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Record W4210927655 · doi:10.1080/00913847.2022.2040890

Rhythmic gymnasts’ injuries in a pediatric sports medicine clinic in the United States: a 10-year retrospective chart review

2022· article· en· W4210927655 on OpenAlexaboutno aff
Reeti K. Gulati, Karen Rychlik, Jacob Wild, Cynthia R. LaBella

Bibliographic record

VenueThe Physician and Sportsmedicine · 2022
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsnot available
Fundersnot available
KeywordsSports medicineChartRhythmMedicineRhythmic gymnasticsRetrospective cohort studyPhysical therapyAthletesPoison controlMedical emergencyEmergency medicinePhysical medicine and rehabilitationPediatricsPsychologySurgeryInternal medicineStatisticsMathematics

Abstract

fetched live from OpenAlex

OBJECTIVES: Rhythmic gymnastics injuries have not been studied thoroughly especially in the United States. Existing research studies are predominantly from Europe or Canada or from more than 15 years ago. The purpose of our study was to provide an updated description of injury patterns among rhythmic gymnasts in the United States. METHODS: A retrospective chart review was conducted of 193 rhythmic gymnastics injuries in 79 females, ages 6-20. Patients were seen between January 2010 and March 2020 in a hospital-based pediatric sports medicine clinic. Gymnast demographics, injury locations, and injury types were collected as available. Descriptive and bivariate statistical analysis was performed using general linear mixed models. RESULTS: 2.61 years. Overuse injuries (76.7%) were more common than acute injuries (23.3%). The most common injury types were strain (20.7%), nonspecific pain (15.5%), and tendinitis/tenosynovitis (10.36%). The most frequently injured body regions were lower extremity (75.1%), followed by trunk/back (19.2%), upper extremity (4.7%), and head/neck (1.0%). The most common injured body parts were foot (24.9%), ankle (15.5%), knee (15.0%), lower back (14.0%), and hip (13.0%). General linear mixed models revealed that older age (p = 0.001) and higher competitive level (p = 0.016) were associated with a greater number of diagnoses. Gymnasts with foot injuries were older than gymnasts with ankle (p = 0.026), hip (p < 0.0001), and knee (p = 0.002) injuries. Gymnasts with higher BMI-for-age percentile were more likely to have acute injuries than overuse (p = 0.035). CONCLUSION: Our data showed that injuries among rhythmic gymnasts were most frequently located in the lower extremities, specifically the foot, followed by trunk/back. Additionally, the most frequent injury types were strains and nonspecific pain, and overuse was the most prevalent mechanism. Gymnasts with foot injuries were older than gymnasts with ankle, hip, and knee injuries. Higher BMI is a predictor of acute injuries.

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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.296
Teacher spread0.282 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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