Faster quadriceps recovery with the far medial subvastus approach in minimally invasive total knee arthroplasty
Bibliographic record
Abstract
PURPOSE: To identify whether less proximal muscle damage during minimally invasive surgery will allow faster recovery after total knee arthroplasty in comparison with a quadriceps incision approach. A limited medial parapatellar approach without tibial medial collateral ligament (MCL) release was compared to a subvastus approach without tibial medial collateral ligament release (far medial subvastus). METHODS: One hundred and eighty patients were studied. In the mini-parapatellar group, ninety patients and in the far medial subvastus group, the remaining ninety patients were included. The evaluation was based on the Knee Society Score, VAS, morphine consumption, range of motion, time to straight leg raising, walking without aid, stairs and period of hospitalization. Alignment on full leg radiographs and component position on plain films were measured. RESULTS: The far medial subvastus group showed faster recovery with earlier straight leg raising (1.7 ± 0.5 vs. 2.7 ± 0.4 days), postoperative weight bearing without aid (1.7 ± 0.6 vs. 2 ± 0.8 days) and stair negotiation (3 ± 0.4 vs. 4 ± 0.3 days) resulting in shorter length of stay (4 ± 0.5 vs. 5 ± 1.2 days). Comparable Knee Society Scores (88.5 ± 6.8 vs. 90 ± 10), Function Scores (90 ± 10) and alignment (5.4° ± 2.1° vs. 5.0° ± 2.4°) between the medial parapatellar and far medial subvastus group were observed at a follow-up of 24 months. An increase in operative time for the far medial subvastus was observed (55 ± 10.6 min vs. 67 ± 12 min tourniquet time) but without complications. CONCLUSION: The MCL sparing far medial subvastus approach allows good surgical exposure, faster straight leg raising, full weight bearing without aid and shorter length of stay with most importantly no radiological malalignment. LEVEL OF EVIDENCE: Therapeutic study, Level II.
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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) | 0.001 | 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".