Antipsychotic drugs and heart muscle disorder in international pharmacovigilance: data mining study.
OBJECTIVE
To examine the relation between antipsychotic drugs and myocarditis and cardiomyopathy.


METHODS
Data mining using bayesian statistics implemented in a neural network architecture.


METHODS
International database on adverse drug reactions run by the World Health Organization programme for international drug monitoring.


METHODS
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.
Coulter
D M
DM
Centre for Adverse Reactions Monitoring and Intensive Medicines Monitoring Programme, Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand.
Bate
A
A
Meyboom
R H
RH
Lindquist
M
M
Edwards
I R
IR
D014150:Antipsychotic Agents / Q000009:adverse effects*; D001499:Bayes Theorem; D009202:Cardiomyopathies / Q000139:chemically induced*; D003024:Clozapine / Q000009:adverse effects*; D016208:Databases, Factual; D016903:Drug Monitoring; D006801:Humans; D009205:Myocarditis / Q000139:chemically induced; D016571:Neural Networks, Computer; D017891:Pharmacoepidemiology / Q000379:methods*; D014944:World Health Organization
D014150:Antipsychotic Agents; D003024:Clozapine