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Hamstring Injuries in Australian Football

2005· article· en· W2028199924 on OpenAlexaff
Brent Hagel

Bibliographic record

VenueClinical Journal of Sport Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineHamstringHamstring injuryFootballPhysical therapyCohortStraight leg raiseInjury preventionPoison controlPhysical medicine and rehabilitationRange of motionEmergency medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify risk factors for hamstring injury in community-level Australian football players. DESIGN: Cohort study. SETTING: The preseason and 2000 season of 4 adult Victorian Amateur Football Association clubs. PARTICIPANTS: All players in the clubs who were training at the time of the baseline assessment were invited to participate (n = 148). Players who were injured and unable to participate in the baseline assessment were excluded (22 players; 15%). ASSESSMENT OF RISK FACTORS: During 3 weeks before preseason practice, each player had a series of musculoskeletal tests and completed a questionnaire. The musculoskeletal screening included flexibility tests of the hamstrings, lower extremities, quadriceps, and iliopsoas; range of motion assessments of the lumbar spine and hip rotation; and the active slump test of neural mobility. Testing was done after a brief warm up by 4 trained screeners. A questionnaire with pre-established validity and reliability included information on playing experience, injury history, and training habits. MAIN OUTCOME MEASURES: The main outcome measure was a first hamstring injury that resulted in missed participation time and/or treatment from a health professional in relation to predictive factors. Criteria defining a hamstring injury were sudden onset of posterior thigh pain, and tenderness on palpation with or without pain on stretching or contracting the hamstring muscle group. Through the season, the clubs' coaching staff collected information on exposure (hours of match and training participation). MAIN RESULTS: A total of 26 hamstring injuries occurred (incidence, 4 injuries per 1000 player hours). More injuries were sustained during competition (77%) than training. Rapid acceleration during running or sprinting was the primary mechanism of injury (81%), with the remainder occurring as the player kicked the ball. After adjustment for exposure, younger age was associated with a lower relative risk (RR) of injury (RR for age > or =23 years, 3.8; 95% CI, 1.1-14.0), as were quadriceps flexibility (RR for >51 degree knee flexion, 0.3; CI, 0.1-0.8) and active knee extension range of motion (RR for >27 degree knee flexion, 2.8; CI, 0.9-8.5; not significant). Frequency of off-season running, body height, and neural mobility were not significantly associated with hamstring injury. CONCLUSIONS: Hamstring injuries in amateur Australian football players most commonly occurred with sprinting and were more frequent in players older than 23 years or with lesser quadriceps flexibility.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.427
Teacher spread0.364 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations28
Published2005
Admission routes1
Has abstractyes

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