Validation of the Polish version of the Western Ontario Rotator Cuff Index in patients following arthroscopic rotator cuff repair
Bibliographic record
Abstract
BACKGROUND: The Western Ontario Rotator Cuff Index (WORC) is a joint specific outcome tool that assesses the quality of life in patients with various rotator cuff problems. Our purpose was to evaluate selected psychometric characteristics (internal consistency, validity, reliability and agreement) of the Polish version of WORC in patients undergoing rotator cuff repair. METHODS: Sixty-nine subjects took part in the study with a mean age 55.5 (range 40-65). All had undergone arthroscopic rotator cuff repair in 2015-2016. Data from 57 patients in whom symptoms in the shoulder joint had not changed within 10-14 days were analyzed in a WORC test-retest using the Intraclass Correlation Coefficient (ICC), Standard Error of Measurement (SEM) and Minimal Detectable Change (MDC). WORC was compared to the short version of the Disabilities of Arm, Shoulder and Hand Questionnaire (QuickDash) and the Short Form-36 v. 2.0 (SF-36). RESULTS: High internal consistency of 0.94 was found using Cronbach's alpha coefficient. Reliability of the WORC resulted in ICC = 0.99, agreement assessed with SEM and MDC amounted to 1.62 and 4.48 respectively. The validity analysis of WORC showed strong correlations with QuickDash and SF-36 PCS (Physical Component Summary), while moderate with SF-36 MCS (Mental Component Summary). WORC had no floor or ceiling effect. CONCLUSIONS: The Polish version of the WORC is a reliable and valid tool with high internal consistency for assessing the quality of life in patients undergoing arthroscopic rotator cuff repair.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".