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Record W2943641519 · doi:10.1177/0363546519837666

Clinical Outcomes After Anterior Shoulder Stabilization in Overhead Athletes: An Analysis of the MOON Shoulder Instability Consortium

2019· article· en· W2943641519 on OpenAlexaboutno aff
Thai Q. Trinh, Micah Naimark, Asheesh Bedi, James E. Carpenter, Christopher Robbins, John A. Grant, Shannon F. Ortiz, Matthew Bollier, John E. Kuhn, Charles L. Cox, C. Benjamin, Brain T. Feeley, Alan L. Zhang, Eric C. McCarty, Jonathan T. Bravman, Julie Y. Bishop, Grant L. Jones, Robert H. Brophy, Rick W. Wright, Matthew V. Smith, Robert G. Marx, Keith M. Baumgarten, Brian R. Wolf, Carolyn M. Hettrich

Bibliographic record

VenueThe American Journal of Sports Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
FundersOrthopaedic Research and Education Foundation
KeywordsMedicineAthletesAnterior shoulderPhysical therapyElbowUnivariate analysisDashSurgeryMultivariate analysisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Traumatic anterior shoulder instability is a common condition affecting sports participation among young athletes. Clinical outcomes after surgical management may vary according to patient activity level and sport involvement. Overhead athletes may experience a higher rate of recurrent instability and difficulty returning to sport postoperatively with limited previous literature to guide treatment. PURPOSE: To report the clinical outcomes of patients undergoing primary arthroscopic anterior shoulder stabilization within the Multicenter Orthopaedic Outcomes Network (MOON) Shoulder Instability Consortium and to identify prognostic factors associated with successful return to sport at 2 years postoperatively. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: Overhead athletes undergoing primary arthroscopic anterior shoulder stabilization as part of the MOON Shoulder Instability Consortium were identified for analysis. Primary outcomes included the rate of recurrent instability, defined as any patient reporting recurrent dislocation or reoperation attributed to persistent instability, and return to sport at 2 years postoperatively. Secondary outcomes included the Western Ontario Shoulder Instability Index and Kerlan-Jobe Orthopaedic Clinic Shoulder and Elbow questionnaire score. Univariate regression analysis was performed to identify patient and surgical factors predictive of return to sport at short-term follow-up. RESULTS: A total of 49 athletes were identified for inclusion. At 2-year follow-up, 31 (63%) athletes reported returning to sport. Of those returning to sport, 22 athletes (45% of the study population) were able to return to their previous levels of competition (nonrefereed, refereed, or professional) in at least 1 overhead sport. Two patients (4.1%) underwent revision stabilization, although 14 (28.6%) reported subjective apprehension or looseness. Age ( P = .87), sex ( P = .82), and baseline level of competition ( P = .37) were not predictive of return to sport. No difference in range of motion in all planes ( P > .05) and Western Ontario Shoulder Instability Index scores (78.0 vs 80.1, P = .73) was noted between those who reported returning to sport and those who did not. CONCLUSION: Primary arthroscopic anterior shoulder stabilization in overhead athletes is associated with a low rate of recurrent stabilization surgery. Return to overhead athletics at short-term follow-up is lower than that previously reported for the general athletic population.

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)0.005
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
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 head0.028
GPT teacher head0.367
Teacher spread0.340 · 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

Citations29
Published2019
Admission routes1
Has abstractyes

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