Risk Of Torsade De Pointes Research Articles

Effects of Dexmedetomidine on Myocardial Repolarization in Children Undergoing General Anesthesia: A Randomized Controlled Trial.

Dexmedetomidine is a highly selective α2-adrenergic agonist, which is increasingly used in pediatric anesthesia and intensive care. Potential adverse effects that have not been rigorously evaluated in children include its effects on myocardial repolarization, which is important given that the drug is listed as a possible risk factor for torsades de pointes. We investigated the effect of 3 different doses of dexmedetomidine on myocardial repolarization and transmural dispersion in children undergoing elective surgery with total IV anesthesia. Sixty-four American Society of Anesthesiologists I-II children 3-10 years of age were randomized to receive dexmedetomidine 0.25 µg/kg, 0.5 µg/kg, 0.75 µg/kg, or 0 µg/kg (control), as a bolus administered over 60 seconds, after induction of anesthesia. Pre- and postintervention 12-lead electrocardiograms were recorded. The interval between the peak and the end of the electrocardiogram T wave (Tp-e; transmural dispersion) and heart rate-corrected QT intervals (myocardial repolarization) were measured by a pediatric electrophysiologist blinded to group allocation. Data were analyzed using an analysis of covariance regression model. The study was powered to detect a 25-millisecond difference in Tp-e. Forty-eight children completed the study, with data analyzed from 12 participants per group. There were no instances of dysrhythmias. Tp-e values were unaffected by dexmedetomidine administration at any of the studied doses (F = 0.09; P = .96). Mean (99% CI) within-group differences were all <2 milliseconds (-5 to 8). Postintervention, corrected QT interval increased in the control group, but decreased in some dexmedetomidine groups (F = 7.23; P < .001), specifically the dexmedetomidine 0.5 and 0.75 µg/kg doses. Within groups, the mean (99% CI) differences between pre- and postintervention corrected QT interval were 12.4 milliseconds (-5.8 to 30.6) in the control group, -9.0 milliseconds (-24.9 to 6.9) for dexmedetomidine 0.25 µg/kg, -18.6 milliseconds (-33.7 to -3.5) for dexmedetomidine 0.5 µg/kg, and -14.1 milliseconds (-27.4 to -0.8) for dexmedetomidine 0.75 µg/kg. Of the bolus doses of dexmedetomidine studied, none had an effect on Tp-e and the dexmedetomidine 0.5 and 0.75 µg/kg doses shortened corrected QT intervals when measured at 1 minute after dexmedetomidine bolus injection during total IV anesthesia. There is no evidence for an increased risk of torsades de pointes in this context.

Relationship of clinical adverse event reports to models of arrhythmia risk

A vital aspect of the drug discovery and development process is the identification and filtering of drugs with high risk of dangerous adverse events. Torsade de Pointes (TdP) is one example of an adverse event that requires thorough in vitro and in vivo drug screening. This is because TdP, a tachycardic ventricular arrhythmia, can develop into fatal cardiac events if left unresolved and has been missed during drug development with profound consequences. These factors led to the development of pre-clinical screening guidelines based on the presence of drug induced QT prolongation (QTp), which has been linked to TdP. These guidelines have high sensitivity, but low specificity, as they tend to predict QTp, which precedes TdP events but does not always lead to TdP. Computational models have the potential to improve these prediction methods by bridging the gaps between preclinical and clinical data. This study proposes the use of adverse event reports obtained from the FDA Adverse Event Reporting System as a representation of clinical TdP risk. By incorporating these reports into computational models, a more accurate risk prediction may be developed.

Classification of drug-induced hERG potassium-channel block from electrocardiographic T-wave features using artificial neural networks.

Human ether-à-go-go-related gene (hERG) potassium-channel block represents a harmful side effect of drug therapy that may cause torsade de pointes (TdP). Analysis of ventricular repolarization through electrocardiographic T-wave features represents a noninvasive way to accurately evaluate the TdP risk in drug-safety studies. This study proposes an artificial neural network (ANN) for noninvasive electrocardiography-based classification of the hERG potassium-channel block. The data were taken from the "ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects" Physionet database; they consisted of median vector magnitude (VM) beats of 22 healthy subjects receiving a single 500μg dose of dofetilide. Fourteen VM beats were considered for each subject, relative to time-points ranging from 0.5hr before to 14.0hr after dofetilide administration. For each VM, changes in two indexes accounting for the early and the late phases of repolarization, ΔERD30% and ΔTS/A , respectively, were computed as difference between values at each postdose time-point and the predose time-point. Thus, the dataset contained 286 ΔERD30% -ΔTS/A pairs, partitioned into training, validation, and test sets (114, 29, and 143 pairs, respectively) and used as inputs of a two-layer feedforward ANN with two target classes: high block (HB) and low block (LB). Optimal ANN (OANN) was identified using the training and validation sets and tested on the test set. Test set area under the receiver operating characteristic was 0.91; sensitivity, specificity, accuracy, and precision were 0.93, 0.83, 0.92, and 0.96, respectively. OANN represents a reliable tool for noninvasive assessment of the hERG potassium-channel block.

Long-term proarrhythmic pharmacotherapy among patients with congenital long QT syndrome and risk of arrhythmia and mortality.

It is Class I recommendation that congenital long QT syndrome (cLQTS) patients should avoid drugs that can cause torsades de pointes (TdP). We determined use of TdP risk drugs after cLQTS diagnosis and associated risk of ventricular arrhythmia and all-cause mortality. Congenital long QT syndrome patients (1995-2015) were identified from four inherited cardiac disease clinics in Denmark. Individual-level linkage of nation-wide registries was performed to determine TdP risk drugs usage (www.crediblemeds.org) and associated risk of ventricular arrhythmias and all-cause mortality. Risk analyses were performed using Cox-hazards analyses. During follow-up, 167/279 (60%) cLQTS patients were treated with a TdP risk drug after diagnosis. Most common TdP risk drugs were antibiotics (34.1%), proton-pump inhibitors (15.0%), antidepressants (12.0%), and antifungals (10.2%). Treatment with a TdP risk drug decreased 1 year after diagnosis compared with 1 year before (28.4% and 23.2%, respectively, P < 0.001). Five years after diagnosis, 33.5% were in treatment (P < 0.001). Risk factors for TdP risk drug treatment were age at diagnosis (5-year increment) [hazard ratio (HR) = 1.07, confidence interval (CI) 1.03-1.11] and previous TdP risk drug treatment (HR = 2.57, CI 1.83-3.61). During follow-up, nine patients were admitted with ventricular arrhythmia (three were in treatment with a TdP risk drug). Eight patients died (four were in treatment with a TdP risk drug). No significant association between TdP risk drug use and ventricular arrhythmias or all-cause mortality was found (P = 0.53 and P = 0.93, respectively), but events were few. Torsades de pointes risk drug usage was common among cLQTS patients after time of diagnosis and increased over time. A critical need for more awareness in prescribing patterns for this high-risk patient group is needed.

Twenty-Four-Hour Measures of Heart Rate-Corrected QT Interval, Peak-to-End of the T-Wave, and Peak-to-End of the T-Wave/Corrected QT Interval Ratio During Antipsychotic Treatment.

Prolonged ventricular repolarization, measured by heart rate-corrected QT interval (QTc) prolongation, might be a biomarker for risk of torsade de pointes (TdP) and sudden cardiac death. However, the predictive value of QTc has been challenged, and a component of QTc, peak-to-end of the T-wave (Tpe), and a high Tpe/QT ratio might be superior biomarkers because they better reflect increased transmural dispersion of ventricular myocyte repolarization, which can lead to TDP. The purpose of this pilot study was to provide the first measurements of heart rate, QTc, Tpe, Tpe/QTc, and their variability over 24 hours in medication-free patients with schizophrenia, during treatment with ziprasidone or other antipsychotic drugs, and healthy controls. Subjects included 12 patients treated with ziprasidone, 30 treated with other antipsychotic drugs, 3 unmedicated patients, and 15 normal controls. Subjects underwent 24-hour analog Holter recording, and the recordings were digitized. A cardiologist blind to treatment selected multiple 10-cycle segments throughout each recording and measured the electrocardiogram metrics. Variability in QTc, Tpe, and Tpe/QTc over the 24 hours was present in all groups; 91.1% of patients and 100% of controls had 1 or more QTc values of 450 milliseconds or greater. Mean QTc length was significantly greater in the ziprasidone-treated than the non-ziprasidone-treated patients (P = 0.02). Mean Tpe was not elevated in the ziprasidone patients, whereas mean Tpe/QTc was lower (P < 0.01). The large variability in QTc, Tpe, and Tpe/QTc observed supports the need for 24-hour electrocardiogram recordings to provide an accurate assessment of risk of TdP. Heart rate-corrected QT interval alone does not capture the risk of TdP.

RISK FACTORS ASSOCIATED WITH DOFETILIDE INTOLERANCE

Dofetilide is a class III antiarrhythmic requiring hospitalization for initiation due to the risk for torsades de pointes (TdP) ventricular tachycardia early in therapy. Dofetilide is subject to many drug interactions, which may increase the risk for intolerance. This is a single-center

RECURRENT TORSADE DE POINTES IN A PATIENT WITH NORMAL QT INTERVAL

One of the life-threatening effect of Dofetilide is QT prolongation, which greatly increases the risk of Torsade de Pointes(TdP). Any prolonged QT interval during the initial doses may lead to reduction or termination of the medication. Very few patients had to stop taking Dofetilide because of QT

TORSADES DE POINTES SECONDARY TO SOTALOL: PREDICTABLE BUT NOT ALWAYS PREVENTABLE

Sotalol is an effective antiarrhythmic drug for the maintenance of sinus rhythm in atrial fibrillation. However, its QTc-prolonging effect increases the risk for torsades de pointes (TdP) and sudden cardiac death. Thus, it is typically loaded in the inpatient setting with close cardiac monitoring

Implementation of the FDA CiPA Qnet Model for Drug Safety Screening Which Increases Efficiency 25 Fold

In silico computer modeling to assess drug proarrhythmia risk is a key component of the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. The recently-published qNet metric shows promise for correctly determining drug-induced Torsades-de-Pointes (TdP) risk (high/intermediate/low) of drugs using an in silico model of the human ventricular action potential (AP). The model combines simulations of multiple ionic channels (including O’Hara Rudy dynamic (ORd) drug-binding hERG model) and in vitro pharmacology data. Using this model, TdP risk can be determined via qNet for the 12 CiPA training and 16 validation compounds. The FDA made an open source R script of this model available (github). This program can be used to calculate both the qNet metric and its uncertainty quantification. Simulating the AP and determining the uncertainty quantification is a computationally-intensive task, not well-suited for R. We translated the FDA R script to C and parallelized the code using both OpenMP (shared memory parallelism) and MPI (distributed memory parallelism). The serial C code produces the same results as the R script, but with a five-fold increase in efficiency. Running the OpenMP C code on a PC with an eight core processor results in ∼25-fold increase in efficiency vs. R script. The MPI version of the code can be run on a high performance computing resource and results in an even greater increase, depending on the number of processors employed. Using the R script to generate a simulation of the effect of a single drug on the AP using 500 samples takes 16.5 days using R script. With the parallel C code, it takes just 15.3 Hours. This reduction in computational time required will significantly reduce the time taken to calculate the arrhythmogenic profile of any compound.

Comparison of Electrocardiographic Biomarkers for Differentiating Drug‐Induced Single vs. Multiple Cardiac Ion Channel Block

Since introduction of the International Conference on Harmonization proarrhythmia guidelines in 2005, no new marketed drugs have been associated with unacceptable risk of Torsade de Pointes. Although cardiac safety improved, these guidelines had the unintended consequence of eliminating potentially beneficial drugs from pipelines early in development. More recently, it has been shown that a corrected QT (QTc) prolonging drug may be safe if it impacts multiple ion channels vs. only human ether‐a‐go‐go related gene (hERG) and that this effect can be discriminated using QT subintervals. We compared the predictive power of four electrocardiogram (ECG) repolarization metrics to discriminate single vs. multichannel block: (i) traditional 10‐second signal averaged triplicates, and (ii) three metrics that used increasing density of automatically measured beat‐to‐beat (btb) intervals. Predictive power was evaluated using logistic regression and quantified with receiver operating characteristic (ROC) area under the curve (AUC). Compared with the traditional 10‐second signal averaged triplicates, the reduction in classification error ranged from 2−6 with increasing density of btb measurements.

Introduction to in silico model for proarrhythmic risk assessment under the CiPA initiative.

In 2005, the International Council for Harmonization (ICH) established cardiotoxicity assessment guidelines to identify the risk of Torsade de Pointes (TdP). It is focused on the blockade of the human ether-à-go-go-related gene (hERG) channel known to cause QT/QTc prolongation and the QT/QTc prolongation shown on the electrocardiogram. However, these biomarkers are not the direct risks of TdP with low specificity as the action potential is influenced by multiple channels along with the hERG channel. Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative emerged to address limitations of the current model. The objective of CiPA is to develop a standardized in silico model of a human ventricular cell to quantitively evaluate the cardiac response for the cardiac toxicity risk and to come up with a metric for the TdP risk assessment. In silico working group under CiPA developed a standardized and reliable in silico model and a metric that can quantitatively evaluate cellular cardiac electrophysiologic activity. The implementation mainly consists of hERG fitting, Hill fitting, and action potential simulation. In this review, we explained how the in silico model of CiPA works, and briefly summarized current overall CiPA studies. We hope this review helps clinical pharmacologists to understand the underlying estimation process of CiPA in silico modeling.

In silico electro-mechanical window shortening and repolarisation abnormalities predict clinical risk of torsade de pointes for 40 reference compounds

In silico electro-mechanical window shortening and repolarisation abnormalities predict clinical risk of torsade de pointes for 40 reference compounds

Statistical design of in silico experiments for the robustness analysis of electrophysiologic response simulators

To assess the risk of Torsade de Pointes, the CiPA initiative has proposed to test in silico models able to reconstruct electrophysiologic responses and analyze mechanistic causes of specific toxicological events such as TdP. One example of such simulators is the O’Hara Rudy’s model, used herein as a benchmark model. Such in silico models are composed of a large number of biological parameters. Their values are never fully known and they are generally estimated with a substantial uncertainty. So, what happens if the values of some parameters are wrong? Can we still trust the simulated responses? In this application context, our objective is to firstly identify the critical modeling parameters. To reduce the computation time, we propose a statistical approach suited to the screening of model parameters. Our approach relies on a Placket-Burman design of numerical assays. 79 models parameters have been tested and only 80 numerical experiments were carried out. The action potential response was split up into five phases and three statistics (duration, AUC and amplitude) were computed for each phase. Accordingly, 15 response variables were analyzed. A Pareto analysis is finally used to rank the most critical parameters. Results show that all the tested modeling factors have the same order of effect on the global response. In other terms, no parameter can be neglected. Two parameters appear as more critical than the other ones: the stimulus current and the initial temperature of the cell. The effects of all the parameters on each of the five beating phase are also estimated and ranked. This study analyzes the sensitivity of the simulated potential action response with respect to uncertainty on 79 modeling parameters. All of them have significant effects on at least one part of the response, which emphasizes the relevance to accurately estimate them to trust simulations. As a consequence, another crucial question is worth asking and deals with the model identifiability, i.e. the possibility to learn the true values of the model parameters after obtaining an infinite (theoretical identifiability) or a finite (practical identifiability) number of in vitro observations.

International Multisite Study of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes for Drug Proarrhythmic Potential Assessment

SUMMARYTo assess the utility of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) as an in vitro proarrhythmia model, we evaluated the concentration dependence and sources of variability of electrophysiologic responses to 28 drugs linked to low, intermediate, and high torsades de pointes (TdP) risk categories using two commercial cell lines and standardized protocols in a blinded multisite study using multielectrode array or voltage-sensing optical approaches. Logistical and ordinal linear regression models were constructed using drug responses as predictors and TdP risk categories as outcomes. Three of seven predictors (drug-induced arrhythmia-like events and prolongation of repolarization at either maximum tested or maximal clinical exposures) categorized drugs with reasonable accuracy (area under the curve values of receiver operator curves ~0.8). hiPSC-CM line, test site, and platform had minimal influence on drug categorization. These results demonstrate the utility of hiPSCCMs to detect drug-induced proarrhythmic effects as part of the evolving Comprehensive In Vitro Proarrhythmia Assay paradigm.

Safety Limits of Antidepressant Use Plus Combinations: Focus on Cardiovascular Function.

Antidepressants have been widely prescribed for depression, anxiety, sleep disorders, and in the management of behavioural symptoms of adult-old patients. Although generally safe, newer generation antidepressants are not devoid of the risk of inducing clinically relevant adverse events. To investigate the association between newer generation antidepressants and the occurrence of cardiovascular adverse events and electrocardiogram (ECG) abnormalities. Studies were included in the review according to the following criteria: a) clinical trials (placebo-controlled or not) or case reports; b) short- or long-term interventions with antidepressants; c) prescription of newer generation antidepressants as first-line treatment; d) samples of adult or adult-old patients. From a total of 301 articles addressing the association between antidepressants and cardiovascular adverse events as primary or secondary outcomes, we selected 30 controlled clinical trials and 10 case reports. In most clinical studies, the effects of antidepressants on cardiac function are usually computed as secondary outcome variables, however with limited information. Conversely, case reports tend to present more comprehensive sets of clinical and laboratorial parameters, but the generalization of such data is limited by the small number of observations. The occurrence of QTc prolongation (with increased risk of torsade de pointes) has been reported. Aging, higher dosages of antidepressants, drug interaction, and pre-existing cardiovascular comorbidities were found as risk factors for the aforementioned cardiovascular and ECG abnormalities. Prescribing antidepressants requires caution given their potential impact on cardiac function, and the clinician should carefully monitor cardiovascular and ECG parameters particularly in cases with underlying heart disease.

Predictive Analytics for Identification of Patients at Risk for QT Interval Prolongation: A Systematic Review

Prolongation of the heart rate-corrected QT (QTc) interval increases the risk for torsade de pointes (TdP), a potentially fatal arrhythmia. The likelihood of TdP is higher in patients with risk factors that include female sex, older age, heart failure with reduced ejection fraction, hypokalemia, hypomagnesemia, concomitant administration of two or more QTc interval-prolonging medications, among others. Assessment and quantification of risk factors may facilitate prediction of patients at highest risk for developing QTc interval prolongation and TdP. Investigators have utilized the field of predictive analytics, which generates predictions using techniques including data mining, modeling, machine learning, and others, to develop methods of risk quantification and prediction of QTc interval prolongation. Predictive analytics have also been incorporated into clinical decision support (CDS) tools to alert clinicians regarding patients at increased risk of developing QTc interval prolongation. The objectives of this article are to assess the effectiveness of predictive analytics for identification of patients at risk of drug-induced QTc interval prolongation and to discuss the efficacy of incorporation of predictive analytics into CDS tools in clinical practice. A systematic review of English-language articles (human subjects only) was performed, yielding 57 articles, with an additional 4 articles identified from other sources; a total of 10 articles were included in this review. Risk scores for QTc interval prolongation have been developed in various patient populations including those in cardiac intensive care units (ICUs) and in broader populations of hospitalized or health system patients. One group developed a risk score that includes information regarding genetic polymorphisms; this score significantly predicted TdP. Development of QTc interval prolongation risk prediction models and incorporation of these models into CDS tools reduce the risk of QTc interval prolongation in cardiac ICUs and identify health system patients at increased risk for mortality. The impact of these QTc interval prolongation predictive analytics on overall patient safety outcomes, such as TdP and sudden cardiac death relative to the cost of development and implementation, requires further study.

Virtual Thorough QT (TQT) Trial\u2014Extrapolation of In Vitro Cardiac Safety Data to In Vivo Situation Using Multi-Scale Physiologically Based Ventricular Cell-wall Model Exemplified with Tolterodine and Fesoterodine

QT interval prolongation typically assessed with dedicated clinical trials called thorough QT/QTc (TQT) studies is used as surrogate to identify the proarrhythmic risk of drugs albeit with criticism in terms of cost-effectiveness in establishing the actual risk of torsade de pointes (TdP). Quantitative systems toxicology and safety (QSTS) models have potential to quantitatively translate the in vitro cardiac safety data to clinical level including simulation of TQT trials. Virtual TQT simulations have been exemplified with use of two related drugs tolterodine and fesoterodine. The impact of bio-relevant concentration in plasma versus estimated heart tissue exposure on predictions was also assessed. Tolterodine and its therapeutically equipotent metabolite formed via CYP2D6 pathway, 5-HMT, inhibit multiple cardiac ion currents (IKr, INa, ICaL). The QSTS model was able to accurately simulate the QT prolongation at therapeutic and supra-therapeutic dose levels of tolterodine well within 95% confidence interval limits of observed data. The model was able to predict the QT prolongation difference between CYP2D6 extensive and poor metaboliser subject groups at both dose levels thus confirming the ability of the model to account for electrophysiologically active metabolite. The QSTS model was able to simulate the negligible QT prolongation observed with fesoterodine establishing that the 5-HMT does not prolong QT interval even though it is a blocker of hERG channel. With examples of TOL and FESO, we demonstrated the utility of the QSTS approaches to simulate virtual TQT trials, which in turn could complement and reduce the clinical studies or help optimise clinical trial designs.

Reining in the QTc: reducing the risk of Torsades de Pointes across a major health system.

Hospitalized patients have a high prevalence of prolonged QTc and are a high-risk population for Torsades de Pointes (TdP). One modifiable risk factor for TdP is the use of QT prolonging drugs. Electronically alerting providers who are ordering QT prolonging drugs in at-risk patients may help to achieve safer prescribing practices. Our previous study decreased inappropriate prescription of IV haloperidol by 36% using a targeted "smart" electronic alert. We wanted to assess an approach to expanding this type of electronic alert to commonly used QT prolonging medications and evaluate how this would affect prescribing practice. This retrospective cohort study evaluated the impact of these alerts for 12 frequently prescribed high-risk medications across a major health system. Between October 2016 and June 2017, a total of 6453 alerts fired and resulted in 3020 (46.8%) orders being cancelled by the provider. Our focused electronic alert significantly decreased prescribing of QT prolonging medications in high-risk patients.

Significance of prolonged QTc in acute exacerbations of COPD requiring hospitalization.

BackgroundA prolonged QT interval is associated with increased risk of Torsade de Pointes and cardiovascular death. The prevalence and clinical relevance of QT prolongation in acute exacerbations of COPD (AECOPD), with high risk for cardiac morbidity and mortality, is currently unclear.MethodsA dual cross-sectional study strategy was therefore designed. A retrospective study evaluated 140 patients with an AECOPD requiring hospitalization, half of which had prolonged QTc on the admission ECG. Univariate and multivariate analyses were conducted to determine associated factors; Kaplan–Meier and Cox regression analyses to assess prognostic significance. A prospective study evaluated 180 pulmonary patients with acute respiratory problems requiring hospitalization, to determine whether a prolonged QTc at admission represents an AECOPD-specific finding and to investigate the change in QTc-duration during hospitalization.ResultsRetrospectively, hypokalemia, cardiac troponin T and conductance abnormalities on ECG were significantly and independently associated with QTc prolongation. A prolonged QTc was associated with increased all-cause mortality (HR 2.698 (95% CI 1.032–7.055), p=0.043), however, this association was no longer significant when corrected for age, FEV1 and cardiac troponin T. Prospectively, QTc prolongation was observed in 1/3 of the patients diagnosed with either an AECOPD, lung cancer, pulmonary infection or miscellaneous acute pulmonary disease, and was not more prevalent in AECOPD. The QTc-duration decreased significantly during hospitalization in patients with and without COPD.ConclusionA prolonged QTc is a marker of underlying cardiovascular disease during an AECOPD. It is not COPD-specific, but a common finding during the acute phase of a pulmonary disease requiring urgent hospital admission.

Increased long QT and torsade de pointes reporting on tamoxifen compared with aromatase inhibitors

ObjectiveA prolonged QTc (LQT) is a surrogate for the risk of torsade de pointes (TdP). QTc interval duration is influenced by sex hormones: oestradiol prolongs and testosterone shortens QTc. Drugs...