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Research · 04 of 06

Benzodiazepine use was associated with more incident heart failure and heart failure admissions

Consider benzodiazepine use a possible heart failure risk marker, and review long-term prescriptions in patients at risk.

Design
Systematic review and meta-analysis of mostly observational studies
Population
11 studies of adults using benzodiazepines for insomnia
Primary outcome
Incident heart failure and heart failure hospitalisation
Effect
Incident HF HR 1.41 (1.16 to 1.72); HF admission HR 1.29 (1.01 to 1.65)

A meta-analysis pooled 11 studies, mostly observational, with follow-up from six months to 15 years. Benzodiazepine use for insomnia was associated with a higher risk of new heart failure (HR 1.41, 95% CI 1.16 to 1.72) and of heart failure hospitalisation (HR 1.29, 1.01 to 1.65) compared with non-use. Comparisons against z-drugs, antipsychotics and suvorexant also leaned against benzodiazepines.

People prescribed benzodiazepines differ from those who are not, through anxiety, poor sleep from undiagnosed breathlessness, or other illness, so confounding is likely. The upper end of the admission estimate sits close to no effect.

The practical point is modest but real: benzodiazepines already carry falls and dependence risks in older adults, and this adds another reason to review long-term use in people with or at risk of heart failure.

  • Review long-term benzodiazepine prescriptions in patients with or at risk of heart failure
  • Ask about orthopnoea and nocturnal breathlessness before attributing poor sleep to insomnia
  • Prefer non-drug insomnia treatment, such as cognitive behavioural therapy for insomnia, where available
  • Taper gradually rather than stopping benzodiazepines abruptly

Why it matters

Poor sleep in a cardiac patient may be heart failure itself, and the sedative can mask it.

Don't overread it

These are associations from observational studies; they do not show that benzodiazepines cause heart failure.

The statistics, in plain English

An HR of 1.41 means about 40% higher risk among users, but observational data cannot separate the drug's effect from the reasons people take it. The admission estimate's lower bound of 1.01 means the true effect could be close to nothing.

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