Association between frailty and risk of fall among diabetic patients
Bibliographic record
Abstract
BACKGROUND: Several epidemiological studies have demonstrated the risk factors for fall, while few studies investigated the association between frailty and risk of fall in diabetic patients aged ≥45 years. METHODS: In this multicity observational study, participants with type 2 diabetes aged ≥45 years were enrolled. Frailty status was measured by a frailty index (FI) of deficit accumulation. We used multivariable regression models to examine the relationship between frailty and fall in diabetic patients, and further investigated the associations between frailty and fall in varied subgroups. RESULTS: A total of 2049 participants with type 2 diabetes were identified in our study. Our results showed a per-s.d. and a per-0.01 increment of FI were associated with an increased risk of fall, with a fully adjusted OR of 1.89 (95% CI: 1.50, 2.38), 1.06 (95% CI: 1.04, 1.09), respectively. The effects were magnified when frailty was considered as dichotomous, with an OR of 3.08 (95% CI: 2.18, 4.34). In further subgroup analyses, we found that the females, the older, rural residents, individuals with no sitting toilet, people with poor balance performance and those in poor health status were susceptible to fall. Especially, for the risk of fall in the older, a per-s.d. increase of FI corresponded to an OR of 2.46 (95% CI: 1.68, 3.62). When frailty was regarded as a binary variable, the effect increased to 4.62 (95% CI: 2.54, 8.38) in the older subgroup. CONCLUSION: Frailty was associated with a higher risk of fall in people with type 2 diabetes, and the effects were higher in vulnerable groups. This evidence suggested that more attention should be paid to vulnerable groups for fall prevention.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".