Prevalence and risk factors of frailty in older adults with diabetes: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: This systematic review and meta-analysis aimed to evaluate the prevalence of frailty and pre-frailty in older adults with diabetes; and to identify the risk factors associated with frailty in this population. DESIGN: Systematic review and meta-analysis. PARTICIPANTS: 24,332 people aged 60 years and older with diabetes. METHODS: Six databases were searched (PubMed, Embase, the Cochrane Library, Web of Science, China Knowledge Resource Integrated Database, and Chinese Biomedical Database) up to 15 January 2024. Random effects models were used in instances of significant heterogeneity. Subgroup analysis and meta-regression were conducted to identify the potential source of heterogeneity. The Agency for Healthcare Research and Quality (AHRQ) and the Newcastle-Ottawa Scale (NOS) were applied to assess the quality of included studies. RESULTS: 3,195 abstracts were screened, and 39 full-text studies were included. In 39 studies with 24,332 older people with diabetes, the pooled prevalence of frailty among older adults with diabetes was 30.0% (95% CI: 23.6%-36.7%). Among the twenty-one studies involving 7,922 older people with diabetes, the pooled prevalence of pre-frailty was 45.1% (95% CI: 38.5%-51.8%). The following risk factors were associated with frailty among older adults with diabetes: older age (OR = 1.08, 95% CI: 1.04-1.13, p<0.05), high HbA1c (OR = 2.14, 95% CI: 1.30-3.50, p<0.001), and less exercise (OR = 3.11, 95% CI: 1.36-7.12, p<0.001). CONCLUSIONS: This suggests that clinical care providers should be vigilant in identifying frailty and risk factors of frailty while screening for and intervening in older adults with diabetes. However, there are not enough studies to identify comprehensive risk factors of frailty in older adults with diabetes. TRIAL REGISTRATION: PROSPERO registration number: CRD42023470933.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.045 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".