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Amir Sarayani,1,2 Joshua D Brown,1,2 Christian Hampp,1,3 William T Donahoo,4,5 Almut G Winterstein1,2 1Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, USA; 2Center for Drug Safety and Evaluation, University of Florida, Gainesville, FL, USA; 3Regeneron Pharmaceuticals Inc., Tarrytown, NY, USA; 4Division of Endocrinology, Diabetes, & Metabolism, College of Medicine, University of Florida, Gainesville, FL, USA; 5Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USACorrespondence: Amir Sarayani, University of Florida College of Pharmacy, 1225 Center Drive, HPNP Bldg, Room 3334, Gainesville, FL, 32610, USA, Email sarayani@gmail.com; sarayani@ufl.eduBackground: High-Dimensional Propensity Score procedure (HDPS) is a data-driven approach to assist control for confounding in pharmacoepidemiologic research. The transition to the International Classification of Disease (ICD-9/10) in the US health system may pose uncertainty in applying the HDPS procedure.Methods: We assembled a base cohort of patients in MarketScan® Commercial Claims Database who had newly initiated celecoxib or traditional NSAIDs to compare gastrointestinal bleeding risk. We then created bootstrapped hypothetical cohorts from the base cohort with predefined patient selection patterns from the ICD eras. Three strategies for HDPS deployment were tested: 1) split the cohort by ICD era, deploy HDPS twice, and pool the relative risks (pooled RR), 2) consider codes from each ICD era as a separate data dimension and deploy HDPS in the entire cohort (data dimensions) and 3) map ICD codes from both eras to Clinical Classifications Software (CCS) concepts before deploying HDPS in the entire cohort (CCS mapping). We calculated percent bias and root-mean-squared error to compare the strategies.Results: A similar bias reduction was observed in cohorts where patient selection pattern from each ICD era was comparable between the exposure groups. In the presence of considerable disparity in patient selection, we observed a bimodal distribution of propensity scores in the data dimensions strategy, indicating instrument-like covariates. Moreover, the CCS mapping strategy resulted in at least 30% less bias than pooled RR and data dimensions strategies (RMSE: 0.14, 0.19, 0.21, respectively) in this scenario.Conclusion: Mapping ICD codes to a stable terminology like CCS serves as a helpful strategy to reduce residual bias when deploying HDPS in pharmacoepidemiologic studies spanning both ICD eras.Keywords: propensity score, confounding, real-world evidence, comparative effectiveness research, ICD-10, ICD-9, HDPS algorithm

Racial and ethnic minorities bear a disproportionate burden of type 2 diabetes (T2D) and its complications, with social determinants of health (SDoH) recognized as key drivers of these disparities. Implementing efficient and effective social needs management strategies is crucial. We propose a machine learning analytic pipeline to calculate the individualized polysocial risk score (iPsRS), which can identify T2D patients at high social risk for hospitalization, incorporating explainable AI techniques and algorithmic fairness optimization. We use electronic health records (EHR) data from T2D patients in the University of Florida Health Integrated Data Repository, incorporating both contextual SDoH (e.g., neighborhood deprivation) and person-level SDoH (e.g., housing instability). After fairness optimization across racial and ethnic groups, the iPsRS achieved a C statistic of 0.71 in predicting 1-year hospitalization. Our iPsRS can fairly and accurately screen patients with T2D who are at increased social risk for hospitalization., (© 2024. The Author(s).)

Aim: To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents using electronic health records (EHRs) from the UF Health System., Materials and Methods: The CP algorithm was iteratively derived based on structured data from EHRs (UF Health System 2012-2020). We randomly selected 536 presumed cases among individuals aged <18 years who had (1) glycated haemoglobin levels ≥ 6.5%; or (2) fasting glucose levels ≥126 mg/dL; or (3) random plasma glucose levels ≥200 mg/dL; or (4) a diabetes-related diagnosis code from an inpatient or outpatient encounter; or (5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type., Results: Presumed cases without type 1 (T1D) or type 2 diabetes (T2D) diagnosis codes were categorized as non-diabetes/other types of diabetes. The rest were categorized as T1D if the most recent diagnosis was T1D, or otherwise categorized as T2D if the most recent diagnosis was T2D. Next, we applied a list of diagnoses and procedures that can determine diabetes type (e.g., steroid use suggests induced diabetes) to correct misclassifications from Step 1. Among the 536 reviewed cases, 159 and 64 had T1D and T2D, respectively. The sensitivity, specificity, and positive predictive values of the CP algorithm were 94%, 98% and 96%, respectively, for T1D and 95%, 95% and 73% for T2D., Conclusion: We developed a highly accurate EHR-based CP for diabetes in youth based on EHR data from UF Health. Consistent with prior studies, T2D was more difficult to identify using these methods., (© 2024 John Wiley & Sons Ltd.)

Background: Studies of new-onset diabetes as a post-acute sequela of SARS-CoV-2 infection are difficult to generalize to all socio-demographic subgroups., Objective: To study the risk of new-onset diabetes after SARS-CoV-2 infection in a socio-demographically diverse sample., Design: Retrospective cohort study of electronic health record (EHR) data available from the OneFlorida + clinical research network within the National Patient-Centered Clinical Research Network (PCORnet)., Subjects: Persons aged 18 or older were included as part of an Exposed cohort (positive SARS-CoV-2 test or COVID-19 diagnosis between 1 March 2020 and 29 January 2022; n = 43,906), a contemporary unexposed cohort (negative SARS-CoV-2 test; n = 162,683), or an age-sex matched historical control cohort (index visits between 2 Mar 2018 and 30 Jan 2020; n = 40,957)., Main Measures: The primary outcome was new-onset type 2 diabetes ≥ 30 days after index visit. Hazard ratios and cases per 1000 person-years of new-onset diabetes were studied using target trial approaches for observational data. Associations were reported by sex, race/ethnicity, age, and hospitalization status subgroups., Key Results: The sample was 62% female, 21.4% non-Hispanic Black, and 21.4% Hispanic; mean age was 51.8 (SD, 18.9) years. Relative to historical controls (cases, 28.2 [26.0-30.5]), the unexposed (HR, 1.28 [95% CI, 1.18-1.39]; excess cases, [5.1-10.3]), and exposed cohorts (HR, 1.64 [95% CI, 1.50-1.80]; excess cases, 17.3 [13.7-20.8]) had higher risk of new-onset T2DM. Relative to the unexposed cohort, the exposed cohort had a higher risk (HR, 1.28 [1.19-1.37]); excess cases, 9.5 [6.4-12.7]). Findings were similar across subgroups., Conclusion: The pandemic period was associated with increased T2DM cases across all socio-demographic subgroups; the greatest risk was observed among individuals exposed to SARS-CoV-2., (© 2024. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Objective: To study body mass index (BMI) changes among individuals aged 18-99 years with and without SARS-CoV-2 infection., Subjects/methods: Using real-world data from the OneFlorida+ Clinical Research Network of the National Patient-Centered Clinical Research Network, we compared changes over time in BMI in an Exposed cohort (positive SARS-CoV-2 test between March 2020-January 2022), to a contemporary Unexposed cohort (negative SARS-CoV-2 tests), and an age/sex-matched Historical control cohort (March 2018-January 2020). BMI (kg/m 2 ) was retrieved from objective measures of height and weight in electronic health records. We used target trial approaches to estimate BMI at start of follow-up and change per 100 days of follow-up for Unexposed and Historical cohorts relative to the Exposed cohort by categories of sex, race & ethnicity, age, and hospitalization status., Results: The study sample consisted of 249,743 participants (19.2% Exposed, 61.5% Unexposed, 19.3% Historical cohort) of whom 62% were women, 21.5% Non-Hispanic Black, 21.4% Hispanic and 5.6% Non-Hispanic other and had an average age of 51.9 years (SD: 18.9). At start of follow-up, relative to the Unexposed cohort (mean BMI: 29.3 kg/m 2 [95% CI: 29.1, 29.4]), the Exposed (0.07 kg/m 2 [95% CI; 0.01, 0.12]) had higher mean BMI and Historical controls (-0.20 kg/m 2 [95% CI; -0.25, -0.15]) had lower mean BMI. Over 100 days, BMI did not change (0 kg/m 2 [95% CI: -0.03, 0.03]) for the Exposed cohort, decreased (-0.04 kg/m 2 [95% CI; -0.05, -0.02]) for the Unexposed cohort and increased (0.03 kg/m 2 [95% CI; 0.01, 0.04]) for the Historical cohort. Observed differences in BMI at start of follow-up and over 100 days were consistent between Unexposed and Exposed cohorts for most subgroups, except at start of follow-up period among Males and those 65 years or older who had lower BMI among Exposed., Conclusions: In a diverse real-world cohort of adults, mean BMI of those with and without SARS-CoV2 infection varied in their trajectories. The mechanisms and implications of weight retention following SARS-CoV-2 infection remain unclear., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Introduction: Diabetes disparities exist based on socioeconomic status, race, and ethnicity. The aim of this study is to compare two cohorts with diabetes from California and Florida to better elucidate how health outcomes are stratified within underserved communities according to state location, race, and ethnicity., Research Design and Methods: Two cohorts were recruited for comparison from 20 Federally Qualified Health Centers as part of a larger ECHO Diabetes program. Participant-level data included surveys and HbA1c collection. Center-level data included Healthcare Effectiveness Data and Information Set metrics. Demographic characteristics were summarized overall and stratified by state (frequencies, percentages, means (95% CIs)). Generalized linear mixed models were used to compute and compare model-estimated rates and means., Results: Participant-level cohort: 582 adults with diabetes were recruited (33.0% type 1 diabetes (T1D), 67.0% type 2 diabetes (T2D)). Mean age was 51.1 years (95% CI 49.5, 52.6); 80.7% publicly insured or uninsured; 43.7% non-Hispanic white (NHW), 31.6% Hispanic, 7.9% non-Hispanic black (NHB) and 16.8% other. Center-level cohort: 32 796 adults with diabetes were represented (3.4% with T1D, 96.6% with T2D; 72.7% publicly insured or uninsured). Florida had higher rates of uninsured (p<0.0001), lower continuous glucose monitor (CGM) use (18.3% Florida; 35.9% California, p<0.0001), and pump use (10.2% Florida; 26.5% California, p<0.0001), and higher proportions of people with T1D/T2D>9% HbA1c (p<0.001). Risk was stratified within states with NHB participants having higher HbA1c (mean 9.5 (95% CI 8.9, 10.0) compared with NHW with a mean of 8.4 (95% CI 7.8, 9.0), p=0.0058), lower pump use (p=0.0426) and CGM use (p=0.0192). People who prefer to speak English were more likely to use a CGM (p=0.0386)., Conclusions: Characteristics of medically underserved communities with diabetes vary by state and by race and ethnicity. Florida's lack of Medicaid expansion could be a factor in worsened risks for vulnerable communities with diabetes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Previous studies have suggested that glucagon-like peptide-1 receptor agonists (GLP-1RAs) may have a disease-modifying effect in the development of Parkinson's disease (PD), but population studies yielded inconsistent results., Objective: The aim was to compare the risk of PD associated with GLP-1RAs compared to dipeptidyl peptidase 4 inhibitors (DPP4i) among older adults with type 2 diabetes (T2D)., Methods: Using U.S. Medicare administrative data from 2016 to 2020, we conducted a population-based cohort study comparing the new use of GLP-1RA with the new use of DPP4i among adults aged ≥66 years with T2D. The primary endpoint was a new diagnosis of PD. A stabilized inverse probability of treatment weighting (sIPTW)-adjusted Cox proportional hazards regression model was employed to estimate the hazard ratio (HR) and 95% confidence intervals (CI) for PD between GLP-1RA and DPP4i users., Results: This study included 89,074 Medicare beneficiaries who initiated either GLP-1RA (n = 30,091) or DPP4i (n = 58,983). The crude incidence rate of PD was lower among GLP-1RA users than DPP4i users (2.85 vs. 3.92 patients per 1000 person-years). An sIPTW-adjusted Cox model showed that GLP-1RA users were associated with a 23% lower risk of PD than DPP4i users (HR, 0.77; 95% CI, 0.63-0.95). Our findings were largely consistent across different subgroup analyses such as sex, race, and molecular structure of GLP-1RA., Conclusion: Among Medicare beneficiaries with T2D, the new use of GLP-1RAs was significantly associated with a decreased risk of PD compared to the new use of DPP4i. © 2024 International Parkinson and Movement Disorder Society., (© 2024 International Parkinson and Movement Disorder Society.)

Introduction: Sodium-glucose cotransporter 2 (SGLT2) inhibitors exhibit potential benefits in reducing dementia risk, yet the optimal beneficiary subgroups remain uncertain., Methods: Individuals with type 2 diabetes (T2D) initiating either SGLT2 inhibitor or sulfonylurea were identified from OneFlorida+ Clinical Research Network (2016-2022). A doubly robust learning was deployed to estimate risk difference (RD) and 95% confidence interval (CI) of all-cause dementia., Results: Among 35,458 individuals with T2D, 1.8% in the SGLT2 inhibitor group and 4.7% in the sulfonylurea group developed all-cause dementia over a 3.2-year follow-up, yielding a lower risk for SGLT2 inhibitors (RD, -2.5%; 95% CI, -3.0% to -2.1%). Hispanic ethnicity and chronic kidney disease were identified as the two important variables to define four subgroups in which RD ranged from -4.3% (-5.5 to -3.2) to -0.9% (-1.9 to 0.2)., Discussion: Compared to sulfonylureas, SGLT2 inhibitors were associated with a reduced risk of all-cause dementia, but the association varied among different subgroups., Highlights: New users of sodium-glucose cotransporter 2 (SGLT2) inhibitors were significantly associated with a lower risk of all-cause dementia as compared to those of sulfonylureas. The association varied among different subgroups defined by Hispanic ethnicity and chronic kidney disease. A significantly lower risk of Alzheimer's disease and vascular dementia was observed among new users of SGLT2 inhibitors compared to those of sulfonylureas., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: A major concern has recently emerged about a potential link between glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and increased risk for suicidal ideation and behaviors based on International Classification of Diseases codes., Objective: To investigate the association between GLP-1 RAs, compared with sodium-glucose cotransporter-2 inhibitors (SGLT2is) or dipeptidyl peptidase-4 inhibitors (DPP4is), and risk for suicidal ideation and behaviors in older adults with type 2 diabetes (T2D)., Design: Two target trial emulation studies comparing propensity score (PS)-matched cohorts for GLP-1 RAs versus SGLT2is and GLP-1 RAs versus DPP4is., Setting: U.S. national Medicare administrative data from January 2017 to December 2020., Patients: Older adults (≥66 years) with T2D; no record of suicidal ideation or behaviors; and a first prescription for a GLP-1 RA, SGLT2i, or DPP4i., Measurements: The primary end point was a composite of suicidal ideation and behaviors. New GLP-1 RA users were matched 1:1 on PS to new users of an SGLT2i or DPP4i in each pairwise comparison. A Cox proportional hazards regression was used to estimate the hazard ratio (HR) and 95% CIs within matched groups., Results: This study included 21 807 pairs of patients treated with a GLP-1 RA versus an SGLT2i and 21 402 pairs of patients treated with a GLP-1 RA versus a DPP4i. The HR of suicidal ideation and behaviors associated with GLP-1 RAs relative to SGLT2is was 1.07 (95% CI, 0.80 to 1.45; rate difference, 0.16 [CI, -0.53 to 0.86] per 1000 person-years); the HR relative to DPP4is was 0.94 (CI, 0.71 to 1.24; rate difference, -0.18 [CI, -0.92 to 0.57] per 1000 person-years)., Limitations: Low event rate; imprecise estimates; unmeasured confounders, such as body mass index; and potential misclassification of outcomes., Conclusion: Among Medicare beneficiaries with T2D, this study found no clear increased risk for suicidal ideation and behaviors with GLP-1 RAs, although estimates were imprecise and a modest adverse risk could not be ruled out., Primary Funding Source: American Foundation for Pharmaceutical Education, Pharmaceutical Research and Manufacturers of America Foundation, National Institute on Aging, and National Institute of Diabetes and Digestive and Kidney Diseases., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M24-0329.

Purpose: The purpose of this study was to examine the association between determinants of health, medication engagement, and A1C levels in adults with type 2 diabetes (T2DM) receiving Tribal health and pharmacy services., Methods: A retrospective analysis of 2020-2021 electronic health record data was conducted and included adult patients with T2DM using Choctaw Nation Health Services Authority prescribed ≥1 noninsulin glucose-lowering medication in 2020, had ≥1 A1C value in 2020 and 2021, and had a valid zip code in 2021. Patients receiving both insulin and other noninsulin glucose-lowering medication were included. The proportion of days covered (PDC) was used to calculate medication engagement. Statistical analyses included bivariate analysis and linear regression., Results: There were 3787 patients included in the analyses; 62.5% were considered engaged (PDC ≥ 0.8). The mean 2020 A1C level was 8.0 (64 mmol/mol) ± 1.8; 33% had an A1C of <7%, 42% had an A1C of 7% to 9%, and 25% had an A1C >9%. The mean A1C in 2021 was 7.9 (63 mmol/mol) ± 1.7; 34% had an A1C of <7%, 44% had an A1C of 7% to 9%, and 22% had an A1C >9%. Older age was weakly correlated with higher engagement; higher engagement was associated with lower A1C levels while adjusting for covariates., Conclusions: Medication engagement was associated with lower A1C levels, and older age was weakly associated with higher engagement to noninsulin glucose-lowering medications, consistent with previous literature. No determinants of health were significantly associated with A1C levels while adjusting for covariates., Competing Interests: Declaration of Conflicting InterestsThe authors declare that there are no conflicts of interest.

Introduction: Human papillomavirus (HPV) causes 99.7% of cervical cancer cases. Cervical cancer is preventable through early detection via HPV testing. However, the number of women screened for cervical cancer has not increased in the last several years. Lower screening rates among women living in high poverty and social vulnerability areas, Black women, and women with chronic co-morbidities (e.g., type 2 diabetes (T2D)) are associated with their higher cervical cancer mortality rates. When screened, Black women are more likely to be diagnosed at later stages and die from cervical cancer. HPV self-collection decreases barriers to cervical cancer screening and can help lessen disparities among underserved women. This study aimed to examine the acceptability of HPV self-collection among Black women with T2D living in socially vulnerable communities., Methods: Qualitative semi-structured interviews were conducted with 29 Black women with T2D living in communities with high social vulnerability. The Health Belief Model informed the development of the interview guide to gather data on the acceptability of HPV self-collection., Results: Three main themes aligned with the Health Belief Model were identified: (1) HPV self-collection provides a comfortable alternative to in-clinic HPV testing (perceived benefits); (2) HPV self-collection would result in awareness of current HPV status (health motivation); and (3) Women were concerned about collecting their sample accurately (perceived barriers)., Discussion/conclusion: Black women with T2D living in communities with high social vulnerability identified multiple benefits of cervical cancer screening through HPV self-collection. Women are concerned about their ability to collect these samples correctly. Our findings call for future studies focusing on increasing self-efficacy and skills to collect HPV samples among Black women with chronic conditions like T2D who reside in underserved communities with high social vulnerability., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Background: Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are highly prevalent but underdiagnosed., Aims: We used an electronic health record data network to test a population-level risk stratification strategy using noninvasive tests (NITs) of liver fibrosis., Methods: Data were obtained from PCORnet ® sites in the East, Midwest, Southwest, and Southeast United States from patients aged [Formula: see text] 18 with or without ICD-10-CM diagnosis codes for NAFLD, NASH, and NASH-cirrhosis between 9/1/2017 and 8/31/2020. Average and standard deviations (SD) for Fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), and Hepatic Steatosis Index (HSI) were estimated by site for each patient cohort. Sample-wide estimates were calculated as weighted averages across study sites., Results: Of 11,875,959 patients, 0.8% and 0.1% were coded with NAFLD and NASH, respectively. NAFLD diagnosis rates in White, Black, and Hispanic patients were 0.93%, 0.50%, and 1.25%, respectively, and for NASH 0.19%, 0.04%, and 0.16%, respectively. Among undiagnosed patients, insufficient EHR data for estimating NITs ranged from 68% (FIB-4) to 76% (NFS). Predicted prevalence of NAFLD by HSI was 60%, with estimated prevalence of advanced fibrosis of 13% by NFS and 7% by FIB-4. Approximately, 15% and 23% of patients were classified in the intermediate range by FIB-4 and NFS, respectively. Among NAFLD-cirrhosis patients, a third had FIB-4 scores in the low or intermediate range., Conclusions: We identified several potential barriers to a population-level NIT-based screening strategy. HSI-based NAFLD screening appears unrealistic. Further research is needed to define merits of NFS- versus FIB-4-based strategies, which may identify different high-risk groups., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: Little is known about the heterogeneous treatment effects of metformin on dementia risk in people with type 2 diabetes (T2D)., Methods: Participants (≥ 50 years) with T2D and normal cognition at baseline were identified from the National Alzheimer's Coordinating Center database (2005-2021). We applied a doubly robust learning approach to estimate risk differences (RD) with a 95% confidence interval (CI) for dementia risk between metformin use and no use in the overall population and subgroups identified through a decision tree model., Results: Among 1393 participants, 104 developed dementia over a 4-year median follow-up. Metformin was significantly associated with a lower risk of dementia in the overall population (RD, -3.2%; 95% CI, -6.2% to -0.2%). We identified four subgroups with varied risks for dementia, defined by neuropsychiatric disorders, non-steroidal anti-inflammatory drugs, and antidepressant use., Discussion: Metformin use was significantly associated with a lower risk of dementia in individuals with T2D, with significant variability among subgroups., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Prior studies have shown disparities in the uptake of cardioprotective newer glucose-lowering drugs (GLDs), including sodium-glucose cotranwsporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1a). This study aimed to characterize geographic variation in the initiation of newer GLDs and the geographic variation in the disparities in initiating these medications., Methods: Using 2017-2018 claims data from a 15% random nationwide sample of Medicare Part D beneficiaries, we identified individuals diagnosed with type 2 diabetes (T2D), who had ≥1 GLD prescriptions, and did not use SGLT2i or GLP1a in the year prior to the index date,1/1/2018. Patients were followed up for a year. The cohort was spatiotemporally linked to Dartmouth hospital-referral regions (HRRs), with each patient assigned to 1 of 306 HRRs. We performed multivariable Poisson regression to estimate adjusted initiation rates, and multivariable logistic regression to assess racial disparities in each HRR., Results: Among 795,469 individuals with T2D included in the analyses, the mean (SD) age was 73 (10) y, 53.3% were women, 12.2% were non-Hispanic Black, and 7.2% initiated a newer GLD in the follow-up year. In the adjusted model including clinical factors, compared to non-Hispanic White patients, non-Hispanic Black (initiation rate ratio, IRR [95% CI]: 0.66 [0.64-0.68]), American Indian/Alaska Native (0.74 [0.66-0.82]), Hispanic (0.85 [0.82-0.87]), and Asian/Pacific islander (0.94 [0.89-0.98]) patients were less likely to initiate newer GLDs. Significant geographic variation was observed across HRRs, with an initiation rate spanning 2.7%-13.6%., Conclusions: This study uncovered substantial geographic variation and the racial disparities in initiating newer GLDs., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The telementoring Project ECHO (Extension for Community Healthcare Outcomes) model has been shown to improve disease management in diabetes in many underserved communities. The authors aim to evaluate if ECHO could also be an effective tool for quality improvement (QI) of diabetes care in these communities., Methods: Thirteen clinics in underserved communities in California and Florida participating in Project ECHO Diabetes were recruited for a 12-month QI program. The program provided weekly tele-education sessions, including a didactic presentation and case-based discussion. In addition, clinics chose their own set of quality measures to improve and met remotely to discuss their efforts, successes, and setbacks every quarter with mentorship from QI experts., Results: Of the 31 QI initiatives attempted by different clinics, all had either made improvements (25 initiatives, 80.6%) or were in the process of making improvements (6 initiatives, 19.4%) in structural, process, and outcome measures. Examples of these measures include whether clinics have protocols to identify high-risk patients (structure), numbers of continuous glucose monitor prescriptions submitted by the clinics (process), and percentage of patients with diabetes whose most recent HbA1c are > 9% (outcome). For one measure, 40.0% of the clinics had achieved a higher percentage of cumulative HbA1c measurement in the third quarter of the year, compared to the fourth quarter in the previous year. The cost of QI implementation varied widely due to different number of personnel involved across sites., Conclusion: A QI program delivered via Project ECHO Diabetes can facilitate quality improvements in underserved communities., (Copyright © 2023 The Joint Commission. Published by Elsevier Inc. All rights reserved.)

Introduction: The COVID-19 pandemic forced health systems worldwide to make rapid adjustments to patient care. Nationwide stay-at-home mandates and public health concerns increased demand for telehealth to maintain patients' continuity of care. These circumstances permitted observation of telehealth implementation in real-world settings at a large scale. This study aimed to understand clinician and health system leader (HSL) experiences in expanding, implementing, and sustaining telehealth during COVID-19 in the OneFlorida+ clinical research network. Methods: We conducted semistructured videoconference interviews with 5 primary care providers, 7 specialist providers, and 12 HSLs across 7 OneFlorida+ health systems and settings. Interviews were audiorecorded, transcribed, and summarized using deductive team-based template coding. We then used matrix analysis to organize the qualitative data and identify inductive themes. Results: Rapid telehealth implementation occurred even among sites with low readiness, facilitated by responsive planning, shifts in resource allocation, and training. Common hurdles in routine telehealth use, including technical and reimbursement issues, were also barriers to telehealth implementation. Acceptability of telehealth was influenced by benefits such as the providers' ability to view a patient's home environment and the availability of tools to enhance patient education. Lower acceptability stemmed from the inability to conduct physical examinations during the shutdown. Conclusions: This study identified a broad range of barriers, facilitators, and strategies for implementing telehealth within large clinical research networks. The findings can contribute to optimizing the effectiveness of telehealth implementation in similar settings, and point toward promising directions for telehealth provider training to improve acceptability and promote sustainability.

Objective: Having sufficient population coverage from the electronic health records (EHRs)-connected health system is essential for building a comprehensive EHR-based diabetes surveillance system. This study aimed to establish an EHR-based type 1 diabetes (T1D) surveillance system for children and adolescents across racial and ethnic groups by identifying the minimum population coverage from EHR-connected health systems to accurately estimate T1D prevalence., Materials and Methods: We conducted a retrospective, cross-sectional analysis involving children and adolescents <20 years old identified from the OneFlorida+ Clinical Research Network (2018-2020). T1D cases were identified using a previously validated computable phenotyping algorithm. The T1D prevalence for each ZIP Code Tabulation Area (ZCTA, 5 digits), defined as the number of T1D cases divided by the total number of residents in the corresponding ZCTA, was calculated. Population coverage for each ZCTA was measured using observed health system penetration rates (HSPR), which was calculated as the ratio of residents in the corresponding ZTCA and captured by OneFlorida+ to the overall population in the same ZCTA reported by the Census. We used a recursive partitioning algorithm to identify the minimum required observed HSPR to estimate T1D prevalence and compare our estimate with the reported T1D prevalence from the SEARCH study., Results: Observed HSPRs of 55%, 55%, and 60% were identified as the minimum thresholds for the non-Hispanic White, non-Hispanic Black, and Hispanic populations. The estimated T1D prevalence for non-Hispanic White and non-Hispanic Black were 2.87 and 2.29 per 1000 youth, which are comparable to the reference study's estimation. The estimated prevalence of T1D for Hispanics (2.76 per 1000 youth) was higher than the reference study's estimation (1.48-1.64 per 1000 youth). The standardized T1D prevalence in the overall Florida population was 2.81 per 1000 youth in 2019., Conclusion: Our study provides a method to estimate T1D prevalence in children and adolescents using EHRs and reports the estimated HSPRs and prevalence of T1D for different race and ethnicity groups to facilitate EHR-based diabetes surveillance., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Understanding the disparities in utilization and weight loss outcomes of metabolic and bariatric surgery (MBS) by demographics will inform strategies targeting potential treatment gaps and enhance overall clinical obesity treatment., Objective: To identify factors associated with utilization and longitudinal weight loss after MBS., Setting: OneFlorida Clinical Research Consortium Database., Methods: We performed a retrospective study using data from the OneFlorida Clinical Research Consortium between 2012 and 2018. We used logistic regression with intersectional effects to identify factors associated with utilization of MBS. Mixed-effect models were used to estimate longitudinal percentage total weight loss among those who underwent MBS with up to 18 months of follow-up., Results: Among 429,821 patients eligible for MBS, 8290 (1.9%) underwent MBS between 2012 and 2018. Intersectional analysis revealed that non-Hispanic Black patients experienced an inferior utilization of MBS compared with non-Hispanic White and Hispanic counterparts, defined by the interaction between race/ethnicity and demographic factors, including male sex, older age, and insurance coverage. In the longitudinal weight loss assessment, 4016 patients (48.3% Roux-en-Y gastric bypass, 51.7% sleeve gastrectomy) were included. We found that non-Hispanic Black patients experienced significantly less weight loss than non-Hispanic White and Hispanic counterparts. Other factors associated with less weight loss over time included undergoing sleeve gastectomy, male sex, lower preoperative body mass index, and having type 2 diabetes at the time of surgery., Conclusions: Our findings will help to design new strategies focusing on the intersection of race/ethnicity and sociodemographic factors to improve access and effectiveness of MBS., (Copyright © 2023 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.)

Background: The association between newer classes of glucose-lowering drugs (GLDs) and the risk of Parkinson's disease (PD) remains unclear., Objective: The aim was to examine the effect of newer GLDs on the risk of PD through a meta-analysis of randomized outcome trials., Methods: The methods included randomized placebo-controlled outcome trials that reported PD events associated with three newer classes of GLDs (ie, dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, and sodium-glucose co-transporter-2 inhibitors) in participants with or without type 2 diabetes. The pooled odds ratio (OR) and 95% confidence interval (CI) were estimated using Peto's method., Results: The study included 24 trials involving 33 PD cases among 185,305 participants during a median follow-up of 2.2 years. Newer GLDs were significantly associated with a lower PD risk (OR: 0.50; 95% CI: 0.25-0.98) than placebo., Conclusion: Newer GLDs may possibly be associated with a decreased risk of PD; however, larger datasets are required to confirm or refute this notion., (© 2023 International Parkinson and Movement Disorder Society.)

Background: Preclinical studies have suggested potential beneficial effects of newer glucose-lowering drugs (GLDs) including dipeptidyl peptidase (DPP)-4 inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), and sodium glucose co-transporter-2 (SGLT2) inhibitors, in protecting humans against cognitive decline and dementia. However, population studies aiming to demonstrate such cognitive benefits from newer GLDs have produced mixed findings. This meta-analysis aimed to evaluate the association between newer GLDs and risk of dementia in adults with type 2 diabetes (T2D)., Methods: Electronic databases were searched up to March 11, 2022 to include observational studies that examined the association between DPP-4 inhibitors, GLP-1RAs, and SGLT2 inhibitors and risk of dementia (including all-cause dementia, Alzheimer's disease [AD], and vascular dementia [VD]) in people with T2D. We conducted a random-effects meta-analysis to calculate the relative risk (RR) with 95% confidence interval (CI) for each class of newer GLD., Results: Ten studies (from nine articles) involving 819,511 individuals with T2D were included. Three studies found that SGLT2 inhibitor users had a lower risk of all-cause dementia than non-SGLT2 inhibitor users (RR, 0.62; 95% CI, 0.39-0.97). Five studies found that users versus nonusers of GLP-1RAs were associated with a significant reduction in the risk of all-cause dementia (RR, 0.72; 95% CI, 0.54-0.97). However, a meta-analysis for AD and VD was unavailable for SGLT2 inhibitors and GLP-1RAs because only one study was included for each drug. In seven studies, users vs. nonusers of DPP-4 inhibitors were significantly associated with a decreased risk of all-cause dementia (RR, 0.84; 95% CI, 0.74-0.94) and VD (RR, 0.59; 95% CI, 0.47-0.75) but not AD (RR, 0.82; 95% CI, 0.63-1.08)., Conclusion: Newer GLDs were associated with a decreased risk of all-cause dementia in people with T2D. Because of the observational nature and significant heterogeneity between studies, the results should be interpreted with caution. Further research is warranted to confirm our findings., (© 2023 The American Geriatrics Society.)

Objective: To examine HbA1c levels and adherence to oral glucose-lowering medications and their association with future HbA1c levels among American Indian adults with type 2 diabetes (T2D) receiving medications at no cost from a tribal health care system., Research Design and Methods: Tribal citizens with T2D who used Choctaw Nation Health Services Authority (CNHSA) and Pharmacies and had HbA1c data during 2017-2018 were included in this study. Medication adherence (proportion of days covered [PDC] ≥0.80) was calculated using 2017 CNHSA electronic health record data., Results: Of the 74,000 tribal citizens living on tribal lands, 4,560 were eligible; 32% had HbA1c at or below target (≤7%), 36% were above target (>7 to ≤9%), and 32% were uncontrolled (>9%) in 2017. The percentage of patients with PDC ≥0.80 was 66% for those using biguanides, 72% for sulfonylureas, 75% for dipeptidyl peptidase 4 inhibitors, and 83% for sodium-glucose cotransporter 2 inhibitors. The proportion of patients with HbA1c at or below target increased slightly from 32% in 2017 to 42% in 2018. Higher average PDC in 2017 was associated with lower HbA1c levels in 2018 (β = -1.143; P < 0.001)., Conclusions: Medication adherence was higher than that found in previous studies using self-report methods in American Indian populations, although a smaller proportion of patients had HbA1c at or below target relative to U.S. adults with T2D. Medication adherence was associated with improved HbA1c levels for most oral glucose-lowering medication classes. Future studies of American Indians should use both longitudinal prescription data from both electronic health records and pharmacy refills., (© 2023 by the American Diabetes Association.)

Background: The U.S. Food and Drug Administration approved phentermine-topiramate for obesity in 2012 and required a Risk Evaluation and Mitigation Strategy (REMS) to prevent prenatal exposure. No such requirement was introduced for topiramate., Objective: To evaluate the rate of prenatal exposure, contraceptive use, and pregnancy testing among patients with phentermine-topiramate compared with topiramate or other antiobesity medications (AOMs)., Design: Retrospective cohort study., Setting: Nationwide health insurance claims database., Participants: Females aged 12 to 55 years with no infertility diagnosis or sterilization procedure. Patients with other indications for topiramate were excluded to identify a cohort that was likely treated for obesity., Measurements: Patients initiated use of phentermine-topiramate, topiramate, or an AOM (liraglutide, lorcaserin, or bupropion-naltrexone). Pregnancy at treatment initiation, conception during treatment, contraceptive use, and pregnancy testing outcomes were ascertained. Measurable confounders were adjusted for, and extensive sensitivity analyses were done., Results: A total of 156 280 treatment episodes were observed. Adjusted prevalence of pregnancy at treatment initiation was 0.9 versus 1.6 per 1000 episodes (prevalence ratio, 0.54 [95% CI, 0.31 to 0.95]) for phentermine-topiramate versus topiramate. The incidence rate of conception during treatment was 9.1 versus 15.0 per 1000 person-years (rate ratio, 0.61 [CI, 0.40 to 0.91]) for phentermine-topiramate versus topiramate. Both outcomes were similarly lower for phentermine-topiramate compared with AOM. Prenatal exposure was marginally lower in topiramate users compared with AOM users. Approximately 20% of patients in all cohorts had at least 50% of treatment days covered by contraceptives. Few patients had pregnancy tests before treatment (≤5%), but this was more common among phentermine-topiramate users., Limitations: Outcome misclassification; unmeasured confounding due to lack of prescriber data to account for possible clustering and spillover effects., Conclusion: Prenatal exposure seemed to be significantly lower among phentermine-topiramate users under the REMS. Pregnancy testing and contraceptive use appeared to be inadequate for all groups, which deserves attention to prevent the remaining potential exposures., Primary Funding Source: None.

Background: We aimed to investigate the association between contextual-level social determinants of health (SDoH) and the use of novel antidiabetic drugs (ADD), including sodium-glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1a) for patients with type 2 diabetes (T2D), and whether the association varies across racial and ethnic groups., Methods: Using electronic health records from the OneFlorida+ network, we assembled a cohort of T2D patients who initiated a second-line ADD in 2015-2020. A set of 81 contextual-level SDoH documenting social and built environment were spatiotemporally linked to individuals based on their residential histories. We assessed the association between the contextual-level SDoH and initiation of SGTL2i/GLP1a and determined their effects across racial groups, adjusting for clinical factors., Results: Of 28,874 individuals, 61% were women, and the mean age was 58 (±15) years. Two contextual-level SDoH factors identified as significantly associated with SGLT2i/GLP1a use were neighborhood deprivation index (odds ratio [OR] 0.87, 95% confidence interval [CI] 0.81-0.94) and the percent of vacant addresses in the neighborhood (OR 0.91, 95% CI 0.85-0.98). Patients living in such neighborhoods are less likely to be prescribed with newer ADD. There was no interaction between race-ethnicity and SDoH on the use of newer ADD. However, in the overall cohort, the non-Hispanic Black individuals were less likely to use newer ADD than the non-Hispanic White individuals (OR 0.82, 95% CI 0.76-0.88)., Conclusion: Using a data-driven approach, we identified the key contextual-level SDoH factors associated with not following evidence-based treatment of T2D. Further investigations are needed to examine the mechanisms underlying these associations.

Introduction: The US FDA required a Risk Evaluation and Mitigation Strategy (REMS) for phentermine/topiramate, an anti-obesity medication, to prevent congenital malformations. No REMS is required for single-ingredient topiramate, which may be used off-label for the same purpose., Objective: The aim of this study was to evaluate the impact of phentermine/topiramate approval in 2012 on subsequent topiramate use among patients with obesity., Methods: We used a national insurance claims database to conduct an interrupted time-series study (2009-2015). Enrollees aged 18-65 years in each examined calendar quarter had full insurance benefits during that quarter and the preceding 6 months. We required patients to have an obesity diagnosis and no other conditions warranting topiramate use. We calculated topiramate or comparator drug (atorvastatin, metformin) initiation rates and evaluated changes in trends before and after 2012 (transition period)., Results: Among topiramate users, 80% were female, and demographic characteristics remained consistent during the study period. Between 2009 and 2011, the topiramate initiation rate (95% confidence interval) among patients with obesity was 0.85 (0.73-0.98) per 1000 patients, with no significant upward or downward trend. In the first quarter of 2013, this rate had increased more than 2.5-fold (change: + 1.36 [1.19-1.52]). Metformin and atorvastatin initiation rates did not change. Topiramate initiation rates were threefold higher than phentermine/topiramate rates during the post-approval period., Conclusion: Phentermine/topiramate approval was associated with increased topiramate use among patients with obesity. Prescribers are encouraged to enhance patient education and monitoring in such clinical use since topiramate prescribing information, compared with REMS for phentermine/topiramate, has less emphasis on preventing prenatal exposure., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: American Indian adults have the highest prevalence of type 2 diabetes (T2D) in any racial or ethnic group and experience high rates of comorbidities. Uncontrolled cardiometabolic risk factors-insulin resistance, resulting in impaired glucose tolerance, dyslipidemia, and hypertension-increase the risk of mortality. Mortality is significantly reduced by glucose- and lipid-lowering and antihypertensive medication adherence. Medication adherence is low among American Indian adults living in non-Indian Health Service health care settings. Virtually nothing is known about the nature and extent of medication adherence among reservation-dwelling American Indian adults who primarily receive their medications without cost from Indian Health Service or tribal facilities. Electronic health records (EHRs) offer a rich but underused data source regarding medication adherence and its potential to predict cardiometabolic control indicators (C-MCIs). With the support of the Choctaw Nation of Oklahoma (CNO), we address this oversight by using EHR data generated by this large, state-of-the-art tribal health care system to investigate C-MCIs., Objective: Our specific aims are to determine, using 2018 EHR data, the bivariate relationships between medication adherence and C-MCIs, demographics, and comorbidities and each C-MCI and demographics and comorbidities; develop machine learning models for predicting future C-MCIs from the previous year's medication adherence, demographics, comorbidities, and common laboratory tests; and identify facilitators of and barriers to medication adherence within the context of social determinants of health (SDOH), EHR-derived medication adherence, and C-MCIs., Methods: Drawing on the tribe's EHR (2018-2021) data for CNO patients with T2D, we will characterize the relationships among medication adherence (to glucose- and lipid-lowering and antihypertensive drugs) and C-MCIs (hemoglobin A1c ≤7%, low-density lipoprotein cholesterol <100 mg/dL, and systolic blood pressure <130 mm Hg); patient demographics (eg, age, sex, SDOH, and residence location); and comorbidities (eg, BMI ≥30, cardiovascular disease, and chronic kidney disease). We will also characterize the association of each C-MCI with demographics and comorbidities. Prescription and pharmacy refill data will be used to calculate the proportion of days covered with medications, a typical measure of medication adherence. Using machine learning techniques, we will develop prediction models for future (2019-2021) C-MCIs based on medication adherence, patient demographics, comorbidities, and common laboratory tests (eg, lipid panel) from the previous year. Finally, key informant interviews (N=90) will explore facilitators of and barriers to medication adherence within the context of local SDOH., Results: Funding was obtained in early 2022. The University of Florida and CNO approved the institutional review board protocols and executed the data use agreements. Data extraction is in process. We expect to obtain results from aims 1 and 2 in 2024., Conclusions: Our findings will yield insights into improving medication adherence and C-MCIs among American Indian adults, consistent with CNO's State of the Nation's Health Report 2017 goal of reducing T2D and its complications., International Registered Report Identifier (irrid): PRR1-10.2196/39193., (©Lisa Scarton, Tarah Nelson, Yingwei Yao, Richard Segal, William T Donahoo, R Turner Goins, Ashley DeVaughan-Circles, Spero M Manson, Diana J Wilkie. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 24.10.2022.)

Background: Nonalcoholic steatohepatitis (NASH), advanced fibrosis, and subsequent cirrhosis and hepatocellular carcinoma are becoming the most common etiology for liver failure and liver transplantation; however, they can only be diagnosed at these potentially reversible stages with a liver biopsy, which is associated with various complications and high expenses. Knowing the difference between the more benign isolated steatosis and the more severe NASH and cirrhosis informs the physician regarding the need for more aggressive management., Objective: We intend to explore the feasibility of using machine learning methods for noninvasive diagnosis of NASH and advanced liver fibrosis and compare machine learning methods with existing quantitative risk scores., Methods: We conducted a retrospective analysis of clinical data from a cohort of 492 patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD), NASH, or advanced fibrosis. We systematically compared 5 widely used machine learning algorithms for the prediction of NAFLD, NASH, and fibrosis using 2 variable encoding strategies. Then, we compared the machine learning methods with 3 existing quantitative scores and identified the important features for prediction using the SHapley Additive exPlanations method., Results: The best machine learning method, gradient boosting (GB), achieved the best area under the curve scores of 0.9043, 0.8166, and 0.8360 for NAFLD, NASH, and advanced fibrosis, respectively. GB also outperformed 3 existing risk scores for fibrosis. Among the variables, alanine aminotransferase (ALT), triglyceride (TG), and BMI were the important risk factors for the prediction of NAFLD, whereas aspartate transaminase (AST), ALT, and TG were the important variables for the prediction of NASH, and AST, hyperglycemia (A 1c ), and high-density lipoprotein were the important variables for predicting advanced fibrosis., Conclusions: It is feasible to use machine learning methods for predicting NAFLD, NASH, and advanced fibrosis using routine clinical data, which potentially can be used to better identify patients who still need liver biopsy. Additionally, understanding the relative importance and differences in predictors could lead to improved understanding of the disease process as well as support for identifying novel treatment options., (©Yonghui Wu, Xi Yang, Heather L Morris, Matthew J Gurka, Elizabeth A Shenkman, Kenneth Cusi, Fernando Bril, William T Donahoo. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 06.06.2022.)

The position statement is issued by The Obesity Society in response to published literature, as well as inquiries made to the Society by patients, providers, Society members, policy makers, and others regarding the efficacy of vaccines in persons with obesity against SARS-CoV-2, the virus that causes COVID-19. The Obesity Society has critically evaluated data from published peer-reviewed literature and briefing documents from Emergency Use Authorization applications submitted by Pfizer-BioNTech, Moderna, and Johnson & Johnson. We conclude that these vaccines are highly efficacious, and their efficacy is not significantly different in people with and without obesity, based on scientific evidence available at the time of publication. The Obesity Society believes there is no definitive way to determine which of these three COVID-19 vaccines is "best" for any weight subpopulation (because of differences in the trial design and outcome measures in the phase 3 trials, elapsed time between doses, and regional differences in the presence of SARS-CoV-2 variants [e.g., South Africa B.1.351 in Johnson & Johnson trial]). All three trials have demonstrated high efficacy against COVID-19-associated hospitalization and death. Therefore, The Obesity Society encourages adults with obesity ≥18 years (≥16 years for Pfizer-BioNTech) to undergo vaccination with any one of the currently available vaccines authorized for emergency use by the US Food and Drug Administration as soon as they are able., (© 2021 The Obesity Society.)

Aims: This study aimed to compare cardiovascular benefits associated with the use of GLP-1RA versus SGLT2i as add-on therapies to metformin among adults with type 2 diabetes (T2D) with and without a history of cardiovascular complications, using real-world data., Methods: Using data from the IBM® MarketScan® Commercial Claims Databases, metformin users above 18years with T2D who initiated GLP-1RA or SGLT2i were identified. The study endpoints include MI, stroke, CHF, and a cardiovascular composite of these three outcomes. Cox proportional hazard regression models were used to compare the risks of cardiovascular endpoints while controlling for demographics and clinical characteristics., Results: We identified 13,006 adults with T2D who initiated a GLP-1RA or SGLT2i as an add-on therapy to metformin and followed for a maximum of 5years. No difference in the endpoints was observed between users of two drugs who did not have established cardiovascular disease at baseline. However, significantly lower CHF risks (HR: 0.47, 95% CI: 0.28-0.79) and cardiovascular composite (HR: 0.67, 95% CI: 0.47-0.97) were observed in SGLT2i users compared with GLP-1RA users, among individuals with established cardiovascular diseases., Conclusions: Results suggest greater cardioprotective benefit from SGLT2i compared to GLP-1RA when used for secondary prevention among adults with T2D., (Copyright © 2021 Elsevier Inc. All rights reserved.)

In this Perspective Statement from The Obesity Society, the Clinical Committee discusses the use of weight loss supplements in the United States and the lack of regulatory oversight and rigorous testing of their efficacy and safety. A number of products and services claiming to promote weight loss are directly marketed to individuals with obesity and those wanting to lose weight. These products are not regulated as "drugs" by the Federal Drug Administration but, rather, are treated as dietary supplements if ingredients are "generally regarded as safe," requiring little or no testing to show efficacy or safety. Health care providers should be aware of the lack of evidence and deficiencies in regulatory oversight of dietary supplements marketed for weight loss. Regulatory authorities should protect consumers by ensuring accurate and safe marketing claims and preventing promotion of unproven and potentially unsafe products and claims., (© 2021 The Obesity Society.)

We used electronic medical record (EMR) data in the National Patient-Centered Clinical Research Network (PCORnet) to characterize "real-world" prescription patterns of Type 2 diabetes (T2D) medications. We identified a retrospective cohort of 613,203 adult patients with T2D from 33 datamarts (median patient number: 12,711) from 2012 through 2017 using a validated computable phenotype. We characterized outpatient T2D prescriptions for each patient in the 90 days before and after cohort entry, as well as demographics, comorbidities, non-T2D prescriptions, and clinical and laboratory variables in the 730 days prior to cohort entry. Approximately half of the individuals in the cohort were females and 20% Black. Hypertension (60.3%) and hyperlipidemia (50.5%) were highly prevalent. Most patients were prescribed either a single T2D drug class (42.2%) or had no evidence of a T2D prescription in the EMR (42.4%). A smaller percentage was prescribed multiple T2D drug types (15.4%). Among patients prescribed a single T2D drug type, metformin was the most common (42.6%), followed by insulin (18.2%) and sulfonylureas (13.9%). Newer classes represented approximately 13% of single T2D drug type prescriptions (dipeptidyl peptidase-4 inhibitors [6.6%], glucagon-like peptide-1 receptor agonists [2.5%], thiazolidinediones [2.0%], and sodium-glucose cotransporter-2 inhibitors [1.6%]). Among patients prescribed multiple T2D drug types, the most common combination was metformin and sulfonylureas (63.5%). Metformin-based regimens were highly prevalent in PCORnet's T2D population, whereas newer agents were prescribed less frequently. PCORnet is a novel source for the potential conduct of observational studies among patients with T2D., (© 2020 The Authors. Pharmacology Research & Perspectives published by John Wiley & Sons Ltd, British Pharmacological Society and American Society for Pharmacology and Experimental Therapeutics.)

Background: The incidence of both type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in children and youth is increasing. However, the current approach for identifying pediatric diabetes and separating by type is costly, because it requires substantial manual efforts., Objective: The purpose of this study was to develop a computable phenotype for accurately and efficiently identifying diabetes and separating T1DM from T2DM in pediatric patients., Methods: This retrospective study utilized a data set from the University of Florida Health Integrated Data Repository to identify 300 patients aged 18 or younger with T1DM, T2DM, or that were healthy based on a developed computable phenotype. Three endocrinology residents/fellows manually reviewed medical records of all probable cases to validate diabetes status and type. This refined computable phenotype was then used to identify all cases of T1DM and T2DM in the OneFlorida Clinical Research Consortium., Results: A total of 295 electronic health records were manually reviewed; of these, 128 cases were found to have T1DM, 35 T2DM, and 132 no diagnosis. The positive predictive value was 94.7%, the sensitivity was 96.9%, specificity was 95.8%, and the negative predictive value was 97.6%. Overall, the computable phenotype was found to be an accurate and sensitive method to pinpoint pediatric patients with T1DM., Conclusions: We developed a computable phenotype for identifying T1DM correctly and efficiently. The computable phenotype that was developed will enable researchers to identify a population accurately and cost-effectively. As such, this will vastly improve the ease of identifying patients for future intervention studies., (©Heather Lynne Morris, William Troy Donahoo, Brittany Bruggeman, Chelsea Zimmerman, Paul Hiers, Victor W Zhong, Desmond Schatz. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 04.09.2020.)

Time-restricted feeding (TRF) is a type of intermittent fasting in which no calories are commonly consumed for approximately 12-18 hours on a daily basis. The health benefits of this eating pattern have been shown in overweight adults, with improvements in cardiometabolic risk factors as well as the preservation of lean mass during weight loss. Although TRF has been well studied in younger and middle-aged adults, few studies have evaluated the effects of TRF in older adults. Thus, the goal of this study was to evaluate older-adult perspectives regarding the real-world advantages, disadvantages, and challenges to adopting a TRF eating pattern among participants aged 65 and over. A four-week single-arm pre- and post-test design was used for this clinical pilot trial TRF intervention study. Participants were instructed to fast for approximately 16 h per day with the daily target range between 14 and 18 h. Participants were provided with the TRF protocol at a baseline visit, along with a pictorial guide that depicted food items and beverages that were allowed and not allowed during fasting windows to reinforce that calorie-containing items were to be avoided. The trial interventionist called each participant weekly to promote adherence, review the protocol, monitor for adverse events, and provide support and guidance for any challenges faced during the intervention. Participants were instructed to complete daily eating time logs by recording the times at which they first consumed calories and when they stopped consuming calories. At the end of the intervention, participants completed an exit interview and a study-specific Diet Satisfaction Survey (Table 1) to assess their satisfaction, feasibility, and overall experience with the study intervention. Of the 10 participants who commenced the study (mean age = 77.1 y; 6 women, 4 men), nine completed the entire protocol. Seven of the ten participants reported easy adjustment to a 16-hour fast and rated the difference from normal eating patterns as minimal. Eight participants reported no decrease in energy during fasting periods, with greater self-reported activity levels in yardwork and light exercise. Adverse events were rare, and included transient headaches, which dissipated with increased water intake, and dizziness in one participant, which subsided with a small snack. The findings of the current trial suggest that TRF is an eating approach that is well tolerated by most older adults. Six participants, however, did not fully understand the requirements of the fasting regimen, despite being provided with specific instructions and a pictorial guide at a baseline visit. This suggests that more instruction and/or participant contact is needed in the early stages of a TRF intervention to promote adherence.

Diabetes is a complex and multifactorial disease affecting more than 415 million people worldwide. Excess adiposity and modifiable lifestyle factors, such as unhealthy dietary patterns and physical inactivity, can play a significant role in the development of type 2 diabetes. Interventions that implement changes to lifestyle behaviors, in addition to pharmacological treatment, may attenuate the development and worsening of diabetes. This narrative review delineates how standard behavioral interventions (SBTs), based in "first wave" behavioral therapies and "second wave" cognitive behavioral therapies, serve as the foundation of diabetes treatment by supporting effective lifestyle changes, including improving adherence to healthful behaviors, medication, and self-monitoring regimens. Moreover, "third wave" "acceptance-based therapies" (ABTs), which integrate techniques from acceptance and commitment therapy, are proposed as a potential novel treatment option for diabetes management. Further research and long-term, randomized controlled trials will clarify the feasibility, acceptability, and effectiveness of ABT for improving glucose control via enhancing medication adherence and promoting effective lifestyle changes in people with diabetes.

Objective: This study examined the relationship between specific metabolic and vascular risk factors and cognition in adults with severe obesity., Methods: A total of 129 adults (with BMI ≥ 35 kg/m 2 ) underwent a baseline clinical evaluation and neuropsychological assessment. Regression analyses examined the relationship between cognition and medical factors (BMI, hemoglobin A1c, diabetes, hypertension, continuous positive airway pressure use, obstructive sleep apnea [OSA], and osteoarthritis)., Results: Diabetes was associated with deficits in overall cognitive performance and with deficits in the executive processing speed and verbal fluency domains. Hemoglobin A1c was inversely related to overall cognitive performance and deficits in the attention domain. Participants using continuous positive airway pressure to treat OSA had stronger learning and memory performance, whereas OSA was associated with reduced total learning. Elevated BMI together with diabetes diagnosis was associated with reduced verbal fluency and greater variability in sustained attention., Conclusions: Obesity-associated comorbidities most notably appeared to have a greater relative influence on cognitive performance than BMI itself in adults with severe obesity. This likely reflects the fact that a very elevated BMI was ubiquitous and thereby probably exerted a similar influence among all adults in the cohort. Accordingly, in the context of severe obesity, diabetes and other comorbidities may have greater sensitivity to cognitive deficits than BMI alone., (© 2019 The Obesity Society.)

A growing body of evidence indicates that time restricted feeding (TRF), a popular form of intermittent fasting, can activate similar biological pathways as caloric restriction, the only intervention consistently found to extend healthy lifespan in a variety of species. Thus, TRF may have the potential to also improve function in older adults. Given the challenges many individuals have in following calorie restriction regimens over long-time periods, evaluation of alternative approaches that may produce weight loss and improve function in overweight, older adults is important. Ten overweight, sedentary older adults (≥65 years) at risk for, or with mobility impairments, defined by slow gait speed (<1.0 m/s) participated in this trial. All participants received the intervention and were instructed to fast for approximately 16 h per day over the entire four-week intervention. Outcomes included changes in body weight, waist circumference, cognitive and physical function, health-related quality of life, and adverse events. Adherence levels were high (mean = 84%) based on days goal was met, and mean weight loss was 2.6 kg ( p < 0.01). Since body composition was not measured in this study, it is unclear if the observed weight loss was due to loss of fat mass, muscle mass, or the combination of fat and muscle mass. There were no significant changes in other outcomes; however, there were clinically meaningful changes in walking speed and improvements in quality of life, with few reported adverse events. The findings of this pilot study suggest that time restricted feeding is an acceptable and feasible eating pattern for overweight, sedentary older adults to follow.

Purpose: PCORnet, the National Patient-Centered Clinical Research Network, represents an innovative system for the conduct of observational and pragmatic studies. We describe the identification and validation of a retrospective cohort of patients with type 2 diabetes (T2DM) from four PCORnet sites., Methods: We adapted existing computable phenotypes (CP) for the identification of patients with T2DM and evaluated their performance across four PCORnet sites (2012-2016). Patients entered the cohort on the earliest date they met one of three CP categories: (CP1) coded T2DM diagnosis (ICD-9/ICD-10) and an antidiabetic prescription, (CP2) diagnosis and glycosylated hemoglobin (HbA1c) ≥6.5%, or (CP3) an antidiabetic prescription and HbA1c ≥6.5%. We required evidence of health care utilization in each of the 2 prior years for each patient, as we also developed an incident T2DM CP to identify the subset of patients without documentation of T2DM in the 365 days before t 0 . Among a systematic sample of patients, we calculated the positive predictive value (PPV) for the T2DM CP and incident-T2DM CP using electronic health record (EHR) review as reference., Results: The CP identified 50 657 patients with T2DM. The PPV of patients randomly selected for validation was 96.2% (n = 1572; CI:95.1-97.0) and was consistently high across sites. The PPV for the incident-T2DM CP was 5.8% (CI:4.5-7.5)., Conclusions: The T2DM CP accurately and efficiently identified patients with T2DM across multiple sites that participate in PCORnet, although the incident T2DM CP requires further study. PCORnet is a valuable data source for future epidemiological and comparative effectiveness research among patients with T2DM., (© 2019 John Wiley & Sons, Ltd.)

We characterized the prevalence of obesity among Florida children 2-19years old using electronic health records (EHRs). The obesity prevalence for 331,641 children was 16.9%. Obesity prevalence at 6-11years (19.5%) and 12-19years (18.9%) were approximately double the prevalence of obesity among children 2-5years (9.9%). The highest prevalence of severe obesity occurred in rural Florida (21.7%) and non-Hispanic children with multiple races had the highest obesity prevalence (21.1%) across all racial/ethnic groups. Our results highlight EHR as a low-cost alternative to estimate the prevalence of obesity and severe obesity in Florida children, both overall and within subpopulations., (Copyright © 2018 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.)

Purpose: Algorithms using information from electronic health records to identify adults with type 1 diabetes have not been well studied. Such algorithms would have applications in pharmacoepidemiology, drug safety research, clinical trials, surveillance, and quality improvement. Our main objectives were to determine the positive predictive value for identifying type 1 diabetes in adults using a published algorithm (developed by Klompas et al) and to compare it to a simple requirement that the majority of diabetes diagnosis codes be type 1., Methods: We applied the Klompas algorithm and the diagnosis code criterion to a cohort of 66 690 adult Kaiser Permanente Colorado members with diabetes. We reviewed 220 charts of those identified as having type 1 diabetes and calculated positive predictive values., Results: The Klompas algorithm identified 3286 (4.9% of 66 690) adults with diabetes as having type 1 diabetes. Based on chart reviews, the overall positive predictive value was 94.5%. The requirement that the majority of diabetes diagnosis codes be type 1 identified 3000 (4.5%) as having type 1 diabetes and had a positive predictive value of 96.4%. However, the algorithm criterion involving dispensing of urine acetone test strips performed poorly, with a positive predictive value of 20.0%., Conclusions: Data from electronic health records can be used to accurately identify adults with type 1 diabetes. When identifying adults with type 1 diabetes, we recommend either a modified version of the Klompas algorithm without the urine acetone test strips criterion or the requirement that the majority of diabetes diagnosis codes be type 1 codes., (Copyright © 2018 John Wiley & Sons, Ltd.)

Objective: Intermittent fasting (IF) is a term used to describe a variety of eating patterns in which no or few calories are consumed for time periods that can range from 12 hours to several days, on a recurring basis. This review is focused on the physiological responses of major organ systems, including the musculoskeletal system, to the onset of the metabolic switch: the point of negative energy balance at which liver glycogen stores are depleted and fatty acids are mobilized (typically beyond 12 hours after cessation of food intake)., Results and Conclusions: Emerging findings suggest that the metabolic switch from glucose to fatty acid-derived ketones represents an evolutionarily conserved trigger point that shifts metabolism from lipid/cholesterol synthesis and fat storage to mobilization of fat through fatty acid oxidation and fatty acid-derived ketones, which serve to preserve muscle mass and function. Thus, IF regimens that induce the metabolic switch have the potential to improve body composition in overweight individuals. Moreover, IF regimens also induce the coordinated activation of signaling pathways that optimize physiological function, enhance performance, and slow aging and disease processes. Future randomized controlled IF trials should use biomarkers of the metabolic switch (e.g., plasma ketone levels) as a measure of compliance and of the magnitude of negative energy balance during the fasting period., (© 2017 The Obesity Society.)

Background: Experience suggests that some physicians view obesity as a purely lifestyle condition rather than a chronic metabolic disease. Physicians may not be aware of the role of biological factors in causing weight regain after an initial weight loss., Methods: A questionnaire was administered at continuing medical education conferences, both primary care and obesity-specific. The questionnaire included items about biological and behavioral factors that predispose to weight regain and general items about treatment of obesity. The sample was separated into primary care physicians (PCPs) and physicians preparing for the obesity medicine (OMs) exam., Results: Among all respondents, behavioral factors were given higher importance ratings, relative to biological factors in causing weight regain. Respondents rated behaviour modification as more effective, relative to medications or surgery to treat obesity. OMs gave higher importance ratings to biological factors, relative to PCPs. OMs also gave higher effectiveness ratings for medications and surgery, relative to PCPs. However, even OMs gave higher effectiveness ratings for behaviour modification, relative to medications or surgery. Respondents who reported a belief in the role of behavioral factors rated lifestyle modification as more effective. Respondents who reported a belief in both behavioral and biological factors rated medications as more effective., Conclusions: Physicians rate biological factors as less important, relative to behavioral factors in causing weight regain. Physicians rate medications and surgery as less effective, relative to lifestyle modification alone. Belief in the importance of behavioral factors correlated with a higher effectiveness rating for lifestyle modification. A better understanding of the biological basis for weight regain may help to increase comfort with the use of biological treatments for obesity.

Introduction: Pain management can be challenging following bariatric surgery, and patients with obesity tend to increase opioid use after undergoing surgery. This report quantifies marijuana (MJ) use and its relationship to pain and other surgery-related outcomes in a population from a state that has legalized MJ., Methods: Data were collected for consecutive patients undergoing weight reduction surgeries between May 1, 2014 and July 31, 2015. Demographics, preoperative comorbidities, medications, and perioperative opioid use were analyzed. The primary outcome evaluated was inpatient opioid pain medication use quantified using natural log morphine equivalents. Secondary outcomes included percentage of total body weight loss after three months, postoperative complications, and changes in medical comorbidities., Results: A total of 434 patients, among whom 36 (8.3%) reported MJ use, comprised the study population. Perioperative opioid requirements were significantly higher in the MJ-user group (natural log morphine equivalents of 3.92 vs 3.52, p = 0.0015) despite lower subjective pain scores (3.70 vs 4.24, p = 0.07). MJ use did not affect percentage of 90-day total body weight loss, development of postoperative complications, or improvement in medical comorbidities., Conclusion: Perioperative opioid use was significantly higher in the MJ-user group despite lower subjective pain scores. The difference in opioid requirements suggests an interaction between MJ use and opioid tolerance or pain threshold. The percentage of total body weight loss, improvement in medical comorbidity, and incidence of postoperative complications at 90-day follow-up were not affected by MJ use in this cohort analysis.