[Meta-analysis of obesity on the outcome of rotator cuff repair].
Bibliographic record
Abstract
OBJECTIVE: To systematically evaluate obesity on the outcome of rotator cuff repair. METHODS: Literatures on the relationship between obesity and outcomes after rotator cuff repair were searched from PubMed, Embase, Cochrane Library, Web of Science, China biology medicine(CBM), CNKI, Wanfang and VIP databases from building database to August 1, 2022, and were screened independently by two authors according to inclusion and exclusion criteria. Endnote X9 and Excel 2019 were used for literature extraction, management and data entry, and Newcastle-Ottawa Scale (NOS) was used to evaluate quality of the included literatures. STATA 16.0 and RevMan 5.4 softwares were used to evaluate postoperative retear rate, reoperation rate, complication rate, American Shoulder and Elbow Surgeons (ASES) score, visual analogue scale (VAS), operative time and external rotation angle of shoulder joint pain were analyzed. RESULTS: =0.32]. CONCLUSION: Obesity is associated with higher rates of retear, resurgery, complications, poorer shoulder function and pain after rotator cuff repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.027 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".