Can visual aides influence rehabilitation and length of stay following knee replacement? A randomized controlled study
Bibliographic record
Abstract
Arthroplasty is increasingly performed within Australia, with a 2.7% rate increase of total knee arthroplasty (TKR) over the last year. With an increasing burden on the public health system and increasing waiting lists, all efforts are being made to decrease length of stay and improve the post operative rehabilitation process. There is currently insufficient evidence to make a conclusive statement about visual aids and improved goal attainment post TKR. The purpose of this study is to evaluate one such visual aid clinical photographs of patients knee range of motion (ROM) pre-and post-operatively and their effect on length of stay. Photographs of knee range of motion were obtained pre and post-operatively while the patient was anesthetized. In this study, a randomized, single blinded design allocated patients to either be shown or not shown their photographs on day 1 post operatively. Primary outcome measures were the number of days the patient remained in hospital. Secondary measures were Western Ontario and McMaster Universities Arthritis Index scores, Oxford Knee Scores, American Society of Anesthesiologists Score and knee ROM. Thirty-two patients (3 exclusions) were randomized to the photo group and 27 patients (4 exclusions) were randomized to the no photo group. The median length of stay between groups was not significantly different. Currently there is not enough evidence to conclude that visual aids effect length of stay or rehabilitation pathways. Further assessment with larger cohort groups is needed. Preoperative targeting and rehabilitation for patients with lower functional status may shorten post operative length of patient stay in our institution.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".