Frailty and mortality among older patients in a tertiary hospital in Nigeria
Bibliographic record
Abstract
BACKGROUND: This study determined the frailty status and its association with mortality among older patients. DESIGN: A prospective cohort design. SETTING: Study was conducted at the medical wards of University College Hospital, Ibadan, Nigeria. PARTICIPANTS AND STUDY TOOLS: Four hundred and fifty older patients (>60 years) were followed up from the day of admission to death or discharge. Information obtained includes socio-demographic characteristics and clinical frailty was assessed using the Canadian Study of Health and Aging (CSHA) scale. Bivariate and multivariate analyses were carried out using SPSS version 21 at a p <0.05. RESULTS: Overall, frailty was identified in 285 (63.3%) respondents. Mortality was significantly higher among frail respondents (25.3%) than non-frail respondents (15.4%) p=0.028. Logistic regression analysis showed factors associated with frailty were: male sex (OR=1.946 [1.005-3.774], p=0.048), non-engagement in occupational activities (OR=2.642 [1.394-5.008], p=0.003), multiple morbidities (OR=4.411 [1.944-10.006], p<0.0001), functional disability (OR=2.114 [1.029-4.343), p=0.042], malnutrition (OR=9.258 [1.029-83.301], p=0.047) and being underweight (OR=7.462 [1.499-37.037], p=0.014). CONCLUSION: The prevalence of frailty among medical in-hospital older patients is very high and calls for its prompt identification and management to improve their survival. FUNDING: The study was self-funded by the authors.
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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 | 0.001 |
| 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 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".