Functional status recovery trajectories in hospitalised older adults with pneumonia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Pneumonia is associated with significant mortality and morbidity in older adults. We investigated changes in functional status over 6 months after pneumonia hospitalisation by frailty status. METHODS AND MEASUREMENTS: This single-centre prospective cohort study enrolled 201 patients (mean age 79.4, 37.3% women) who were hospitalised with pneumonia. A deficit-accumulation frailty index (range: 0-1; robust <0.15, pre-frail 0.15-0.24, mild-to-moderately frail 0.25-0.44, severely frail ≥0.45) was calculated on admission. Functional status, defined as self-reported ability to perform 21 activities and physical tasks independently, was measured by telephone at 1, 3 and 6 months after discharge. Group-based trajectory model was used to identify functional trajectories. We examined the probability of each trajectory based on frailty levels. RESULTS: On admission, 51 (25.4%) were robust, 43 (21.4%) pre-frail, 40 (20.0%) mild-to-moderately frail and 67 (33.3%) severely frail patients. Four trajectories were identified: excellent (14.4%), good (25.4%), poor (28.9%) and very poor (31.3%). The trajectory was more strongly correlated with frailty level on admission than pneumonia severity. The most common trajectory was excellent trajectory (59.9%) in robust patients, good trajectory (74.4%) in pre-frail patients, poor trajectory (85.0%) in mild-to-moderately frail patients and very poor trajectory (89.6%) in severely frail patients. The risk of poor or very poor trajectory from robust to severely frail patients was 11.8%, 25.6%, 92.5% and 100%, respectively. CONCLUSIONS: Frailty was a strong determinant of lack of functional recovery over 6 months after pneumonia hospitalisation in older adults. Our results call for hospital-based and post-acute care interventions for frail patients.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".