Evidence map›Paper›PMID 37071626›Full record

ArticlePloS one2023

Epidemiology and patients' self-reported knowledge of implantable medical devices: Results of a cross-sectional survey in Hungary.

Áron Hölgyesi, Barbara Tóth, Miklós Kozlovszky, József Kuti, Miklós Weszl, György Balázs, Petra Baji, Levente Kovács, László Gulácsi, Zsombor Zrubka and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
8.3field-weighted citation impact, top 2% of its field
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

7 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
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  4. Population norms for the EQ-5D-5L for Hungary: comparison of online surveys and computer assisted personal interviews.The European journal of health economics : HEPAC : health economics in prevention and care · 2025
    Article
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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

11 authors at 3 institutions in 2 countries.

Áron HölgyesiDoctoral School of Molecular Medicine, Semmelweis University, Budapest, Hungary.ORCID 0000-0001-8131-2839
Barbara TóthDoctoral School of Applied Informatics and Applied Mathemathics, Óbuda University, Budapest, Hungary.
Miklós KozlovszkyBioTech Research Center, Óbuda University, Budapest, Hungary.
József KutiAntal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary.
Miklós WeszlDepartment of Translational Medicine, Semmelweis University, Budapest, Hungary.
György BalázsEMKI-CERT Ltd., Budapest, Hungary.
Petra BajiDepartment of Health Economics, Corvinus University of Budapest, Budapest, Hungary.
Levente KovácsPhysiological Controls Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.ORCID 0000-0002-3188-0800
László GulácsiHealth Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.
Zsombor ZrubkaHealth Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.ORCID 0000-0002-1992-6087
Márta PéntekDoctoral School of Molecular Medicine, Semmelweis University, Budapest, Hungary.ORCID 0000-0001-9636-6012
Obuda University · HUSemmelweis University · HUCorvinus University of Budapest · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImplantable medical devices (IMDs) are medical instruments embedded inside the body. Well-informed and empowered patients living with IMDs are key players of improving IMD-related patient safety and health outcomes. However, little is known about IMD patients' epidemiology, characteristics, and current awareness levels. Our primary aim was to investigate the point and lifetime prevalence of patients living with IMDs. Patients' IMD-related knowledge and determinants of IMDs' impact on their life were also explored.

methodsAn online cross-sectional survey was conducted. Respondents' IMD history, whether they received instructions for use and IMD's overall impact on life were recorded by self-reports. Patients' knowledge about living with IMDs was assessed on visual analogue scales (VAS, 0-10). Shared decision-making was analyzed by the 9-item Shared Decision Making Questionnaire (SDM-Q-9). Descriptive statistics and subgroup comparisons between IMD wearers were performed for statistical differences. Significant determinants of IMD's overall impact on life were examined in linear regression analysis.

resultsIn the total sample (N = 1400, mean age 58.1 ±11.1; female 53.7%), nearly one third of respondents were living with IMD (30.9%; 433/1400). Among them, the most frequent IMDs were tooth implants (30.9%) and intraocular lens (26.8%). Mean knowledge VAS scores were similar (range: 5.5 ±3.8-6.5 ±3.2) but differences by IMD types were observed. Patients who received instructions for use or reported better impact on life indicated higher self-reported knowledge. Regression confirmed that patients' knowledge was significant predictor of IMD's impact on life, but this effect was overwritten by the SDM-Q-9.

conclusionsThis first comprehensive epidemiological study on IMDs provides basic data for public health strategy planning alongside the implementation of MDR. Improved self-perceived outcomes were associated with higher knowledge hence education of patients receiving IMD deserves consideration. We suggest to investigate further the role of shared decision-making on IMD's overall impact on patients' life in future prospective studies.

Indexed as

Decision Making, SharedEye, ArtificialAgedCross-Sectional StudiesFemaleHumansHungaryMiddle AgedSelf Report

Identifiers

PMID37071626
PMCPMC10112797
OpenAlexW4366240467

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.