Nursing home (NH) residents are an important population for pharmacoepidemiologic research due to their prevalence of multimorbidity and polypharmacy. Medicare claims are commonly used to study medication use in this population, but medications dispensed during hospitalizations or post-acute care are unobservable due to bundled payment structures. We developed algorithms to identify NH days when medication dispensings can be observed in claims. Using a cohort of NH residents in the United States from 2013 to 2020, we linked Medicare fee-for-service (FFS) claims with Minimum Data Set clinical assessments. NH days were classified as "observable medication use time" if residents were enrolled in Medicare parts A, B, and D were not receiving post-acute care and were not hospitalized. Among 12.3 million NH residents and 2.7 billion NH days, 1.1 billion days (72.4% of Medicare-enrolled days and 39.6% of all NH days) were identified as observable medication use time. Within the first 100 days of NH admission, 27.3% of days were medication-observable, increasing to 89.4% after 100 days. On average, we identified 68% more person-time, and 51% more residents, compared to standard 100-day definitions for "long-stay" NH residents. Our algorithms enhance researchers' ability to measure medication exposure time, improving the validity of pharmacoepidemiologic studies.

Background: Antibiotic allergy evaluation is an important antibiotic stewardship intervention, but is less commonly integrated into inpatient oncology care. Our objective was to evaluate the acceptability and feasibility of a pharmacist-driven penicillin allergy delabeling intervention for patients with hematologic malignancy (HM). Methods: We conducted a cross-sectional survey of physicians and advanced practice providers (APPs) who care for patients with HM at the Hospital of the University of Pennsylvania. The survey was administered from March 2025 to September 2025 in preparation for a planned Allergy Delabeling in Antibiotic Stewardship (RENEW) intervention. The survey included questions on current allergy evaluation practices, the perceived safety of RENEW and validated acceptability of intervention measure (AIM) and feasibility of intervention measure (FIM). AIM and FIM consist of 4 items scored 1-5 and is reported as a mean total score (5-20), with higher scores indicating greater acceptability and feasibility. Data were analyzed using descriptive statistics. Result: Of 70 eligible prescribers, 27 (38.6%) completed the survey: 21 (77.7%) physicians and 6 (22.2%) APPs. The majority (20, 74.1%) reported assessing documented antibiotic allergies of HM patients on admission and at the time an antibiotic is required (25, 92.6%). Nineteen (70.4%) respondents were comfortable modifying a documented antibiotic allergy in the medical record based on their assessment, while just under half (13, 48.1%) were comfortable deleting the allergy in the record based on their assessment. Nineteen (70.4%) respondents felt that penicillin skin testing was safe in patients with HM while 8 (29.6%) were not sure. Over half (14, 51.9%) were unsure if it is safe to evaluate penicillin allergy using an oral challenge based on clinical history without a skin test. The majority (22, 81.5%) said they would be comfortable having a patient’s antibiotic allergy removed from the medical record following negative allergy testing in the RENEW intervention. Compared to other patient safety initiatives, 24 (88.9%) believed evaluating documented antibiotic allergies is important or very important. Mean totals (SD; range) for acceptability and feasibility of the RENEW intervention were AIM, 17.2 (3.5; 8-20) and FIM, 17.7 (3.1; 8-20). Conclusion: Although the low response rate may limit generalizability, the majority of inpatient oncology clinicians perceived that a penicillin allergy delabeling intervention for patients with HM was acceptable and feasible to implement. Overall, clinicians believed that evaluating antibiotic allergy labels in patients with HM is an important and safe initiative, yet there was some uncertainty regarding the safety of a direct oral challenge.

The cardiovascular risks of exogenous testosterone have been a subject of controversy. In this study, our objective was to examine the association between testosterone (versus glaucoma treatments as an active comparator, with no assumed effect) and the new onset of cardiovascular, cerebrovascular and thromboembolic adverse events, in a US commercial insurance database. Data were analyzed by three complementary designs: inverse propensity score weighting (IPSW), calendar time instrumental variable and instrumented difference-in-differences. Results of these analyses suggest that there is no difference between testosterone and glaucoma treatments regarding the risk of the composite primary endpoint of acute myocardial infarction, ischemic stroke and sudden cardiac arrest/ventricular arrhythmia. In contrast, IPSW analysis identified a negative association between testosterone and the secondary endpoint of venous thromboembolism. However, this association was attenuated towards the null in the calendar time instrumental variable and difference-in-differences analysis, which suggests that there might be unmeasured confounding in the IPSW analysis. Because there is no uniquely suitable method that offers a universally optimal solution for evaluating causal relationships between exposures and outcomes from observational data, using multiple state-of-the-art methods to answer the question of interest can help in assessing the robustness of findings to various forms of unmeasured confounding, thereby aiding in causal inference.

PURPOSE:The REDUCE-IT randomized trial demonstrated a cardiovascular benefit of icosapent ethyl (IPE) but also raised potential safety signals for atrial fibrillation (AF) and serious bleeding. We aimed to evaluate the real-world safety of IPE versus mixed omega-3 polyunsaturated fatty acid (OM-3) formulations. METHODS:This retrospective active comparator new-user cohort study compared rates of new-onset AF and major bleeding (MB) among adult new users of IPE versus OM-3 in 2020-2024 US Veterans Affairs data. Daily drug exposure was determined via prescription dispensing dates. AF and MB outcomes were identified via validated algorithms based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision, clinical modification. Confounding was accounted for via nearest-neighbor pairwise propensity score (PS) matching. The PS, constructed via logistic regression, was informed by expert-identified variables meeting the disjunctive cause criterion. Cox regression was used to estimate adjusted hazard ratios (aHRs), interpretable as average treatment effects for the treated. RESULTS:Cohorts for analyses of AF and MB endpoints included 1927 and 2015 people, respectively, in each of the IPE and OM-3 exposure groups. The median age was 70 years, and the groups exhibited a predominance of white (80%) males (93%). The median follow-up time was 1.29 years per person. Baseline covariates were well balanced by treatment arm after PS matching. Incidence rates for AF were 7.29 versus 7.48 per 100 person-years among new users of IPE versus OM-3. The aHR for AF was 1.15 (95% confidence interval 0.82-1.63). Incidence rates for MB were 3.27 versus 3.35 per 100 person-years among new users of IPE versus OM-3. The aHR for MB was 1.22 (95% confidence interval 0.87-3.02). CONCLUSIONS:Our measures of association were consistent with the null, but we were unable to rule out harms from IPE (vs. OM-3) more modest than a 63% increased rate of AF and threefold increased rate of MB.

BACKGROUND:Opioid exposure during cancer therapy may increase long-term unsafe opioid prescribing. This study sought to determine the rates of coprescription of benzodiazepine and opioid medications and new persistent opioid use after surgical treatment of early-stage cancer. METHODS:A retrospective cohort study was conducted among a US veteran population via the Veterans Affairs Corporate Data Warehouse database. Participants were opioid-naive persons aged ≥21 years with a new diagnosis of stage 0-III cancer between January 1, 2015, and December 31, 2016. Outcomes were days of coprescription of benzodiazepines and opioids in the 13 months posttreatment and new persistent opioid use. The exposure was total morphine milligram equivalents (MMEs) attributed to treatment and prescribed from 30 days before through 14 days after the index surgical procedure. RESULTS:Among 9213 veterans, coprescription of benzodiazepines and opioids occurred in 366 patients (4.0%) and new persistent opioid use in 981 patients (10.6%). In a linear model adjusting for patient, clinical, and geographic factors, persons in the highest quartile compared to no opioid exposure had increased days with coprescription of benzodiazepines and opioids (mean difference, 1.0; 95% CI, 0.3-1.7). In a discrete time survival analysis, persons in the highest quartile of MME exposure compared to none had a greater risk of new persistent opioid use (hazard ratio, 1.6; 95% CI, 1.3-1.9). CONCLUSIONS:More than one of 10 opioid-naive veterans undergoing curative-intent surgical treatment for cancer developed new persistent opioid use. Optimizing cancer treatment pain management strategies to mitigate long-term opioid-related health risks is crucial.

BACKGROUND:Nursing home (NH) residents are at increased risk of drug-drug interactions (DDIs) due to multimorbidity and polypharmacy. While prior research suggests that many DDIs lead to adverse drug events in older adults, the extent of exposure to potentially clinically relevant DDIs among United States (US) NH residents is largely unknown. METHODS:In this cohort study, we calculated the prevalence and duration of exposure to 98 potential DDIs among US NH residents from 2018 to 2020. DDIs were sourced from three expert consensus publications, some of which defined similar interactions and overlapping drug combinations, allowing comparisons within and across lists. Data were drawn from Medicare claims linked to Minimum Data Set 3.0 clinical assessments. Eligible residents included Medicare Fee-for-Service beneficiaries aged ≥ 66 years living in NHs with observable Part D prescription drug data. DDI exposure was defined as ≥ 1 day of concurrent use of orally administered medications. Prevalence was calculated as the proportion of residents exposed to each DDI; duration was measured as the median number of days residents concurrently used the medications of interest. RESULTS:Among 485,251 NH residents, 61.6% experienced ≥ 1 potential DDI over 272,780 person-years. The 12 most prevalent DDIs involved central nervous system (CNS)-active drugs, anticholinergics, antihypertensives, opioids, and diuretics. Of these DDIs, concurrent use of acetylcholinesterase inhibitors and heart rate-reducing drugs had the longest median exposure duration (81 days; Q1-Q3, 24-235). The most prevalent DDI, concomitant use of ≥ 3 CNS-active drugs, was observed in 27.1% (95% CLs, 27.0%, 27.2%) of residents. CONCLUSIONS:Nearly two-thirds of NH residents were exposed to medication combinations linked to potential DDIs, although the prevalence and duration of exposure associated with individual DDIs varied. Future research should determine which DDIs are most clinically significant and investigate barriers to reducing exposure duration in this high-risk population.

The self-controlled case-series (SCCS) research design is increasingly used in pharmacoepidemiologic studies of drug-drug interactions (DDIs), with the target of inference being the incidence rate ratio (IRR) associated with concomitant exposure to the object plus precipitant drug vs the object drug alone. While day-level drug exposure can be inferred from dispensing claims, these inferences may be inaccurate, leading to biased IRRs. Grace periods (periods assuming continued treatment impact after days' supply exhaustion) are frequently used by researchers, but the impact of grace period decisions on bias from exposure misclassification remains unclear. Motivated by an SCCS study examining the potential DDI between clopidogrel (object) and warfarin (precipitant), we investigated bias due to precipitant or object exposure misclassification using simulations. We show that misclassified precipitant treatment always biases the estimated IRR toward the null, whereas misclassified object treatment may lead to bias in either direction or no bias, depending on the scenario. Further, including a grace period for each object dispensing may unintentionally increase the risk of misclassification bias. To minimize such bias, we recommend (1) avoiding the use of grace periods when specifying object drug exposure episodes and (2) including a washout period following each precipitant exposed period.This article is part of a Special Collection on Pharmacoepidemiology.

Introduction: Limited data exist on the cardiovascular effectiveness of once-weekly (OW) glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in real-world practice. Methods: We assessed the OW GLP-1 RA effects on vascular risk factors in adults with type 2 diabetes and atherosclerotic cardiovascular disease using data from a large-scale US electronic health record database (index date = first prescription of OW GLP-1 RA). Exploratory analyses were performed on patients newly initiating OW GLP-1 RAs with semaglutide, OW GLP-1 RAs without semaglutide, and semaglutide. Changes in vascular risk factors were evaluated by comparing mean measures between the 12-month pre- and post-index periods. Analyses were conducted for all three cohorts and subpopulations including stratified by tercile of baseline vascular risk factor value. Results: In the final cohorts ([1] OW GLP-1 RA including semaglutide: n = 20,084; [2] OW GLP-1 RA excluding semaglutide: n = 16,894; [3] semaglutide: n = 3,435), significant mean reductions (P < 0.001) were observed from baseline to post-index in hemoglobin A1c (%, [1] -1.1; [2] -1.1; [3] -1.2), low-density lipoprotein cholesterol (mg/dL, [1] -6.4; [2] -6.4; [3] -6.9), total cholesterol (mg/dL, [1] -11.0; [2] -11.1; [3] -10.7), triglycerides (mg/dL, [1] -31.8; [2] -31.4; [3] -33.1), systolic blood pressure (mmHg, [1] -1.5; [2] -1.2; [3] -3.1), body weight (kg, [1] -2.7; [2] -2.4; [3] -4.3) and body mass index (kg/m2; [1] -0.9; [2] -0.8; [3] -1.4). Largest reductions were observed in the top tercile. Conclusion: Our data suggest GLP-1 RAs are associated with significant reductions in key vascular risk factors in real-world practice.

In a prior screening study, saxagliptin, a dipeptidyl peptidase-4 inhibitor (DPP-4i), was found to have an increased rate of serious bleeding when used concomitantly with several oral anticoagulants (OACs). We aimed to confirm or refute the associations between concomitant use of individual OACs and DPP-4is and serious bleeding in a large US database, using self-controlled case series (SCCS) and case-crossover (CCO) designs. The study population was eligible Medicare beneficiaries co-exposed to a DPP-4i (precipitant) and either an OAC (object drug) or lisinopril (negative control object drug) in 2016-2020. For the SCCS, we used conditional Poisson regression to estimate adjusted rate ratios (RRs) between each co-exposure (vs. not) and serious bleeding and divided the RR by the adjusted RR for the corresponding lisinopril + precipitant pair to obtain ratios of RRs (RRRs). For the CCO, we estimated the adjusted odds ratios (ORs) of exposure to the precipitant in the focal window vs. referent window using multivariable conditional logistic regression and divided the ORs in the object drug-exposed cases over the ORs in negative object drug-exposed cases to obtain the ratios of ORs (RORs). The adjusted RRRs for serious bleeding ranged from 0.32 (0.05-1.91) for apixaban/lisinopril + saxagliptin to 3.49 (1.29-9.48) for warfarin/lisinopril + linagliptin. The adjusted RORs ranged from 0.01 (0.00-0.20) for rivaroxaban/lisinopril + saxagliptin to 2.99 (0.74-12.11) for apixaban/lisinopril + linagliptin. While we could not confirm previously identified signals because of statistical imprecision, several numerically elevated estimates still warrant caution in concomitant use and further examination.

PURPOSE:High-dimensional propensity score (hdPS) is a semiautomated method that leverages a vast number of covariates available in healthcare databases to improve confounding adjustment. A novel combined Super Learner (SL)-hdPS approach was proposed to assist with selecting the number of covariates for propensity score inclusion, and was found in plasmode simulation studies to improve bias reduction and precision compared to hdPS alone. However, the approach has not been examined in the applied setting. METHODS:We compared SL-hdPS's performance with that of several hdPS models, each with prespecified covariates and a different number of empirically-identified covariates, using a cohort study comparing real-world bleeding rates between ibrutinib- and bendamustine-rituximab (BR)-treated individuals with chronic lymphocytic leukemia in Optum's de-identified Clinformatics® Data Mart commercial claims database (2013-2020). We used inverse probability of treatment weighting for confounding adjustment and Cox proportional hazards regression to estimate hazard ratios (HRs) for bleeding outcomes. Parameters of interest included prespecified and empirically-identified covariate balance (absolute standardized difference [ASD] thresholds of <0.10 and <0.05) and outcome HR precision (95% confidence intervals). RESULTS:We identified 2423 ibrutinib- and 1102 BR-treated individuals. Including >200 empirically-identified covariates in the hdPS model compromised covariate balance at both ASD thresholds. SL-hdPS balanced more covariates than all individual hdPS models at both ASD thresholds. The bleeding HR 95% confidence intervals were generally narrower with SL-hdPS than with individual hdPS models. CONCLUSION:In a real-world application, hdPS was sensitive to the number of covariates included, while use of SL for covariate selection resulted in improved covariate balance and possibly improved precision.

The global rise in polypharmacy has increased both the necessity and complexity of drug-drug interaction (DDI) assessments, given the growing potential for interactions involving more than two drugs. Leveraging large-scale healthcare claims data, we piloted a semi-automated, high-throughput case-crossover-based approach for drug-drug-drug interaction (3DI) screening. Cases were direct-acting oral anticoagulant (DOAC) users with either a major bleeding event during ongoing dispensings for potentially interacting, enzyme-inhibiting antihypertensive drugs (AHDs) (Study 1), or a thromboembolic event during ongoing dispensings for potentially interacting, enzyme-inducing antiseizure medications (ASMs) (Study 2). 3DI detection was based on screening for additional drug exposures that served as acute outcome triggers. To mitigate direct effects and confounding by concomitant drugs, self-controlled estimates were adjusted using negative cases (external "control" DOAC users with the same outcomes but co-dispensings for non-interacting AHDs or ASMs). Signal thresholds were set based on P-values and false discovery rate q-values to address multiple comparisons. Study 1: 285 drugs were examined among 3,306 episodes. Self-controlled assessments with q-value thresholds yielded 9 3DI signals (cases) and 40 DDI signals (negative cases). External adjustment generated 10 3DI signals from the P-value threshold and no signals from the q-value threshold. Study 2: 126 drugs were examined among 604 episodes. Assessments with P-value thresholds yielded 3 3DI and 26 DDI signals following self-control, as well as 4 3DI signals following adjustment. No 3DI signals met the q-value threshold. The presented self- and externally-controlled approach aimed to advance paradigms for real-world higher order drug interaction screening among high-susceptibility populations with pre-existent DDI risk.

Concurrent use of skeletal muscle relaxants (SMRs) and opioids has been linked to an increased risk of injury. However, it remains unclear whether the injury risks differ by specific SMR when combined with opioids. We conducted nine retrospective cohort studies within a US Medicaid population. Each cohort consisted exclusively of person-time exposed to both an SMR and one of the three most dispensed opioids-hydrocodone, oxycodone, and tramadol. Opioid users were further divided into three cohorts based on the initiation order of SMRs and opioids-synchronically triggered, opioid-triggered, and SMR-triggered. Within each cohort, we used Cox proportional hazard models to compare the injury rates for different SMRs compared to methocarbamol, adjusting for covariates. We identified 349,543, 139,458, and 218,967 concurrent users of SMRs with hydrocodone, oxycodone, and tramadol, respectively. In the oxycodone-SMR-triggered cohort, the adjusted hazard ratios (HRs) were 1.86 (95% CI, 1.23-2.82) for carisoprodol and 1.73 (1.09-2.73) for tizanidine. In the tramadol-synchronically triggered cohort, the adjusted HRs were 0.69 (0.49-0.97) for metaxalone and 0.62 (0.42-0.90) for tizanidine. In the tramadol-SMR-triggered cohort, the adjusted HRs were 1.51 (1.01-2.26) for baclofen and 1.48 (1.03-2.11) for cyclobenzaprine. All other HRs were statistically nonsignificant. In conclusion, the relative injury rate associated with different SMRs used concurrently with the three most dispensed opioids appears to vary depending on the specific opioid and the order of combination initiation. If confirmed by future studies, clinicians should consider the varying injury rates when prescribing SMRs to individuals using hydrocodone, oxycodone, and tramadol.

Methadone has a high potential for risky drug-drug interactions that can lead to opioid overdose, yet evidence on the magnitude of this risk remains limited. Since methadone is transported via P-glycoprotein (P-gp), the use of statins that inhibit P-gp may elevate methadone plasma concentrations, potentially leading to opioid overdose. We explored this hypothesis by examining whether concomitant use of methadone and P-gp-inhibiting statins was associated with opioid overdose. Using Medicaid claims data from 2003 to 2020, we conducted a cohort study among new concomitant users of methadone and statins. We compared overdose rates among individuals exposed to P-gp-inhibiting statins (simvastatin, atorvastatin, or lovastatin) vs. those exposed to rosuvastatin (negative control), adjusting for baseline covariates. We identified 69,263 individuals newly exposed to methadone and a statin of interest; the overall incidence rate of opioid overdose was 26.0 per 1,000 person-years. Adjusted hazard ratios (HRs) for methadone + P-gp-inhibiting statins consistently showed no association, ranging from 0.76 (95% CI = 0.48-1.22) for atorvastatin to 0.78 (95% CI = 0.50-1.22) for simvastatin, compared with methadone + rosuvastatin. Similar results were observed in sensitivity analysis that treated all P-gp-inhibiting statins as a single exposure group, as well as analyses stratified by baseline diagnosis of opioid use disorder or overdose, the duration of baseline methadone use, and calendar year intervals. Our findings suggest that concomitant use of methadone with simvastatin, atorvastatin, or lovastatin is not associated with the risk of opioid overdose compared to concomitant use of methadone and rosuvastatin.

Importance Direct-acting oral anticoagulants (DOACs) are commonly prescribed with antiseizure medications (ASMs) due to concurrency of and the association between atrial fibrillation (AF) and epilepsy. However, enzyme-inducing (EI) ASMs may reduce absorption and accelerate metabolism of DOACs, potentially lowering DOAC levels and elevating thromboembolism risk. Objective To assess the rates of thromboembolic and major bleeding events in adults with AF and epilepsy dispensed DOACs and EI ASMs vs DOACs with non-EI ASMs. Design, Setting, and Participants This active-comparator, new-user cohort study included US health care data from the Clinformatics Data Mart database from October 2010 to September 2021 for a nationally representative population of adults with AF and epilepsy. Exposure Evaluations included episodes of contiguous coadministration of DOACs for AF with EI ASMs (exposed) or non-EI ASMs (referent) for epilepsy. Main Outcomes and MeasuresThromboembolic events (primary outcome) and major bleeding events (secondary outcome) were identified based on a series of validated, diagnosis-based coding algorithms. Data-adaptive, high-dimensional propensity score matching was used to control for observed confounders and proxies for unobserved confounders. Adjusted hazard ratios (AHRs) were estimated using Cox proportional hazards regression models with robust variance estimators to account for clustering within matched pairs. Results This study included 14 078 episodes (median age, 74 [IQR, 67-81]; 52.4% female) and 14 158 episodes (median age, 74 [IQR, 67-81]; 52.4% female) of incident DOAC and ASM use that met eligibility criteria for assessment of thromboembolic and major bleeding outcomes, respectively. Incidence was 88.5 per 1000 person-years for thromboembolic events and 68.3 per 1000 person-years for bleeding events. Compared with use of non-EI ASMs, use of EI ASMs with DOACs was not associated with a difference in risk of thromboembolic events (AHR, 1.10; 95% CI, 0.82-1.46) but was associated with a reduction in risk of major bleeding events (AHR, 0.63; 95% CI, 0.44-0.89). Conclusions and RelevanceIn this cohort study, EI ASMs were not associated with alteration in DOAC efficacy. Further research is needed on the reduction in bleeding risk associated with EI ASMs, as this may suggest that pharmacokinetic interactions are associated with lowering DOAC levels without negating therapeutic effects.

ObjectivePrior studies demonstrate that some untoward clinical outcomes vary by outdoor temperature. This is true of some endpoints common among persons with diabetes, a population vulnerable to climate change-associated health risks. Yet, prior work has been agnostic to the antidiabetes drugs taken by such persons. We examined whether relationships between ambient temperature and adverse health outcomes among persons with type 2 diabetes (T2D) varied by exposure to different antidiabetes drugs.DesignRetrospective cohort.SettingHealthcare and meteorological data from five US states, 1999–2010.ParticipantsUS Medicaid beneficiaries with T2D categorised by use of antidiabetes drugs.ExposureMaximum daily ambient temperature (t-max).OutcomesHospital presentation for serious hypoglycaemia, diabetic ketoacidosis (DKA) or sudden cardiac arrest (examined separately).MethodsWe linked US Medicaid to US Department of Commerce data that permitted us to follow individuals longitudinally and examine health plan enrolment, healthcare claims, and meteorological exposures—all at the person-day level. We mapped daily temperature from weather stations to Zone Improvement Plan (ZIP) codes, then assigned a t-max to each person-day based on the residential ZIP code. Among prespecified subcohorts of users of different pharmacologic classes of antidiabetes drugs, we calculated age and sex-adjusted occurrence rates for each outcome by t-max stratum. We used modified Poisson regression to assess relationships between linear and quadratic t-max terms and each outcome. We examined effect modification between t-max and a covariable for current exposure to a specific antidiabetes drug and assessed significance via Wald tests.ResultsWe identified ∼3 million persons with T2D among whom 713 464 used sulfonylureas (SUs), dipeptidyl peptidase-4 inhibitors (DPP-4is), meglitinides, or glucagon-like peptide 1 receptor agonists (GLP1RAs). We identified a positive linear association between t-max and serious hypoglycaemia among non-insulin users of glimepiride and of glyburide but not glipizide (Wald p value for interaction among SUs=0.048). We identified an inverse linear association between t-max and DKA among users of the DPP-4i sitagliptin (p=0.016) but not the GLP1RA exenatide (p=0.080). We did not identify associations between t-max and sudden cardiac arrest among users of SUs, meglitinides, exenatide, or DPP-4is.ConclusionsWe identified some antidiabetes drug class-specific and agent-specific differences in the relationship between ambient temperature and untoward glycaemic but not arrhythmogenic, safety outcomes.

INTRODUCTION:This study aimed to assess recent trends in the US use of glucagon-like peptide-1 receptor agonist (GLP-1 RA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i) in people with type 2 diabetes (T2D) and atherosclerotic cardiovascular disease (ASCVD), including incident use following newly diagnosed ASCVD. RESEARCH DESIGN AND METHODS:This real-world, retrospective observational study used de-identified data from the TriNetX Dataworks-USA network. A longitudinal analysis of cross-sectional data (interval: January 01, 2018 to December 31, 2022) assessed the yearly prevalent use of GLP-1 RA and SGLT2i. A nested cohort study (January 01, 2017 to January 31, 2023) assessed the proportions of patients with T2D newly prescribed GLP-1 RAs and SGLT2is after incident ASCVD diagnosis. RESULTS:Prevalent use of GLP-1 RA and/or SGLT2i increased from 9.2% of patients in 2018 to 27.1% in 2022, with eligible annual patient numbers ranging from 279,474 to 348,997. GLP-1 RA-alone use rose from 5.2% to 9.9% and SGLT2i-alone use rose from 2.8% to 12.2% over this interval. Incident use of GLP-1 RA and/or SGLT2i within the year following ASCVD diagnosis increased from 5.9% to 17.0% (2018-2022). For GLP-1 RA alone, this increase was from 3.6% to 7.8%, while for SGLT2i alone, it was from 1.8% to 7.0%. CONCLUSIONS:Use of GLP-1 RAs/SGLT2is in patients with T2D and ASCVD has increased in recent years in the USA, but remains suboptimal given the prevalence of ASCVD and its high morbidity and mortality.

Background and Purpose. Skeletal muscle relaxants (SMRs) are commonly co-prescribed with potentially interacting medications that may contribute to increased risk of unintentional traumatic injury (hereafter, injury). While prior research has investigated clinical outcomes for some pairwise drug interactions involving SMRs, drug interactions involving more than two drugs, such as drug triads (3DIs), largely remain unexamined. We sought to identify SMR 3DI signals associated with injury via automated high-throughput pharmacoepidemiologic screening of 2000–2019 healthcare data for members of commercial and Medicare Advantage health plans. Experimental Approach. We performed a self-controlled case series study for each drug triad consisting of an SMR base pair (i.e., concomitant use of an SMR with another medication), and a co-dispensed medication (i.e., candidate interacting precipitant) taken during ongoing use of the base pair. We included patients aged ≥16 years with an injury occurring during base pair-exposed observation time. We used conditional Poisson regression to calculate adjusted rate ratios (RRs) with 95% confidence intervals (CIs) for injury with each SMR base pair + candidate interacting precipitant (i.e., triad) versus the SMR-containing base pair alone. Key Results. Among 58,478 triads, 29 were significantly positively associated with injury; confounder-adjusted RRs ranged from 1.39 (95% CI=1.01–1.91) for tizanidine+omeprazole with gabapentin to 2.23 (95% CI=1.02–4.87) for tizanidine+diclofenac with alprazolam. Most identified 3DI signals are new and have not been formally investigated. Conclusions and Implications. We identified 29 SMR 3DI signals associated with increased rates of injury. Future etiologic studies should confirm or refute these SMR 3DI signals.

Background: Overactive bladder (OAB) is a common non-motor symptom of Parkinson disease (PD), often treated with antimuscarinics or beta-3 agonists. There is lack of evidence to guide OAB management in PD.Objectives: To assess the comparative safety of antimuscarinics versus beta-3 agonists for OAB treatment in PD.Methods: We employed a new-user, active-comparator cohort study design. We included Medicare beneficiaries age >= 65 years with PD who were new users of either antimuscarinic or beta-3 agonist. The primary outcome was any acute care encounter (i.e., non-elective hospitalization or emergency department visit) within 90 days of OAB drug initiation. The main secondary outcome was a composite measure of acute care encounters for anticholinergic related adverse events (AEs). Matching on high-dimensional propensity score (hdPS) was used to address potential confounding. We used Cox proportional hazards models to examine the association between OAB drug category and outcomes. We repeated analyses for 30- and 180-day follow-up periods.Results: We identified 27,091 individuals meeting inclusion criteria (mean age: 77.8 years). After hdPS matching, antimuscarinic users had increased risks for any acute care encounter (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.12-1.37) and encounters for anticholinergic related AEs (HR 1.18, 95% CI 1.04-1.34) compared to beta-3 agonist users. Similar associations were observed for sensitivity analyses.Conclusions: Among persons with PD, anticholinergic initiation was associated with a higher risk of acute care encounters compared with beta-3 agonist initiation. The long-term safety of anticholinergic vs. beta-3 agonist therapy in the PD population should be evaluated in a prospective study.