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Record W2797747249 · doi:10.1177/0363546518760573

Risk Factors for Elbow and Shoulder Injuries in Adolescent Baseball Players: A Systematic Review

2018· review· en· W2797747249 on OpenAlexaboutno aff
R Norton, Christopher Honstad, Rajat Joshi, Matthew Silvis, Vernon M. Chinchilli, Aman Dhawan

Bibliographic record

VenueThe American Journal of Sports Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsThrowingElbowMedicinePhysical therapyRange of motionSports medicinePhysical medicine and rehabilitationSurgeryEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: The incidence of shoulder and elbow injuries among adolescent baseball players is on the rise. These injuries may lead to surgery or retirement at a young age. PURPOSE: To identify independent risk factors for elbow and shoulder injuries in adolescent baseball players. A secondary aim was to determine whether the literature supports the Major League Baseball and USA Baseball Pitch Smart guidelines. STUDY DESIGN: Systematic review. METHODS: A systematic review was performed in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines utilizing MEDLINE, SPORTDiscus, and Web of Science. Because of study heterogeneity, a quantitative synthesis was not performed. A qualitative review was performed on 19 independent risk factors for elbow and shoulder injuries in adolescent baseball players. Level of evidence was assigned per the Oxford Centre for Evidence-Based Medicine Working Group, and risk of bias was graded per the Newcastle-Ottawa Scale. RESULTS: Twenty-two articles met criteria for inclusion. Of the 19 independent variables that were analyzed, age, height, playing for multiple teams, pitch velocity, and arm fatigue were found to be independent risk factors for throwing arm injuries. Pitches per game appears to be a risk factor for shoulder injuries. Seven independent variables (innings pitched per game, showcase participation, games per year, training days per week, pitch type, shoulder external rotation, and shoulder total range of motion) do not appear to be significant risk factors. The data were inconclusive for the remaining 6 variables (weight, months of pitching per year, innings or pitches per year, catching, shoulder horizontal adduction, and glenohumeral internal rotation deficit). CONCLUSION: The results from this study demonstrate that age, height, playing for multiple teams, pitch velocity, and arm fatigue are clear risk factors for throwing arm injuries in adolescent baseball players. Pitches per game appears to be a risk factor for shoulder injuries. Other variables are either inconclusive or do not appear to be specific risk factors for 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 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)0.003
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 score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.052
GPT teacher head0.379
Teacher spread0.327 · 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

Citations96
Published2018
Admission routes1
Has abstractyes

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