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Matthew J Swanson,1,2 Colin L Uyeki,1 Sarah R Yoder,1 Sanket S Dhruva,3 Jennifer E Miller,4 Joseph S Ross4– 6 1Frank H. Netter MD School of Medicine, Quinnipiac University, North Haven, CT, USA; 2Leonard N. Stern School of Business, New York University, New York, NY, USA; 3Department of Medicine, University of California, San Francisco School of Medicine, San Francisco, CA, USA; 4Department of Medicine, Yale School of Medicine, New Haven, CT, USA; 5Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA; 6Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USACorrespondence: Matthew J Swanson, Frank H. Netter MD School of Medicine, Quinnipiac University, 370 Bassett Road, North Haven, CT, 06473-1908, USA, Email Matthew.Swanson@stern.nyu.eduBackground: Representation of diverse study populations in pivotal clinical trials for medical devices and subgroup analyses for demographic groups to explore differences in safety and effectiveness are essential to understanding the benefits and risks in diverse populations. The US Food and Drug Administration (FDA) has taken many steps to improve transparency and subgroup analyses over the past decade, but there has not been a recent evaluation of demographic reporting and subgroup analyses.Methods: We reviewed all FDA Premarket Approvals for high-risk cardiovascular devices from 2014 to 2022, focusing on pivotal studies supporting device approval. We abstracted detailed demographic data about the age, sex, race, ethnicity, and socioeconomic position of study participants. We also assessed the presence and results of subgroup analyses to understand the safety and effectiveness of devices across trial populations.Results: Analysis of 92 pivotal studies revealed that age and sex were reported in 96.7% of the studies, while race and ethnicity were reported in 71.7% and 58.7%, respectively. However, only 7.9% of studies explicitly detailed the participation of older adults (≥ 65 years) and no studies reported patients’ socioeconomic position. Subgroup analyses by sex were conducted in 70.7% of studies, with 12.3% reporting significant differences. In contrast, analyses by race and ethnicity were performed in only 12.0% of the studies, with 9.1% reporting significant differences.Conclusion: Approximately one-third of pivotal studies for high-risk cardiovascular devices approved by the FDA from 2014 to 2022 did not report the race of study participants, nearly 40% did not report ethnicity, and more than 90% did not report the participation of older adults (≥ 65 years). Subgroup analyses were infrequently conducted by age or race and ethnicity. There is a need for better trial demographic reporting and conduct of subgroup analyses in premarketing studies to ensure the safety and effectiveness of medical devices for all patients.Keywords: FDA, clinical trial, cardiovascular device, diversity, inclusion, equity

Maryam Mooghali,1,2 Joseph S Ross,1– 4 Kushal T Kadakia,5 Sanket S Dhruva6,7 1Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; 2Yale Collaboration for Regulatory Rigor, Integrity, and Transparency (CRRIT), Yale School of Medicine, New Haven, CT, USA; 3Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA; 4Center for Outcomes Research and Evaluation, Yale-New Haven Health System, New Haven, CT, USA; 5Harvard Medical School, Boston, MA, USA; 6Department of Medicine, UCSF School of Medicine, San Francisco, CA, USA; 7San Francisco Veterans Affairs Health Care System, San Francisco, CA, USACorrespondence: Maryam Mooghali, Yale Center for Outcomes Research and Evaluation (CORE), 195 Church Street, New Haven, CT, 06510, USA, Tel +1 203 497-1239, Email maryam.mooghali@yale.eduBackground: Medical device recalls are initiated in response to safety concerns. Class I (highest severity) recalls imply a reasonable likelihood of serious adverse events or death associated with device use. Recalled devices must be identified, assessed, and corrected or removed, upon which a recall can be terminated.Objective: To characterize Class I medical device recalls and corresponding recalled devices.Methods: This was a cross-sectional study of Class I recalls posted on the Food and Drug Administration’s annual log from January 1, 2018 to June 30, 2022 for moderate-risk and high-risk medical devices. Devices were categorized by therapeutic use, need for implantation, and life-sustaining designation; recalls were categorized by reason, status, and time elapsed.Results: There were 189 unique Class I medical device recalls, including 151 (79.9%) for moderate-risk and 34 (18.0%) for high-risk devices. Sixty-five (34.4%) recalls were for cardiovascular devices, 36 (19.0%) for implanted devices, and 37 (19.6%) for life-sustaining devices. The median number of device units recalled in the US per recall notice was 4620 (interquartile range [IQR], 578– 42,591), with 11 (5.8%) recalls associated with more than 1 million device units. Overall, 125 (66.1%) devices had multiple recalls, with a median of 4 (IQR, 3– 11) recalls issued per recalled device. As of September 15, 2022, 50 (26.5%) recalls were terminated, with a median of 24 (IQR, 17.3– 30.8) months elapsed between recall initiation and termination. Recalls were terminated more commonly among devices recalled once compared to those recalled multiple times (36.2% vs 19.2%; p=0.02) and for recalls that recommended discontinuing further use of affected devices compared to those that recommended device assessment and/or education of affected population (31.8% vs 18.2%; p=0.04).Conclusion: High-severity medical device recalls are common and affect millions of device units annually in the US. Recall termination takes a significant amount of time, putting patients at risk for serious safety concerns.Keywords: medical devices recalls, device safety, Food and Drug Administration

Joseph S Ross,1–4 Jonathan Bates,4 Craig S Parzynski,4 Joseph G Akar,4,5 Jeptha P Curtis,4,5 Nihar R Desai,4,5 James V Freeman,4,5 Ginger M Gamble,4 Richard Kuntz,6 Shu-Xia Li,4 Danica Marinac-Dabic,7 Frederick A Masoudi,8 Sharon-Lise T Normand,9,10 Isuru Ranasinghe,11 Richard E Shaw,12 Harlan M Krumholz2–5 1Section of General Medicine, Department of Medicine, 2Robert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, 3Department of Health Policy and Management, Yale School of Public Health, 4Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, 5Section of Cardiovascular Medicine, Department of Medicine, Yale School of Medicine, New Haven, CT, 6Medtronic Inc, Minneapolis, MN, 7Division of Epidemiology, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, 8Division of Cardiology, Department of Medicine, University of Colorado, Aurora, CO, 9Department of Health Care Policy, Harvard Medical School, 10Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA; 11Discipline of Medicine, University of Adelaide, Adelaide, SA, Australia; 12Department of Clinical Informatics, California Pacific Medical Center, San Francisco, CA, USA Background: Machine learning methods may complement traditional analytic methods for medical device surveillance.Methods and results: Using data from the National Cardiovascular Data Registry for implantable cardioverter–defibrillators (ICDs) linked to Medicare administrative claims for longitudinal follow-up, we applied three statistical approaches to safety-signal detection for commonly used dual-chamber ICDs that used two propensity score (PS) models: one specified by subject-matter experts (PS-SME), and the other one by machine learning-based selection (PS-ML). The first approach used PS-SME and cumulative incidence (time-to-event), the second approach used PS-SME and cumulative risk (Data Extraction and Longitudinal Trend Analysis [DELTA]), and the third approach used PS-ML and cumulative risk (embedded feature selection). Safety-signal surveillance was conducted for eleven dual-chamber ICD models implanted at least 2,000 times over 3 years. Between 2006 and 2010, there were 71,948 Medicare fee-for-service beneficiaries who received dual-chamber ICDs. Cumulative device-specific unadjusted 3-year event rates varied for three surveyed safety signals: death from any cause, 12.8%–20.9%; nonfatal ICD-related adverse events, 19.3%–26.3%; and death from any cause or nonfatal ICD-related adverse event, 27.1%–37.6%. Agreement among safety signals detected/not detected between the time-to-event and DELTA approaches was 90.9% (360 of 396, k=0.068), between the time-to-event and embedded feature-selection approaches was 91.7% (363 of 396, k=–0.028), and between the DELTA and embedded feature selection approaches was 88.1% (349 of 396, k=–0.042).Conclusion: Three statistical approaches, including one machine learning method, identified important safety signals, but without exact agreement. Ensemble methods may be needed to detect all safety signals for further evaluation during medical device surveillance. Keywords: implanted cardioverter–defibrillator, methodology, surveillance

Joseph S Ross, Katrina L Blount, Jessica D Ritchie, Beth Hodshon, Harlan M Krumholz Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA Background: In the US, once a medical device is made available for use, several requirements have been established by the US Food and Drug Administration (FDA) to ensure ongoing post-market surveillance of device safety and effectiveness. Our objective was to determine how commonly medical device manufacturers initiate post-market clinical studies or augment FDA post-market surveillance requirements for higher-risk devices that are most often approved via the FDA's pre-market approval (PMA) pathway. Methods and results: We conducted a cross-sectional survey of 47 manufacturers with operations in California, Minnesota, and Massachusetts who market devices approved via the PMA pathway. Among 22 respondents (response rate =47%), nearly all self-reported conducting post-market clinical research studies, commonly between 1 and 5; only 1 respondent reported never conducting post-market clinical research studies. While manufacturers most often engaged in these studies to satisfy FDA requirements, other reasons were reported, including performance monitoring and surveillance and market acceptance initiatives. Risks of conducting and not conducting post-market clinical research studies were described through open-ended response to questions. Conclusion: Medical device manufacturers commonly initiate post-market clinical studies at the request of the FDA. Clinical data from these studies should be integrated into national post-market surveillance initiatives. Keywords: FDA, PMA pathway, post-market surveillance

Objective: To examine the association between regional brain uptake of a novel amyloid positron emission tomography (PET) tracer florbetapir F 18 ([(18)F]-AV-45) and cognitive performance in a pilot study.Design: Cross-sectional comparison of [(18)F]-AV-45 in AD patients versus controls.Setting: Three specialty memory clinics.Participants: Eleven participants with probable Alzheimer disease (AD) by NINDS/ADRDA criteria and 15 healthy comparison (HC) participants.Measurements: Participants underwent PET imaging following a 370 MBq (10 mCi) intravenous administration of [(18)F]-AV-45. Regional/cerebellar standardized uptake value ratios (SUVRs) were calculated. Cognition was assessed using Mini-Mental State Examination, Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog), Wechsler Logical Memory IA (immediate recall) test (LMIA), and verbal category fluency.Results: Greater [(18)F]-AV-45 SUVR was associated with poorer performance on all cognitive tests. In the HC group, occipital, parietal, precuneus, temporal, and cortical average SUVR was associated with greater ADAS-Cog, and greater anterior cingulate SUVR was associated with lower LMIA. Two HC participants had [(18)F]-AV-45 cortical/cerebellar SUVR greater than 1.5, one of whom had deficits in episodic recall and on follow-up met criteria for amnestic mild cognitive impairment.Conclusion: [(18)F]-AV-45 SUVR in several brain regions was associated with worse global cognitive performance particularly in HC, suggesting its potential as a marker of preclinical AD. [ABSTRACT FROM AUTHOR]

Importance: To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race.Objective: To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia.Design, Setting, and Patients: We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge.Main Outcome Measures: We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing.Results: From 2007 through 2009, we identified 329,308 30-day readmissions after 1,330,157 HF hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute MI hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race.Conclusion and Relevance: Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge. [ABSTRACT FROM AUTHOR]

Background: The use of coronary artery bypass grafting (CABG) surgery in China is growing, but little is known about hospital-level performance. We sought to characterize the variation in performance across hospitals participating in a national registry in China.Methods and Results: The study sample was drawn from the Chinese Cardiac Surgery Registry, a national multicenter database that includes 43 hospitals across 13 provinces and 4 direct-controlled municipalities in China. We assessed consecutive patients undergoing isolated CABG surgery during the period of January 1, 2007, through December 31, 2008. Hierarchical generalized linear models were used to estimate hospital-level risk-standardized in-hospital all-cause mortality rates (RSMR) and major complication rates (RSMCR), which included death, myocardial infarction, reoperation for bleeding, mediastinal infection, stroke, reintubation, and renal failure. Among 8739 patients who underwent isolated CABG surgery, the mean age was 62.2 years (SD=9.2), and 78% were male. Observed in-hospital mortality and complication rates were 2.2% (95% confidence interval [CI], 1.9-2.5%) and 6.6% (95% CI, 6.1-7.1%), respectively. The mean RSMR was 1.9% (SD=1.1), with a range of 0.7-5.8%, and the mean RSMCR was 6.4% (SD=1.5), with a range of 3.8-10.1%. The odds of dying and the odds of having a complication after CABG surgery at a hospital 1 SD below the average relative to a hospital 1 SD above the average were 2.06 (95% CI, 1.40-3.04) and 1.53 (95% CI, 1.31-1.79), respectively. The Eastern region had the lowest RSMR and RSMCR (1.6% and 5.8%, respectively), whereas the Central region had the highest RSMR (2.5%) and the Southern region had the highest RSMCR (7.7%).Conclusions: Mortality and complication rates after CABG surgery in the Chinese Cardiac Surgery Registry are generally low but vary by hospital and region within China. These results suggest that there are opportunities to improve outcomes in some CABG facilities. [ABSTRACT FROM AUTHOR]

Background: Reducing blood pressure (BP) after stroke reduces risk for recurrent events. Our aim was to describe hypertension care among veterans with ischemic stroke including BP control by discharge and over the 6 months after the stroke event.Methods and Results: The Office of Quality and Performance Stroke Special Study included a systematic sample of veterans hospitalized for ischemic stroke in 2007. We examined BP control (<140/90 mm Hg) at discharge excluding those who died, enrolled in hospice, or had unknown discharge disposition (n=3640, n=3382 adjusted analysis). The second outcome was BP control (<140/90 mm Hg) within 6-months after stroke, excluding patients who died/readmitted within 30 days, were lost to follow-up, or did not have a BP recorded (n=2054, n=1915 adjusted analysis). The population was 62.7% white and 97.7% men; 46.9% were <65 years of age; and 29% and 37% had a history of cerebrovascular or cardiovascular disease, respectively. Among the 3640 stroke patients, 1573 (43%) had their last documented BP before discharge as >140/90 mm Hg. Black race (adjusted odds ratio, 0.77; 95% confidence interval, 0.65 to 0.91), diabetes (odds ratio, 0.73; 95% confidence interval, 0.62 to 0.86), and hypertension history (odds ratio, 0.51; 95% confidence interval, 0.42 to 0.63) were associated with lower odds for controlled BP at discharge. Of the 2054 stroke patients seen within 6 months from their index event, 673 (32.8%) remained uncontrolled. By 6 months after the event, neither race nor diabetes was associated with BP control, whereas history of hypertension continued to have lower odds of BP control. For each 10-point increase in systolic BP >140 mm Hg at discharge, odds of BP control within 6 months after discharge decreased by 12% (95% confidence interval [8%, 18%]).Conclusions: BP values in excess of national guidelines are common after stroke. Forty-three percent of patients were discharged with an elevated BP, and 33% remained uncontrolled by 6 months. [ABSTRACT FROM AUTHOR]