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Updated: May 12, 2026

Monitoring the Wall Mechanics During Stent Deployment in a Vessel
Published on: May 8, 2012
Device-related patient outcomes for coronary stents: A MAUDE database analysis
Zihan Gao1, Willie Lei2, Eleanor Gao3
1David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Abstract:
The growing prevalence of coronary artery diseases in the US corresponds to the increasing use of minimally invasive techniques that require coronary stents. Although extensive research is available on the perioperative outcomes of the 3 stent options - bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable drug-eluting stents (BVS), a knowledge gap exists in the longitudinal monitoring of patient outcomes due to device-related causes. Therefore, our study examines the device-related patient outcome and the relative performance for BMS, DES, and BVS. Data on 3 device outcomes (deaths, injuries, and malfunction) for each stent type was obtained from the January 2011 to February 2020 Manufacturer and User Facility Device Experience (MAUDE) database. Statistical visualizations and analysis were used to identify trends and significant differences between groups. Of a total of 68,618 adverse event reports, DES, BMS, and BVS each accounted for 88.5 %, 10.2 %, and 1.25 % of the cases, respectively. Device malfunctions were the most reported event (47.2 %), followed by injuries (44.1 %) and deaths (8.66 %). Over time, BMS malfunction rates showed a steady decrease (R = -0.87), while DES malfunction rates increased significantly (R = 0.79). An inversely proportional relationship between DES injuries and malfunctions was observed. The increase in DES malfunctions was 4 times greater than the decrease in BMS malfunctions. Approximately 7 % of reported adverse events were classified as misreported, with most involving DES. These results suggest 2 plausible interpretations: 1) reporting categorization for devices shifted from injuries to malfunction, and 2) stents choice is transitioning from BMS to DES. Our findings also highlight the need to improve reporting accuracy for MAUDE database data.
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