Evidence map›Paper›PMID 26060416›Full record

ArticleMedical devices (Auckland, N.Z.)2015

Post-market clinical research conducted by medical device manufacturers: a cross-sectional survey.

Joseph S Ross, Katrina L Blount, Jessica D Ritchie, Beth Hodshon, Harlan M Krumholz

Abstract read
In one paragraph

Article in Medical devices (Auckland, N.Z.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Joseph S RossCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA.
Katrina L BlountCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA.
Jessica D RitchieCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA.
Beth HodshonCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA.
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA.

Funding

FDA HHS U01 FD004585
6 · The paper itself

Abstract

backgroundIn 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

resultsWe 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.

conclusionMedical 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.

Indexed as

FDAPMA pathwaypost-market surveillance

Identifiers

PMID26060416
PMCPMC4454210

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.