Considerations of Throwing Athletes With Upper Extremity Injury When Completing the Single Assessment Numeric Evaluation (SANE): A Report From the Athletic Training Practice-Based Research Network
Bibliographic record
Abstract
CONTEXT: The Single Assessment Numeric Evaluation (SANE) is a widely used patient-reported outcome (PRO) measure that provides an efficient but limited view of patient perceptions of health. Knowledge of what throwing athletes with upper extremity injury consider when answering the SANE would inform score interpretation and increase its value for clinical decision-making in this patient population. OBJECTIVE: To investigate the global rating of the SANE and its ability to capture constructs of health reflected in PRO measures that are commonly used in throwing athletes with upper extremity sport-related injury. DESIGN: Cross-sectional study. SETTING: Retrospective database review. PATIENTS OR OTHER PARTICIPANTS: De-identified patient records of baseball and softball athletes diagnosed with upper extremity sport-related injury between October 2009 and June 2021 were reviewed. MAIN OUTCOME MEASURE(S): Primary outcomes were scores on the SANE; Functional Arm Scale for Throwers total; Disabilities of the Arm, Shoulder, and Hand total; and Global Rating of Daily Activities. The first administration of all PROs that patients completed postinjury was analyzed as a potential predictor of SANE scores. The proportion of variance uniquely accounted for in the SANE by each predictor (R2) variable was estimated. RESULTS: Fifty-five patients completed PRO measures. The Functional Arm Scale for Throwers total uniquely accounted for 32.9% (P < .001), the Global Rating of Daily Activities uniquely accounted for 11.6% (P < .001), and the Disabilities of the Arm, Shoulder, and Hand total uniquely accounted for 4.6% (P = .036) of the variance in the SANE score. Overall, the predictors accounted for 49.2% of the variance in the SANE score (P < .001). CONCLUSIONS: Given that the SANE captures multiple constructs of health, it may be useful in gathering a quick, broad view of throwing athletes' perception of their health. When SANE scores suggest diminished health, then multi-item PROs should be considered to further explore constructs of health most affected.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".