Multiple surgical treatment comparisons for irreparable rotator cuff tears: A network meta-analysis
Bibliographic record
Abstract
BACKGROUND: To evaluate the effect of different surgical methods in the treatment of patients with irreparable rotator cuff tears (IRCTs) using a network meta-analysis. METHODS: A search of the PubMed, EMbase, The Cochrane Library, VIP, WanFang Data, and CNKI databases was performed in January 2023 to search for randomized controlled trials and cohort studies of different surgical methods in the treatment of IRCTs. Risk assessment of the included randomized controlled trials was conducted using the risk of bias assessment tool recommended by the Cochrane Manual, and the Newcastle-Ottawa Scale was used for the risk assessment of cohort studies. Data were analyzed and plotted using Stata 15.0 software. RESULTS: A total of 17 studies involving 2123 patients and 10 surgical methods were included in this study. According to the surface under the cumulative ranking curve, the probability ranking in descending order is latissimus dorsi transfer (LDT) + partial repair > LDT > reverse total shoulder arthroplasty > superior capsular reconstruction > patch > partial repair > debridement + tenotomy of the long head of the biceps > debridement > in space subacromial balloon spacer + tenotomy of the long head of the biceps > in space subacromial balloon spacer. CONCLUSION: Among the multiple surgical treatments for patients with IRCTs, LDT + partial repair may have the best effect, and more randomized controlled trials with larger sample sizes are needed for further verification.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".