Class I Recalls of Cardiovascular Devices Between 2013 and 2022 : A Cross-Sectional Analysis.

BACKGROUND: Cardiovascular devices account for one third of all Class I recalls, the U.S. Food and Drug Administration's (FDA) most severe designation, indicating a reasonable probability of "serious adverse health consequences or death." Understanding recalls and their causes is important for patient safety. OBJECTIVE: To characterize Class I recalls of cardiovascular devices and the clinical evidence supporting authorization. DESIGN: In this cross-sectional study, cardiovascular device recalls from 1 January 2013 through 31 December 2022 were identified using the FDA's annual log. Information about devices was extracted from publicly available FDA decision summaries. SETTING: The FDA Medical Device Recalls database. PARTICIPANTS: Cardiovascular devices with Class I recalls. MEASUREMENTS: Recalls were characterized by their causes and scope. Devices were characterized by their regulatory history (product code, special designations) and clinical evidence (premarket testing, postmarket surveillance). Clinical studies were analyzed for quality, including end point selection (clinical vs. surrogate, use of composites). RESULTS: From 2013 to 2022, there were 137 Class I recall events affecting 157 unique cardiovascular devices, of which 112 (71.3%) were moderate-risk 510(k) devices and 45 (28.7%) were high-risk premarket approval (PMA) devices. Recalls affected a median of 7649 units (IQR, 953 to 28 446) and were most commonly attributed to device design (43 [31.4%]). Forty-two (26.8%) devices had multiple Class I recalls. Thirty (19.1%) devices underwent premarket clinical testing (7 [6.2%] 510(k) devices, 17 [85.0%] PMA devices, and 6 [24.0%] PMA supplement devices). Most studies used surrogate (27 [79.4%]) and composite (24 [70.6%]) measures as primary end points. Twenty-two (48.9%) PMA devices had required postapproval studies, with 14 reporting delays. No 510(k) devices were subject to postmarket surveillance. LIMITATION: Details about clinical testing may be missing from FDA summaries. CONCLUSION: Cardiovascular devices with Class I recalls were infrequently subjected to premarket or postmarket testing, with recalls affecting thousands of patients annually. PRIMARY FUNDING SOURCE: None.

Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks.

BACKGROUND: Improving hypertension control is a public health priority. However, consistent identification of uncontrolled hypertension using computable definitions in electronic health records (EHR) across health systems remains uncertain. METHODS: In this retrospective cohort study, we applied two computable definitions to the EHR data to identify patients with controlled and uncontrolled hypertension and to evaluate differences in characteristics, treatment, and clinical outcomes between these patient populations. We included adult patients (≥ 18 years) with hypertension (based on either ICD-10 codes of hypertension or two elevated blood pressure [BP] measurements) receiving ambulatory care within Yale-New Haven Health System (YNHHS; a large US health system) and OneFlorida Clinical Research Consortium (OneFlorida; a Clinical Research Network comprised of 16 health systems) between October 2015 and December 2018. We identified patients with controlled and uncontrolled hypertension based on either a single BP measurement from a randomly selected visit or all BP measurements recorded between hypertension identification and the randomly selected visit). RESULTS: Overall, 253,207 and 182,827 adults at YNHHS and OneFlorida were identified as having hypertension. Of these patients, 83.1% at YNHHS and 76.8% at OneFlorida were identified using ICD-10-CM codes, whereas 16.9% and 23.2%, respectively, were identified using elevated BP measurements (≥ 140/90 mmHg). A total of 24.1% of patients at YNHHS and 21.6% at OneFlorida had both diagnosis code for hypertension and elevated blood pressure measurements. Uncontrolled hypertension was observed among 32.5% and 43.7% of patients at YNHHS and OneFlorida, respectively. Uncontrolled hypertension was disproportionately higher among Black patients when compared with White patients (38.9% versus 31.5% in YNHHS; p < 0.001; 49.7% versus 41.2% in OneFlorida; p < 0.001). Medication prescription for hypertension management was more common in patients with uncontrolled hypertension when compared with those with controlled hypertension (overall treatment rate: 39.3% versus 37.3% in YNHHS; p = 0.04; 42.2% versus 34.8% in OneFlorida; p < 0.001). Patients with controlled and uncontrolled hypertension had similar incidence rates of deaths, CVD events, and healthcare visits at 3, 6, 12, and 24 months. The two computable definitions generated consistent results. CONCLUSIONS: While the current EHR systems are not fully optimized for disease surveillance and stratification, our findings illustrate the potential of leveraging EHR data to conduct digital population surveillance in the realm of hypertension management.

Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.

BACKGROUND: Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist among the public and medical community. Given the rapid and transformative recent growth of AI in cardiovascular care, to inform practice guidelines and regulatory policies that facilitate ethical and trustworthy use of AI in medicine, we conducted a literature review to identify key ethical and trust barriers and facilitators from patients' and healthcare providers' perspectives when using AI in cardiovascular care. METHODS: In this rapid literature review, we searched six bibliographic databases to identify publications discussing transparency, trust, or ethical concerns (outcomes of interest) associated with AI-based medical devices (interventions of interest) in the context of cardiovascular care from patients', caregivers', or healthcare providers' perspectives. The search was completed on May 24, 2022 and was not limited by date or study design. RESULTS: After reviewing 7,925 papers from six databases and 3,603 papers identified through citation chasing, 145 articles were included. Key ethical concerns included privacy, security, or confidentiality issues (n = 59, 40.7%); risk of healthcare inequity or disparity (n = 36, 24.8%); risk of patient harm (n = 24, 16.6%); accountability and responsibility concerns (n = 19, 13.1%); problematic informed consent and potential loss of patient autonomy (n = 17, 11.7%); and issues related to data ownership (n = 11, 7.6%). Major trust barriers included data privacy and security concerns, potential risk of patient harm, perceived lack of transparency about AI-enabled medical devices, concerns about AI replacing human aspects of care, concerns about prioritizing profits over patients' interests, and lack of robust evidence related to the accuracy and limitations of AI-based medical devices. Ethical and trust facilitators included ensuring data privacy and data validation, conducting clinical trials in diverse cohorts, providing appropriate training and resources to patients and healthcare providers and improving their engagement in different phases of AI implementation, and establishing further regulatory oversights. CONCLUSION: This review revealed key ethical concerns and barriers and facilitators of trust in AI-enabled medical devices from patients' and healthcare providers' perspectives. Successful integration of AI into cardiovascular care necessitates implementation of mitigation strategies. These strategies should focus on enhanced regulatory oversight on the use of patient data and promoting transparency around the use of AI in patient care.

Harnessing policy to promote inclusive medical product evidence: development of a reference standard and structured audit of clinical trial diversity policies.

Objective: To develop a reference standard based on US Food and Drug Administration and stakeholder guidance for pharmaceutical companies' policies on diversity in clinical trials and to assess these policies. Design: Development of a reference standard and structured audit for clinical trial diversity policies. Setting: 50 pharmaceutical companies selected from the top 500 by their market capitalizations in 2021 (the 25 largest companies and 25 non-large companies, randomly selected from the remaining 475 companies). Population: Data from pharmaceutical company websites and annual reports. Policy guidance from the Pharmaceutical Research and Manufacturers of America, International Federation of Pharmaceutical Manufacturers and Associations, Biotechnology Industry Organization, International Committee of Medical Journal Editors, the US Food and Drug Administration, European Medicines Agency, and World Health Organization, up to 15 May 2023. Main outcome measures: Multicomponent measure based on distinct themes derived from FDA and stakeholder guidance. Results: Reviewing FDA and stakeholder guidance identified 14 distinct themes recommended for improving diversity in clinical trials, which were built into a reference standard: (1) enrollment targets that reflect the prevalence of targeted conditions in populations, (2) broad eligibility criteria for trials, (3) diversity in the workforce, (4) identification and remedy of barriers to trial recruitment and retention, (5) incorporation of patient input into trial design, (6) health literacy, (7) multidimensional approaches to diversity, (8) sites with diverse providers and patient populations, (9) data collection after product approval, (10) diverse enrollment in every country where trials are conducted, (11) diverse enrollment should be a focus for all phases of clinical trials, not just later stage or pivotal trials, (12) varied trial design, (13) expanded access, and (14) public reporting of the personal characteristics of participants in trials. Applying this reference standard, 48% (24/50) of companies had no public policy on diversity in clinical trials; among those with policies, content varied widely. Large companies were more likely to have a public policy than non-large companies (21/25, 84% v 5/25, 20%, P<0.001). Large companies most frequently committed to using epidemiological based trial enrollment targets representing the prevalence of indicated conditions in various populations (n=15, 71%), dealing with barriers to trial recruitment (n=15, 71%), and improving patient awareness of trial opportunities (n=14, 67%). The location of the company was not associated with having a public diversity policy (P=0.17). The average company policy had five of the 14 commitments (36%, range 0-8) recommended in FDA and stakeholder guidance. Conclusions: The findings of the study showed that many pharmaceutical companies did not have public policies on diversity in clinical trials, although policies were more common in large than non-large companies. Policies that were publicly available varied widely and lacked important commitments recommended by stakeholder guidance. The results of the study suggest that corporate policies can be better leveraged to promote representation and fair inclusion in research, and implementation of FDA and stakeholder guidance.

Feasibility of using real-world data to emulate substance use disorder clinical trials: a cross-sectional study.

INTRODUCTION: Real-world evidence is receiving considerable attention as a way to evaluate the efficacy and safety of medical products for substance use disorders (SUDs). However, the feasibility of using real-world data (RWD) to emulate clinical trials evaluating treatments for SUDs is uncertain. The aim of this study is to identify the number of clinical trials evaluating treatments for SUDs with reported results that could be feasibly emulated using observational data from contemporary insurance claims and/or electronic health record (EHR) data. METHODS: In this cross-sectional study, all phase 2-4 trials evaluating treatments for SUDs registered on ClinicalTrials.gov with reported results were identified. Each trial was evaluated to determine if the indications, interventions, at least 80% of eligibility criteria, comparators, and primary end points could be ascertained using contemporarily available administrative claims and/or structured EHR data. RESULTS: There were 272 SUD trials on ClinicalTrials.gov with reported results. Of these, when examining feasibility using contemporarily available administrative claims and/or structured EHR data, 262 (96.3%) had indications that were ascertainable; 194 (71.3%) had interventions that were ascertainable; 21 (7.7%) had at least 80% of eligibility criteria that were ascertainable; 17 (6.3%) had active comparators that were ascertainable; and 61 (22.4%) had primary end points that were ascertainable. In total, there were no trials for which all 5 characteristics were ascertainable using contemporarily available administrative claims and/or structured EHR data. When considering placebo comparators as ascertainable, there were 6 (2.2%) trials that had all 5 key characteristics classified as ascertainable from contemporarily available administrative claims and/or structured EHR data. CONCLUSIONS: No trials evaluating treatments for SUDs could be feasibly emulated using contemporarily available RWD, demonstrating a need for an increase in the resolution of data capture within a public health system to facilitate trial emulation.

Differential times of submission and approval of CFTR modulators for the treatment of Cystic Fibrosis in the United States and the European Union.

BACKGROUND: The objective of this study was to assess the differential times of submission and approval of CFTR modulators in the United States (US) and the European Union (EU). METHODS: By collecting publicly available data from the websites of the Food and Drug Administration and the European Medicines Agency, we quantified differential times in submission, review duration, and approvals of initial marketing authorization and variation of indications of CFTR modulators in the US and the EU by December 31, 2023. RESULTS: Applications regarding marketing of 4 CFTR modulators were submitted 103 (SD ±143) days later in the EU than in the US: 31 (SD ±39) days later for initial approval, and 124 (SD ±155) days for supplemental indications. The regulatory review process was completed in 181 days [IQR, 179 - 182] in the US and 325 days [IQR, 276 - 382] in the EU: 167 days [IQR, 102 - 232] in the US and 346 days [IQR, 302 - 400] in the EU for first approvals, 181 days [IQR, 181 - 182] in the US and 324 days [IQR, 264 - 382] in the EU for supplemental indication approvals. CFTR modulators were approved 267 (SD 143) days later in the EU than in the US: 220 (SD ±76) days for initial approval and 280 (SD ±157) days for supplemental indications. CONCLUSION: We found significant differences in times of submission and for approval of CFTR modulators between the US and EU, whereby initial approvals and subsequent indication approvals were always first granted in the US.

Reciprocal restriction fragment length polymorphism (RFLP) analysis reveals mitochondrial heteroplasmy in Caenorhabditis briggsae hybrids.

Although mitochondria are typically inherited maternally, exceptions exist. We previously demonstrated that within-species crosses of Caenorhabditis briggsae result in paternal mitochondrial transmission, and it would be useful to know whether hybrids have only paternal mitochondria (homoplasmy) or paternal and maternal mitochondria (heteroplasmy). We developed a reciprocal restriction fragment length polymorphism analysis to separately detect paternal and maternal mitochondrial DNA. Using new hybrid lines, this approach revealed that some hybrids are heteroplasmous and others have become homoplasmous for the paternal mitotype. These results motivate additional investigation of how paternal mitochondrial transmission is apparently facile in C. briggsae .

Premarket Pivotal Trial End Points and Postmarketing Requirements for FDA Breakthrough Therapies.

Importance: The US Food and Drug Administration (FDA) awards the breakthrough therapy designation to expedite development and review of therapeutics intended to treat serious conditions when preliminary clinical evidence demonstrates potential substantial improvement over existing therapies on clinically significant end points. Under the 21st Century Cures Act of 2016, the FDA is required to publish and routinely update a list of surrogate markers to provide industry sponsors with indication-specific information about end points that were or may be considered for approval. Therapeutics that are granted breakthrough therapy designation can receive accelerated or traditional approval; however, little is known about those approved through the latter pathway, where postmarketing confirmatory studies are typically not required, regardless of the end point used. Objective: To evaluate the primary end points used in premarket pivotal trials supporting FDA breakthrough therapy-designated approvals and to determine whether postmarketing studies confirming efficacy were required for approvals based on pivotal trials using surrogate markers as primary end points. Design, Setting, and Participants: This cross-sectional study used data from the Drugs@FDA database for all original breakthrough therapy-designated approvals from inception to December 31, 2023, in the US. The first designation was approved on November 1, 2013. Data analysis was performed in January 2024. Main Outcomes and Measures: Descriptive analyses were used to characterize the breakthrough therapy-designated indication approval pathways, the primary end points of pivotal efficacy trials, and their postmarketing requirements or commitments. Results: From 2013 to 2023, the FDA approved 157 original indications with breakthrough therapy designation. Of these, 52 (33%) were granted accelerated approval and 105 (67%) were granted traditional approval. All accelerated approvals were based on pivotal trials using surrogate markers as primary end points and had FDA-required postmarketing studies to confirm efficacy. Of these 52 indications, 51 (98%) were approved based on surrogate end points listed in the FDA table of surrogate end points for the same indication. Among traditional approvals, 61 (58%) were based on pivotal trials using surrogate markers as primary end points, of which 4 (7%) had FDA-required postmarketing studies to confirm efficacy and 39 (64%) were approved based on surrogate end points listed in the FDA table for the same indication. Conclusions and Relevance: In this cross-sectional study of original FDA breakthrough therapy-designated approvals from 2013 to 2023, trials supporting these approvals often used surrogate markers as primary end points (even when not approved via accelerated approval) and lacked FDA-required postmarketing studies to verify clinical benefit. These findings suggest that requiring postmarketing studies for breakthrough therapy-designated indications approved based on surrogate markers, regardless of approval pathway, may increase patient and clinician certainty of the expected clinical benefit.

Discrepancies in the results reported for multiple sclerosis clinical trials: A comparison between ClinicalTrials.gov and peer-reviewed journals.

OBJECTIVE: We aimed to compare the results of phase III and IV clinical trials examining drugs to treat multiple sclerosis (MS) registered at ClinicalTrials.gov to those published in peer-reviewed journals. METHODS: After identifying trials registered at ClinicalTrials.gov, consecutive searches were conducted in PubMed, EMBASE and Google Scholar for matching publications. Information regarding participants and efficacy and safety results was extracted and compared. The degree of consistency was classified as 'concordant', 'discrepant' or 'not comparable'. The Kaplan-Meier method was used to model time to reporting. RESULTS: In total, 65 trials were appraised. The median time from completion to reporting was shorter for ClinicalTrials.gov (16.4 vs 27.3 months; p = 0.010). Information availability was generally higher in journals except for serious adverse events (SAEs) (86.2% vs 100.0%, p = 0.029) and their description (78.2% vs 100.0%, p < 0.001). However, 45 trials had at least one reporting discrepancy (69.2%). Three studies omitted one or more primary outcomes in the matching journal publication. Regarding safety results, the lowest consistencies were found for causes of death (60.0%) and description of SAEs (27.9%). CONCLUSION: Consulting both ClinicalTrials.gov and journals increases the accessibility to MS clinical trial results. Some data were frequently missing or disagreed between sources, raising concerns about transparency and generalizability of results.

Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes: A Multinational, Federated Analysis of LEGEND-T2DM.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials. OBJECTIVES: The aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM. METHODS: Across the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis. RESULTS: Over 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13]). CONCLUSIONS: In patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD.

Quantitative bias analysis methods for summary-level epidemiologic data in the peer-reviewed literature: a systematic review.

OBJECTIVES: Quantitative bias analysis (QBA) methods evaluate the impact of biases arising from systematic errors on observational study results. This systematic review aimed to summarize the range and characteristics of QBA methods for summary-level data published in the peer-reviewed literature. STUDY DESIGN AND SETTING: We searched MEDLINE, Embase, Scopus, and Web of Science for English-language articles describing QBA methods. For each QBA method, we recorded key characteristics, including applicable study designs, bias(es) addressed; bias parameters, and publicly available software. The study protocol was preregistered on the Open Science Framework (https://osf.io/ue6vm/). RESULTS: Our search identified 10,249 records, of which 53 were articles describing 57 QBA methods for summary-level data. Of the 57 QBA methods, 53 (93%) were explicitly designed for observational studies, and 4 (7%) for meta-analyses. There were 29 (51%) QBA methods that addressed unmeasured confounding, 19 (33%) misclassification bias, 6 (11%) selection bias, and 3 (5%) multiple biases. Thirty-eight (67%) QBA methods were designed to generate bias-adjusted effect estimates and 18 (32%) were designed to describe how bias could explain away observed findings. Twenty-two (39%) articles provided code or online tools to implement the QBA methods. CONCLUSION: In this systematic review, we identified a total of 57 QBA methods for summary-level epidemiologic data published in the peer-reviewed literature. Future investigators can use this systematic review to identify different QBA methods for summary-level epidemiologic data. PLAIN LANGUAGE SUMMARY: Quantitative bias analysis (QBA) methods can be used to evaluate the impact of biases on observational study results. However, little is known about the full range and characteristics of available methods in the peer-reviewed literature that can be used to conduct QBA using information reported in manuscripts and other publicly available sources without requiring the raw data from a study. In this systematic review, we identified 57 QBA methods for summary-level data from observational studies. Overall, there were 29 methods that addressed unmeasured confounding, 19 that addressed misclassification bias, six that addressed selection bias, and three that addressed multiple biases. This systematic review may help future investigators identify different QBA methods for summary-level data.

At-Home Testing for Survivors of Sexual Assault-Empowerment or Exploitation?

In this Viewpoint, the accuracy, usefulness, and marketing of at-home rape kits is explored.

Unveiling the Adoption and Barriers of Telemedicine in US Hospitals: A Comprehensive Analysis (2017-2022).

BACKGROUND: Telemedicine has emerged as a vital healthcare delivery model, especially pronounced during the COVID-19 pandemic. Our study uniquely focuses on an institutional lens, examining US hospitals to offer targeted policy implications. OBJECTIVE: To investigate the trend in telemedicine adoption across US hospitals from 2017 to 2022 and analyze the institutional challenges they encounter, particularly in the realm of electronic health information exchange. DESIGN: Cross-sectional study leveraging data from the American Hospital Association's (AHA) annual surveys for the years 2017 to 2021 and the 2022 AHA IT Supplement Survey. SETTING: The study includes a national sample of US hospitals, covering a diverse range of hospital types including large, nonprofit, teaching, and system-affiliated institutions. PARTICIPANTS: US hospitals form the study's participants, with a substantial response rate to the surveys. MAIN MEASURES: Key metrics include the number of telemedicine patient encounters, percentage of hospitals offering telemedicine services, and institutional challenges to electronic health information exchange. KEY RESULTS: Telemedicine encounters saw a 75% increase, growing from approximately 111.4 million in 2020 to nearly 194.4 million in 2021. The percentage of hospitals offering at least one form of telemedicine service went from 46% in 2017 to 72% in 2021. Larger, nonprofit, and teaching hospitals were more prone to telehealth adoption, without notable urban-rural disparities. While over 90% of hospitals allow patients to view and download medical records, only 41% permit online data submission. Importantly, 25% of hospitals identified Certified Health IT Developers such as EHR vendor as frequent culprits in information blocking, with cost being the primary obstacle. CONCLUSIONS: The findings underscore the rapid yet uneven adoption of telemedicine services in U.S. hospitals. The results point to the need for comprehensive policy interventions to address the challenges identified and realize telemedicine's full potential in healthcare delivery and resilience.

Altmetric Attention Scores and Citations of Published Research With or Without Preprints.

This cross-sectional study assesses how frequently research articles published in the clinical journals with high impact factors are preprinted and whether preprinting is associated with changes in media attention and citation counts.

Use of Muscle Relaxants After Surgery in Traditional Medicare Part D Enrollees.

BACKGROUND: Surgeons have come under increased scrutiny for postoperative pain management, particularly for opioid prescribing. To decrease opioid use but still provide pain control, nonopioid medications such as muscle relaxants are being used, which can be harmful in older adults. However, the prevalence of muscle relaxant prescribing, trends in use over time, and risk of prolonged use are unknown. STUDY DESIGN: Using a 20% representative Medicare sample, we conducted a retrospective analysis of muscle relaxant prescribing to patients ≥ 65 years of age. We merged patient data from Medicare Carrier, MedPAR, and Outpatient Files with Medicare Part D for the years 2013-2018. A total of 14 surgical procedures were included to represent a wide range of anatomic regions and specialties. RESULTS: The study cohort included 543,929 patients. Of the cohort, 8111 (1.5%) received a new muscle relaxant prescription at discharge. Spine procedures accounted for 12% of all procedures but 56% of postoperative prescribing. Overall, the rate of prescribing increased over the time period (1.4-2.0%, p < 0.001), with increases in prescribing primarily in the spine (7-9.6%, p < 0.0001) and orthopedic procedure groups (0.9-1.4%, p < 0.0001). Of patients discharged with a new muscle relaxant prescription, 10.7% had prolonged use. CONCLUSIONS: The use of muscle relaxants in the postoperative period for older adults is low, but increasing over time, especially in ortho and spine procedures. While pain control after surgery is crucial, surgeons should carefully consider the risks of muscle relaxant use, especially for older adults who are at higher risk for medication-related problems.