General hospital psychiatry · 2024
Comprehensive signal detection of delirium-associated medication using the Food and Drug Administration Adverse Event Reporting System.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Hatano Masakazu, Sogawa Rintaro, Shin Kenji, Esumi Satoru, Ishikawa Akira, Mizumura Ryosuke, Araki Haruna, Yamada Shigeki
Аннотация
OBJECTIVE: Several medications are associated with delirium; however, studies with adequate statistical power are limited, and it is difficult to determine the effects of the various concomitant medications used in clinical practice. Therefore, in this study, we aimed to comprehensively evaluate the safety signals of delirium-associated drugs using a spontaneous adverse event reporting system.
METHOD: The JAPIC AERS (Food and Drug Administration Adverse Event Reporting System pre-processed by the Japan Pharmaceutical Information Center) was used for the analysis in this pharmacovigilance study. The reporting odds ratio (ROR) for delirium was adjusted for using multivariate logistic regression analysis with sex, age, indication, and melatonin receptor agonist use, and 22 drug categories were targeted as covariates.
RESULTS: After excluding patients with missing information, 7,527,568 patients were included in the study. Delirium signals were detected even after adjusting for covariates in 17 drug categories, including benzodiazepines (adjusted ROR, 1.76; 95% confidence interval [CI], 1.64-1.89), opioids (adjusted ROR, 4.42; 95% CI, 4.21-4.64), and tricyclic antidepressants (adjusted ROR, 2.44; 95% CI, 2.20-2.71).
CONCLUSIONS: These findings suggest that many drug classes, such as benzodiazepines, are independent risk factors for delirium and strengthen the evidence of an association between delirium and medications.
METHOD: The JAPIC AERS (Food and Drug Administration Adverse Event Reporting System pre-processed by the Japan Pharmaceutical Information Center) was used for the analysis in this pharmacovigilance study. The reporting odds ratio (ROR) for delirium was adjusted for using multivariate logistic regression analysis with sex, age, indication, and melatonin receptor agonist use, and 22 drug categories were targeted as covariates.
RESULTS: After excluding patients with missing information, 7,527,568 patients were included in the study. Delirium signals were detected even after adjusting for covariates in 17 drug categories, including benzodiazepines (adjusted ROR, 1.76; 95% confidence interval [CI], 1.64-1.89), opioids (adjusted ROR, 4.42; 95% CI, 4.21-4.64), and tricyclic antidepressants (adjusted ROR, 2.44; 95% CI, 2.20-2.71).
CONCLUSIONS: These findings suggest that many drug classes, such as benzodiazepines, are independent risk factors for delirium and strengthen the evidence of an association between delirium and medications.