Medication use and falls in community-dwelling older persons
Bibliographic record
Abstract
BACKGROUND: The association between injurious falls requiring a visit to the emergency department and various classes of medications was examined in a case-control study of community living persons aged 66 years and older. METHODS: Administrative databases from an urban health region provided the information used. Five controls for each case were randomly selected from community dwelling older persons who had not reported an injurious fall to one of the six regional emergency departments in the study year. Two series of analyses on medication use within 30 days of the fall were conducted using logistic regression, the first controlling for age, sex, and median income, the second controlling for co-morbid diagnoses as well. RESULTS: During the study year there were 2,405 falls reported by 2,278 individuals to six regional emergency departments giving a crude fall rate of 31.6 per 1,000 population per year. The initial analysis identified seven medication classes that were associated with an increased risk of an injurious fall, while controlling for age, gender and income. However, with further analyses controlling for the additional effects of co-morbid disease, narcotic pain-killers (odds ratio 1.68), anti-convulsants (odds ratio 1.51) and anti-depressants (odds ratio 1.46) were significant independent predictors of sustaining an injurious fall. CONCLUSION: These results are based on a Canadian population-based study with a large community sample. The study found that taking certain medications were independent predictors of sustaining an injurious fall in our elderly population - in addition to the risk associated with their medical condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".