings are limited by a small sample size and low sensitivity of hormone assays. Our suggestive findings can be combined with future larger studies to assess clinically important differences. Trial Registration: NCT00017953.

Exercise and QUality diet After Leukemia (EQUAL): A randomized weight loss trial among adult survivors of childhood leukemia in the Childhood Cancer Survivor Study.

BACKGROUND: Obesity is prevalent in childhood cancer survivors and interacts with cancer treatments to potentiate risk for cardiovascular (CV) death. We tested a remote weight-loss intervention that was effective among adults with CV risk factors in a cohort of adult survivors of childhood acute lymphoblastic leukemia (ALL) with overweight/obesity. METHODS: In this phase 3 efficacy trial, survivors of ALL enrolled in the Childhood Cancer Survivor Study with body mass index (BMI)≥25 kg/m2 were randomized to a remotely-delivered weight-loss intervention versus self-directed weight loss, stratified by history of cranial radiotherapy (CRT). The primary endpoint was the difference in weight loss at 24-months in an intent-to-treat analysis. Analyses were performed using linear mixed effects models. RESULTS: Among 358 survivors (59% female, median attained age: 37 years, IQR: 33-43), baseline mean (SD) weight was 98.6 kg (24.0) for the intervention group (n=181) and 94.9 kg (20.3) for controls (n=177). Adherence to the intervention was poor; 15% of individuals in the intervention completed 24/30 planned coaching calls. Weight at 24-months was available for 274 (77%) participants. After controlling for CRT, sex, race/ethnicity, and age, the mean (SE) change in weight from baseline to 24-months was -0.4 kg (0.8) for intervention and 0.2 kg (0.6) for control participants (p=0.59). CONCLUSIONS: A remote weight-loss intervention that was successful among adults with CV conditions did not result in significant weight loss among adult survivors of childhood ALL. IMPACT: Future interventions in this population must be tailored to the unique needs of survivors to encourage engagement and adherence.

Effect of Isocaloric, Time-Restricted Eating on Body Weight in Adults With Obesity : A Randomized Controlled Trial.

BACKGROUND: Time-restricted eating (TRE) lowers body weight in many studies. Whether TRE induces weight loss independent of reductions in calorie intake, as seen in rodent studies, is unknown. OBJECTIVE: To determine the effect of TRE versus a usual eating pattern (UEP) on body weight in the setting of stable caloric intake. DESIGN: Randomized, isocaloric feeding study. (ClinicalTrials.gov: NCT03527368). SETTING: Clinical research unit. PARTICIPANTS: Adults with obesity and prediabetes or diet-controlled diabetes. INTERVENTION: Participants were randomly assigned 1:1 to TRE (10-hour eating window, 80% of calories before 1 p.m.) or UEP (≤16-hour window, ≥50% of calories after 5 p.m.) for 12 weeks. Both groups had the same nutrient content and were isocaloric with total calories determined at baseline. MEASUREMENTS: Primary outcome was change in body weight at 12 weeks. Secondary outcomes were fasting glucose, homeostatic model assessment for insulin resistance (HOMA-IR), glucose area under the curve by oral glucose tolerance test, and glycated albumin. We used linear mixed models to evaluate the effect of interventions on outcomes. RESULTS: All 41 randomly assigned participants (mean age, 59 years; 93% women; 93% Black race; mean BMI, 36 kg/m2) completed the intervention. Baseline weight was 95.6 kg (95% CI, 89.6 to 101.6 kg) in the TRE group and 103.7 kg (CI, 95.3 to 112.0 kg) in the UEP group. At 12 weeks, weight decreased by 2.3 kg (CI, 1.0 to 3.5 kg) in the TRE group and by 2.6 kg (CI, 1.5 to 3.7 kg) in the UEP group (average difference TRE vs. UEP, 0.3 kg [CI, -1.2 to 1.9 kg]). Change in glycemic measures did not differ between groups. LIMITATION: Small, single-site study; baseline differences in weight by group. CONCLUSION: In the setting of isocaloric eating, TRE did not decrease weight or improve glucose homeostasis relative to a UEP, suggesting that any effects of TRE on weight in prior studies may be due to reductions in caloric intake. PRIMARY FUNDING SOURCE: American Heart Association.

Improving Diabetes Screening in the Primary Care Clinic.

BACKGROUND: In our suburban primary care clinic, the average rate of screening for diabetes among eligible patients was only 51%, similar to national screening data. We conducted a quality improvement project to increase this rate. METHODS: During the 6-month preintervention phase, we collected baseline data on the percentage of eligible patients screened per week (percentage of patients with hemoglobin A1c checked in the prior 3 years out of patients eligible for screening who completed a visit during the week). We then implemented a two-phase intervention. In phase 1 (approximately 8 months), we generated an electronic health record (EHR) report to identify eligible patients and pended laboratory orders for physicians to sign. In phase 2 (approximately 3 months), we replaced the phase 1 intervention with an EHR clinical decision support tool that automatically identifies eligible patients. We compared screening rates in the preintervention vs. intervention period. For phase 1, we also assessed laboratory completion rates and the laboratory results. We surveyed physicians regarding intervention acceptability and satisfaction at 3, 6, 9, and 12 months during the intervention period. RESULTS: The weekly percentage of patients screened increased from an average of 51% in the preintervention phase to 65% in the intervention phase (p < 0.001). During phase 1, most patients underwent laboratory blood testing as recommended (83% within 3 months), and results were consistent with prediabetes in 23% and with diabetes in 4%. Overall, most physicians believed that the intervention appropriately identified patients due for screening and was helpful (100% of respondents agreed at 9 months vs. 71% at 3 months). CONCLUSION: We successfully implemented a systematic screening intervention involving a manual workflow and EHR tool and improved diabetes screening rates in our clinic.

Design and Implementation of a Time-Restricted Eating Intervention in a Randomized, Controlled Eating Study.

The efficacy of time-restricted eating for weight loss has not been established, as prior studies were limited by a lack of controlled isocaloric designs. This study describes the design and implementation of interventions in a controlled eating study evaluating time-restricted eating. We designed a randomized, controlled, parallel-arm eating study comparing time-restricted eating (TRE) to a usual eating pattern (UEP) for the primary outcome of weight change. Participants were aged 21-69 years with prediabetes and obesity. TRE consumed 80% of calories by 1300 h (military time), and UEP consumed ≥ 50% of calories after 1700 h (military time). Both arms consumed identical macro- and micro-nutrients based on a healthy, palatable diet. We calculated individual calorie requirements, which were maintained throughout the intervention. The desired distribution of calories across eating windows in both arms was achieved, as were the weekly averages for macronutrients and micronutrients. We actively monitored participants and adapted diets to facilitate adherence. We provide the first report, to our knowledge, on the design and implementation of eating study interventions that isolated the effect of meal timing on weight while maintaining constant caloric intake and identical diets during the study period.

Nonalcoholic fatty liver disease from a primary care perspective.

Nonalcoholic fatty liver disease (NAFLD) affects up to one-third of the US population. Approximately one-fifth of patients with NAFLD have nonalcoholic steatohepatitis (NASH), characterized by hepatocyte damage and inflammation with or without fibrosis. NASH leads to greater risk of liver-related complications and liver-related mortality, with the poorest outcomes seen in patients with advanced fibrosis. NASH is also associated with other metabolic comorbidities and conveys an increased risk of adverse cardiovascular outcomes and extrahepatic cancers. Despite its high prevalence, NAFLD is frequently underdiagnosed. This is a significant concern, given that early diagnosis of NAFLD is a key step in preventing progression to NASH. In this review, we describe the clinical impact of NASH from the perspective of both the clinician and the patient. In addition, we provide practical guidance on the diagnosis and management of NASH for primary care providers, who play a pivotal role in the frontline care of patients with NASH, and we use case studies to illustrate real-world scenarios encountered in the primary care setting.

Obesity and Overweight: Probing Causes, Consequences, and Novel Therapeutic Approaches Through the American Heart Association's Strategically Focused Research Network.

As the worldwide prevalence of overweight and obesity continues to rise, so too does the urgency to fully understand mediating mechanisms, to discover new targets for safe and effective therapeutic intervention, and to identify biomarkers to track obesity and the success of weight loss interventions. In 2016, the American Heart Association sought applications for a Strategically Focused Research Network (SFRN) on Obesity. In 2017, 4 centers were named, including Johns Hopkins University School of Medicine, New York University Grossman School of Medicine, University of Alabama at Birmingham, and Vanderbilt University Medical Center. These 4 centers were convened to study mechanisms and therapeutic targets in obesity, to train a talented cadre of American Heart Association SFRN-designated fellows, and to initiate and sustain effective and enduring collaborations within the individual centers and throughout the SFRN networks. This review summarizes the central themes, major findings, successful training of highly motivated and productive fellows, and the innovative collaborations and studies forged through this SFRN on Obesity. Leveraging expertise in in vitro and cellular model assays, animal models, and humans, the work of these 4 centers has made a significant impact in the field of obesity, opening doors to important discoveries, and the identification of a future generation of obesity-focused investigators and next-step clinical trials. The creation of the SFRN on Obesity for these 4 centers is but the beginning of innovative science and, importantly, the birth of new collaborations and research partnerships to propel the field forward.

Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort.

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10 years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/m2; 77.9% were women, and 77.5% reported White race. Mean interval from first to last meal was 11.5 (2.3) hours and was not associated with weight change. The number of meals per day was positively associated with weight change. The average difference in annual weight change (95% CI) associated with an increase of 1 daily meal was 0.28 kg (0.02-0.53). Conclusions Number of daily meals was positively associated with weight change over 6 years. Our findings did not support the use of time-restricted eating as a strategy for long-term weight loss in a general medical population.

Engaging Payors and Primary Care Physicians Together in Improving Diabetes Prevention.

BACKGROUND: Type 2 diabetes can be prevented through lifestyle programs like the Diabetes Prevention Programs (DPP), but few people with prediabetes participate in them, in part because their insurance does not reliably cover DPPs. Prior studies have not focused on payor-level barriers. OBJECTIVE: To understand barriers to DPP uptake that exist and intersect at different levels (patients, PCPs, and payors) to inform strategies to improve diabetes prevention in primary care settings through interviews with PCPs and payors. DESIGN: From May 2020 to October 2021, we conducted remote, semi-structured interviews with PCPs and payors. PARTICIPANTS: PCPs were from primary care practices affiliated with one mid-Atlantic academic system. Payor leaders were from regional commercial, Medicare, and Medicaid plans. APPROACH: Using a standardized interview guide focused on barriers, facilitators, and potential intervention components, interviews were audio-recorded using Zoom and professionally transcribed. Two reviewers double-coded transcripts using the framework analytic approach. KEY RESULTS: We interviewed 16 PCPs from 13 primary care clinics and 7 payor leaders representing 6 insurance plans. Two themes emerged from PCP reports of patient-level barriers: (1) lack of programs and insurance coverage of resources to address nutrition and exercise and (2) inadequate resources to address social determinants of health that impact diabetes prevention. Among barriers PCPs faced, we identified two themes: (1) low PCP knowledge about DPPs and misperceptions of insurance coverage of DPPs and (2) inadequate clinical staff to address diabetes prevention. Barriers common to PCPs and payors included (1) absence of prediabetes quality measures and (2) inadequate engagement of PCPs and patients with payors. CONCLUSIONS: Discussions with PCPs and payors revealed systemic barriers that suggest important priorities to improve prediabetes clinical care, including universal coverage of DPPs, clarity about coverage benefits, data reporting and outreach by payors to PCPs, and adoption of appropriate prediabetes quality measures.

Magnetic Resonance Imaging Predictors of Hepatocellular Carcinoma Progression and Dropout in Patients in Liver Transplantation Waiting List.

With the rising incidence of hepatocellular carcinoma (HCC), more patients are now eligible for liver transplantation. Consequently, HCC progression and dropout from the waiting list are also anticipated to rise. We developed a predictive model based on radiographic features and alpha-fetoprotein to identify high-risk patients. Methods: This is a case-cohort retrospective study of 76 patients with HCC who were listed for liver transplantation with subsequent liver transplantation or delisting due to HCC progression. We analyzed imaging-based predictive variables including tumor margin (well- versus ill-defined), capsule bulging lesions, volumetric analysis and distance to portal vein, tumor numbers, and tumor diameter. Volumetric analysis of the index lesions was used to quantify index tumor total volume and volumetric enhancement, whereas logistic regression and receiver operating characteristic curve (ROC) analyses were used to predict the main outcome of disease progression. Results: In univariate analyses, the following baseline variables were significantly associated with disease progression: size and number of lesions, sum of lesion diameters, lesions bulging the capsule, and total and venous-enhancing (viable) tumor volumes. Based on multivariable analyses, a risk model including lesion numbers and diameter, capsule bulging, tumor margin (infiltrative versus well-defined), and alpha-fetoprotein was developed to predict HCC progression and dropout. The model has an area under the ROC of 82%, which was significantly higher than Milan criteria that has an area under the ROC of 67%. Conclusions: Our model has a high predictive test for patient dropout due to HCC progression. This model can identify high-risk patients who may benefit from more aggressive HCC treatment early after diagnosis to prevent dropout due to such disease progression.

Optimal cardiometabolic health and risk of heart failure in type 2 diabetes: an analysis from the Look AHEAD trial.

AIMS: To evaluate the contribution of baseline and longitudinal changes in cardiometabolic health (CMH) towards heart failure (HF) risk among adults with type 2 diabetes (T2D). METHODS AND RESULTS: Participants of the Look AHEAD trial with T2D and without prevalent HF were included. Adjusted Cox models were used to create a CMH score incorporating target levels of parameters weighted based on relative risk for HF. The associations of baseline and changes in the CMH score with risk of overall HF, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF) were assessed using Cox models. Among the 5080 participants, 257 incident HF events occurred over 12.4 years of follow-up. The CMH score included 2 points each for target levels of waist circumference, glomerular filtration rate, urine albumin-to-creatinine ratio, and 1 point each for blood pressure and glycated haemoglobin at target. High baseline CMH score (6-8) was significantly associated with lower overall HF risk (adjusted hazard ratio [HR], ref = low score (0-3): 0.31, 95% confidence interval [CI] 0.21-0.47) with similar associations observed for HFpEF and HFrEF. Improvement in CMH was significantly associated with lower risk of overall HF (adjusted HR per 1-unit increase in score at 4 years: 0.80, 95% CI 0.70-0.91). In the ACCORD validation cohort, the baseline CMH score performed well for predicting HF risk with adequate discrimination (C-index 0.70), calibration (chi-square 5.53, p = 0.70), and risk stratification (adjusted HR [high (6-8) vs. low score (0-3)]: 0.35, 95% CI 0.26-0.46). In the Look AHEAD subgroup with available biomarker data, incorporating N-terminal pro-B-type natriuretic peptide to the baseline CMH score improved model discrimination (C-index 0.79) and risk stratification (adjusted HR [high (8-10) vs. low score (0-4)]: 0.18, 95% CI 0.09-0.35). CONCLUSIONS: Achieving target levels of more CMH parameters at baseline and sustained improvements were associated with lower HF risk in T2D.

Nonalcoholic Fatty Liver Disease: Review of Management for Primary Care Providers.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in the United States and worldwide. The progressive form of NAFLD, nonalcoholic steatohepatitis (NASH), is a leading indication for liver transplant. Comorbidities associated with NAFLD development and NASH include type 2 diabetes, obesity, metabolic syndrome, and dyslipidemia. Extrahepatic morbidity and mortality are considerable as NAFLD is associated with an increased risk of cardiovascular disease and chronic kidney disease. Once NAFLD is diagnosed, the presence of liver fibrosis is the central determinant of hepatic prognosis. Severe liver fibrosis requires aggressive clinical management. No pharmacologic agents have regulatory approval in the United States for the treatment of NAFLD or NASH. Management is centered on efforts to reduce underlying obesity (lifestyle, medications, surgical or endoscopic interventions) and metabolic derangements (prediabetes, type 2 diabetes, hypertension, hyperlipidemia, and others). Current pharmacologic therapy for NAFLD is limited mainly to the use of vitamin E and pioglitazone, although other agents are being investigated in clinical trials. Cardiovascular and metabolic risk factors must also be assessed and managed. Here, NAFLD evaluation, diagnosis, and management are considered in the primary care setting and endocrinology clinics.

Effect of renin-angiotensin system antihypertensive medication use on cognitive function in diabetes mellitus with obesity or overweight: An ancillary study to the Action for Health in Diabetes (Look AHEAD) trial.

AIM: To determine whether antihypertensive medication (AHM) acting through the renin angiotensin system (RAS-AHM), compared with other AHM, can mitigate effects on cognitive function and risk for impairment in a population with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: This secondary analysis of the randomized controlled Action for Health in Diabetes (Look AHEAD) study included 712 community-dwelling participants who were followed over 15 years. Logistic regression was used to relate RAS-AHM use to cognitive impairment, and linear regression was used to relate RAS-AHM use to domain-specific cognitive function after adjusting for potential confounders. RESULTS: A total of 563 individuals reported RAS-AHM use and 149 reported other-AHM use during the study. RAS-AHM users have college or higher education (53%), had higher baseline glycated haemoglobin (57 mmol/mol), and reported higher diabetes medication use (86%), while other-AHM users were more likely to be White (72%), obese (25%) and to have cardiovascular history (19%). RAS-AHM use was not associated with a reduced risk of dementia compared with other-AHM use. We did observe better executive function (Trail Making Test, part B, P < 0.04), processing speed (Digit Symbol Substitution Test, P < 0.004), verbal memory (Rey Auditory Verbal Learning Test-delayed recall, P < 0.005), and composite score (P < 0.008) among RAS-AHM users compared with other-AHM users. CONCLUSION: In this sample of adults with T2DM, free of dementia at baseline, we observed a slower decline in processing speed, executive function, verbal memory, and composite score among RAS-AHM users.

Comparative Safety and Effectiveness of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy for Weight Loss and Type 2 Diabetes Across Race and Ethnicity in the PCORnet Bariatric Study Cohort.

Importance: Bariatric surgery is the most effective treatment for severe obesity; yet it is unclear whether the long-term safety and comparative effectiveness of these operations differ across racial and ethnic groups. Objective: To compare outcomes of Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) across racial and ethnic groups in the National Patient-Centered Clinical Research Network (PCORnet) Bariatric Study. Design, Setting, and Participants: This was a retrospective, observational, comparative effectiveness cohort study that comprised 25 health care systems in the PCORnet Bariatric Study. Patients were adults and adolescents aged 12 to 79 years who underwent a primary (first nonrevisional) RYGB or SG operation between January 1, 2005, and September 30, 2015, at participating health systems. Patient race and ethnicity included Black, Hispanic, White, other, and unrecorded. Data were analyzed from July 1, 2021, to January 17, 2022. Exposure: RYGB or SG. Outcomes: Percentage total weight loss (%TWL); type 2 diabetes remission, relapse, and change in hemoglobin A1c (HbA1c) level; and postsurgical safety and utilization outcomes (operations, interventions, revisions/conversions, endoscopy, hospitalizations, mortality, 30-day major adverse events) at 1, 3, and 5 years after surgery. Results: A total of 36 871 patients (mean [SE] age, 45.0 [11.7] years; 29 746 female patients [81%]) were included in the weight analysis. Patients identified with the following race and ethnic categories: 6891 Black (19%), 8756 Hispanic (24%), 19 645 White (53%), 826 other (2%), and 783 unrecorded (2%). Weight loss and mean reductions in HbA1c level were larger for RYGB than SG in all years for Black, Hispanic, and White patients (difference in 5-year weight loss: Black, -7.6%; 95% CI, -8.0 to -7.1; P < .001; Hispanic, -6.2%; 95% CI, -6.6 to -5.9; P < .001; White, -5.9%; 95% CI, -6.3 to -5.7; P < .001; difference in change in year 5 HbA1c level: Black, -0.29; 95% CI, -0.51 to -0.08; P = .009; Hispanic, -0.45; 95% CI, -0.61 to -0.29; P < .001; and White, -0.25; 95% CI, -0.40 to -0.11; P = .001.) The magnitude of these differences was small among racial and ethnic groups (1%-3% of %TWL). Black and Hispanic patients had higher risk of hospitalization when they had RYGB compared with SG (hazard ratio [HR], 1.45; 95% CI, 1.17-1.79; P = .001 and 1.48; 95% CI, 1.22-1.79; P < .001, respectively). Hispanic patients had greater risk of all-cause mortality (HR, 2.41; 95% CI, 1.24-4.70; P = .01) and higher odds of a 30-day major adverse event (odds ratio, 1.92; 95% CI, 1.38-2.68; P < .001) for RYGB compared with SG. There was no interaction between race and ethnicity and operation type for diabetes remission and relapse. Conclusions and Relevance: Variability of the comparative effectiveness of operations for %TWL and HbA1c level across race and ethnicity was clinically small; however, differences in safety and utilization outcomes were clinically and statistically significant for Black and Hispanic patients who had RYGB compared with SG. These findings can inform shared decision-making regarding bariatric operation choice for different racial and ethnic groups of patients.

Comparison of Hormonal Response to a Mixed-Meal Challenge in Hypoglycemia After Sleeve Gastrectomy vs Gastric Bypass.

CONTEXT: Exaggerated postprandial incretin and insulin responses are well documented in postbariatric surgery hypoglycemia (PBH) after Roux-en-Y gastric bypass (RYGB). However, less is known about PBH after sleeve gastrectomy (SG). OBJECTIVE: We sought to compare meal-stimulated hormonal response in those with PBH after SG vs RYGB. METHODS: We enrolled 23 post-SG (12 with and 11 without PBH) and 20 post-RYGB (7 with and 13 without PBH) individuals who underwent bariatric surgery at our institution. PBH was defined as plasma glucose less than 60 mg/dL on 4-hour mixed-meal tolerance test (MTT). Islet and incretin hormones were compared across the 4 groups. RESULTS: Participants (N = 43) were on average 5 years post surgery, with a mean age of 48 years, mean preoperative body mass index of 48.4, 81% female, 61% White, and 53% post SG. Regardless of PBH, the SG group showed lower glucose, glucagon, and glucagon-like peptide 1 (GLP-1) responses to MTT and similar insulin and glucose-dependent insulinotropic polypeptide (GIP) responses compared to the RYGB group. Among those with PBH, the SG group following the MTT showed a lower peak glucose (P = .02), a similar peak insulin (90.3 mU/L vs 171mU/L; P = .18), lower glucagon (P < .01), early GLP-1 response (AUC0-60 min; P = .01), and slower time to peak GIP (P = .02) compared to PBH after RYGB. CONCLUSION: Among individuals with PBH, those who underwent SG were significantly different compared to RYGB in meal-stimulated hormonal responses, including lower glucagon and GLP-1 responses, but similar insulin and GIP responses. Future studies are needed to better understand the differential contribution of insulin and non-insulin-mediated mechanisms behind PBH after SG vs RYGB.

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study.

BACKGROUND: To address the obesity epidemic, there is a need for novel paradigms, including those that address the timing of eating and sleep in relation to circadian rhythms. Electronic health records (EHRs) are an efficient way to identify potentially eligible participants for health research studies. Mobile health (mHealth) apps offer available and convenient data collection of health behaviors, such as timing of eating and sleep. OBJECTIVE: The aim of this descriptive analysis was to report on recruitment, retention, and app use from a 6-month cohort study using a mobile app called Daily24. METHODS: Using an EHR query, adult patients from three health care systems in the PaTH clinical research network were identified as potentially eligible, invited electronically to participate, and instructed to download and use the Daily24 mobile app, which focuses on eating and sleep timing. Online surveys were completed at baseline and 4 months. We described app use and identified predictors of app use, defined as 1 or more days of use, versus nonuse and usage categories (ie, immediate, consistent, and sustained) using multivariate regression analyses. RESULTS: Of 70,661 patients who were sent research invitations, 1021 (1.44%) completed electronic consent forms and online baseline surveys; 4 withdrew, leaving a total of 1017 participants in the analytic sample. A total of 53.79% (n=547) of the participants were app users and, of those, 75.3% (n=412), 50.1% (n=274), and 25.4% (n=139) were immediate, consistent, and sustained users, respectively. Median app use was 28 (IQR 7-75) days over 6 months. Younger age, White race, higher educational level, higher income, having no children younger than 18 years, and having used 1 to 5 health apps significantly predicted app use (vs nonuse) in adjusted models. Older age and lower BMI predicted early, consistent, and sustained use. About half (532/1017, 52.31%) of the participants completed the 4-month online surveys. A total of 33.5% (183/547), 29.3% (157/536), and 27.1% (143/527) of app users were still using the app for at least 2 days per month during months 4, 5, and 6 of the study, respectively. CONCLUSIONS: EHR recruitment offers an efficient (ie, high reach, low touch, and minimal participant burden) approach to recruiting participants from health care settings into mHealth research. Efforts to recruit and retain less engaged subgroups are needed to collect more generalizable data. Additionally, future app iterations should include more evidence-based features to increase participant use.

GDF15 and Cortisol Response to Meal Tolerance Test in Post-Sleeve Gastrectomy Patients with Weight Regain.

BACKGROUND: Hormonal factors behind weight regain (WR) after surgical weight loss remain inadequately understood. Growth/differentiation factor 15 (GDF15) has emerged as a potential therapeutic target in obesity treatment. Cortisol, another stress hormone, has also been associated with weight gain at both low and high circulating concentrations. We aimed to compare meal-stimulated GDF15 and cortisol response in adults with and without WR after sleeve gastrectomy (SG). We hypothesized that GDF15 and cortisol response to meal tolerance test (MTT) will be lower in those with versus without WR after SG. METHODS: Cross-sectional study comprised 21 adults without diabetes, who underwent SG. WR was defined as 100 × (current weight - nadir)/(preoperative weight - nadir) > 10%. GDF15, cortisol, insulin, glucose, and incretins (total glucagon-like peptide (GLP)-1 and glucose-dependent insulinotropic polypeptide (GIP) circulating concentrations) were measured during MTT (0-240 min) after 3-6 years post-bariatric surgery. RESULTS: All participants were 48% White, 85% female, with mean (SD) age: 43(10) years, and BMI: 36.2(7.6) kg/m2. Compared to the non-WR group (n = 6), the WR group (n = 15) had significantly higher BMI (WR: 38.6 ± 7.6 kg/m2, non-WR: 30.3 ± 3.5 kg/m2, p = 0.02) and showed lower GDF15 response (WR AUC vs non-WR AUC (116143 ± 13973 vs 185798 ± 38884 ng*min/L, p = 0.047)) and lower cortisol response (WR AUC vs non-WR AUC (3492 ± 210 vs 4880 ± 655 µg*min/dL, p = 0.015)). Incretin response did not differ between the groups. CONCLUSIONS: GDF15 and cortisol responses to MTT were lower in those who regained the weight after SG compared to those who did not, suggesting that dysregulation in GDF15 and cortisol response following bariatric surgery.

Adherence to Diet and Meal Timing in a Randomized Controlled Feeding Study of Time-Restricted Feeding.

Adherence is critical in feeding studies to determine the efficacy of dietary interventions. This time-restricted intake of meals (TRIM) investigation was a controlled feeding study that randomized 41 participants to follow 12 weeks of time-restricted feeding (TRF) or a usual feeding pattern (UFP). Adherence was optimized through careful screening and participant orientation, flexibility in beverages and seasonings, and frequent contact between participants and staff. Adherence was measured daily using a self-administered diary form. We calculated the percentage of participant-days with perfect adherence to meal timing (ate all meals within their designated time window) and to food consumption (ate all study food and no non-study food). Adherence was compared between study arms, days of the week, and weeks of the study period using generalized estimating equations (GEE) regression. There was perfect adherence to meal timing on 87% of participant-days and to food consumption on 94% of participant-days, with no significant difference by arm. In UFP, but not TRF, participants had lower adherence to meal timing over the weekend (p-value = 0.002) and during the first two weeks of intervention (p-value = 0.03). A controlled feeding study randomizing free-living individuals to different meal timings achieved a high degree of adherence to meal timing and food consumption, utilizing multiple strategies.

Validation of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms.

BACKGROUND AND AIMS: Management of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH. METHODS: We studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI). RESULTS: The NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI > 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam features. The FAST™ score had higher diagnostic accuracy than other non-invasive algorithms for the diagnosis of at-risk NASH (AUROC for NFS, FIB-4, and APRI 0.67, 0.73, 0.74, respectively). CONCLUSION: We validated the FAST™ score for the diagnosis of at-risk NASH in a large, multi-racial population in North America, with a prevalence of at-risk NASH of 37%. Diagnostic performance varies by subgroups of NASH patients defined by race and obesity. FAST™ performed better than other non-invasive algorithms for the diagnosis of at-risk NASH.