Prevalence of frailty in a tertiary hospital: A point prevalence observational study
Bibliographic record
Abstract
INTRODUCTION: Frailty is an important concept in modern healthcare due to its association with adverse outcomes. Its prevalence varies in the literature and there is a paucity of literature looking at the prevalence of frailty in an inpatient setting. Its significance lies on its impact on resource utilisation and costs. AIM: To determine the prevalence of frailty in the adult population in a tertiary New Zealand hospital. METHODS: Eligible patients aged 18 years and over were invited to participate, and frailty assessment was performed using the Reported Edmonton Frail Scale. A score of 8 or more was considered frail. Factors associated with frailty were assessed. RESULTS: Of 640 occupied inpatient beds, 420 patients were assessed. 220 patients were excluded, of which 89 were absent from their bed-space, 73 declined and 41 were critically unwell. The overall prevalence of frailty across assessed patients was 48.8%. The prevalence of frailty increased significantly with age; patients aged 85 and over were significantly more likely to be frail compared to those aged under 65 (OR 6.25, 95% CI 3.17-12.7). Maori patients were significantly more likely to be frail (OR 4.0, 95% CI 1.45-11.9). When compared to those patients admitted to a medical specialty, patients admitted to surgical specialty were less likely to be frail (OR 0.52 95% CI 0.31-0.86) and those admitted for rehabilitation were more likely to be frail (OR 1.86 95% CI 1.03-3.41). Frail patients were more likely to come from a rest home (OR 2.81, 95% CI 1.38-6.14) or hospital level care (OR 9.62, 95% CI 2.68-61.6). CONCLUSION: Frailty is highly prevalent in the hospital setting with 48.8% of all inpatients classified as frail. This high number of frail patients has significant resource implications and an increased understanding of the burden of frailty in this population may aid targeting of interventions towards this vulnerable population.
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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 | 0.001 |
| 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) | 0.001 | 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 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".