Intervallo QT lungo
Reazione avversa da farmaco (ADR)
Varianti ✨Per l'analisi computazionale dettagliata delle varianti, si prega di selezionare l'abbonamento standard a pagamento.
Informazioni dei farmaci per i pazienti
Non abbiamo ulteriori avvertenze per la co-somministrazione di trimipramine e lopinavir. Si prega di consultare le informazioni specialistiche pertinenti.
I cambiamenti riportati in seguito all'esposizione corrispondono ai cambiamenti nell'area sottesa alla curva concentrazione plasmatica-tempo [ AUC ]. Non è stato possibile rilevare nessun tipo di cambiamento nell'esposizione alla trimipramine. Allo stato attuale non è possibile valutare come influisce la lopinavir. Non è stato possibile rilevare nessun tipo di cambiamento nell'esposizione alla lopinavir. Allo stato attuale non è possibile valutare come influisce la trimipramine.
I parametri farmacocinetici della popolazione media sono utilizzati come punto di partenza per calcolare i cambiamenti del singolo individuo esposto alle interazioni farmacologiche
La trimipramine ha una significativa biodisponibilità [ F ] orale pari al 41%, perciò attraverso un'interazione farmacologica la concentrazione plasmatica massima [Cmax] tende a cambiare di poco. L'emivita [ t12 ] del farmaco è di 23.5 ore e la concentrazione allo stato stazionario [Css] si raggiunge dopo circa 94 ore. Il legame proteico [ Pb ] è moderatamente forte al 94.9%. Tra l'altro, il metabolismo avviene rispettivamente attraverso gli enzimi CYP2C19, CYP2C9 e CYP2D6. e il trasporto attivo avviene in particolare attraverso i trasportatori PGP e TRA8X8.
La biodisponibilità della lopinavir non è nota. Il legame con le proteine [ Pb ] non è noto. Il metabolismo avviene principalmente attraverso l'enzima CYP3A4 e il trasporto attivo avviene in particolare attraverso i trasportatori PGP e TRA8X8.
|Effetti serotoninergici a||2||++||Ø|
Avvertenze: Per precauzione, si dovrebbe porre particolare attenzione ai sintomi causati da una sovrastimolazione serotoninergica, soprattutto se viene aumentato il dosaggio del farmaco e/o si supera l'intervallo terapeutico.
Valutazione: La trimipramine modula il sistema serotoninegico in modo limitato. Il rischio di sindrome serotoninergica è basso se viene rispettato il corretto dosaggio. Sulla base dei dati a nostra disposizione, la lopinavir non potenzia l'attività serotoninergica.
|Kiesel & Durán b||3||+++||Ø|
Avvertenze e precauzioni: Per precauzione, si dovrebbe porre attenzione ai sintomi di tipo anticolinergico, soprattutto se il dosaggio è stato aumentato oppure se è al di sopra dell'intervallo terapeutico.
Valutazione: La trimipramine aumenta notevolmente gli effetti anticolinergici. Sulla base dei dati a nostra disposizione, la lopinavir non causa un aumento dell'attività anticolinergica.
Intervallo QT lungo
Valutazione: La co-somministrazione di trimipramine e lopinavir potrebbe causare tachicardia ventricolare a torsione di punta.
Effetti collaterali generali
|Effetti collaterali||∑ frequenza||tri||lop|
|Aumento di peso||1.0 %||+||n.a.|
|Visione offuscata||1.0 %||+||n.a.|
Infarto miocardico: trimipramine
Morte cardiaca improvvisa: trimipramine
Epatite colestatica: trimipramine
Abbiamo valutato il rischio individuale di effetti indesiderati in base alle risposte fornite ed alle informazioni scientifiche disponibili. Le informazioni contenute nel sito hanno esclusivamente scopo informativo e non sostituiscono il parere del medico. Si accomanda pertanto di chiedere sempre il parere del proprio medico curante e/o di specialisti riguardo qualsiasi indicazione riportata. Nella versione alpha test, il rischio di tutti i farmaci non è stato ancora completamente valutato.
Abstract: Little is known about the impact of cytochrome P450 polymorphisms on the metabolism of trimipramine, which is still widely used as antidepressant due to its positive effect on sleep patterns. A single oral dose of 75 mg trimipramine was given to 42 healthy volunteers selected according to their CYP2D6, CYP2C19, and CYP2C9 genotypes. The reference group included 8 subjects with homozygous active wild-type genotypes of all 3 enzymes (EM). This group was compared with 7 intermediate (IM) with 1 and 7 poor metabolizers (PM) with zero active alleles of CYP2D6 and CYP2C19, respectively, and with 4 subjects with the genotype CYP2C9*3/*3. Pharmacokinetics of trimipramine and its demethylated metabolite strongly depended on the CYP2D6 genotype. Median oral clearance of trimipramine was 276 L/h (range 180-444) in the reference group but only 36 L/h (range 24-48) in CYP2D6 PMs (P < 0.001). These differences could only be explained by an effect of CYP genotypes on both parameters, systemic clearance and bioavailability, the latter being at least 3-fold higher in CYP2D6 PMs than in the reference group. The desmethyltrimipramine area under the concentration-time curve was 40-fold greater in CYP2D6 PMs than in the reference group (1.7 vs. 0.04 mg/L x h in EMs), but below the quantification limit in most carriers of deficiencies of CYP2C19 or CYP2C9. This indicates that both CYP2C enzymes contribute to the demethylation of desmethyltrimipramine and CYP2D6 to further metabolism.
Abstract: OBJECTIVE: To assess the potential of anticholinergic drugs as a cause of non-degenerative mild cognitive impairment in elderly people. DESIGN: Longitudinal cohort study. SETTING: 63 randomly selected general practices in the Montpellier region of southern France. PARTICIPANTS: 372 people aged > 60 years without dementia at recruitment. MAIN OUTCOME MEASURES: Anticholinergic burden from drug use, cognitive examination, and neurological assessment. RESULTS: 9.2% of subjects continuously used anticholinergic drugs during the year before cognitive assessment. Compared with non-users, they had poorer performance on reaction time, attention, delayed non-verbal memory, narrative recall, visuospatial construction, and language tasks but not on tasks of reasoning, immediate and delayed recall of wordlists, and implicit memory. Eighty per cent of the continuous users were classified as having mild cognitive impairment compared with 35% of non-users, and anticholinergic drug use was a strong predictor of mild cognitive impairment (odds ratio 5.12, P = 0.001). No difference was found between users and non-users in risk of developing dementia at follow-up after eight years. CONCLUSIONS: Elderly people taking anticholinergic drugs had significant deficits in cognitive functioning and were highly likely to be classified as mildly cognitively impaired, although not at increased risk for dementia. Doctors should assess current use of anticholinergic drugs in elderly people with mild cognitive impairment before considering administration of acetylcholinesterase inhibitors.
Abstract: Anticholinergic Drug Scale (ADS) scores were previously associated with serum anticholinergic activity (SAA) in a pilot study. To replicate these results, the association between ADS scores and SAA was determined using simple linear regression in subjects from a study of delirium in 201 long-term care facility residents who were not included in the pilot study. Simple and multiple linear regression models were then used to determine whether the ADS could be modified to more effectively predict SAA in all 297 subjects. In the replication analysis, ADS scores were significantly associated with SAA (R2 = .0947, P < .0001). In the modification analysis, each model significantly predicted SAA, including ADS scores (R2 = .0741, P < .0001). The modifications examined did not appear useful in optimizing the ADS. This study replicated findings on the association of the ADS with SAA. Future work will determine whether the ADS is clinically useful for preventing anticholinergic adverse effects.
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: Cognitive decline is common in Parkinson's disease (PD). Although some of the aetiological factors are known, it is not yet known whether drugs with anticholinergic activity (AA) contribute to this cognitive decline. Such knowledge would provide opportunities to prevent acceleration of cognitive decline in PD. OBJECTIVE: To study whether the use of agents with anticholinergic properties is an independent risk factor for cognitive decline in patients with PD. METHODS: A community-based cohort of patients with PD (n=235) were included and assessed at baseline. They were reassessed 4 and 8 years later. Cognition was assessed using the Mini-Mental State Examination (MMSE). A detailed assessment of the AA of all drugs prescribed was made, and AA was classified according to a standardised scale. Relationships between cognitive decline and AA load and duration of treatment were assessed using bivariate and multivariate statistical analyses. RESULTS: More than 40% used drugs with AA at baseline. During the 8-year follow-up, the cognitive decline was higher in those who had been taking AA drugs (median decline on MMSE 6.5 points) compared with those who had not taken such drugs (median decline 1 point; p=0.025). In linear regression analyses adjusting for age, baseline cognition and depression, significant associations with decline on MMSE were found for total AA load (standardised beta=0.229, p=0.04) as well as the duration of using AA drugs (standardised beta 0.231, p=0.032). CONCLUSION: Our findings suggest that there is an association between anticholinergic drug use and cognitive decline in PD. This may provide an important opportunity for clinicians to avoid increasing progression of cognitive decline by avoiding drugs with AA. Increased awareness by clinicians is required about the classes of drugs that have anticholinergic properties.
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: PURPOSE: The purpose of this study was to ascertain, in the context of an integrated health care delivery system, the association between a comprehensive list of drugs known to have potential QT liability and QT prolongation or shortening. METHODS: By using a self-controlled crossover study with 59 467 subjects, we ascertained intra-individual change in log-linear regression-corrected QT (QTcreg ) during the period between 1995 and mid-2008 for 90 drugs while adjusting for age, gender, race/ethnicity, comorbid conditions, number of electrocardiograms (ECGs), and time between pre-ECG and post-ECG. The proportion of users of each drug-developing incident long QT was also estimated. RESULTS: Two drugs (nicardipine and levalbuterol) had no statistically significant intra-individual QTcreg shortening effects, 10 drugs had no statistically significant prolonging effect, and 78 (87%) of the drugs had statistically significant intra-individual mean QTcreg lengthening effects, ranging from 7.6 ms for aripiprazole to 25.2 ms for amiodarone. Three drugs were associated with mean QTcreg prolongation of 20 ms or greater: amiodarone (antiarrhythmic), terfenadine (antihistaminic), and quinidine (antiarrhythmic); whereas 11 drugs were associated with mean QTcreg prolongation of 15 ms or greater but less than 20 ms: trimipramine (tricyclic antidepressant), clomipramine (tricyclic antidepressant), disopyramide (antiarrhythmic), chlorpromazine (antipsychotic), sotalol (beta blocker), itraconazole (antifungal), phenylpropanolamine (decongestant/anorectic), fenfluramine (appetite suppressant), midodrine (antihypotensive), digoxin (cardiac glycoside/antiarrhythmic), and procainamide (antiarrhythmic). CONCLUSIONS: QT prolonging effects were common and varied in strength. Our results lend support to past Food and Drug Administration regulatory actions and support the role for ongoing surveillance of drug-induced QT prolongation.