Risk of falls associated with antiepileptic drug use in ambulatory elderly populations
Bibliographic record
Abstract
BACKGROUND: Falls are a major cause of morbidity and mortality in older adults. About a third of those aged 65 years or older fall at least once each year, which can result in hospitalizations, hip fractures and nursing home admissions that incur high costs to individuals, families and society. The objective of this clinical review was to assess the risk of falls in ambulatory older adults who take antiepileptic drugs, medications that can increase fall risk and decrease bone density. METHODS: PubMed, EMBASE, MEDLINE and the Cochrane Library electronic databases were searched from inception to July 2014. Case-control, quasi-experimental and observational design studies published in English that assessed quantifiable fall risk associated with antiepileptic drug use in ambulatory patient populations with a mean or median age of 65 years or older were eligible for inclusion. One author screened all titles and abstracts from the initial search. Two authors independently reviewed and abstracted data from full-text articles that met eligibility criteria. RESULTS: Searches yielded 399 unique articles, of which 7 met inclusion criteria-4 prospective or longitudinal cohort studies, 1 cohort study with a nested case-control, 1 cross-sectional survey and 1 retrospective cross-sectional database analysis. Studies that calculated the relative risk of falls associated with antiepileptic drug use reported a range of 1.29 to 1.62. Studies that reported odds ratios of falls associated with antiepileptic drug use ranged from 1.75 to 6.2 for 1 fall or at least 1 fall and from 2.56 to 7.1 for more frequent falls. DISCUSSION: Health care professionals should monitor older adults while they take antiepileptic drugs to balance the need for such pharmacotherapy against an increased risk of falling and injuries from falls.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".