QT time prolongation
Adverse drug events
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Explanations of the substances for patients
We have no additional warnings for the combination of lopinavir and zuclopenthixol. Please also consult the relevant specialist information.
The reported changes in exposure correspond to the changes in the plasma concentration-time curve [ AUC ]. We do not expect any change in exposure for lopinavir, when combined with zuclopenthixol (100%). We did not detect any change in exposure to zuclopenthixol. We currently cannot estimate the influence of lopinavir.
The pharmacokinetic parameters of the average population are used as the starting point for calculating the individual changes in exposure due to the interactions.
The bioavailability of lopinavir is unknown. Protein binding [ Pb ] is not known. The metabolism mainly takes place via CYP3A4 and the active transport takes place in particular via PGP.
Zuclopenthixol has a mean oral bioavailability [ F ] of 49%, which is why the maximum plasma levels [Cmax] tend to change with an interaction. The terminal half-life [ t12 ] is 20 hours and constant plasma levels [ Css ] are reached after approximately 80 hours. The protein binding [ Pb ] is 98% strong. The metabolism takes place via CYP2D6 and CYP3A4, among others.
|Serotonergic Effects a||0||Ø||Ø|
Rating: According to our knowledge, neither lopinavir nor zuclopenthixol increase serotonergic activity.
|Kiesel & Durán b||2||Ø||++|
Recommendation: As a precaution, attention should be paid to anticholinergic symptoms, especially after increasing the dose and at doses in the upper therapeutic range.
Rating: Zuclopenthixol modulates the anticholinergic system to a moderate extent. The risk of anticholinergic syndrome with this medication is rather low if the dosage is in the usual range. According to our knowledge, lopinavir does not increase anticholinergic activity.
QT time prolongation
Rating: In combination, lopinavir and zuclopenthixol can potentially trigger ventricular arrhythmias of the torsades de pointes type.
General adverse effects
|Side effects||∑ frequency||lop||zuc|
|Tardive dyskinesia||0.2 %||n.a.||0.2|
|Cerebrovascular accident||0.0 %||n.a.||0.0|
|Neuroleptic malignant syndrome||0.0 %||n.a.||0.0|
|Abnormal ejaculation||0.0 %||n.a.||0.0|
|Erectile dysfunction||0.0 %||n.a.||0.0|
Based on your answers and scientific information, we assess the individual risk of undesirable side effects. These recommendations are intended to advise professionals and are not a substitute for consultation with a doctor. In the restricted test version (alpha), the risk of all substances has not yet been conclusively assessed.
Abstract: On the basis of a single clinical trial in first-line treatment, the atazanavir and ritonavir combination appears to be no more effective than the fixed-dose combination of lopinavir and ritonavir. The adverse effect profiles were slightly different, but atazanavir carries a troubling risk of torsades de pointes.
Abstract: BACKGROUND: Drug-induced torsades de pointes (TdP) is a complex regulatory and clinical problem due to the rarity of this sometimes fatal adverse event. In this context, the US FDA Adverse Event Reporting System (AERS) is an important source of information, which can be applied to the analysis of TdP liability of marketed drugs. OBJECTIVE: To critically evaluate the risk of antimicrobial-induced TdP by detecting alert signals in the AERS, on the basis of both quantitative and qualitative analyses. METHODS: Reports of TdP from January 2004 through December 2008 were retrieved from the public version of the AERS. The absolute number of cases and reporting odds ratio as a measure of disproportionality were evaluated for each antimicrobial drug (quantitative approach). A list of drugs with suspected TdP liability (provided by the Arizona Centre of Education and Research on Therapeutics [CERT]) was used as a reference to define signals. In a further analysis, to refine signal detection, we identified TdP cases without co-medications listed by Arizona CERT (qualitative approach). RESULTS: Over the 5-year period, 374 reports of TdP were retrieved: 28 antibacterials, 8 antifungals, 1 antileprosy and 26 antivirals were involved. Antimicrobials more frequently reported were levofloxacin (55) and moxifloxacin (37) among the antibacterials, fluconazole (47) and voriconazole (17) among the antifungals, and lamivudine (8) and nelfinavir (6) among the antivirals. A significant disproportionality was observed for 17 compounds, including several macrolides, fluoroquinolones, linezolid, triazole antifungals, caspofungin, indinavir and nelfinavir. With the qualitative approach, we identified the following additional drugs or fixed dose combinations, characterized by at least two TdP cases without co-medications listed by Arizona CERT: ceftriaxone, piperacillin/tazobactam, cotrimoxazole, metronidazole, ribavirin, lamivudine and lopinavir/ritonavir. DISCUSSION: Disproportionality for macrolides, fluoroquinolones and most of the azole antifungals should be viewed as 'expected' according to Arizona CERT list. By contrast, signals were generated by linezolid, caspofungin, posaconazole, indinavir and nelfinavir. Drugs detected only by the qualitative approach should be further investigated by increasing the sensitivity of the method, e.g. by searching also for the TdP surrogate marker, prolongation of the QT interval. CONCLUSIONS: The freely available version of the FDA AERS database represents an important source to detect signals of TdP. In particular, our analysis generated five signals among antimicrobials for which further investigations and active surveillance are warranted. These signals should be considered in evaluating the benefit-risk profile of these drugs.
Abstract: Background QT prolongation and associated arrhythmias, torsades de pointes (TdP), are considerable negative outcomes of many antipsychotic and antidepressant agents frequently used by psychiatric patients. Objective To identify the prevalence, levels, and predictors of QT prolonging drug-drug interactions (QT-DDIs), and AZCERT (Arizona Center for Education and Research on Therapeutics) classification of drugs involved in QT-DDIs. Setting Psychiatry wards of three major tertiary care hospitals of Khyber-Pakhtunkhwa, Pakistan. Method This was a multicenter cross-sectional study. Micromedex DrugReax was used for identification of QT-DDIs. TdP risks were identified by the AZCERT classification. Multivariate logistic regression analysis was performed to identify predictors of QT-DDIs. Main outcome measure Prevalence of QT-DDIs (overall, age-wise and gender-wise) and their levels of severity and documentation; AZCERT classes of drugs involved in QT-DDIs; and odds ratios for predictors of QT-DDIs. Results Of 600 patients, 58.5% were female. Median age was 25 years (IQR = 20-35). Overall 51.7% patients had QT-DDIs. Of total 698 identified QT-DDIs, most were of major-severity (98.4%) and fair-documentation (93.7%). According to the AZCERT classification, 36.4% of the interacting drugs were included in list-1 (known risk of TdP), 26.9% in list-2 (possible risk of TdP) and 27.5% in list-3 (conditional risk of TdP). Drugs commonly involved in QT-DDI were olanzapine (n = 146), haloperidol (138), escitalopram (122), risperidone (91), zuclopenthixol (87), quetiapine (n80) and fluoxetine (74). In multivariate logistic regression analysis, QT-DDIs were significantly associated with 6-7 prescribed medications (p = 0.04) and >7 medications (p = 0.03). Similarly, there was significant association of occurrence of QT-DDIs with 2-3 QT drugs (p < 0.001) and >3 QT drugs (p < 0.001). Conclusion A considerable number of patients are exposed to QT-DDIs in psychiatry. There is a need to implement protocol for monitoring the outcomes of QT-DDIs.