Hypnotics Use and Falls in Hospital Inpatients Stratified by Age
Bibliographic record
Abstract
BACKGROUND: Little is known about the association between hypnotics use and falls among inpatients in young and middle-aged populations. We aimed to determine whether the use of hypnotics elevated the fall risk in adult inpatients aged 20 and above. METHODS: Patients admitted to the Kanto Rosai Hospital, Kanagawa, Japan, between April 1, 2013 and January 31, 2014 were followed up until discharge. We estimated the incidence rate ratio (IRR) and 95% confidence intervals (CI) of falls for the use of hypnotic drugs with a Poisson regression model, adjusted for sex, age, activities of daily living, and comorbidities. RESULTS: For the 6,949 inpatients whose medical records were examined, the incidence of falls was significantly higher in hypnotics’ users than in non-users. The IRR was 1.52 (95% CI, 1.10-2.11). When stratified by age, the risk of hypnotics use in the patients aged 65 and above was statistically elevated (IRR, 1.48; 95% CI, 1.02-2.13); the risk in the patients aged 25-64 was elevated but not significant (IRR, 1.33; 95% CI, 0.63-2.81). CONCLUSION: Usage of hypnotics elevated fall risk in the older inpatients, though this association was not significant in the young and middle-aged inpatients. Further studies are needed.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 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".