Prehabilitation versus usual care before total knee arthroplasty: A case report comparing outcomes within the same individual
Bibliographic record
Abstract
This case report compared pre- and postoperative functional ability, knee strength, and pain of a female who underwent two separate total knee arthroplasty (TKA) procedures. The female patient was part of a larger research study. The first surgery on the right knee was preceded with usual care and the second surgery on the left knee was preceded by prehabilitation. Functional ability was assessed by a 6-minute walk, chair raises, and the time required to ascend and descend stairs. Knee extension and flexion isokinetic strength was assessed using the KinCom Isokinetic Dynamometer. Pain was assessed using the Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC). Functional abilities, knee strength, and pain were assessed at baseline measurements 4 weeks before surgery, 1 week before surgery, and at 1 and 3 months post surgery during each TKA procedure. Results indicate that the prehabilitation intervention had a favorable impact on improving functional ability up to 30%, increasing knee strength by 50% and decreasing pain prior to the left knee TKA. For this patient, prehabilitation increased functional ability and strength prior to surgery. Gains in strength were maintained in the nonsurgical knee after surgery. These findings indicate that prehabilitation may be effective at facilitating the rehabilitation following a TKA.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.002 | 0.001 |
| 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".