- Design
- Retrospective population-based cohort
- Population
- 120,867 adults aged 65 or over prescribed at least one fall-risk-increasing drug
- Primary outcome
- Fall-related hospitalisation within the year
- Effect
- 2.3% admitted; SSRIs, older antiepileptics and moderate anticholinergics associated with higher risk; AUC 0.73
A population-based cohort in Age and Ageing (4 September 2026) followed 120,867 adults aged 65 or over who were prescribed at least one fall-risk-increasing drug, to see which drug groups best identified those likely to be admitted after a fall.
Over the year, 2.3% had a fall-related hospitalisation. Selective serotonin reuptake inhibitors, older antiepileptics and drugs with moderate anticholinergic activity were associated with higher risk. A broader framework counting any drug with a fall-related adverse reaction added little. The model discriminated moderately (AUC 0.73).
So many older people take a fall-risk drug that a review of all of them is impractical. This suggests where to look first. It is observational, and drug choice reflects underlying conditions such as depression and epilepsy that carry their own fall risk, so the associations do not prove the drugs are the cause.
- Prioritise medication review in older adults taking SSRIs, older antiepileptics or anticholinergic drugs.
- Consider whether an anticholinergic drug can be stopped or replaced with a less anticholinergic one.
- Check sodium in older adults on SSRIs, as hyponatraemia adds to fall risk.
- Review older antiepileptics such as phenytoin and carbamazepine with the prescriber before changing them.
Why it matters
It turns an unworkably long list of fall-risk drugs into a shorter list to review first.
Don't overread it
This was observational; the conditions these drugs treat may explain part of the risk.
The statistics, in plain English
An AUC of 0.73 means that, given one person who was admitted after a fall and one who was not, the model ranked the admitted person higher about 73% of the time. That is moderate, useful for prioritising but not for predicting individual falls.
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