Reporting Functional Outcome After Knee Arthroplasty and Regional Anesthesia
Bibliographic record
Abstract
The introduction of ultrasound guidance for regional anesthesia has resulted in an explosion of interest in its use for postoperative analgesia, particularly for orthopedic surgery. Regional anesthesia demonstrates unequivocal superiority compared with systemic opioids with respect to analgesia, reduced opioid consumption, increased patient satisfaction, and earlier achievement of discharge criteria. Improved acute postoperative analgesia can facilitate effective rehabilitation. Investigators are in the early stages of reporting the effects of regional anesthesia on functional outcome. Recent studies reporting functional outcomes have been plagued with sample sizes of inadequate power to generate meaningful results. Furthermore, the functional outcome measures are used inappropriately in terms of clinically meaningful difference, assessment intervals, and/or duration of follow-up. This report aims to address these issues by discussing functional outcomes used in the physiotherapy or orthopedic literature and their appropriate utilization, so that future research into the effects of regional anesthesia can be methodologically sound. Outcomes discussed include those that are physical-performance-based (ie, range of motion, quadriceps strength, Timed Up and Go test, 6-Minute Walk Test, Stair Time, and Self-paced Walk Test) and those that are self-reported (ie,Western Ontario and McMaster Universities Osteoarthritis Index, Knee Osteoarthritis Severity Score, Lower Extremity Function Scale).
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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 | 0.025 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".