All-inside versus inside-out suture techniques in arthroscopic meniscus repair
Bibliographic record
Abstract
BACKGROUND: With advancements in our understanding of meniscal function, treatment options for meniscal injuries have evolved considerably over the past few decades. The aim of the current study was to compare the all-inside and inside-out techniques with regard to retear rate, functional outcomes, and perioperative complications in patients who had undergone arthroscopic meniscus repair. We hypothesized that there was no significant difference between the 2 groups in terms of postoperative outcomes after arthroscopic meniscus repair. METHODS: This study was a prospective randomized blinded study, with a parallel design and an allocation ratio of 1:1 for the treatment groups. This study was approved by the Institutional Review Board in our hospital and written informed consent was obtained from all subjects participating in the trial. It was carried out in accordance with the principles of the Helsinki Declaration. A total of 70 patients who meet inclusion criteria are randomized to either all-inside or inside-out group. The primary outcome measure was retear rate. Retear was determined by repeat arthroscopic evaluation of patients with follow-up for symptoms of persistent or new pain, catching, or locking that was possibly related to the meniscal repair. Secondary outcomes included disease-specific quality of life measurement with the Western Ontario Meniscal Evaluation Tool, range of motion, operative time, and adverse events at surgery or throughout the follow-up period. RESULTS: This study has limited inclusion and exclusion criteria and a well-controlled intervention. TRIAL REGISTRATION: This study protocol was registered in Research Registry (researchregistry5589).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".