Full‐Thickness Rotator Cuff Tears: What Is the Rate of Tear Progression? A Systematic Review
Bibliographic record
Abstract
PURPOSE: To systematically review the literature and determine the rate of radiographic tear progression of nonoperatively treated full-thickness rotator cuff tears. METHODS: The PubMed, Embase, and Cochrane Library databases were systematically reviewed to identify all articles related to nonoperatively treated rotator cuff tears. English-language studies of Level I through IV evidence examining chronic, full-thickness rotator cuff tears in adults were included. Partial-thickness tears were excluded. Rotator cuff tears were analyzed according to the presence or absence of symptoms. The primary outcome was radiographic tear progression defined as an increase in tear size of 5 mm or greater on magnetic resonance imaging or ultrasound. RESULTS: Eight studies were included for statistical analysis, and 411 tears were analyzed for progression. No difference in the rate of tear progression was detected between the asymptomatic and symptomatic groups (40.6% at 46.8 months and 34.1% at 37.8 months, respectively; P = .65). Calculation of the number needed to treat showed that for an 8% retear rate at 2-year follow-up, approximately 7 patients with rotator cuff tears would have to undergo operative repair to prevent 1 tear from progressing radiographically. CONCLUSIONS: This study showed that with the data available, asymptomatic and symptomatic rotator cuff tears carry similar rates of tear progression over time. Most of these tears will not progress significantly over short- to intermediate-term follow-up. LEVEL OF EVIDENCE: Level IV, systematic review of Level I through IV evidence.
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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 | 0.023 | 0.131 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".