Complications and failure modes of polymer-jacketed guidewires; insights from the MAUDE database

Assessing the Reproducibility of Research Based on the Food and Drug Administration Manufacturer and User Facility Device Experience Data

OBJECTIVE

This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes.

METHODS

Studies using MAUDE data were sourced from PubMed by searching for "MAUDE" or "Manufacturer and User Facility Device Experience" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow.

RESULTS

As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107).

CONCLUSIONS

Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.

Device entrapment during percutaneous coronary intervention

INTRODUCTION

Device entrapment is a life-threatening complication during percutaneous coronary intervention (PCI). However, the success for its management is predominantly based on operator experience with limited available guidance in the published literature.

METHODS

A systematic review was performed on December 2021; we searched PubMed for articles on device entrapment during PCI. In addition, backward snowballing (i.e., review of references from identified articles and pertinent reviews) was employed.

RESULTS

A total of 4209 articles were retrieved, of which 150 studies were included in the synthesis of the data. A methodical algorithmic approach to prevention and management of device entrapment can help to optimize outcomes. The recommended sequence of steps are as follows: (a) pulling, (b) trapping, (c) snaring, (d) plaque modification, (e) telescoping, and (f) surgery.

CONCLUSIONS

In-depth knowledge of the techniques and necessary tools can help optimize the likelihood of successful equipment retrieval and minimization of complications.