Association between citalopram, escitalopram and QTc prolongation in a real-world geriatric setting
- PMID: 30877856
- DOI: 10.1016/j.jad.2019.02.060
Association between citalopram, escitalopram and QTc prolongation in a real-world geriatric setting
Abstract
Background: Although the US Food and Drug Administration (FDA) recommended upper limits for citalopram dosing in older adults due to risk of corrected-QT (QTc) prolongation, which was adopted, and extended to escitalopram by Health Canada, the scientific basis is unclear. The objective of this study was to assess the relationship between citalopram/escitalopram dosages and QTc interval in a real-world geriatric setting.
Methods: We reviewed electronic health records at a university-affiliated geriatric health care center, over a 7-year period, to identify patients prescribed citalopram and escitalopram, who had an ECG within 90 days of initiation or dosage change. Linear regression analyses were conducted to assess the relationship between antidepressant dosage and QTc interval.
Results: 137 patients were identified (citalopram=97, escitalopram=40). No association was found between citalopram, escitalopram and QTc, in unadjusted or adjusted analyses. Among covariates, older age was significantly associated with QTc prolongation in the escitalopram group.
Limitations: Limitations to the current study include its retrospective design and the small sample size.
Conclusions: These data do not support the FDA or Health Canada's recommended maximum dosages of citalopram or escitalopram in the elderly. Therefore, for patients already on higher doses of these medications, the risk of QTc prolongation may not always outweigh the risk of dose lowering, such as relapse. Until larger prospective studies become available, the decision to comply or not with these federal agencies' recommendations should be weighed on an individual basis, taking into consideration all potential risk factors.
Keywords: Antidepressants; Citalopram; Escitalopram; Geriatric psychiatry; QTc interval.
Copyright © 2019. Published by Elsevier B.V.
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