Rehabilitation following Autologous Chondrocyte Implantation Surgery: Case Report Using an Accelerated Weight-Bearing Protocol
Bibliographic record
Abstract
Purpose: This case report describes the rehabilitation of a patient following autologous chondrocyte implantation (ACI) surgery using an accelerated weight-bearing protocol. Method: The patient was a 40-year-old female who had undergone previous right knee surgical procedures, including meniscectomy and anterior cruciate ligament reconstruction, 2 years prior to receiving right knee ACI for a grade IV, 12 × 10 mm osteochondral lesion. The morning after implantation, 6 to 8 hours of daily continuous passive motion was started (0–45°), 33/d progressing 15°/d as tolerated to120°. Physical therapy began 1 week postsurgery; weight bearing was initiated with a three-point touch-down gait using a locked brace set at 0°. The rehabilitation programme is described, as well as measures of range of motion, active extension lag, knee joint line girth, visual analogue scale pain ratings, and Activities of Daily Living Scale scores of the Knee Outcome Survey. Results: All functional goals defined by the protocol and pertinent to the patient were met over a 17-week period. At discharge, only continued graft precautions limited the patient's perception of knee function. The patient reported 100% knee function at follow-up (30 months after surgery). Conclusion: The accelerated weight-bearing protocol described in this report allowed this patient to safely progress through rehabilitation with a full return to an active life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".