Bibliographic record
Abstract
Objective:The purpose of this study was to evaluate the therapeutic effect that arthroscopic debridement in osteoarthritic knees.Methods: A total of 73 patients with an osteoarthritis knee,who failure to the strict conservative treatment and really understand that the goal of surgery was to relieve symptoms and not to 'cure',were accepted the arthroscopic debridement.Surgical treatment included debridement of synovium and osteochondral loose bodies,chipping of meniscal lesions,stabilization of chondral defects,removal of impinging osteophytes,notchplasty,and resection of Cyst.Age,symptoms,compartments involved,range of motion,and level of satisfaction were evaluated.And,the Hospital for Special Surgery(HSS) and Western Ontario and MacMaster University(WOMAC) scores were also evaluated preoperative and postoperative,respectively.Results: At 2 years available follow up,61 of 73 patients were satisfied.Five patients were impossible to evaluate for deterioration,and another 7 were considered failures requiring further surgery.Mean HSS scores improved from 28.6 to 52.4.Mean WOMAC scores improved from 40.6 to 31.5.All 12 failures had severe flexion contractures(15°),aggravated malalignment(varus10°),and involved tricompartment disease(mean preoperative HSS scores,23.5;mean preoperative WOMAC scores,62;mean preoperative flexion contractures,15.8°).Conclusions: Arthroscopic debridement has really improved symptoms and good clinical outcom for knee osteoarthritis in appropriately selected patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".