A modified minimally invasive subvastus approach shows superior early postoperative clinical outcomes compared to the medial parapatellar approach in total knee arthroplasty for osteoarthritis patients: a comparative study
Bibliographic record
Abstract
OBJECTIVE: This study compared the modified minimally invasive subvastus approach (MMSA) versus the medial parapatellar approach (MPA) in total knee arthroplasty (TKA) for osteoarthritis, focusing on perioperative blood loss, postoperative pain, quadriceps strength, and knee mobility. METHODS: In this retrospective cohort study, we enrolled patients undergoing TKA from June 2020 to June 2022. Inclusion criteria were adults aged 40-80 with end-stage knee osteoarthritis undergoing primary TKA. Exclusion criteria included neuromuscular disorders, active infections, severe osteoporosis, prior knee surgery, and rheumatoid arthritis. We compared the MMSA group (n = 36) with the MPA group (n = 57) for primary outcomes including blood loss, postoperative pain, quadriceps strength, knee range of motion, and clinical scores including Oxford Knee Score (OKS) and Western Ontario and McMaster Universities (WOMAC) score. RESULTS: The MMSA group showed reduced blood loss, less pain on day 3, and better quadriceps strength and knee mobility compared to the MPA group. Clinical scores (WOMAC and OKS) were significantly better in the MMSA group in the early postoperative period, indicating improved function and reduced pain. However, the MMSA group had longer operation times. Long-term recovery and prosthesis placement accuracy, including prosthesis angles, were similar in both groups. CONCLUSION: The MMSA offers superior short-term outcomes post-TKA without compromising long-term recovery, indicating its potential as a preferred approach for patients aiming to minimize postoperative complications and expedite recovery. This study provides evidence for the clinical superiority of MMSA in the early postoperative period.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".