The effects of exercise and active assisted cycle ergometry in post‐operative total knee arthroplasty patients ‐ a randomized controlled trial
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to examine the effect of the use of an active assisted cycle ergometer as an adjunct to post-operative treatment following total knee arthroplasty. METHOD: A total of 55 participants aged 50-80 years who had undergone unilateral total knee arthroplasty were randomly assigned to either the control group (standard of care) or the active assisted cycle ergometer (AACE) group. The effect on patient motivation, blood biomarkers, and knee pain, function, range of motion (ROM), strength, and swelling was examined. Qualitative feedback was also obtained post-operatively. RESULTS: Although there was no statistically significant difference in the standard of care compared to the AACE group, there was a trend for a greater reduction in knee pain on the visual analog scale, improved Lower Extremity Functional Scale scores, and knee extension ROM and strength. A greater percentage of the experimental group demonstrated higher motivation. There was no significant difference in swelling or blood biomarker measures. Qualitative feedback from the AACE group post-operatively was also positive. CONCLUSIONS: The use of an AACE protocol as an adjunct to total knee arthroplasty rehabilitation may improve post-operative clinical outcomes. This study has been registered at clinicaltrials.gov (identifier NCT02265523 , Oct 16 2014). LEVEL OF EVIDENCE: Level 1 - randomized controlled trial. Further research with a larger sample size is needed to confirm the benefits of the ergometer use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".