Evaluation of the risk factors for falls in the geriatric population presenting to the emergency department
Bibliographic record
Abstract
BACKGROUND: We evaluated risk factors and frailty assessments to identify fall-prone geriatric patients in the emergency department (ED). METHODS: This prospective study included 264 consecutive patients aged ≥65 years who presented to the ED. The participants were divided into those who had fallen or not. The patient groups were compared in terms of age, sex, presenting complaints (falls vs. others), comorbidities, medications, frailty assessment tools, and orthostatic hypotension (OH). RESULTS: In total, 264 patients were included: 129 (48.8%) patients who had fallen and 135 (51.2%) who hadn't fallen. The mean ages of patients who had fallen and those who had not fallen were 80.48±8.38 and 79.42±7.94 years, respectively. In addition, 62.01% (n=80) and 51.85% (n=70) of patients were females. There were no statistically significant differences between the groups in terms of age or sex (P=0.290 and P=0.096, respectively). In total, 89.92% (n=116) of patients who had fallen had at least one chronic medical condition. There was a significant difference in the proportion of patients with OH between the groups. Frailty scores such as the Edmonton Frail Scale, Frail Non-Disabled Questionnaire, PRISMA-7 questionnaire, Identification of Seniors at Risk test, and Rockwood Clinical Frailty Scale scores were also significantly different between the groups. A higher PRISMA-7 score at admission was found to be an independent predictor of fall risk. CONCLUSION: Falls occur more frequently in the older population and in females. In addition, the frailty assessment scores, except for the FRESH Frailty Scale, were associated with falls in geriatric patients. After elimination of non-significant variables in multivariate analysis, a high PRISMA-7 questionnaire score at admission was identified as an independent predictor of fall risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".