Antipsychotic drugs and heart muscle disorder in international pharmacovigilance: data mining study

Abstract

Objectives: To examine the relation between antipsychotic drugs and myocarditis and cardiomyopathy. Design: Data mining using bayesian statistics implemented in a neural network architecture. Setting: International database on adverse drug reactions run by the World Health Organization programme for international drug monitoring. Main outcome measures: Reports mentioning antipsychotic drugs, cardiomyopathy, or myocarditis. Results: A strong signal existed for an association between clozapine and cardiomyopathy and myocarditis. An association was also seen with other antipsychotics as a group. The association was based on sufficient cases with adequate documentation and apparent lack of confounding to constitute a signal. Associations between myocarditis or cardiomyopathy and lithium, chlorpromazine, fluphenazine, haloperidol, and risperidone need further investigation. Conclusions: Some antipsychotic drugs seem to be linked to cardiomyopathy and myocarditis. The study shows the potential of bayesian neural networks in analysing data on drug safety.