Publications

OBJECTIVES: To more clearly define the landscape of digital medical devices subject to US Food and Drug Administration (FDA) oversight, this analysis leverages publicly available regulatory documents to characterise the prevalence and trends of software and cybersecurity features in regulated medical devices.

DESIGN: We analysed data from publicly available FDA product summaries to understand the frequency and recent time trends of inclusion of software and cybersecurity content in publicly available product information.

SETTING: The full set of regulated medical devices, approved over the years 2002-2016 included in the FDA's 510(k) and premarket approval databases.

PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the share of devices containing software that included cybersecurity content in their product summaries. Secondary outcomes were differences in these shares (a) over time and (b) across regulatory areas.

RESULTS: Among regulated devices, 13.79% were identified as including software. Among these products, only 2.13% had product summaries that included cybersecurity content over the period studied. The overall share of devices including cybersecurity content was higher in recent years, growing from an average of 1.4% in the first decade of our sample to 5.5% in 2015 and 2016, the most recent years included. The share of devices including cybersecurity content also varied across regulatory areas from a low of 0% to a high of 22.2%.

CONCLUSIONS: To ensure the safest possible healthcare delivery environment for patients and hospitals, regulators and manufacturers should work together to make the software and cybersecurity content of new medical devices more easily accessible.

PURPOSE: Physical activity improves outcomes across a broad spectrum of cardiovascular disease. The safety and effectiveness of exercise-based interventions in patients with implantable cardioverter-defibrillators (ICDs) including cardiac resynchronization therapy defibrillators (CRT-Ds) remain poorly understood.

METHODS: We identified clinical studies using the following search terms: "implantable cardioverter-defibrillators"; "ICD"; "cardiac resynchronization therapy"; "CRT"; and any one of the following: "activity"; "exercise"; "training"; or "rehabilitation"; from January 1, 2000 to October 1, 2015. Eligible studies were evaluated for design and clinical endpoints.

RESULTS: A total of 16 studies were included: 8 randomized controlled trials, 5 single-arm trials, 2 observational cohort trials, and 1 randomized crossover trial. A total of 2547 patients were included (intervention groups = 1215 patients, control groups = 1332 patients). Exercise interventions varied widely in character, duration (median 84 d, range: 23-168 d), and follow-up time (median 109 d, range: 23 d to 48 mo). Exercise performance measures were the most common primary endpoints (87.5%), with most studies (81%) demonstrating significant improvement. Implantable cardioverter-defibrillator shocks were uncommon during active exercise intervention, with 6 shocks in 635 patients (0.9%). Implantable cardioverter-defibrillator shocks in follow-up were less common in patients receiving any exercise intervention (15.6% vs 23%, OR = 0.68; 95% CI, 0.48-0.80, P < .001). (Equation is included in full-text article.)O2 peak improved significantly in patients receiving exercise intervention (1.98 vs 0.36 mL/kg/min, P < .001).

CONCLUSION: In conclusion, exercise interventions in patients with ICDs and CRT-Ds appear safe and effective. Lack of consensus on design and endpoints remains a barrier to broader application to this important patient population.

RATIONALE: Multiple clinical trials support the effectiveness of cardiac resynchronization therapy (CRT); however, optimal patient selection remains challenging due to substantial treatment heterogeneity among patients who meet the clinical practice guidelines.

OBJECTIVE: To apply machine learning to create an algorithm that predicts CRT outcome using electronic health record (EHR) data avaible before the procedure.

METHODS AND RESULTS: We applied machine learning and natural language processing to the EHR of 990 patients who received CRT at two academic hospitals between 2004-2015. The primary outcome was reduced CRT benefit, defined as <0% improvement in left ventricular ejection fraction (LVEF) 6-18 months post-procedure or death by 18 months. Data regarding demographics, laboratory values, medications, clinical characteristics, and past health services utilization were extracted from the EHR available before the CRT procedure. Bigrams (i.e., two-word sequences) were also extracted from the clinical notes using natural language processing. Patients accrued on average 75 clinical notes (SD, 29) before the procedure including data not captured anywhere else in the EHR. A machine learning model was built using 80% of the patient sample (training and validation dataset), and tested on a held-out 20% patient sample (test dataset). Among 990 patients receiving CRT the mean age was 71.6 (SD, 11.8), 78.1% were male, 87.2% non-Hispanic white, and the mean baseline LVEF was 24.8% (SD, 7.69). Out of 990 patients, 403 (40.7%) were identified as having a reduced benefit from the CRT device (<0% LVEF improvement in 25.2%, death by 18 months in 15.6%). The final model identified 26% of these patients at a positive predictive value of 79% (model performance: Fβ (β = 0.1): 77%; recall 0.26; precision 0.79; accuracy 0.65).

CONCLUSIONS: A machine learning model that leveraged readily available EHR data and clinical notes identified a subset of CRT patients who may not benefit from CRT before the procedure.

Background Regulators increasingly rely on registries for decision making related to high-risk medical devices in the United States. However, the limited uniform standards for registries may create substantial variability in registry implementation and utility to regulators. We surveyed the current landscape of US cardiovascular device registries and chart the extent of inconsistency in goals, administration, enrollment procedures, and approach to data access. Methods and Results A systematic review using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines identified studies (1995-2017) referencing cardiovascular device registries with a US-based institution. Registries were then evaluated by reviewing associated articles and websites. Extracted data included device type, primary scientific aim(s), funding, stewardship (eg, administration of registry procedures), enrollment procedures, informed consent process, and mechanisms to access data for research. The 138 cardiovascular device registries in the cohort covered devices addressing interventional cardiology (65.9%), arrhythmias (15.2%), heart failure (10.1%), and valvular disease (10.1%). While the majority (55.8%) were industry-funded, stewardship was predominantly overseen by academic centers (74.0%). Most registry participation was voluntary (77.5%), but a substantial minority (19.7%) were required as a condition of device implantation. Informed consent requirements varied widely, with written consent required in only 55.1% of registries. Registry data were primarily accessible only to stewards (84.1%), with 13.8% providing pathways for external applications. Conclusions The majority of cardiovascular device registries were funded privately under the auspices of academic institutions, which set the rules for data access. The substantial variation between cardiovascular device registries suggests a role for regulators to further strengthen guidelines to improve quality, consistency, and ethical standards.

BACKGROUND: The risk of death or appropriate therapy varies widely among recipients of implantable cardioverter-defibrillators (ICDs). The goals of this study were to develop a risk prediction tool that jointly considers future outcome probabilities of ICD shock and death.

METHODS AND RESULTS: We performed a secondary analysis of patients receiving ICDs as part of the SCD-HeFT trial (Sudden Cardiac Death in Heart Failure Trial). We applied an illness-death regression model to jointly model both ICD shocks and death under the semi-competing risks framework, which predicts for each patient their probability of having received ICD shocks, dying, or both at any given point in time. Among 803 ICD recipients (mean age, 60 years; 23% women) followed for a median of 41.1 months, 430 (53.5%) patients completed the study without dying or receiving an ICD shock, 206 (25.7%) received at least 1 shock but survived, 113 (14.1%) died before experiencing a shock, and 54 (6.7%) received at least 1 shock and subsequently died. Predicted outcome probabilities based on baseline demographic and clinical variables reveal substantial heterogeneity in joint shock and death risks, both between patients at each time point and for each single patient across time. Overall, predictive performance for ICD shock and death individually was adequate, based on area under the curve at 5 years of 0.65 for shocks and of 0.79 for death.

CONCLUSIONS: Our analysis of outcomes after ICD implantation provides an alternative predictive model for individual risk of death or ICD shocks. If validated, this may provide a useful tool for individualized counseling regarding likely outcomes after device implantation, while also informing the design of further studies to focus the clinical effectiveness and cost-effectiveness of ICD therapy.

CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00000609.

BACKGROUND: Little is known about real-world facility-level preferences for cardiac resynchronization therapy devices with (CRT-D) and without (CRT-P) defibrillator backup. We quantify this variation at the facility level and exploit this variation to compare outcomes of patients receiving these 2 devices.

METHODS AND RESULTS: Claims data from fee-for-service Medicare beneficiaries were used to identify new CRT-P and CRT-D implants, 2006 to 2012. We modeled factors associated with receipt of each device, and compared mortality, hospitalizations, and reoperations for patients receiving each using both logistic regression and instrumental variable analysis to account for confounding. Among 71 459 device recipients (CRT-P, 11 925; CRT-D, 59 534; 31% women), CRT-P recipients were older, more likely to be women, and had more comorbidities. Variation in device selection among facilities was substantial: After adjustment for patient characteristics, the odds of receiving a CRT-P (versus CRT-D) device were 7.6× higher for a patient treated at a facility in the highest CRT-P use quartile versus a facility in the lowest CRT-P use quartile. Logistic modeling suggested a survival advantage for CRT-D devices but with falsification end points indicating residual confounding. By contrast, in the instrumental variable analysis using facility variability as the proposed instrument, clinical characteristics and falsification end points were well balanced, and 1-year mortality in patients who received CRT-P versus CRT-D implants did not differ, while CRT-P patients had a lower probability of hospitalizations and reoperations in the year following implant.

CONCLUSIONS: CRT-P versus CRT-D selection varies substantially among facilities, adjusted for clinical factors. After instrumental variable adjustment for clinical covariates and facility preference, survival was no different between the devices. Therefore, CRT-P may be preferred for Medicare beneficiaries considering new CRT implantation.