[Clinical effects of arthroscopy-assisted anterior cruciate ligament tibial eminence avulsion fracture compared with traditional open surgery:a Meta-analysis].
Bibliographic record
Abstract
OBJECTIVE: To systematically evaluate the clinical efficacy of arthroscopy and traditional incision in the treatment of tibial avulsion fracture of anterior cruciate ligament (ACL). METHODS: From July 2010 to July 2020, clinical comparative trial about arthroscopy and traditional incision in the treatment of ACL tibial avulsion fracture was conducted by using computer-based databases, including Embase, Pubmed, Central, Cinahl, PQDT, CNKI, Weipu, Wanfang, Cochrane Library, CBM. Literature screening and data extraction were carried out according to the inclusion and exclusion criteria, and the quality of the included literature was evaluated by improved Jadad score and Ottawa Newcastle scale (NOS). The operation time, hospital stay, fracture healing time, knee range of motion, postoperative excellent and good rate, complication rate, Lysholm score, International Knee Documentation Committee (IKDC) score and Tegner score were statistically analyzed by Review Manager 5.3 software. RESULTS: <0.001] in the arthroscopic group were higher than those in the traditional incision group. CONCLUSION: Compared with the traditional open reduction and internal fixation, arthroscopic surgery in patients with ACL tibial avulsion fracture can shorten the operation time, hospital stay and fracture healing time, reduce the incidence of postoperative complications, and obtain good postoperative knee function. It can be recommended as one of the first choice for patients with ACL tibial avulsion fracture.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.035 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".