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Record W2152379818 · doi:10.1177/2325967113s00098

Return to Sport Following Arthroscopic Anterior Shoulder Stabilization

2013· article· en· W2152379818 on OpenAlexaboutno aff
Matthew J. Kraeutler, Nick Aberle, Cyndi Long, Eric C. McCarty

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyBasketballReturn to sportAthletesFootballSurgery

Abstract

fetched live from OpenAlex

Objectives: The purpose of this study was to determine the capacity to return to sport and other patient-rated outcomes following arthroscopic shoulder stabilization in a case series comparing upper extremity/contact (UE) and lower extremity (LE) athletes. Methods: Patients who underwent arthroscopic anterior shoulder stabilization by the senior author between November 2006 and November 2010 were contacted for follow up on their return to play and outcomes assessment. Outcomes included a questionnaire that had the Single Assessment Numeric Evaluation (SANE), ASES Shoulder Score, Marx Shoulder Activity Scale, and Western Ontario Shoulder Instability Index (WOSI). Results: The cohort consisted of 48 patients involved in active sports. They identified themselves as participating in a sport around the time of their injury that primarily involved either the upper extremity (n = 35) or lower extremity (n = 13). Contact athletes were grouped with the upper extremity athletes. Upper extremity and contact sports included football, basketball, ice hockey, rock climbing, baseball, volleyball, and weightlifting. Lower extremity sports included running, skiing, snowboarding, mountain biking, and soccer. Average time to follow-up was 37 months (range, 19-79 months) in the UE group and 41 months (range, 18-76 months) in the LE group (p = 0.57). Average age at the time of surgery was 26 years (range, 16-42 years) in the UE group and 29 years (range, 18-45 years) in the LE group (p = 0.33). Twenty-three patients (23/35, 66%) in the UE group and 10 patients (10/13, 77%) in the LE group were able to return to their sport by the time of follow-up (p = 0.39). Average time to return to sport was 6.2 months (range, 3-12 months) in the UE/C group and 7.9 months (range, 3-18 months) in the LE group (p = 0.28). Of those patients able to return to their sport, 16 patients (16/23, 70%) in the UE group and 5 patients (5/10, 50%) in the LE group were able to return to their pre-injury activity level (p = 0.18). The average Marx Activity Scale was 11.9 and 11.5 in the UE and LE groups, respectively (p = 0.72), while the average SANE score was 85 and 87 in the UE and LE groups, respectively (p = 0.53). The average ASES score was 89 in the UE group and 94 in the LE group (p = 0.12). The WOSI score was 23% versus 26% in the UE and LE groups, respectively (p = 0.62). Patients were able to indicate reasons for their inability to return, many had more than one: eight patients did not return secondary to loss of strength, six due to pain, five had a fear of reinjury, 3 cited loss of speed as a reason, and 3 felt a sense of instability. Six patients did not return due to a loss of interest in their sport, or development of a new sport interest. Conclusion: There is no significant difference between upper and lower extremity athletes in terms of return to sport, time to return to sport, or other functional outcomes in this cohort. There may be a trend towards greater return to pre-injury activity level in upper extremity athletes, however further evaluation on a larger sample size is necessary to determine this. Despite high scores on the shoulder outcome measures, the athlete’s rate of return to their sport was only moderate.

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)0.000
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.302
Teacher spread0.286 · 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".

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Citations2
Published2013
Admission routes1
Has abstractyes

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