Evidence map›Paper›PMID 37041065›Full record

ArticleBMJ open2023

Clinical evidence for high-risk medical devices used to manage diabetes: protocol for a systematic review and meta-analysis.

Arjola Bano, Markus Laimer, Faina Wehrli, Juri Kunzler, Tania Rivero, Alan G Fraser, Christoph Stettler, Roman Hovorka, Lia Bally

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. A European regulatory pathway for Tidepool loop following clearance in the United States?Diabetic medicine : a journal of the British Diabetic Association · 2024
    Article
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

9 authors at 3 institutions in 4 countries.

Arjola BanoDepartment of Cardiology, Inselspital, Bern University Hospital, Bern, Switzerland arjola.bano@ispm.unibe.ch.ORCID 0000-0003-0956-7145
Markus LaimerDepartment of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.
Faina WehrliDepartment of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.
Juri KunzlerDepartment of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.
Tania RiveroMedical Library, University Library of Bern, University of Bern, Bern, Switzerland.
Alan G FraserDepartment of Cardiology, University Hospital of Wales, Cardiff, UK.
Christoph StettlerDepartment of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.
Roman HovorkaWellcome Trust, MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK.
Lia BallyDepartment of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.ORCID 0000-0003-1993-7672
University of Bern · CHUniversity Hospital of Wales · GBWellcome/MRC Institute of Metabolic Science · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMedical devices, including high-risk medical devices, have greatly contributed to recent improvements in the management of diabetes. However, the clinical evidence that is submitted for regulatory approval is not transparent, and thus a comprehensive summary of the evidence for high-risk devices approved for managing diabetes in Europe is lacking. In the framework of the Coordinating Research and Evidence for Medical Devices group, we will, therefore, perform a systematic review and meta-analysis, which will evaluate the efficacy, safety and usability of high-risk medical devices for the management of diabetes. METHOD AND ANALYSIS: This study has been reported according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. We will search Embase (Elsevier), Medline All (Ovid), Cochrane Library (Wiley), Science Citation Index Expanded and Emerging Sources Citation Index (Web of Science) to identify interventional and observational studies that evaluate the efficacy and/or safety and/or usability of high-risk medical devices for the management of diabetes. No language or publication dates' limits will be applied. Animal studies will be excluded. In accordance with the Medical Device Regulation in European Union, high-risk medical devices are those in classes IIb and III. The following medical devices for diabetes management are considered as having a high risk: implantable continuous glucose monitoring systems, implantable pumps and automated insulin delivery devices. Selection of studies, data extraction and quality of evidence assessment will be performed independently by two researchers. Sensitivity analysis will be performed to identify and explain potential heterogeneity. ETHICS AND DISSEMINATION: No ethical approval is needed for this systematic review, as it is based in already published data. Our findings will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42022366871.

Indexed as

Blood Glucose Self-MonitoringDiabetes Mellitus, Type 2Blood GlucoseHumansMeta-Analysis as TopicSystematic Reviews as TopicBlood GlucoseDIABETES & ENDOCRINOLOGYEPIDEMIOLOGYGeneral diabetesGeneral endocrinology

Identifiers

PMID37041065
PMCPMC10106051
OpenAlexW4364374342

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.