A multicenter retrospective cohort study on predicting the risk for amiodarone pulmonary toxicity.

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2022-04

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Abstract

Background

Amiodarone is one of the most commonly used anti-arrhythmic agents. Amiodarone pulmonary toxicity is a potentially fatal adverse effect associated with amiodarone use. Previous studies on the epidemiology and risk factors for amiodarone pulmonary toxicity showed diverse results.

Methods

A multicenter retrospective cohort study was conducted to identify clinic-epidemiologic markers associated with amiodarone pulmonary toxicity for development of a prediction rule. Patients taking amiodarone who were managed in 3 centres in Hong Kong from 2005 to 2015 were included in this study. Penalized logistic regression was used to model the outcome as it is rare.

Results

A total of 34 cases with amiodarone pulmonary toxicity were identified among 1786 patients taking amiodarone for at least 90 days from 2005 to 2015. The incidence of amiodarone pulmonary toxicity was estimated to be 1.9%. The risk factors for amiodarone pulmonary toxicity included advanced age (OR 1.047, 95% CI 1.010-1.085, p = 0.013), ventricular arrhythmia (OR 2.703, 95% CI 1.053-6.935, p = 0.039), underlying lung disease (OR 2.511, 95% CI 1.146-5.501, p = 0.021) and cumulative dose of amiodarone (OR 4.762, 95% CI 1.310-17.309 p = 0.018).

Conclusions

The incidence of amiodarone pulmonary toxicity in Chinese patients in Hong Kong is estimated to be 1.9% in this study. Age, underlying lung disease, ventricular arrhythmia and cumulative dose of amiodarone are associated with the development of amiodarone pulmonary toxicity. A prediction rule was developed to inform the risk of developing amiodarone pulmonary toxicity.

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Published Version (Please cite this version)

10.1186/s12890-022-01926-y

Publication Info

Kwok, Wang Chun, Ting Fung Ma, Johnny Wai Man Chan, Herbert H Pang and James Chung Man Ho (2022). A multicenter retrospective cohort study on predicting the risk for amiodarone pulmonary toxicity. BMC pulmonary medicine, 22(1). p. 128. 10.1186/s12890-022-01926-y Retrieved from https://hdl.handle.net/10161/30410.

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Scholars@Duke

Pang

Herbert Pang

Adjunct Assistant Professor in the Department of Biostatistics & Bioinformatics

Classification and Predictive Models
Design and Analysis of Biomarker Clinical Trials
Genomics
Pathway Analysis


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