Evidence map›Paper›PMID 40757598›Full record

ArticleMuscles (Basel, Switzerland)2024

Hip Muscle Strength Ratios Predicting Groin Injury in Male Soccer Players Using Machine Learning and Multivariate Analysis-A Prospective Cohort Study.

Afxentios Kekelekis, Rabiu Muazu Musa, Pantelis T Nikolaidis, Filipe Manuel Clemente, Eleftherios Kellis

Abstract read
In one paragraph

Article in Muscles (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Adductor-Related Athletic Groin Pain: A Clinical Commentary.International journal of sports physical therapy · 2026
    Article
  4. 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

5 authors.

Afxentios KekelekisLaboratory of Neuromechanics, School of Physical Education and Sport Science at Serres, Aristotle University of Thessaloniki, 62100 Serres, Greece.ORCID 0000-0002-3992-349X
Rabiu Muazu MusaCentre for Fundamental and Continuing Education, Universiti Malaysia Terengganu, Kuala Nerus 21030, Malaysia.ORCID 0000-0001-5332-1770
Pantelis T NikolaidisSchool of Health and Caring Sciences, University of West Attica, 11521 Athens, Greece.ORCID 0000-0001-8030-7122
Filipe Manuel ClementeEscola Superior Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial d Nun'Álvares, 4900-347 Viana do Castelo, Portugal.ORCID 0000-0001-9813-2842
Eleftherios KellisLaboratory of Neuromechanics, School of Physical Education and Sport Science at Serres, Aristotle University of Thessaloniki, 62100 Serres, Greece.ORCID 0000-0002-8179-6340

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite ongoing efforts, the relationship between groin strength and injury remains unclear. The challenge of accurately predicting injuries presents an opportunity for researchers to develop prevention strategies to reduce the occurrence of such injuries. Consequently, this issue requires further investigation to obtain insights into effective mitigation strategies. In 120 male soccer players, the maximum isometric strength of the hip muscle groups was measured, and the strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus.

Indexed as

groin injuryhandheld dynamometerhip muscle strength ratiosinjury predictionmachine learningsoccer

Identifiers

PMID40757598
PMCPMC12225289

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.