Evidence map›Paper›PMID 36652105›Full record

ArticleTherapeutic innovation & regulatory science2023

Validation of CORE-MD PMS Support Tool: A Novel Strategy for Aggregating Information from Notices of Failures to Support Medical Devices' Post-Market Surveillance.

Yijun Ren, Michele Bertoldi, Alan G Fraser, Enrico Gianluca Caiani

Abstract read
In one paragraph

Article in Therapeutic innovation & regulatory science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 citing papers in PubMed.

  1. Article
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  3. Clinical significance of field safety notices concerning implantable pacemakers and defibrillators.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026
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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

4 authors.

Yijun RenDepartment of Electronics, Information and Biomedical Engineering, Politecnico di Milano, Milan, Italy.
Michele BertoldiDepartment of Electronics, Information and Biomedical Engineering, Politecnico di Milano, Milan, Italy.
Alan G FraserDepartment of Cardiology, University Hospital of Wales, Wales, CF14 4XW, UK.
Enrico Gianluca CaianiDepartment of Electronics, Information and Biomedical Engineering, Politecnico di Milano, Milan, Italy. enrico.caiani@polimi.it.ORCID 0000-0002-1770-6486

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe EU Medical Device Regulation 2017/745 defines new rules for the certification and post-market surveillance of medical devices (MD), including an additional review by Expert Panels of clinical evaluation data for high-risk MD if reports and alerts suggest possibly associated increased risks. Within the EU-funded CORE-MD project, our aim was to develop a tool to support such process in which web-accessible safety notices (SN) are automatically retrieved and aggregated based on their specific MD categories and the European Medical Device Nomenclature (EMDN) classification by applying an Entity Resolution (ER) approach to enrich data integrating different sources. The performance of such approach was tested through a pilot study on the Italian data.

methodsInformation relevant to 7622 SN from 2009 to 2021 was retrieved from the Italian Ministry of Health website by Web scraping. For incomplete EMDN data (68%), the MD best match was searched within a list of about 1.5 M MD on the Italian market, using Natural Language Processing techniques and pairwise ER. The performance of this approach was tested on the 2440 SN (32%) already provided with the EMDN code as reference standard.

resultsThe implemented ER method was able to correctly assign the correct manufacturer to the MD in each SN in 99% of the cases. Moreover, the correct EMDN code at level 1 was assigned in 2382 SN (97.62%), at level 2 in 2366 SN (96.97%) and at level 3 in 2329 SN (95.45%).

conclusionThe proposed approach was able to cope with the incompleteness of the publicly available data in the SN. In this way, grouping of SN relevant to a specific MD category/group/type could be used as possible sentinel for increased rates in reported serious incidents in high-risk MD.

Indexed as

Pilot ProjectsItalyMedical device regulationMedical devicesNatural language processingPost-market surveillanceSafety signal detectionWeb scraping

Identifiers

PMID36652105
PMCPMC10133046

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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.