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Record W4229447811 · doi:10.1097/jsa.0000000000000345

The Influence of Athletes’ Age in the Onset of Osteoarthritis: A Systematic Review

2022· review· en· W4229447811 on OpenAlexaboutno aff
Filippo Migliorini, Gianluca Vecchio, Andrea Pintore, Francesco Oliva, Nicola Maffulli

Bibliographic record

VenueSports Medicine and Arthroscopy Review · 2022
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAthletesPhysical therapyOsteoarthritisSystematic reviewMEDLINEGerontologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

PURPOSE: Whether sport participation is a risk factor for osteoarthritis (OA) development or progression is controversial. Mechanical overload, injuries, genetics, and acquired disorders concur to the onset of OA, with high variability between sports and participants. This study investigated the association between participation in specific sports and the risk of developing knee and hip OA in athletes at different ages. We hypothesized that young athletes who are exposed to high levels of physical activities have a greater risk of developing OA. MATERIALS AND METHODS: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Google scholar, EMABSE, and Web of Science were accessed in October 2021. No time constrains were used for the search. All the published clinical studies reporting data about relationship between physical activity, OA, and age were included. RESULTS: The Newcastle-Ottawa Scale resulted in a final score ≥7 for all studies, attesting good quality of the methodological assessment. Data from 27,364 patients were retrieved. The mean age was 48.2±16.7 years. In all, 21.8% were women. CONCLUSIONS: Our systematic review suggests an association between high levels of physical activities and knee and hip OA in men younger than 50 years. People who practice intense physical activity, such as professional athletes or heavy workers, are more prone to develop early-onset OA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.338
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2022
Admission routes1
Has abstractyes

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