Patient-related risk factors for in-hospital functional decline in older adults: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Functional decline (FD) is a common and serious problem among hospitalised older adults. OBJECTIVE: This systematic review and meta-analysis aims to identify patient-related risk factors for in-hospital FD in older adults. METHODS: Previous reviews on this topic (1970-2007) and the databases PubMed, Embase, and CINAHL (January 2007-December 2020) were searched. Reference lists of included articles were screened. Studies investigating patient-related risk factors for FD from (pre)admission to discharge in older adults admitted to an acute geriatric or internal medical unit were included. Study quality was assessed using the modified Newcastle-Ottawa Scale. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using random-effects models. The quality of evidence was assessed using GRADE. RESULTS: Twenty-nine studies met the inclusion criteria. Statistically significant risk factors were living in a nursing home (OR, 2.42; 95% CI, 1.29-4.52), impairment in instrumental activities of daily living (OR, 2.08; 95% CI, 1.51-2.86), history of falls (OR, 1.71; 95% CI, 1.00-2.92), cognitive impairment (OR, 1.83; 95% CI, 1.56-2.14), dementia (OR, 1.71; 95% CI, 1.23-2.38), delirium (OR, 2.34; 95% CI, 1.88-2.93), (risk of) malnutrition (OR, 1.76; 95% CI, 1.03-3.03), hypoalbuminemia (OR, 1.79; 95% CI, 1.36-2.36), comorbidity (OR, 1.09; 95% CI, 1.03-1.16), and the presence of pressure ulcers (OR, 3.33; 95% CI, 1.82-6.09). The narrative synthesis suggested prehospital FD, needing assistance with walking, and low body mass index as additional risk factors. CONCLUSIONS: Several patient-related risk factors for in-hospital FD were identified that can be used at hospital admission to identify older patients at risk of FD.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".