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Record W2323271884 · doi:10.1177/2325967114s00023

Aircast Award for Basic Science - Return to Play Following In-season Anterior Shoulder Instability: A Prospective Multicenter Study

2014· article· en· W2323271884 on OpenAlexaboutno aff
Jonathan F. Dickens, Brett D. Owens, Kenneth L. Cameron, Kelly G. Kilcoyne, C. Dain Allred, Steven J. Svoboda, Robert T. Sullivan, John M. Tokish, Karen Y. Peck, John Paul Rue

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSubluxationMedicineAthletesPhysical therapyAnterior shoulderRehabilitationElbowObservational studyPhysical medicine and rehabilitationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Objectives: There is no consensus on the optimal treatment of young in-season athletes with anterior shoulder instability and limited data are available to guide return to play and treatment. The purpose of this study was to examine the likelihood of return to sport following an in-season shoulder instability event based on the type of instability (subluxation vs. dislocation). Additionally, injury factors and patient reported outcome scores administered at the time of injury were evaluated to assess the predictability of eventual successful return to sport and time to return sport during the competitive season following injury. Methods: Over two academic years, 45 contact intercollegiate athletes were prospectively enrolled in a multicenter observational study to assess return to play following in-season anterior glenohumeral instability. The primary outcomes of interest were the ability to return to sport and time lost from sport following an acute anterior shoulder instability event. Baseline data collection included sport played, previous instability events, direction of instability, and type of instability (subluxation or dislocation). Patient reported outcome scores specific to the shoulder were obtained at the time of injury and included the Western Ontario Shoulder Instability Index (WOSI), Single Assessment Numeric Evaluation (SANE), Simple Shoulder Test (SST), and American Shoulder and Elbow Score (ASES). All observed patients underwent a standardized accelerated rehabilitation program without shoulder immobilization, following the initial shoulder instability event. Subjects were followed during the course of their competitive season to determine return to play success and recurrent instability. Results: Thirty-three of 45 (73%) athletes returned to sport for either all or part of the season after a median 5 days lost from competition (IQR=13)(Fig 1). Of the 33 athletes returning to in-season sport following an instability event, 63% (22/33) completed the season. Athletes with a subluxation were 5.3 times more likely (OR=5.32, 95%CI: 1.00, 28.07, p=0.049) to return to sport following an initial in-season shoulder instability event when compared to those with dislocations. Logistic regression analysis suggests that the WOSI (OR=1.05; 95% CI 1.00, 1.09; p=0.037) and SST (OR=1.03, 95% CI 1.00, 1.05; p=0.044) administered after the initial instability event are predictive of ability to return to play . For every 1 point higher the WOSI scaled score at the time of injury, the athlete was 5% more likely to return to play during the same season. Time loss from sport following a shoulder instability event was inversely correlated with the WOSI (p=0.039), SST (p=0.007), and ASES (p=0.02) scores at the time of initial injury. The SST demonstrated the strongest correlation with time lost from sport, and for every 10 points higher the SST scale score was at the time of injury an athlete returned to sport 1.2 (95%CI: 0.4, 1.9) days sooner (p=0.004). Based on the logistic regression analysis, time lost from sport is predicted using the SST score after the initial instability event (Table 1). Conclusion: In the largest prospective study evaluating shoulder instability in mid-season contact athletes, we demonstrate that 73% of athletes return to play after one week. While the majority of athletes who return to sport complete the season, recurrent instability events are common regardless of whether the initial injury was a subluxation or dislocation.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.019
GPT teacher head0.328
Teacher spread0.309 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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