Association of Lifestyle Intervention With Risk for Cardiovascular Events Differs by Level of Glycated Hemoglobin.

PURPOSE: We reevaluated the Action for Health in Diabetes (Look AHEAD) intensive lifestyle intervention (ILI) to assess whether the effect of ILI on cardiovascular disease (CVD) prevention differed by baseline glycated hemoglobin (HbA1c). METHODS: Look AHEAD randomized 5145 adults, aged 45 to 76 years with type 2 diabetes and overweight/obesity to ILI or a diabetes support and education (DSE) control group for a median of 9.6 years. ILI focused on achieving weight loss through decreased caloric intake and increased physical activity. We assessed the parent trial's primary composite CVD outcome. We evaluated additive and multiplicative heterogeneity of the intervention on CVD risk by baseline HbA1c. RESULTS: Mean baseline HbA1c was 7.3% (SD 1.2) and ranged from 4.4% (quintile 1) to 14.5% (quintile 5). We observed additive and multiplicative heterogeneity of the association between ILI and CVD (all P < .001) by baseline HbA1c. Randomization to ILI was associated with lower CVD risk for HbA1c quintiles 1 [hazard ratio (HR): 0.68, 95% confidence interval (CI): 0.53, 0.88] and 2 (HR: 0.80, 95% CI: 0.66, 0.96) and associated with higher CVD risk for HbA1c quintile 5 (HR: 1.27, 95% CI: 1.02, 1.58), compared to DSE. CONCLUSION: Among adults with type 2 diabetes and overweight/obesity, randomization to a lifestyle intervention was differentially associated with CVD risk by baseline HbA1c such that it was associated with lower risk at lower HbA1c levels and higher risk at higher HbA1c levels. There is a critical need to develop and tailor lifestyle interventions to be successful for individuals with type 2 diabetes and high HbA1c.

Will the Doctor "See" You Now? The Development and Implementation of a Targeted Telemedicine System for Primary Care.

Objectives: The coronavirus disease 2019 (COVID-19) pandemic led to a rapid adoption of telehealth. For underserved populations lacking internet access, telemedicine was accomplished by phone rather than an audio-video connection. The latter is presumed a more effective form and better approximation of an in-person visit. We sought to provide a telehealth platform to overcome barriers for underserved groups to hold video visits with their health care providers and evaluate differences between the two telehealth modalities as assessed by physicians and patients. Methods: We designed a simplified tablet solution for video visits and piloted its use among patients who otherwise would have been completing audio-only visits. Patients consented to participation and were randomized in a 1:1 fashion to continue with their scheduled phone visit (control) versus being shipped a tablet to facilitate a video visit (intervention). Participants and providers completed communication and satisfaction surveys. Results: Tablet and connectivity design features included removal of all functions but for the telemedicine program, LTE always-on wireless internet connectivity, absence of external equipment (cords chargers and keyboard), and no registration with a digital portal. In total, 18 patients were enrolled. Intervention patients with video-enabled devices compared to control patients agreed more strongly that they were satisfied with their visits (4.75/5 vs. 3.75/5, p = 0.02). Conclusion: The delivered simplified tablet solution for video visits holds promise to improve access to video visits for underserved groups. Strategies to facilitate patient acceptance of devices are needed to expand the scope and potential impact of this effort.

Weighing cessation: Rising adiposity of current smokers in NHANES.

BACKGROUND: Rising rates of obesity may have interacting effects with smoking given associated cardiovascular risks and cessation-associated weight gain. This study aimed to assess the change in body mass index (BMI) magnitude and prevalence of obesity and central adiposity over time among current smokers and to compare with that of former and never smokers to describe how the obesity and tobacco epidemics interrelate. METHODS: Using data from the National Health and Nutrition Examination Survey (NHANES) 1976-2018, survey-weighted, internally standardized analyses were used to look at outcomes of BMI, BMI category, and central adiposity by smoking status. A nonparametric test assessed trend over time. RESULTS: The standardized proportion of current smokers with obesity increased from 11.6% in NHANES II to 36.3% in continuous NHANES 2017-2018; at the latest assessment this proportion was significantly lower than for former smokers. Mean BMI among current smokers also increased, from 24.7 kg/m2 to 28.5 kg/m2 among current smokers, which is significantly lower than among former smokers and never smokers at the latest time point. The standardized proportion of current smokers with central adiposity also increased, from 34.3% to 54.1%; again, at the latest time point the proportion was lower than for former smokers or never smokers. CONCLUSION: Between 1976 and 2018, smoking rates decreased while adiposity increased among current, former, and never smokers. Over a third of current smokers meet BMI criteria for obesity and over half have an elevated waist circumference. It is imperative that weight management strategies be incorporated into smoking cessation approaches.

Associations between the use of a real-time benefit tool and measures related to prescription obtainment found in order type subgroups.

BACKGROUND: The use of real-time benefit tool (RTBT) may help increase transparency of patients' out-of-pocket (OOP) costs, thereby reducing patients' OOP spend and increasing prescription obtainment. OBJECTIVE: We have previously reported on the potential benefit of RTBT in electronic health records at a large health system. We explore the benefit of RTBT by subgroups of prescriptions (i.e., order types). METHODS: In a retrospective cohort, we reviewed orders generated with and without RTBT use. We compared the 2 groups on key metrics related to prescription obtainment (fill rate, modification rate, cancellation rate, time to ready, time to sold, abandonment rate, and cancellation and transfer rate). Subgroup analysis included orders without over-the-counter (OTC) medications, orders without specialty medications, and orders without OTC and specialty medications. RESULTS: Fill rate, cancellation rate, time to ready, time to sold, abandonment rate, and cancellation and transfer rate were statistically significantly different between the RTBT and non-RTBT groups, favoring the RTBT group (all, P < 0.01). Differences in modification rates were not statistically significant between the 2 groups. CONCLUSION: RTBTs have the potential to increase prescription obtainment. A consistent difference in key outcome measures between the RTBT and the non-RTBT groups was apparent among prescription orders regardless of whether OTC and specialty medications were included in the analysis.

Does COVID-19 Infection Increase the Risk of Diabetes? Current Evidence.

PURPOSE OF REVIEW: Multiple studies report an increased incidence of diabetes following SARS-CoV-2 infection. Given the potential increased global burden of diabetes, understanding the effect of SARS-CoV-2 in the epidemiology of diabetes is important. Our aim was to review the evidence pertaining to the risk of incident diabetes after COVID-19 infection. RECENT FINDINGS: Incident diabetes risk increased by approximately 60% compared to patients without SARS-CoV-2 infection. Risk also increased compared to non-COVID-19 respiratory infections, suggesting SARS-CoV-2-mediated mechanisms rather than general morbidity after respiratory illness. Evidence is mixed regarding the association between SARS-CoV-2 infection and T1D. SARS-CoV-2 infection is associated with an elevated risk of T2D, but it is unclear whether the incident diabetes is persistent over time or differs in severity over time. SARS-CoV-2 infection is associated with an increased risk of incident diabetes. Future studies should evaluate vaccination, viral variant, and patient- and treatment-related factors that influence risk.

Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection? A population-level view in the EHR-based RECOVER program.

Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies.

Intensive behavioral Therapy for weight loss in patients with, or At-Risk of, type 2 Diabetes: Results from the PaTH to health diabetes study.

Intensive behavioral therapy (IBT) is an important component of obesity treatment and can reduce the risk of type 2 diabetes (T2DM). Objective was to compare the effectiveness of IBT to usual care in achieving weight loss in two study cohorts within PaTH Network: T2DM and At-Risk of T2DM. The TD2M cohort was defined as age 18 years and older with an indication of T2DM in the EHR based on a validated algorithm and at least 2 outpatient primary care visits. The At-Risk of T2DM cohort was defined by a BMI ≥ 25 kg/m2. The primary outcome was weight change within 1-year of index date. Mixed-effects models assessed the effectiveness of IBT by comparing the changes between study groups. Between 2009 and 2020, a total of 567,908 patients were identified in the T2DM cohort and2,054,256 patients in the At-Risk of T2DM cohort. Both IBT patients and matched non-IBT patients in the T2DM cohort had decreased mean weight (primary outcome) (-1.56 lbs, 95 %CI: -1.88, -1.24 vs -1.70 lbs, 95 %CI: -1.95, -1.44) in 1-year after index date. In the At-Risk of T2DM cohort, both IBT and non-IBT patients experienced weight gain and resultant increased BMI. Patients with more than one IBT visit gained less weight than those with only one visit (1.22 lbs, 95 %CI: 0.82, 1.62 vs 6.72 lbs, 95 %CI: 6.48, 6.97; p < 0.001). IBT was unlikely to result in clinically significant weight loss. Barriers to utilizing IBT require further research to ensure broader adoption of obesity management in primary care.

Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection?

Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include an increased incidence of diabetes. Our objective was to describe the temporal relationship between new diagnoses of diabetes mellitus and SARS-CoV-2 infection in a nationally representative database. There appears to be a sharp increase in diabetes diagnoses in the 30 days surrounding SARS-CoV-2 infection, followed by a decrease in new diagnoses in the post-acute period, up to 360 days after infection. These results underscore the need for further investigation, as understanding the timing of new diabetes onset after COVID-19 has implications regarding potential etiology and screening and treatment strategies.

Clinical interventions to break the obesity and cancer link: a narrative review.

Excess body weight is a significant risk factor for the development and recurrence of many types of cancer. Patients with a history or current diagnosis of cancer who are overweight or have obesity have an increased risk of cancer treatment-related morbidity, recurrence, and decreased quality of life. Weight loss and maintenance of a healthy body weight may reduce cancer morbidity and recurrence in cancer survivors. While guidelines for cancer survivorship elaborate sufficiently on lifestyle interventions, little guidance is provided when considering additional therapies like anti-obesity pharmacotherapy or bariatric surgery for weight loss. This review will highlight and address current recommendations and feasible interventions that clinicians may consider to further reduce the incidence and recurrence of cancer in patients with obesity.

Increases in Circulating and Fecal Butyrate are Associated With Reduced Blood Pressure and Hypertension: Results From the SPIRIT Trial.

Background Short chain fatty acids (SCFAs) are microbially derived end products of dietary fiber fermentation. The SCFA butyrate reduces blood pressure (BP) in mouse models. The association of SCFAs, including butyrate, with BP in humans is unclear, due in part to predominantly cross-sectional analyses and different biospecimens (blood versus fecal) for SCFA measurement. Longitudinal studies including both circulating and fecal SCFAs are lacking. Methods and Results We leveraged existing data from the SPIRIT (Survivorship Promotion In Reducing IGF-1 Trial), which randomized 121 adult cancer survivors with overweight/obesity to a behavioral weight-loss intervention, metformin, or self-directed weight-loss. Of participants with baseline serum and fecal SCFAs measured (n=111), a subset had serum (n=93) and fecal (n=89) SCFA measurements 12 months later. We used Poisson regression with robust error variance to estimate baseline associations of SCFAs with hypertension, and we assessed the percent change in SCFAs from baseline with corresponding 12-month changes in BP using multiple linear regression. Baseline fecal butyrate was inversely associated with prevalent hypertension (standardized PR [95%CI]: 0.71 [0.54, 0.92]). A 10% increase in fecal butyrate from baseline was associated with decreased systolic BP (ß [95%CI]: -0.56 [-1.01, -0.10] mm Hg), and a 10% increase in serum butyrate was associated with decreased systolic (ß [95%CI]: -1.39 [-2.15, -0.63] mm Hg) and diastolic (ß [95%CI]: -0.55 [-1.03, -0.08] mm Hg) BPs. Butyrate associations with systolic BP were linear and not modified by sex, race, or intervention arm. Conclusions Increased serum or fecal butyrate is associated with lowered BP. Butyrate may be a target for SCFA-centered BP-lowering interventions. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02431676.

Hospitalization and mortality in patients with COVID-19 with or at risk of type 2 diabetes: data from five health systems in Pennsylvania and Maryland.

OBJECTIVE: To identify the demographic and clinical characteristics associated with adverse COVID-19 outcomes across a 12-month period in 2020 and 2021. RESEARCH DESIGN AND METHODS: We conducted a retrospective cohort study using electronic health records from five academic health systems in Pennsylvania and Maryland, including patients with COVID-19 with type 2 diabetes or at risk of type 2 diabetes. Patients were classified based on 30-day outcomes: (1) no hospitalization; (2) hospitalization only; or (3) a composite measure including admission to the intensive care unit (ICU), intubation, or death. Analyses were conducted in patients with type 2 diabetes and patients at risk of type 2 diabetes separately. RESULTS: We included 15 725 patients with COVID-19 diagnoses between March 2020 and February 2021. Older age and higher Charlson Comorbidity Index scores were associated with higher odds of adverse outcomes, while COVID-19 diagnoses later in the study period were associated with lower odds of severe outcomes. In patients with type 2 diabetes, individuals on insulin treatment had higher odds for ICU/intubation/death (OR=1.59, 95% CI 1.27 to 1.99), whereas those on metformin had lower odds (OR=0.56, 95% CI 0.45 to 0.71). Compared with non-Hispanic White patients, Hispanic patients had higher odds of hospitalization in patients with type 2 diabetes (OR=1.73, 95% CI 1.36 to 2.19) or at risk of type 2 diabetes (OR=1.77, 95% CI 1.43 to 2.18.) CONCLUSIONS: Adults who were older, in racial minority groups, had multiple chronic conditions or were on insulin treatment had higher risks for severe COVID-19 outcomes. This study reinforced the urgency of preventing COVID-19 and its complications in vulnerable populations. TRIAL REGISTRATION NUMBER: NCT02788903.

A behavioral weight-loss intervention, but not metformin, decreases a marker of gut barrier permeability: results from the SPIRIT randomized trial.

BACKGROUND/OBJECTIVES: Lipopolysaccharide-binding protein (LBP), a biomarker of gut barrier permeability to lipopolysaccharides, is higher in adults with obesity and type 2 diabetes. Behavioral weight loss and metformin have distinct effects on the gut microbiome, but their impact on gut permeability to lipopolysaccharides is unknown. This study's objective was to determine the effects of a behavioral weight-loss intervention or metformin treatment on plasma LBP. SUBJECTS/METHODS: SPIRIT was a randomized trial of adults with overweight or obesity. Participants were randomized to one of three arms: metformin treatment, coach-directed behavioral weight loss on a DASH diet, or self-directed care (control). Of 121 participants, a random subset (n = 88) was selected to have LBP measured at baseline, 6 months, and 12 months post intervention. Intervention effects on LBP over time were assessed using generalized estimating equations (GEE). We also examined whether the intervention effects were modified by change in diet and weight. RESULTS: Arms were balanced by sex (83% female), race (51% white), and age (mean 60 years), with no differences in baseline LBP (median 4.23 µg/mL). At 1 year, mean weight change was -3.00% in the metformin arm, -3.02% in the coach-directed behavioral weight-loss arm, and +0.33% in the self-directed (control) arm. The corresponding change in LBP was +1.03, -0.98, +1.03 µg/mL. The behavioral weight-loss intervention reduced LBP compared to self-directed care (ß = -0.17, 95% CI: -0.33 to -0.01); no other between-arm comparisons were significant. Behavioral weight-loss participants who reduced dietary fat showed the greatest reductions in 6-month LBP (ß = -2.84, 95% CI: -5.17 to -0.50). CONCLUSIONS: Despite similar weight loss in the behavioral weight loss arm and the metformin arm, only the behavioral weight-loss intervention reduced LBP compared to control. Lifestyle weight-loss interventions that promote a DASH diet may be effective at reducing gut barrier permeability to lipopolysaccharides. CLINICAL TRIALS REGISTRATION NUMBER: NCT02431676, https://clinicaltrials.gov.

Use of Health Information Technology by Adults With Diabetes in the United States: Cross-sectional Analysis of National Health Interview Survey Data (2016-2018).

BACKGROUND: The use of health information technology (HIT) has been proposed to improve disease management in patients with type 2 diabetes mellitus. OBJECTIVE: This study aims to report the prevalence of HIT use in adults with diabetes in the United States and examine the factors associated with HIT use. METHODS: We analyzed data from 7999 adults who self-reported a diabetes diagnosis as collected by the National Health Interview Survey (2016-2018). All analyses were weighted to account for the complex survey design. RESULTS: Overall, 41.2% of adults with diabetes reported looking up health information on the web, and 22.8% used eHealth services (defined as filled a prescription on the web, scheduled an appointment with a health care provider on the web, or communicated with a health care provider via email). In multivariable models, patients who were female (vs male: prevalence ratio [PR] 1.16, 95% CI 1.10-1.24), had higher education (above college vs less than high school: PR 3.61, 95% CI 3.01-4.33), had higher income (high income vs poor: PR 1.40, 95% CI 1.23-1.59), or had obesity (vs normal weight: PR 1.11, 95% CI 1.01-1.22) were more likely to search for health information on the web. Similar associations were observed among age, race and ethnicity, education, income, and the use of eHealth services. Patients on insulin were more likely to use eHealth services (on insulin vs no medication: PR 1.21, 95% CI 1.04-1.41). CONCLUSIONS: Among adults with diabetes, HIT use was lower in those who were older, were members of racial minority groups, had less formal education, or had lower household income. Health education interventions promoted through HIT should account for sociodemographic factors.

Depressive Symptoms and Burnout Among Medical Students: a Prospective Study.

BACKGROUND: Depressive symptoms and burnout are common among medical students. However, few studies have investigated their trajectory over the course of medical school. OBJECTIVE: Evaluate year-by-year changes in depressive and burnout symptoms over the course of medical school training. DESIGN: Prospective study. PARTICIPANTS: Medical students who matriculated at a private medical school in Maryland from 2010 to 2016 (n=758). MAIN MEASURES: Clinically significant depressive symptoms were defined as a score of ≥10 on the 9-item Patient Health Questionnaire (PHQ-9), and burnout was measured using the Maslach Burnout Inventory (MBI). High emotional exhaustion, high depersonalization, and low personal accomplishment were defined as scores of ≥ 27, ≥10, and ≤33 on the respective MBI subscales. KEY RESULTS: At matriculation, the prevalences of significant depressive symptoms, high emotional exhaustion, high depersonalization, and low personal accomplishment were 4.3%, 9.4%, 8.6%, and 37.7%, respectively. After adjustment for age, sex, race/ethnicity, marital status, and cohort, compared with year 1, the odds of significant depressive symptoms was significantly higher at the beginning of the 2nd, 3rd, and 4th years of study (ORs=2.63, 2.85, and 3.77, respectively; all ps<0.001). Compared with the 1st year, the odds of high emotional exhaustion also increased during the 2nd, 3rd, and 4th years of study, (ORs=3.46, 4.79, 8.20, respectively; all ps<0.001), as did the odds of high depersonalization (ORs=3.55, 6.14, 12.53, respectively; all ps<0.001). The odds of low personal accomplishment did not significantly differ across years of study. CONCLUSIONS: The results of this study suggest that symptoms of depression and burnout may increase during medical school. Because of the high prevalence of depressive symptoms and burnout in medical students, interventions earlier in the medical career pathway that aim to prevent, detect, and treat these symptoms may be of benefit to the physician community.

Randomized trial of two artificial intelligence coaching interventions to increase physical activity in cancer survivors.

Physical activity (PA) has numerous health benefits. Personalized coaching may increase adherence to PA recommendations, but it is challenging to deliver personalized coaching in a scalable manner. The objective of our study was to determine whether novel artificially intelligent (AI) coaching interventions increase PA among overweight or obese, physically inactive cancer survivors compared to a control arm that receives health information. We conducted a single-center, three-arm randomized trial with equal allocation to (1) voice-assisted AI coaching delivered by smart speaker (MyCoach), (2) autonomous AI coaching delivered by text message (SmartText), and (3) control. Data collection was automated via sensors and voice technology, effectively masking outcome ascertainment. The primary outcome was change in mean steps per day from baseline to the end of follow-up at 4 weeks. Of the 42 randomized participants, 91% were female, and 36% were Black; mean age was 62.1 years, and mean BMI was 32.9 kg/m2. The majority were breast cancer survivors (85.7%). At the end of 4 weeks follow-up, steps increased in the MyCoach arm by an average of 3618.2 steps/day; the net gain in this arm was significantly greater [net difference = 3568.9 steps/day (95% CI: 1483-5655), P value <0.001] compared to control arm, and [net difference = 2160.6 steps/day (95% CI: 11-4310), P value 0.049] compared to SmartText. In conclusion, AI-based voice-assisted coaching shows promise as a practical method of delivering scalable, individualized coaching to increase physical activity in sedentary cancer survivors. Additional research is needed to replicate these findings in a broader population of cancer survivors and to investigate the effects of these interventions in the general population.ClinicalTrials.gov Identifier: NCT03212079, July 11, 2017, https://clinicaltrials.gov/ct2/show/NCT03212079 .

Hospital utilization for hypoglycemia among patients with type 2 diabetes using pooled data from six health systems.

INTRODUCTION: Hypoglycemia is the most common serious adverse effect of diabetes treatment and a major cause of medication-related hospitalization. This study aimed to identify trends and predictors of hospital utilization for hypoglycemia among patients with type 2 diabetes using electronic health record data pooled from six academic health systems. RESEARCH DESIGN AND METHODS: This retrospective open cohort study included 549 041 adults with type 2 diabetes receiving regular care from the included health systems between 2009 and 2019. The primary outcome was the yearly event rate for hypoglycemia hospital utilization: emergency department visits, observation visits, or inpatient admissions for hypoglycemia identified using a validated International Classification of Diseases Ninth Revision (ICD-9) algorithm from 2009 to 2014. After the transition to ICD-10 in 2015, we used two ICD-10 code sets (limited and expanded) for hypoglycemia hospital utilization from prior studies. We identified independent predictors of hypoglycemia hospital utilization using multivariable logistic regression analysis with data from 2014. RESULTS: Yearly rates of hypoglycemia hospital utilization decreased from 2.7 to 1.6 events per 1000 patients from 2009 to 2014 (p-trend=0.023). From 2016 to 2019, yearly event rates were stable ranging from 5.6 to 6.6, or 6.3 to 7.3, using the limited and expanded ICD-10 code sets, respectively. In 2014, the strongest independent risk factors for hypoglycemia hospital utilization were chronic kidney disease (OR 2.86, 95% CI 2.33 to 3.57), ages 18-39 years (OR 2.43 vs age 40-64 years, 95% CI 1.78 to 3.31), and insulin use (OR 2.13 vs no diabetes medications, 95% CI 1.67 to 2.73). CONCLUSIONS: Rates of hypoglycemia hospital utilization decreased from 2009 to 2014 and varied considerably by clinical risk factors such that younger adults, insulin users, and those with chronic kidney disease were at especially high risk. There is a need to validate hypoglycemia ascertainment using ICD-10 codes, which detect a substantially higher number of events compared with ICD-9.

Effects of a Behavioral Weight Loss Intervention and Metformin Treatment on Serum Urate: Results from a Randomized Clinical Trial.

Background: Lower body mass index (BMI) has been associated with lower serum urate (SU), but only in observational studies. We sought to determine the effects of behavioral weight loss and metformin treatment on SU in a randomized trial. Methods and Findings: The Survivorship Promotion In Reducing IGF-1 Trial (SPIRIT) was a parallel three-arm randomized controlled trial of overweight/obese adult cancer survivors without gout at a single center in Maryland, United States. Participants were randomized to: (1) coach-directed weight loss (behavioral telephonic coaching), (2) metformin (up to 2000 mg daily), or (3) self-directed weight loss (informational brochures; reference group). SU and BMI were assessed at baseline and at 3, 6, and 12 months post-randomization. The 121 participants had a mean ± standard deviation (SD) age of 60 ± 9 years, 79% were female, and 45% were Black. At baseline, BMI was 35 ± 5 kg/m2, and SU was 5.6 ± 1.3 mg/dL. Compared to the self-directed group, at 12 months, the coach-directed group reduced BMI by 0.9 kg/m2 (95% confidence interval (CI): -1.5, -0.4) and metformin reduced BMI by 0.6 kg/m2 (95% CI: -1.1, -0.1). However, compared to the self-directed group, the coach-directed group unexpectedly increased SU by 0.3 mg/dL (95% CI: 0.05, 0.6), and metformin non-significantly increased SU by 0.2 mg/dL (95% CI: -0.04, 0.5); these effects were attenuated when analyses included change in estimated glomerular filtration rate (eGFR). Conclusions: In this randomized trial of cancer survivors without gout, reductions in BMI either increased or did not change SU, potentially due to effects on eGFR. These results do not support a focus on BMI reduction for SU reduction; however, long-term studies are needed. ClinicalTrials.gov Registration: NCT02431676.