In a prospective population-based study, the degree of mobility impairment during hospitalisation is associated with higher degrees of frailty
Bibliographic record
Abstract
BACKGROUND: Hospitals pose a high risk for frailty to develop or accelerate. Still, few community-based cohort studies follow patients before, during, and after hospitalisation. We investigated the degree of immobility during hospitalisation and its impact on subsequent frailty. METHODS: In a prospective population-based cohort of individuals aged ≥ 70 from a London UK borough, we performed comprehensive community assessments at baseline and after two years. At each hospitalisation, we measured daily mobility and other clinical variables. Acute immobility burden, a summative level of poor mobility for all hospitalisations, was calculated for each participant and operationalized as low/high based on the population median. A frailty index was calculated for all participants during baseline and follow-up assessments. We estimated the effect of these exposures on follow-up frailty index scores using linear regression. RESULTS: We included 1177 participants. Those admitted (N = 114) were assessed over 1999 bed-days. The degree of baseline frailty had the largest association with subsequent frailty. However, a high immobility burden during hospitalisation was consistently related to additional increases in frailty (low burden: β = 0.02 per unit increase in FI (95%CI: -0.002-0.04), high burden: β = 0.07, (95%CI: 0.041-0.10)). Immobility burden remained associated with subsequent frailty even when limiting the analysis to: those who were independently mobile; the first seven days of hospitalisation; and accounting for illness severity. High immobility burden was prognostic of subsequent death. CONCLUSIONS: The degree of immobility during hospitalisation, a potentially modifiable risk factor, may determine whether hospitalisation contributes to increasing frailty.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".