The minimally invasive far medial subvastus approach for total knee arthroplasty in valgus knees
Bibliographic record
Abstract
PURPOSE: The lateral approach in the valgus knee asks for a lot of soft tissue releases during the arthrotomy. The hypothesis of this study was that the far medial subvastus approach could be used in valgus knees and would guarantee both functional and radiological good to excellent results. METHODS: This is a retrospective study on 78 patients (84 knees) undergoing primary total knee arthroplasty (TKA) for type I or II fixed valgus knees. The mean (SD) preoperative mechanical alignment was 187° (4°) HKA angle. Functional recovery, pain, tourniquet times, necessary soft tissue releases as well as radiological alignment were measured. RESULTS: The Knee Score improved significantly from 45 (10) to 90 (10) (P < 0.05) and the function score improved as well from 35 (20) to 85 (10) (P < 0.05). Flexion improved from 110° (10°) to 137° (8°). Hospital stay was 4 (1.2) days. Alignment was corrected to 181° (1.5°) HKA angle with a postoperative joint line shift of +2.8 (3.2) mm. No clinical instability, as evaluated by the senior author, or osteolytic lines was observed at minimal one-year radiological follow-up. CONCLUSION: The far medial subvastus approach is an excellent approach to perform Krackow type I and II TKA with primary PS implants.
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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 | 0.001 | 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".