Getting fit for hip and knee replacement: The Fit-Joints multimodal intervention for frail patients with osteoarthritis – a pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Older adults with frailty have high risk for poor postoperative outcomes. OBJECTIVE: To evaluate the feasibility of a multimodal prehabilitation program in older adults with frailty awaiting hip or knee replacement. DESIGN: Parallel two-arm randomized controlled pilot trial. PARTICIPANTS AND SETTING: Community-dwelling older adults with frailty awaiting joint replacement aged ≥60 years recruited from the Musculoskeletal Central Intake and Assessment Centre (MSK CIAC), Ontario. INTERVENTION: Exercise, protein and vitamin D supplements, and medication review. MEASUREMENT: Feasibility was assessed based on predefined progression criteria for recruitment, retention, data completion and adherence to intervention components. Clinical outcomes including Oxford Knee and Hip Scores, frailty index, Short Physical Performance Battery and health-related quality of life were collected at baseline, 1-week preoperative, 6-weeks and 6-months postoperative and were evaluated using generalized linear mixed models for repeated measures. RESULTS: A total of 69 participants were enrolled. Recruitment rate was 35 %. Participants' mean age was 74 (standard deviation (SD): 7.5); 51 % were prefrail and 36 % were frail. Participant retention was 81 %, and data completion was ≥80 %. Mean adherence to strength exercises was 4 days (95 % confidence interval (CI): 3-5 days/week), balance 3 days (95 % CI: 2-4 days/week), and flexibility 3 days (95 % CI: 3-4 days/week). Adherence to vitamin D intake was 82 % (95 % CI: 73-92 %), and medication review consultation completion was 86 % (95 % CI: 68-95 %). These outcomes met the target values for feasibility success. The Oxford Knee Score at 6-months postoperative 8.78 (95 % CI: 0.40-17.16) showed a clinically meaningful and statistically significant difference between treatment groups. There were also indications of clinically relevant changes for frailty and quality of life post-surgery. CONCLUSION: This trial provides strong evidence of feasibility and indications of improvements in postoperative clinical outcomes. Challenges to implementation and adherence were identified that can inform modifications to study design for future trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT02885337. Registered August 31, 2016. https://classic. CLINICALTRIALS: gov/ct2/show/NCT02885337.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".