Evidence map›Paper›PMID 37192797›Full record

ArticleBMJ open2023

Relationship between a daily injury risk estimation feedback (I-REF) based on machine learning techniques and actual injury risk in athletics (track and field): protocol for a prospective cohort study over an athletics season.

Pierre-Eddy Dandrieux, Laurent Navarro, David Blanco, Alexis Ruffault, Christophe Ley, Antoine Bruneau, Joris Chapon, Karsten Hollander, Pascal Edouard

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. 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 5 institutions in 5 countries.

Pierre-Eddy DandrieuxInter-university Laboratory of Human Movement Biology, EA 7424, F-42023, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Saint-Etienne, Auvergne-Rhône-Alpes, France pierre.eddy.dandrieux@univ-st-etienne.fr.ORCID 0000-0001-7230-6728
Laurent NavarroCentre CIS, F-42023, Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, INSERM, U 1059 Sainbiose, Saint-Etienne, Auvergne-Rhône-Alpes, France.ORCID 0000-0002-8788-8027
David BlancoPhysiotherapy Department, Universitat Internacional de Catalunya, Barcelona, Catalunya, Spain.ORCID 0000-0003-2961-9328
Alexis RuffaultLaboratory Sport, Expertise, and Performance (EA 7370), French Institute of Sport (INSEP), Paris, France.ORCID 0000-0001-6610-4169
Christophe LeyDepartment of Mathematics, University of Luxembourg, Esch-sur-Alzette, Luxembourg.ORCID 0000-0002-2290-8437
Antoine BruneauFrench Athletics Federation, Paris, France.
Joris ChaponInter-university Laboratory of Human Movement Biology, EA 7424, F-42023, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Saint-Etienne, Auvergne-Rhône-Alpes, France.ORCID 0009-0004-0640-4185
Karsten HollanderInstitute of Interdisciplinary Exercise Science and Sports Medicine, Medical School Hamburg, Hamburg, Germany.ORCID 0000-0002-5682-9665
Pascal EdouardInter-university Laboratory of Human Movement Biology, EA 7424, F-42023, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Saint-Etienne, Auvergne-Rhône-Alpes, France.ORCID 0000-0003-1969-3612
Université Claude Bernard Lyon 1 · FRMSH Medical School Hamburg – University of Applied Sciences and Medical University · DEUniversitat Internacional de Catalunya · ESUniversity of Liège · BEUniversity of Luxembourg · LU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTwo-thirds of athletes (65%) have at least one injury complaint leading to participation restriction (ICPR) in athletics (track and field) during one season. The emerging practice of medicine and public health supported by electronic processes and communication in sports medicine represents an opportunity for developing new injury risk reduction strategies. Modelling and predicting the risk of injury in real-time through artificial intelligence using machine learning techniques might represent an innovative injury risk reduction strategy. Thus, the primary aim of this study will be to analyse the relationship between the level of METHOD AND ANALYSIS: We will conduct a prospective cohort study, called ETHICS AND DISSEMINATION: This prospective cohort study was reviewed and approved by the Saint-Etienne University Hospital Ethical Committee (Institutional Review Board: IORG0007394, IRBN1062022/CHUSTE). Results of the study will be disseminated in peer-reviewed journals and in international scientific congresses, as well as to the included participants.

Indexed as

Athletic InjuriesTrack and FieldArtificial IntelligenceFeedbackHumansMachine LearningProspective StudiesSeasonsEPIDEMIOLOGYPUBLIC HEALTHSPORTS MEDICINE

Identifiers

PMID37192797
PMCPMC10193054
OpenAlexW4376870999

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.