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Effects of atypical antipsychotic drugs on QT interval in patients with mental disorders
Wilbert S Aronow1, Tatyana A Shamliyan2
1Department of Cardiology, Westchester Medical Center, New York Medical College, Valhalla, NY, USA.
Background:
Drug-induced QT prolongation is associated with higher risk of cardiac arrhythmias and cardiovascular mortality. We investigated the effects of atypical antipsychotic drugs on QT interval in children and adults with mental disorders.
Methods:
We conducted random-effects direct frequentist meta-analyses of aggregate data from randomized controlled trials (RCT) and appraised the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Our search in PubMed, EMBASE, the Cochrane Library, clinicaltrials.gov, and PharmaPendium up to October 2017 identified studies that examined aripiprazole, quetiapine, risperidone, olanzapine, ziprasidone and brexpiprazole.
Results:
Low quality evidence suggests that aripiprazole (four meta-analyses and twelve RCTs), brexpiprazole (one systematic review and four RCTs) or olanzapine (five meta-analyses and twenty RCTs) do not increase QT interval. Low quality evidence suggests that ziprasidone (five meta-analyses and 11 RCTs) increases QT interval and the rates of QT prolongation while risperidone (four meta-analyses, 70 RCTs) and quetiapine (two meta-analyses and seven RCTs) are associated with QT prolongation and greater odds of torsades de pointes ventricular tachycardia especially in cases of drug overdose.
Conclusions:
The main conclusion of our study is that in people with mental disorders and under treatment with atypical antipsychotic drugs, in order to avoid QT prolongation and reduce the risk of ventricular tachycardia clinicians may recommend aripiprazole, brexpiprazole or olanzapine in licensed doses. Long-term comparative safety needs to be established.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.