One‐Year Follow‐Up Is Sufficient Time for Patient‐Reported Outcomes Following Rotator Cuff Repair: A Systematic Review and Meta‐analysis
Bibliographic record
Abstract
PURPOSE: To perform a systematic review to determine whether there were clinically significant differences in patient-reported outcome measures from 1- to 2-year follow-up following rotator cuff repair (RCR). METHODS: A literature search of 3 databases was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Randomized controlled trials (RCTs) reporting on patient-reported outcomes at the 1- and 2-year follow-up following RCR were included. Meta-analysis was performed, and a P value <.05 was considered statistically significant. RESULTS: Nineteen randomized controlled trials with 2,110 patients were included. There was a statistically significant difference in American Shoulder and Elbow Score score between the 1-year (mean, 87) and 2-year (mean, 89.4) follow-up (P < .00001), but this did not reach the minimal clinically important difference. There was no statistically significant difference in visual analog scale pain score between the 1-year (mean, 0.9) and 2-year (mean, 0.8) follow-up (P = .10). Additionally, the differences in Simple Shoulder Test; University of California, Los Angeles score; Constant score; and Western Ontario Rotator Cuff index between the 1- and 2-year follow-up did not reach the minimal clinically important difference despite statistically significant differences. CONCLUSIONS: Statistically significant differences in patient-reported outcomes are reported between the 1- and 2-year follow-up points, although these differences fail to reach minimally clinically important differences. As a result, the 1-year follow-up may be sufficient to determine clinical outcomes from RCR. LEVEL OF EVIDENCE: Level II, systematic review of Level I and II studies.
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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 | 0.033 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.052 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".