Develop and validate a computable phenotype for the identification of Alzheimer's disease patients using electronic health record data.

INTRODUCTION: Alzheimer's disease (AD) is often misclassified in electronic health records (EHRs) when relying solely on diagnosis codes. This study aimed to develop a more accurate, computable phenotype (CP) for identifying AD patients using structured and unstructured EHR data. METHODS: We used EHRs from the University of Florida Health (UFHealth) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UTHealth) and the University of Minnesota (UMN). RESULTS: Our best-performing CP was "patient has at least 2 AD diagnoses and AD-related keywords in AD encounters," with an F1-score of 0.817 at UF, 0.961 at UTHealth, and 0.623 at UMN, respectively. DISCUSSION: We developed and validated rule-based CPs for AD identification with good performance, which will be crucial for studies that aim to use real-world data like EHRs. Highlights: Developed a computable phenotype (CP) to identify Alzheimer's disease (AD) patients using EHR data.Utilized both structured and unstructured EHR data to enhance CP accuracy.Achieved a high F1-score of 0.817 at UFHealth, and 0.961 and 0.623 at UTHealth and UMN.Validated the CP across different demographics, ensuring robustness and fairness.

Glucagon-Like Peptide-1 Receptor Agonists and Risk for Suicidal Ideation and Behaviors in U.S. Older Adults With Type 2 Diabetes : A Target Trial Emulation Study.

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.

Heterogeneous treatment effects of sodium-glucose cotransporter 2 inhibitors on risk of dementia in people with type 2 diabetes: A population-based cohort study.

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.

Sodium-glucose cotransporter-2 inhibitors and incidence of atrial fibrillation in older adults with type 2 diabetes: a retrospective cohort analysis.

Objectives: To investigate the risk of atrial fibrillation (AF) with sodium-glucose cotransporter-2 inhibitors (SGLT2is) compared to dipeptidyl peptidase-4 inhibitor (DPP4i) use in older US adults and across diverse subgroups. Methods: We conducted a retrospective cohort analysis using claims data from 15% random samples of Medicare fee-for-service beneficiaries. Patients were adults with type 2 diabetes (T2D), no preexisting AF, and were newly initiated on SGLT2i or DPP4i. The outcome was the first incident AF. Inverse probability treatment weighting (IPTW) was used to balance the baseline covariates between the treatment groups including sociodemographics, comorbidities, and co-medications. Cox regression models were used to assess the effect of SGLT2i compared to DPP4i on incident AF. Results: Of the 97,436 eligible individuals (mean age 71.2 ± 9.8 years, 54.6% women), 1.01% (n = 983) had incident AF over a median follow-up of 361 days. The adjusted incidence rate was 8.39 (95% CI: 6.67-9.99) and 11.70 (95% CI: 10.9-12.55) per 1,000 person-years in the SGLT2i and DPP4i groups, respectively. SGLT2is were associated with a significantly lower risk of incident AF (HR 0.73; 95% CI, 0.57 to 0.91; p = 0.01) than DPP4is. The risk reduction of incident AF was significant in non-Hispanic White individuals and subgroups with existing atherosclerotic cardiovascular diseases and chronic kidney disease. Conclusion: Compared to the use of DPP4i, that of SGLT2i was associated with a lower risk of AF in patients with T2D. Our findings contribute to the real-world evidence regarding the effectiveness of SGLT2i in preventing AF and support a tailored therapeutic approach to optimize treatment selection based on individual characteristics.

Association between low cognitive performance and diabetes-related health indicators across racial and ethnic groups in adults with diabetes.

AIM: To examine the associations between low cognitive performance (LCP) and diabetes-related health indicators (including body mass index [BMI], HbA1c, systolic blood pressure [SBP], low-density lipoprotein [LDL] and self-reported poor physical health) and whether these associations vary across racial/ethnic subgroups. METHODS: We identified adults aged 60 years or older with self-reported diabetes from the 2011-2014 National Health and Nutrition Examination Survey. Individuals with cognitive test scores in the lowest quartile were defined as having LCP. We used regression models to measure the associations of LCP with diabetes-related biometrics (BMI, HbA1c, SBP and LDL); and self-reported poor physical health. Moreover, we explored potential variations in these associations across racial/ethnic subgroups. RESULTS: Of 873 (261 with LCP) adults with diabetes, LCP was associated with higher HbA1c, SBP and LDL (adjusted difference: 0.41%, 5.01 mmHg and 5.08 mg/dL, respectively; P < .05), and greater odds of reporting poor physical health (adjusted odds ratio: 1.59, P < .05). The association between LCP and HbA1c was consistent across racial/ethnic groups, and notably pronounced in Hispanic and Other. BMI worsened with LCP, except for non-Hispanic Black. Excluding the Other group, elevated SBP was observed in people with LCP, with Hispanic showing the most significant association. LDL levels were elevated with LCP for Hispanic and Other. Physical health worsened with LCP for both non-Hispanic Black and Hispanic. CONCLUSIONS: We quantified the association between LCP and diabetes-related health indicators. These associations were more pronounced in Hispanic and Other racial/ethnic groups.

COVID-19 pandemic and trends in clinical outcomes and medication use for patients with established atrial fibrillation: A nationwide analysis of claims data.

Study objective: The COVID-19 pandemic disrupted multiple aspects of the health care system, including the diagnosis and control of chronic conditions. This study aimed to quantify pandemic-related changes in the rates of clinical events among patients with atrial fibrillation (AF). Design/setting/participants: In this retrospective cohort study, we identified individuals with established AF at any time before 2019 using de-identified Optum's Clinformatics® Data Mart, and followed them from 3/18/2019 to death, or disenrollment, or the end of the study (09/30/2021). Main outcome: Rates of clinical event, including all-cause hospitalization, ischemic stroke, and bleeding. We constructed interrupted time series to test changes in outcomes after the onset of the COVID-19 pandemic (3/11/2020, date of pandemic declaration). We then identified the first month after the start of the pandemic in which outcomes returned to pre-pandemic levels. Results: A total of 561,758 patients, with a mean age of 77 ± 9.9 years, were included in the study. The monthly incidence rate of all-cause hospitalization decreased from 2.8 % in the period immediately before the pandemic declaration to 1.7 % in the period immediately after, with p-value for level change<0.001. The rate of new ischemic stroke diagnoses decreased from 0.28 % in the period immediately before pandemic declaration to 0.20 % in the period immediately after, and the rate of major bleeding diagnoses from 0.81 % to 0.59 %, both p-values for level change<0.01. The incidence rate of ischemic stroke and bleeding events returned to pre-pandemic levels in October and November 2020, respectively. Conclusions: The COVID-19 pandemic was associated with a decrease in health care visits for ischemic stroke and bleeding in a nationwide cohort of patients with established AF.

Racial and Ethnic Inequities in Spatial Access to Pharmacies: A Geographic Information System Analysis.

BACKGROUND: Pharmacy accessibility is crucial for equity in healthcare access because community pharmacists may reach individuals who do not have access to other healthcare providers. OBJECTIVE: To determine whether spatial access to pharmacies differs among racial/ethnic groups across the rural-urban continuum. METHODS: We obtained a 30% random sample of the Research Triangle Institute (RTI) synthetic population, sampled at the census block level. For each individual, we defined optimal pharmacy access as having a driving distance ≤2 miles to the closest pharmacy in urban counties, ≤5 miles in suburban counties, and ≤10 miles in rural counties. We used a logistic regression model to measure the association between race/ethnicity and pharmacy access, while controlling for racial/ethnic composition of the census tract, Area Deprivation Index, income, age, gender, and US region. The model included an interaction between race/ethnicity and urbanicity to evaluate whether racial/ethnic inequities differed across the rural-urban continuum. RESULTS: The sample included 90,749,446 individuals of whom 80.6% had optimal pharmacy access. Racial/ethnic inequities in pharmacy access differed across the rural-urban continuum (p-value for interaction= <0.0001). In rural areas, Black (OR 0.87; 95%CI 0.86-0.87), Hispanic (OR 0.80; 95%CI 0.79-0.80), and Indigenous (OR 0.47; 95%CI 0.47-0.48) individuals had lower odds of optimal pharmacy access, compared to White individuals. Hispanic (OR 0.96; 95%CI 0.96-0.97) and Indigenous individuals (OR 0.75; 95%CI 0.75-0.76) had lower odds of optimal pharmacy access compared to White individuals in suburban areas. In Western states, Asian had lower odds of optimal pharmacy access in suburban (OR 0.88; 95%CI 0.86-0.90) and rural areas (OR 0.91; 95%CI 0.87-0.95) compared to White Individuals. CONCLUSIONS: Racial/ethnic inequities in spatial access to community pharmacies vary between urban and rural communities. Underrepresented racial/ethnic groups have significantly lower pharmacy access in rural and some suburban areas, but not in urban areas.

Comparative Genitourinary Safety of In-class Sodium-Glucose Cotransporter-2 Inhibitors among Patients with Heart Failure with Preserved Ejection Fraction: A Cohort Study.

PURPOSE: The American Heart Association recommended sodium-glucose cotransporter-2 inhibitors (SGLT2i) for the management of heart failure with preserved ejection fraction (HFpEF). However, little is known about their real-world in-class comparative safety in patients with HFpEF. We aimed to assess the comparative safety of SGLT2i in the risk of urinary tract infection (UTI) or genital infection separately or as a composite outcome among patients with HFpEF. METHODS: This cohort study using MarketScan® Commercial and Medicare supplemental databases (2012-2020) included patients aged ≥ 18 years with a diagnosis of HFpEF who initiated SGLT2i therapy. Three pairwise comparison groups were established: cohort 1, dapagliflozin versus canagliflozin; cohort 2, empagliflozin versus canagliflozin; and cohort 3, dapagliflozin versus empagliflozin. After stabilized inverse probability treatment weighting, Cox proportional hazards regression was used to compare the risk of UTI or genital infection separately or as a composite outcome in each cohort. RESULTS: The risk of the composite outcome did not significantly differ between canagliflozin and dapagliflozin (adjusted hazard ratio [aHR] 0.64; 95% confidence interval [CI] 0.36-1.14) or between empagliflozin and canagliflozin (aHR 1.25; 95% CI 0.77-2.05). Similarly, there was no evidence of difference between dapagliflozin and empagliflozin in this risk (aHR 0.76; 95% CI 0.48-1.21). The results of analyses separately assessing UTI or genital infection were similar. CONCLUSIONS: There was no significant difference in the risk of UTI or genital infection among patients with HFpEF who initiated canagliflozin, dapagliflozin, or empagliflozin.

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are used for the management of heart failure with preserved ejection fraction (HFpEF). It is important to assess their comparative risk of urinary tract infection (UTI) or genital infection among patients with HFpEF. We compared patients with HFpEF using SGLT2i in three pairwise groups: cohort 1, dapagliflozin versus canagliflozin; cohort 2, empagliflozin versus canagliflozin; and cohort 3, dapagliflozin versus empagliflozin. We found that there was no significant difference in the risk of genitourinary infections including UTI or genital infections among dapagliflozin, empagliflozin, and canagliflozin.

Racial/Ethnic Disparities in Use of Angiotensin II Receptor Type 2/4 Stimulatory Vs. Inhibitory Antihypertensive Among Hypertensive Adults in the USA.

OBJECTIVES: Studies showed angiotensin II type 2 receptor/angiotensin II type 4 receptor (AT2R/AT4R) stimulatory antihypertensive was associated with a lower risk of dementia and cognitive impairment compared to the inhibitory one. This study aimed to identify the racial and ethnic differences in using these agents among the USA adults with hypertension. METHODS: A cross-sectional study was conducted using data from the Medical Expenditure Panel Survey (MEPS, 2016-2019). Individuals with a diagnosis of hypertension or self-reported hypertension and without dementia or Alzheimer's disease diagnosis were included in the analysis. We applied two multivariable logistic regressions to compare racial/ethnic differences in AT2R/AT4R stimulatory antihypertensive use and AT2R/AT4R inhibitory antihypertensive use, adjusting for covariates. RESULTS: Twenty-four thousand five hundred eighty-one individuals with hypertension and without dementia or Alzheimer's disease were identified. Among non-Hispanic Whites, 72.39% were using AT2R/AT4R inhibitory antihypertensive agents, vs. 66.97% using AT2R/AT4R stimulatory antihypertensive agents. In contrast, both non-Hispanic Black and Asian Americans were using more AT2R/AT4R stimulatory agents than inhibitory ones (16.40% vs. 12.16% and 4.79% vs. 3.43%, respectively). Compared to non-Hispanic White, non-Hispanic Black (OR 1.980, 95% CI 1.839-2.132) and non-Hispanic Asian Americans (OR 1.545, 95% CI 1.356-1.761) were significantly associated with higher odds of prescribing AT2R/AT4R stimulatory agents, while Hispanics (OR 0.744, 95% CI 0.685-0.808) were associated with lower odds of prescribing AT2R/AT4R inhibitory agents compared to non-Hispanic Whites. CONCLUSIONS: The results showed that the high-dementia risk populations like non-Hispanic Black and Asian American races are proportionally prescribed with higher use of low-dementia risk antihypertensive agents, compared to non-Hispanic Whites.

A scoping review of fair machine learning techniques when using real-world data.

OBJECTIVE: The integration of artificial intelligence (AI) and machine learning (ML) in health care to aid clinical decisions is widespread. However, as AI and ML take important roles in health care, there are concerns about AI and ML associated fairness and bias. That is, an AI tool may have a disparate impact, with its benefits and drawbacks unevenly distributed across societal strata and subpopulations, potentially exacerbating existing health inequities. Thus, the objectives of this scoping review were to summarize existing literature and identify gaps in the topic of tackling algorithmic bias and optimizing fairness in AI/ML models using real-world data (RWD) in health care domains. METHODS: We conducted a thorough review of techniques for assessing and optimizing AI/ML model fairness in health care when using RWD in health care domains. The focus lies on appraising different quantification metrics for accessing fairness, publicly accessible datasets for ML fairness research, and bias mitigation approaches. RESULTS: We identified 11 papers that are focused on optimizing model fairness in health care applications. The current research on mitigating bias issues in RWD is limited, both in terms of disease variety and health care applications, as well as the accessibility of public datasets for ML fairness research. Existing studies often indicate positive outcomes when using pre-processing techniques to address algorithmic bias. There remain unresolved questions within the field that require further research, which includes pinpointing the root causes of bias in ML models, broadening fairness research in AI/ML with the use of RWD and exploring its implications in healthcare settings, and evaluating and addressing bias in multi-modal data. CONCLUSION: This paper provides useful reference material and insights to researchers regarding AI/ML fairness in real-world health care data and reveals the gaps in the field. Fair AI/ML in health care is a burgeoning field that requires a heightened research focus to cover diverse applications and different types of RWD.

Comparative effectiveness of sacubitril/valsartan versus angiotensin receptor blockers in patients with heart failure with preserved ejection fraction: A real-world study.

PURPOSE: Sacubitril/valsartan (SAC/VAL) or angiotensin receptor blockers (ARBs) are recommended therapy for heart failure with preserved ejection fraction (HFpEF), but little is known about their real-world comparative effectiveness among patients with HFpEF. The objective of this study was to determine the comparative effectiveness of SAC/VAL vs ARBs in preventing HF-related hospitalization or all-cause hospitalization among patients with HFpEF. METHODS: We conducted a cohort study using IBM MarketScan commercial and Medicare supplemental databases to identify patients aged 18 years or older with a diagnosis of HFpEF and initiation of SAC/VAL (2015-2020) or ARB (2009-2014) therapy. The index date was the date of the first SAC/VAL or ARB prescription fill. After propensity score (PS) matching with a ratio of 1 up to 3, Cox proportional hazards regression was used with robust variance estimators to compare the risks of HF-related hospitalization and all-cause hospitalization between the 2 therapies. Several subgroup and sensitivity analyses were conducted to check the robustness of the main analysis. RESULTS: After PS matching, 2,520 patients (846 receiving SAC/VAL and 1,674 receiving an ARB) were included in the final analyses. After controlling for covariates, there was no difference in the risk of HF-related hospitalization between SAC/VAL and ARB recipients (adjusted hazard ratio [aHR], 1.33; 95% confidence interval [CI], 0.99-1.77). There was also no difference in the risk of all-cause hospitalization between SAC/VAL and ARB recipients (aHR, 1.06; 95% CI, 0.91-1.24). CONCLUSION: Among individuals with private or Medicare Advantage insurance plans, there was no significant difference in the risk of HF-related hospitalization or all-cause hospitalization between adults with HFpEF who received SAC/VAL and those who received ARB therapy.

Develop and Validate a Computable Phenotype for the Identification of Alzheimer's Disease Patients Using Electronic Health Record Data.

INTRODUCTION: Alzheimer's Disease (AD) are often misclassified in electronic health records (EHRs) when relying solely on diagnostic codes. This study aims to develop a more accurate, computable phenotype (CP) for identifying AD patients by using both structured and unstructured EHR data. METHODS: We used EHRs from the University of Florida Health (UF Health) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UT Health) and the University of Minnesota (UMN). RESULTS: Our best-performing CP is " patient has at least 2 AD diagnoses and AD-related keywords " with an F1-score of 0.817 at UF, and 0.961 and 0.623 at UT Health and UMN, respectively. DISCUSSION: We developed and validated rule-based CPs for AD identification with good performance, crucial for studies that aim to use real-world data like EHRs.

Geographic variation and racial disparities in adoption of newer glucose-lowering drugs with cardiovascular benefits among US Medicare beneficiaries with type 2 diabetes.

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.

Medicare Part D Coverage of Anti-obesity Medications: a Call for Forward-Looking Policy Reform.

When the Medicare Part D benefit was constructed, drugs for weight loss were explicitly excluded from coverage, as the limited effectiveness and unfavorable safety profile of medications available at the time failed to justify coverage of drugs perceived to be used for cosmetic purposes. In recent years, drugs activating the glucagon-like peptide-1 receptor (GLP-1R) pathway have proved to achieve significant reductions in body weight with a favorable safety profile. The effectiveness of GLP-1R agonists in reducing weight and improving the metabolic profile warrants the reconsideration of the historical exclusion of weight loss drugs from Part D coverage. In this perspective, we outline policy options to enable Part D coverage of GLP-1R agonists. These include legislative change through the passage of the Treat and Reduce Obesity Act and evaluation of coverage policies under the waiver authority of the Center for Medicare and Medicaid Innovation.

5-Year simulation of diabetes-related complications in people treated with tirzepatide or semaglutide versus insulin glargine.

AIM: This study compared the 5-year incidence rate of macrovascular and microvascular complications for tirzepatide, semaglutide and insulin glargine in individuals with type 2 diabetes, using the Building, Relating, Assessing, and Validating Outcomes (BRAVO) diabetes simulation model. RESEARCH DESIGN AND METHODS: This study was a 5-year SURPASS-2 trial extrapolation, with an insulin glargine arm added as an additional comparator. The 1-year treatment effects of tirzepatide (5, 10 or 15 mg), semaglutide (1 mg) and insulin glargine on glycated haemoglobin, systolic blood pressure, low-density lipoprotein and body weights were obtained from the SUSTAIN-4 and SURPASS-2 trials. We used the BRAVO model to predict 5-year complications for each study arm under two scenarios: the 1-year treatment effects persisted (optimistic) or diminished to none in 5 years (conservative). RESULTS: When compared with insulin glargine, we projected a 5-year risk reduction in cardiovascular adverse events [rate ratio (RR) 0.64, 95% confidence interval (CI) 0.61-0.67] and microvascular composite (RR 0.67, 95% CI 0.64-0.70) with 15 mg tirzepatide, and 5-year risk reduction in cardiovascular adverse events (RR 0.75, 95% CI 0.72-0.79) and microvascular composite (RR 0.79, 95% CI 0.76-0.82) with semaglutide (1 mg) under an optimistic scenario. Lower doses of tirzepatide also had similar, albeit smaller benefits. Treatment effects for tirzepatide and semaglutide were smaller but still significantly higher than insulin glargine under a conservative scenario. The 5-year risk reduction in diabetes-related complication events and mortality for the 15 mg tirzepatide compared with insulin glargine ranged from 49% to 10% under an optimistic scenario, which was reduced by 17%-33% when a conservative scenario was assumed. CONCLUSION: With the use of the BRAVO diabetes model, tirzepatide and semaglutide exhibited potential to reduce the risk of macrovascular and microvascular complications among individuals with type 2 diabetes, compared with insulin glargine in a 5-year window. Based on the current modelling assumptions, tirzepatide (15 mg) may potentially outperform semaglutide (1 mg). While the BRAVO model offered insights, the long-term cardiovascular benefit of tirzepatide should be further validated in a prospective clinical trial.

Heterogeneous treatment effects of metformin on risk of dementia in patients with type 2 diabetes: A longitudinal observational study.

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.

Incremental burden on health-related quality of life, health service utilization and direct medical expenditures associated with cognitive impairment among non-institutionalized people with diabetes aged 65 years and older.

AIMS: To quantify the incremental health and economic burden associated with cognitive impairment (CI) among non-institutionalized people with diabetes ≥65 years in the United States. MATERIALS AND METHODS: Using 2016-2019 Medical Expenditure Panel Surveys data, we identified participants ≥65 years with diabetes. We used propensity score weighting to quantify the CI-associated incremental burden on health-related quality of life measured by the 12-item Short Form Survey (SF-12), including the mental component summary score, physical component summary score and health utility. We also compared the annual health service utilization and expenditures on ambulatory visits, prescriptions, home care, emergency room (ER), hospitalizations and total annual direct medical expenditures. RESULTS: We included 5094 adults aged ≥65 with diabetes, of whom 804 had CI. After propensity score weighting, CI was associated with a lower mental component summary score (-8.4, p < .001), physical component summary score (-5.2, p < .001) and health utility (-0.12, p < .001). The CI group had more ambulatory visits (+4.4, p = .004) and prescriptions (+9.9, p < .001), with higher probabilities of having home care (+11.3%, p < .001) and ER visits (+8.2%, p = .001). People with CI spent $5441 (p < .001) more annually, $2039 (p = .002) more on prescriptions, $2695 (p < .001) more on home care and $118 (p < .001) more on ER visits. There is no statistically significant difference in the utilization and expenditure of hospitalizations. CONCLUSION: CI was associated with worse health-related quality of life, higher health service utilization and expenditures. Our findings can be used to monitor the health and economic burden of CI in non-institutionalized older persons with diabetes.

COVID-19 pandemic and initiation of treatment for atrial fibrillation: a nationwide analysis of claims data.

BACKGROUND: The COVID-19 pandemic profoundly disrupted the delivery of medical care. It remains unclear whether individuals diagnosed with new onset disease during the pandemic were less likely to initiate treatments after diagnosis. We sought to evaluate changes in the treatment initiation of patients newly diagnosed with atrial fibrillation (AF) after the onset of the COVID-19 pandemic. METHODS: In this retrospective cohort study, we identified individuals with incident AF from 01/01/2016-09/30/2021 using Optum's de-identified Clinformatics® Data Mart Database. The primary outcome was initiation of oral anticoagulation (OAC) within 30 days of AF diagnosis. Secondary outcomes included initiation of OAC within 180 days of diagnosis, initiation of warfarin, direct oral anticoagulants (DOACs), rhythm control medications and electrical cardioversion within 30 days of diagnosis. We constructed interrupted time series analyses to examine changes in the outcomes following the onset of the pandemic. RESULTS: A total of 573,524 patients (age 73.0 ± 10.9 years) were included in the study. There were no significant changes in the initiation of OAC, DOAC, and rhythm control medications associated with the onset of the pandemic. There was a significant decrease in initiation of electrical cardioversion associated with the onset of the pandemic. The rate of electronic cardioversion within 30 days of diagnosis decreased by 4.9% per 1,000 patients after the onset of the pandemic and decreased by about 35% in April 2020, compared to April 2019, from 5.53% to 3.58%. CONCLUSION: The COVID-19 pandemic did not affect the OAC initiation within 30 days of AF diagnosis but was associated with a decline in the provision of procedures for patients newly diagnosed with AF.

Association between first-line antidepressant use and risk of dementia in older adults: a retrospective cohort study.

BACKGROUND: Prior studies suggested that antidepressant use is associated with an increased risk of dementia compared to no use, which is subject to confounding by indication. We aimed to compare the dementia risk among older adults with depression receiving first-line antidepressants (i.e., SSRI/SNRI) versus psychotherapy, which is also considered the first-line therapy for depression. METHODS: This retrospective cohort study was conducted using the US Medical Expenditure Panel Survey from 2010 to 2019. We included adults aged ≥ 50 years diagnosed with depression who initiated SSRI/SNRI or psychotherapy. We excluded patients with a dementia diagnosis before the first record of SSRI/SNRI use or psychotherapy. The exposure was the patient's receipt of SSRI/SNRI (identified from self-report questionnaires) or psychotherapy (identified from the Outpatient Visits or Office-Based Medical Provider Visits files). The outcome was a new diagnosis of dementia within 2 years (i.e., survey panel period) identified using ICD-9/ICD-10 codes from the Medical Conditions file. Using a multivariable logistic regression model, we reported adjusted odds ratios (aORs) with 95% confidence intervals (CIs). We also conducted subgroup analyses by patient sex, age group, race/ethnicity, severity of depression, combined use of other non-SSRI/SNRI antidepressants, and presence of underlying cognitive impairment. RESULTS: Among 2,710 eligible patients (mean age = 61 ± 8, female = 69%, White = 84%), 89% used SSRIs/SNRIs, and 11% received psychotherapy. The SSRI/SNRI users had a higher crude incidence of dementia than the psychotherapy group (16.4% vs. 11.8%), with an aOR of 1.36 (95% CI = 1.06-1.74). Subgroup analyses yielded similar findings as the main analyses, except no significant association for patients who were aged < 65 years (1.23, 95% CI = 0.93-1.62), male (1.34, 95% CI = 0.95-1.90), Black (0.76, 95% CI = 0.48-1.19), had a higher PHQ-2 (1.39, 95% CI = 0.90-2.15), and had underlying cognitive impairment (1.06, 95% CI = 0.80-1.42). CONCLUSIONS: Our findings suggested that older adults with depression receiving SSRIs/SNRIs were associated with an increased dementia risk compared to those receiving psychotherapy.

A Fair Individualized Polysocial Risk Score for Identifying Increased Social Risk in Type 2 Diabetes.

Background: Racial and ethnic minority groups and individuals facing social disadvantages, which often stem from their social determinants of health (SDoH), bear a disproportionate burden of type 2 diabetes (T2D) and its complications. It is crucial to implement effective social risk management strategies at the point of care. Objective: To develop an electronic health records (EHR)-based machine learning (ML) analytical pipeline to address unmet social needs associated with hospitalization risk in patients with T2D. Methods: We identified real-world patients with T2D from the EHR data from University of Florida (UF) Health Integrated Data Repository (IDR), incorporating both contextual SDoH (e.g., neighborhood deprivation) and individual-level SDoH (e.g., housing instability). The 2015-2020 data were used for training and validation and 2021-2022 data for independent testing. We developed a machine learning analytic pipeline, namely individualized polysocial risk score (iPsRS), to identify high social risk associated with hospitalizations in T2D patients, along with explainable AI (XAI) and fairness optimization. Results: The study cohort included 10,192 real-world patients with T2D, with a mean age of 59 years and 58% female. Of the cohort, 50% were non-Hispanic White, 39% were non-Hispanic Black, 6% were Hispanic, and 5% were other races/ethnicities. Our iPsRS, including both contextual and individual-level SDoH as input factors, achieved a C statistic of 0.72 in predicting 1-year hospitalization after fairness optimization across racial and ethnic groups. The iPsRS showed excellent utility for capturing individuals at high hospitalization risk because of SDoH, that is, the actual 1-year hospitalization rate in the top 5% of iPsRS was 28.1%, ~13 times as high as the bottom decile (2.2% for 1-year hospitalization rate). Conclusion: Our ML pipeline iPsRS can fairly and accurately screen for patients who have increased social risk leading to hospitalization in real word patients with T2D.