Does the person’s context influence engagement in life activities following primary knee replacement? Results from a Canadian prospective cohort study
Bibliographic record
Abstract
OBJECTIVE: The impact of the context of a person's life on recovery from surgical interventions is not well understood. This study evaluated if people's social, environmental and biomedical context was associated with change in frequency in engagement in life activities after total knee replacement (TKR). METHODS: 418 people aged 30+ years who had TKR were followed presurgery to 1 year postsurgery. The outcome was change in frequency in engagement in life activities measured by the Late Life Disability Index (LLDI). Predictor variables of interest evaluated in multivariable linear regression analysis were positive and negative life events (Life Experiences Survey), development of a new comorbidity, another joint replacement and complications after TKR surgery. RESULTS: Mean age was 65 years, 36% were male; 22% and 21% had no comorbidity presurgery and postsurgery. Presurgery LLDI frequency was 69.6 (±11.4) and the mean change was 6.1 (±10.2). Thirty-four per cent and 65% reported at least one positive or negative life event. Seven per cent developed hypertension, 6% cardiovascular disease, 2% lung disease and 2% diabetes. Eleven per cent had a complication and 9% another hip or knee replaced. Smaller changes in LLDI frequency were associated with more negative life events (beta=-0.56; 95% CI -0.92 to-0.18) and complications (beta=-4.01; 95% CI -6.63 to -1.38) after adjusting for age, sex, education, body mass index, comorbidities presurgery, number of symptomatic joints and knee-specific pain and function, LLDI limitations and depression. A new comorbidity or another joint replacement was not associated with outcome in unadjusted or adjusted analysis. CONCLUSIONS: Multifaceted life experiences shape the context of peoples' lives impacting their engagement in activities important for healthy living post-TKR.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".