Trajectories of functional decline and predictors in long-term care settings: a retrospective cohort analysis of Canadian nursing home residents
Bibliographic record
Abstract
Decline in the ability to perform activities of daily living (ADL) or 'functional decline' is a major health concern among aging populations. With intervention, ADL decline may be delayed, prevented or reversed. The capacity to anticipate the trajectory of future functional change can enhance care planning and improve outcome for residents. METHODS: This is a 36 months' retrospective longitudinal analysis of LTC residents in five Canadian provinces. Group-based trajectory modelling (GBTM) was performed to identify distinct trajectories and resident attributes associated with membership of the trajectory groups. RESULTS: A total of 204 036 LTC residents were included in this study. Their admission mean age was 83.7 years (SD = 8.6), and 63.3% were females. Our model identified four distinct trajectories namely: 'Catastrophic decline' (n = 48 441, 22.7%), 'Rapid decline with some recovery' (n = 27 620, 18.7%), 'Progressive decline' trajectory (n = 30 287, 14.4%), and the 'No/Minimal decline' (n = 97 688, 47.9%) Residents' admission ADL Hierarchy score was the single, strongest predictor of functional decline trajectory that residents followed. Residents with ADLH 5-6 OR 0.03 (0.03-0.04) were least likely to follow a catastrophic decline trajectory, while those with ADLH 5-6 OR 39.05 (36/60-41.88) were most likely to follow a minimal or no decline trajectory. CONCLUSION: Results of this study further highlight the heterogeneity of health trajectory among residents in LTC setting, re-affirming the need for personalized care. The study shows who among residents would be most at risk for different levels of functional decline.The study findings provide useful information that would assist both immediate and advanced care planning as well as to forecast care personnel requirements into the future based on total acuity levels of residents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".