Drug-induced QTc Prolongation Research Articles

A Calculated Risk: Evaluation of QTc Drug-Drug Interaction (DDI) Clinical Decision Support (CDS) Alerts and Performance of the Tisdale Risk Score Calculator.

A risk factor for a potentially fatal ventricular arrhythmia Torsade de Pointes is a prolongation in the heart rate-corrected QT interval (QTc) ≥ 500milliseconds (ms) or an increase of ≥60ms from a patient's baseline value, which can cause sudden cardiac death. The Tisdale risk score calculator uses clinical variables to predict which hospitalized patients are at the highest risk for QTc prolongation. To determine the rate of overridden QTc drug-drug interaction (DDI)-related clinical decision support (CDS) alerts per patient admission and the prevalence by Tisdale risk score category of these overridden alerts. Secondary outcome was to determine the rate of drug-induced QTc prolongation (diQTP) associated with overrides. Our organization's enterprise data warehouse was used to retrospectively access QTc DDI alerts presented for patients aged ≥18years who were admitted to Brigham and Women's Hospital during 2022. The QTc DDI CDS alerts were included if shown to a physician, fellow, resident, physician assistant, or nurse practitioner when entering the order in inpatient areas for patients with a length of stay of at least 2days. Variables collected for the Tisdale calculator included age, sex, whether patient was on a loop diuretic, potassium level, admission QTc value, admitting diagnosis of acute myocardial infarction, sepsis, or heart failure, and number of QTc-prolonging drugs given to the patient. A total of 2649 patients with 3033 patient admissions had 18,432 QTc DDI alerts presented that were overridden. An average of 3 unique QTc DDI alerts were presented per patient admission and the alerts were overridden an average of 6 times per patient admission. Overall, 6% of patient admissions were low risk (score ≤ 6), 64% moderate risk (score 7-10), and 30% high risk (score ≥ 11) of QTc prolongation. The most common QTc DDI alerts overridden resulting in an diQTP were quetiapine and propofol (11%) and amiodarone and haloperidol (7%). The diQTP occurred in 883 of patient admissions (29%) and was more frequent in those with higher risk score, with 46% of patient admissions with diQTP in high risk, 23% in moderate risk, and 8% in low risk. Use of the Tisdale calculator to assess patient-specific risk of QT prolongation combined with CDS may improve overall alert quality and acceptance rate, which may decrease the diQTP rate.

Detecting QT prolongation from a single-lead ECG with deep learning.

For a number of antiarrhythmics, drug loading requires a 3-day hospitalization with continuous monitoring for QT-prolongation. Automated QT monitoring with wearable ECG monitors would enable out-of-hospital care. We therefore develop a deep learning model that infers QT intervals from ECG Lead-I-the lead that is often available in ambulatory ECG monitors-and use this model to detect clinically meaningful QT-prolongation episodes during Dofetilide drug loading. QTNet-a deep neural network that infers QT intervals from Lead-I ECG-was trained using over 3 million ECGs from 653 thousand patients at the Massachusetts General Hospital and tested on an internal-test set consisting of 633 thousand ECGs from 135 thousand patients. QTNet is further evaluated on an external-validation set containing 3.1 million ECGs from 667 thousand patients at another healthcare institution. On both evaluations, the model achieves mean absolute errors of 12.63ms (internal-test) and 12.30ms (external-validation) for estimating absolute QT intervals. The associated Pearson correlation coefficients are 0.91 (internal-test) and 0.92 (external-validation). Finally, QTNet was used to detect Dofetilide-induced QT prolongation in a publicly available database (ECGRDVQ-dataset) containing ECGs from subjects enrolled in a clinical trial evaluating the effects of antiarrhythmic drugs. QTNet detects Dofetilide-induced QTc prolongation with 87% sensitivity and 77% specificity. The negative predictive value of the model is greater than 95% when the pre-test probability of drug-induced QTc prolongation is below 25%. These results show that drug-induced QT prolongation risk can be tracked from ECG Lead-I using deep learning.

Genetic characterization of drug-induced long QT syndrome in a large prospective cohort

Abstract Introduction Drug-induced long QT syndrome (DI-LQTS) is a clinical entity with a poorly defined etiopathogenesis. Purpose The objective of the study was to determine the genetic basis of a prospective cohort of patients with DI-LQTS in the setting of a tertiary hospital center. Methods Prospective observational study with consecutive inclusion of patients with the diagnosis of DI-LQTS according to standard criteria, in a tertiary hospital, between 2018 and 2022. A genetic study was performed through massive DNA sequencing to identify variants in known genes associated with cardiopathy, arrhythmogenic and cardiomyopathy. Results 86 patients (age 65±15 years, 59% men) were included. The mean corrected QT interval (QTc) of the entire cohort was 543±56 ms. The drugs associated with QTc interval prolongation were: psychotropics 51%, antiarrhythmics 38%, anesthetics 30%, antibiotics 16%, antineoplastics 5%, others 4%. Twenty-one patients (24%) presented with ventricular arrhythmias at the time of drug-induced QTc prolongation: 10 (12%) ventricular fibrillation, 7 (8%) sustained ventricular tachycardia, 3 (3%) non-sustained ventricular tachycardia, 1 (1%) frequent ventricular premature beats. Genetic information was obtained in 83 (97%) patients. 17 pathogenic mutations associated with heart disease were identified in 15 (18%) patients: 4 (5%) patients with 5 mutations in ion channel genes (KCNE1, KCNE1B, KCNH2, RYR1, RYR2), and 12 (14%) patients with 12 mutations in genes associated with cardiomyopathy (NF1, PKD2, ABCC6, TTN, FHOD3, MYO6, COL11A1, CCDC40, CRELD1, COL4A1). Two patients had 2 pathogenic mutations each, one of them with both mutations associated with channelopathy, and another with a mutation associated with channelopathy and a second mutation related to cardiomyopathy. Only 1 patient carrying a pathogenic mutation related to cardiomyopathy had a clear phenotype, while in 3 carrier patients there was a history of transient systolic dysfunction, 2 due to tachycardiocardiopathy and 1 due to peripartum cardiomyopathy. The identification of a pathogenic mutation was not related to significant differences in QTc interval prolongation (544±63 vs 542±55 ms) or risk of ventricular arrhythmias (26% vs 24%). Conclusions The genetic basis of drug-induced long QT syndrome is essentially different from that of the congenital form of the disease. The identification of pathogenic mutations in genes associated with cardiomyopathy is relatively frequent, while those associated with ion channel genes are uncommon.

Results from a Joined Prospective Study to Evaluate the Sensitivity of the In Vivo Dog QT Assay in Line with the ICH E14/S7B Q&A Best Practices.

The ICH E14/S7B Q&As highlighted the need for best practices concerning the design, execution, analysis, interpretation, and reporting of the in vivo non-rodent QT assay as a component of the integrated risk assessment to potentially support a TQT waiver or substitute. We conducted a dog telemetry study to assess the effects on QTc of six reference compounds (five positive and one negative) previously evaluated by Darpo et al. (2015) in humans. The sensitivity of the assay to detect QTc increases was determined, and exposure-response analysis was performed, as done in clinical practice. By-timepoint analysis showed QTc prolongation induced by moxifloxacin, dofetilide, dolasetron, ondansetron, and quinine within human relevant plasma exposures ranges. Moreover, a hysteresis was observed for quinine. As expected, levocetirizine showed no statistically significant effect on QTc across a range of exposure, well exceeding the therapeutic Cmax. Power analyses confirmed the study ability to detect statistically significant QTc changes of less than 10 milliseconds with 80% probability, even with a sample size as low as n = 4 animals. Finally, concentration-QTc modeling enabled to predict the minimal plasma concentration needed to detect a 10 milliseconds QTc prolongation, including for quinine. The comparison with clinical available data supported the relevance of dogs under these experimental conditions as a robust translational predictor of drug-induced QTc prolongation in humans as a key pillar of the integrated risk assessment.

ICH S7B In Vitro Assays Do Not Address Mechanisms of QTC Prolongation for Peptides and Proteins - Data in Support of Not Needing Dedicated QTC Studies.

Current cardiac safety testing focuses on detecting drug-induced QTC prolongation as a surrogate for risk of Torsade de Pointes. The nonclinical strategy, described in International Conference on Harmonization (ICH) S7B, includes in vitro assessment of hERG block or ventricular repolarization delay and in vivo QT prolongation. Several studies have reported predictive values of ICH S7B results for clinical QTC outcomes for small molecules; none has examined peptides and proteins other than monoclonal antibodies. To address this knowledge gap, information for peptides and proteins submitted to the US Food and Drug Administration (FDA) was collected. Results of hERG assays, ventricular repolarization assays, and in vivo QT assessment were compared with clinical QTC study outcomes. The results show that 14% clinical QTC studies for approved and investigational products failed to exclude 10-ms QTC prolongation. Clinical QTC prolongation for these molecules lacked concentration-dependence which is expected for hERG block-mediated mechanism or QTC prolongation could not be excluded due to characterization in the clinical study. The hERG and ventricular repolarization assays do not identify clinical QTC prolongation potential for peptides and proteins. Lack of alignment between hERG and ventricular repolarization assay results and clinical QTC outcomes suggests that the mechanisms of QTC prolongation by some peptides and proteins are unrelated to direct cardiac ion channel block. Similar to large targeted proteins and monoclonal antibodies, peptides and proteins regardless of size have a low likelihood of direct cardiac ion channel interactions. This characteristic supports waiving the requirement for thorough QT assessment for products comprised of naturally occurring amino acids unless proarrhythmia potential is suggested by nonclinical or clinical data.

Assessment of Drug-Induced QTc Prolongation in Mental Health Practice: Validation of an Evidence-Based Algorithm.

Drug-induced QTc interval prolongation (QTcIP) can lead to serious consequences and is often a concern for mental health practitioners, as access to experts such as cardiologists, for consultation is time-limiting and can delay treatment decisions. This research aimed at validating the content of an algorithm for the assessment, management and monitoring of drug-induced QTcIP in mental health practice. Following an initial face validity by content experts, a cross-sectional survey of mental health care practitioners with a 4-point Likert-type scale was used to assess the validity of the decision steps on the QTcIP algorithm (QTcIPA) by estimating the content validity index (CVI) and the modified kappa statistic (κ*). Participants' open-ended comments were also thematically analyzed. Mental health practitioners found the QTcIPA to be appropriate, safe, and evidence-based, as indicated by the high individual item CVI scores ranging from 0.89 to 1 for all of the steps/decision statements in the three domains assessed: appropriateness, safety and reliability of the references used. Five themes emerged from the qualitative analysis of the open-ended comments, of which three were identified as strengths, including practical usability, reliable references and beneficial for pharmacists. Two themes were recognized as limitations, namely, the need for additional clinical content and application barriers. These results suggest that the QTcIPA may be a useful tool for mental health clinicians at the time of prescribing medications with potential risk of QTcIP. Future research will explore the implementation of the QTcIPA into clinical practice using computerized decision support tools through web-based and mobile applications.

Machine Learning Techniques Outperform Conventional Statistical Methods in the Prediction of High Risk QTc Prolongation Related to a Drug-Drug Interaction.

In clinical practice, many drug therapies are associated with prolongation of the QT interval. In literature, estimation of the risk of prescribing drug-induced QT prolongation is mainly executed by means of logistic regression; only one paper reported the use of machine learning techniques. In this paper, we compare the performance of both techniques on the same dataset. High risk for QT prolongation was defined as having a corrected QT interval (QTc) ≥ 450ms or ≥ 470ms for respectively male and female patients. Both conventional statistical methods (CSM) and machine learning techniques (MLT) were used. All algorithms were validated internally and with a hold-out dataset of respectively 512 and 102 drug-drug interactions with possible drug-induced QTc prolongation. MLT outperformed the best CSM in both internal and hold-out validation. Random forest and Adaboost classification performed best in the hold-out set with an equal harmonic mean of sensitivity and specificity (HMSS) of 81.2% and an equal accuracy of 82.4% in a hold-out dataset. Sensitivity and specificity were both high (respectively 75.6% and 87.7%). The most important features were baseline QTc value, C-reactive protein level, heart rate at baseline, age, calcium level, renal function, serum potassium level and the atrial fibrillation status. All CSM performed similarly with HMSS varying between 60.3% and 66.3%. The overall performance of logistic regression was 62.0%. MLT (bagging and boosting) outperform CSM in predicting drug-induced QTc prolongation. Additionally, 19.2% was gained in terms of performance by random forest and Adaboost classification compared to logistic regression (the most used technique in literature in estimating the risk for QTc prolongation). Future research should focus on testing the classification on fully external data, further exploring potential of other (new) machine and deep learning models and on generating data pipelines to automatically feed the data to the classifier used.

Drug-Induced QTc Prolongation: What We Know and Where We Are Going.

Drug-induced QTc prolongation is a concerning electrocardiogram (ECG) abnormality. This cardiac disturbance carries a 10% risk of sudden cardiac death due to the malignant arrhythmia, Torsades de Pointes. The Arizona Center for Education and Research on Therapeutics (AzCERT) has classified QTc prolonging therapeutic classes, such as antiarrhythmics, antipsychotics, anti-infectives, and others. AzCERT criteria categorize medications into three risk categories: "known," "possible," and "conditional risk" of QTc prolongation and Torsades de Pointes. The list of QTc prolonging medications continues to expand as new drug classes are approved and studied. Risk factors for QTc prolongation can be delineated into modifiable or non-modifiable. A validated risk scoring tool may be utilized to predict the likelihood of prolongation in patients receiving AzCERT classified medication. The resultant risk score may be applied to a clinical decision support system, which offers mitigation strategies. Mitigation strategies including discontinuation of possible offending agents with a selection of an alternative agent, assessment of potential drug interactions or dose adjustments through pharmacokinetic and pharmacodynamic monitoring, and initiation of both ECG and electrolyte monitoring are essential to prevent a drug-induced arrhythmia. The challenges presented by the COVID-19 pandemic have led to the development of innovative continuous monitoring technology, increasing protection for both patients and healthcare workers. Early intervention strategies may reduce adverse events and improve clinical outcomes in patients identified to be at risk of QTc prolongation.

The Challenges of Predicting Drug-Induced QTc Prolongation in Humans.

The content of this article derives from a Health and Environmental Sciences Institute (HESI) consortium with a focus to improve cardiac safety during drug development. A detailed literature review was conducted to evaluate the concordance between nonclinical repolarization assays and the clinical thorough QT (TQT) study. Food and Drug Administration and HESI developed a joint database of nonclinical and clinical data, and a retrospective analysis of 150 anonymized drug candidates was reviewed to compare the performance of 3 standard nonclinical assays with clinical TQT study findings as well as investigate mechanism(s) potentially responsible for apparent discrepancies identified. The nonclinical assays were functional (IKr) current block (Human ether-a-go-go related gene), action potential duration, and corrected QT interval in animals (in vivo corrected QT). Although these nonclinical assays demonstrated good specificity for predicting negative clinical QT prolongation, they had relatively poor sensitivity for predicting positive clinical QT prolongation. After review, 28 discordant TQT-positive drugs were identified. This article provides an overview of direct and indirect mechanisms responsible for QT prolongation and theoretical reasons for lack of concordance between clinical TQT studies and nonclinical assays. We examine 6 specific and discordant TQT-positive drugs as case examples. These were derived from the unique HESI/Food and Drug Administration database. We would like to emphasize some reasons for discordant data including, insufficient or inadequate nonclinical data, effects of the drug on other cardiac ion channels, and indirect and/or nonelectrophysiological effects of drugs, including altered heart rate. We also outline best practices that were developed based upon our evaluation.

Influence of baseline QTc on sotalol-induced prolongation of ventricular repolarization in men and women.

The extent of sotalol-induced QTc prolongation on the electrocardiogram, is variable among subjects and influenced by sex. However, the influence of baseline QTc on the extent of drug-induced QTc prolongation remains unclear. This was studied around peak plasma concentration in a large cohort of 376 healthy male and 614 healthy female subjects who received 80 mg of sotalol orally. Baseline QTc was 379 ± 16 ms in men and 393 ± 15 ms in women (P< .0001). The change in QTc from baseline was highly variable among both sexes and was greater in women than in men (26.5± 13.2 vs.13.0±10.8ms; P< .0001). The slope of the regression line between QTc on sotalol and baseline QTc did not significantly differ from unity in men and in women, indicating that the extent of QTc prolongation with sotalol was not influenced by baseline QTc. Assessing QTc after administration of an IKr blocker may be more important than measuring a baseline QTc.

Dasiglucagon Effects on QTc in Healthy Volunteers: A Randomized, Placebo-Controlled, Dose-Escalation, Double-Blind Study

BackgroundDasiglucagon is a novel glucagon analog that is stable in aqueous formulation and approved for use in severe hypoglycemia. Concentration QTc analyses are critical for assessing risk of drug-induced QTc prolongation and potential for fatal cardiac arrhythmias such as torsades de pointes.ObjectiveThe aim of this study was to determine whether dasiglucagon treatment resulted in any clinically relevant effect on cardiac repolarization in healthy volunteers.MethodsThis double-blind, placebo-controlled, dose-escalation Phase I trial was conducted at a single center in Germany between November 2018 and June 2019. Sixty healthy volunteers aged 18 to 45 years were randomized within dose cohorts to receive intravenous dasiglucagon, intravenous placebo, or subcutaneous dasiglucagon. In the intravenous administration cohorts, doses ranged from 0.03 mg to 1.5 mg. The subcutaneous administration cohort received the approved 0.6 mg dose. In the intravenous administration cohorts, serial electrocardiograms were extracted from continuous Holter monitors at prespecified time points beginning the day before dosing and through 24 hours postdose. Heart rate, PR interval, and QRS duration were evaluated. Concentration-QT analyses corrected by Fridericia's formula (QTcF) were performed using both a linear mixed-effects and a maximum estimated effect (Emax) model.ResultsAt the doses studied, dasiglucagon did not have any clinically relevant effect on heart rate, PR interval, or QRS duration. A minor prolongation of the QTcF interval was observed without any clear dose or concentration dependency. Both the linear and Emax models predicted mean and 90% CIs of placebo-corrected change in QTcF remained below 10 ms (the threshold of regulatory concern), although the linear model did not fit the data well at low dasiglucagon plasma concentrations. In the Emax model, the Emax of dasiglucagon was 3.6 ms (90% CI, 1.23–5.95 ms), and the amount to produce half the effect of Emax) was 426.0 pmol/L (90% CI, −48.8 to 900.71 pmol/L). The treatment effect-specific intercept was −0.44 ms (90% CI, −2.37 to 1.49 ms). The most frequently observed treatment-emergent adverse events reported in the trial were gastrointestinal disorders such as nausea and vomiting.ConclusionsDasiglucagon does not cause clinically relevant QTc prolongation in concentrations up to ≈30,000 pmol/L, a level 5-fold higher than the highest observed plasma concentrations in clinical trials investigating use of the approved 0.6 mg SC dose. ClinicalTrials.gov Identifier: NCT03735225; EudraCT identifier: 2018-002025-32. (Curr Ther Res Clin Exp. 2022; 83:XXX–XXX)

Abstract 9536: Prediction of Drug-Induced QTc Prolongation With an ECG Based Machine Learning Model

Introduction: Initiation of QTc-prolonging medications may lead to the rare but potentially catastrophic event, torsades de pointes (TDP). At present, no adequate, generalizable tools exist to predict drug-induced long QTc (LQT); machine learning from ECG data is a promising approach. Hypothesis: Prediction of drug-induced LQT using an ECG-based machine learning model is feasible, and outperforms a model trained on baseline QTc, age, and sex alone. Methods: We identified baseline 12-lead ECGs with QTc values &lt; 500 ms for patients who had not received any known, conditional, or possible QTc prolonging medication per CredibleMeds at the time of ECG or within the past 90 days. We matched these with ECGs from the same patients while they were taking at least one CredibleMeds drug (“on-drug” ECGs). Using 5-fold cross-validation, we trained and tested two machine learning models using the baseline ECGs of the 92,848 resulting pairs to predict drug-induced LQT (≥500 ms) in the on-drug ECGs: a deep neural network using ECG voltage data, and a gradient-boosted tree using the baseline QTc. Age and sex were also inputs to both models. Results: On-drug LQT prevalence was 16%. The ECG model demonstrated superior performance in predicting on-drug LQT (area under the receiver operating characteristic curve (AUC) = 0.756) compared to the QTc model (0.710). At a potential operating point (Figure), the ECG model had 89% sensitivity and 95% negative predictive value. Even in the subset of patients with baseline QTc &lt; 470/480 ms (male/female; post-drug LQT prevalence = 14%), the ECG model demonstrated good performance (AUC = 0.736). Conclusions: An ECG-based machine learning model can stratify patients by risk of developing drug-induced LQT better than a model using baseline QTc alone. This model may have clinical value to identify high-risk drug starts that would benefit from closer monitoring and others who are at low risk of drug-induced LQT.

Content Validation of an Algorithm for the Assessment, Management and Monitoring of Drug-Induced QTc Prolongation in the Psychiatric Population.

BackgroundQTc interval (QTcI) prolongation leads to serious complications, making it a concern for clinicians. Assessing the risk of QTcI prolongation in the psychiatric population is important because they are exposed to multiple medications known to increase the risk of life-threatening arrhythmias.AimThe study aims to validate the content of an algorithm for the assessment, management and monitoring of drug-induced QTc prolongation in the psychiatric population.MethodologyQualitative semi-structured interviews of cardiologists, to gather information regarding their approach in assessing the risk of drug-induced QTc prolongation at the time of prescribing. After the interview, an orientation to the algorithm was provided with a link to a cross-sectional, anonymous survey. The online survey included quantitative and qualitative components to gather feedback on the relevance and appropriateness of each step in the algorithm.ResultsInterview responses were incorporated into 4 themes. Responses indicated a lack of a unified protocol when assessing QTcI prolongation, which supports the need of an algorithm that includes a verified risk scoring tool. Quantitative survey results showed a mean score ranging from 3.08 to 3.67 out of 4 for the appropriateness of the algorithm’s steps, 3.08 to 3.58 for the safety and 3.17 to 3.75 for the reliability of references used. Additional analysis using the modified kappa and I-CVI statistical measures indicate high validity of contents and high degree of agreement between raters. As per the open-ended questions, cardiologists supported the implementation of the algorithm; however, they recommended simplification of the steps as they appear to be cumbersome.ConclusionThe results demonstrate that the implementation of the algorithm after minor alterations can prove to be useful as a tool for the risk assessment of QTc prolongation. Further validation of the algorithm with mental health pharmacists and clinicians will be conducted as a separate phase of the study.

In silico Exploration of Interactions Between Potential COVID-19 Antiviral Treatments and the Pore of the hERG Potassium Channel-A Drug Antitarget.

Background: In the absence of SARS-CoV-2 specific antiviral treatments, various repurposed pharmaceutical approaches are under investigation for the treatment of COVID-19. Antiviral drugs considered for this condition include atazanavir, remdesivir, lopinavir-ritonavir, and favipiravir. Whilst the combination of lopinavir and ritonavir has been previously linked to prolongation of the QTc interval on the ECG and risk of torsades de pointes arrhythmia, less is known in this regard about atazanavir, remdesivir, and favipiravir. Unwanted abnormalities of drug-induced QTc prolongation by diverse drugs are commonly mediated by a single cardiac anti-target, the hERG potassium channel. This computational modeling study was undertaken in order to explore the ability of these five drugs to interact with known determinants of drug binding to the hERG channel pore.Methods: Atazanavir, remdesivir, ritonavir, lopinavir and favipiravir were docked to in silico models of the pore domain of hERG, derived from cryo-EM structures of hERG and the closely related EAG channel.Results: Atazanavir was readily accommodated in the open hERG channel pore in proximity to the S6 Y652 and F656 residues, consistent with published experimental data implicating these aromatic residues in atazanavir binding to the channel. Lopinavir, ritonavir, and remdesivir were also accommodated in the open channel, making contacts in a model-dependent fashion with S6 aromatic residues and with residues at the base of the selectivity filter/pore helix. The ability of remdesivir (at 30 μM) to inhibit the channel was confirmed using patch-clamp recording. None of these four drugs could be accommodated in the closed channel structure. Favipiravir, a much smaller molecule, was able to fit within the closed channel and could adopt multiple binding poses in the open channel, but with few simultaneous interactions with key binding residues. Only favipiravir and remdesivir showed the potential to interact with lateral pockets below the selectivity filter of the channel.Conclusions: All the antiviral drugs studied here can, in principle, interact with components of the hERG potassium channel canonical binding site, but are likely to differ in their ability to access lateral binding pockets. Favipiravir's small size and relatively paucity of simultaneous interactions may confer reduced hERG liability compared to the other drugs. Experimental structure-function studies are now warranted to validate these observations.

QT prolongation associated with hydroxychloroquine and protease inhibitors in COVID-19.

What is known and ObjectiveHydroxychloroquine and protease inhibitors were widely used as off‐label treatment options for COVID‐19 but the safety data of these drugs among the COVID‐19 population are largely lacking. Drug‐induced QTc prolongation is a known adverse reaction of hydroxychloroquine, especially during chronic treatment. However, when administered concurrently with potential pro‐arrhythmic drugs such as protease inhibitors, the risk of QTc prolongation imposed on these patients is not known. We aim to investigate the incidence of QTc prolongation events and potential factors associated with its occurrence in COVID‐19 population.MethodsWe included 446 SARS‐CoV‐2 RT‐PCR‐positive patients taking at least one treatment drug for COVID‐19 within a period of one month (March–April 2020). In addition to COVID‐19‐related treatment (HCQ/PI), concomitant drugs with risks of QTc prolongation were considered. We defined QTc prolongation as QTc interval of ≥470 ms in postpubertal males, and ≥480 ms in postpubertal females.Results and DiscussionQTc prolongation events occurred in 28/446 (6.3%) patients with an incidence rate of 1 case per 100 person‐days. A total of 26/28 (93%) patients who had prolonged QTc intervals received at least two pro‐QT drugs. Multivariate analysis showed that HCQ and PI combination therapy had five times higher odds of QTc prolongation as compared to HCQ‐only therapy after controlling for age, cardiovascular disease, SIRS and the use of concurrent QTc‐prolonging agents besides HCQ and/or PI (OR 5.2; 95% CI, 1.11‐24.49; p = 0.036). Independent of drug therapy, presence of SIRS resulted in four times higher odds of QTc prolongation (OR 4.3; 95% CI, 1.66‐11.06; p = 0.003). In HCQ‐PI combination group, having concomitant pro‐QT drugs led to four times higher odds of QTc prolongation (OR 3.8; 95% CI, 1.53‐9.73; p = 0.004). Four patients who had prolonged QTc intervals died but none were cardiac‐related deaths.What is new and conclusionIn our cohort, hydroxychloroquine monotherapy had low potential to increase QTc intervals. However, when given concurrently with protease inhibitors which have possible or conditional risk, the odds of QTc prolongation increased fivefold. Interestingly, independent of drug therapy, the presence of systemic inflammatory response syndrome (SIRS) resulted in four times higher odds of QTc prolongation, leading to the postulation that some QTc events seen in COVID‐19 patients may be due to the disease itself. ECG monitoring should be continued for at least a week from the initiation of treatment.

Potential drug-drug interactions with psychotropic drugs in paediatric inpatients: A cross-sectional study.

Polypharmacy and drug-drug interactions (DDIs) are important problems that necessitate more attention in paediatric inpatients. This study aimed to determine and evaluate DDIs in paediatric inpatients using psychotropic drugs. It was conducted as a retrospective cross-sectional study. Inpatients consulted by child and adolescent psychiatrists (CAPs) and had at least one psychotropic drug-using between January 2016 and September 2017 were retrospectively included. To determine the clinical significance of DDIs by Micromedex® and DDI Predictor online databases. DDIs between psychotropic and other drugs, the type, severity, and duration of potential DDIs were evaluated. During the study period, 564 patients' records were reviewed and 200 patients were considered eligible and included in the study. The median (min-max) age was 13.70 (1.5-17.83) years. The mean (SD) number of psychotropics used during hospitalisation was 1.29 (0.55) and the total number of drugs was 7.39 (4.45). A total of 336 potential DDIs were detected (2.19 DDIs/patient) in all patients. The most common potential outcome of psychotropic DDIs was drug-induced QTc prolongation (67.56%). While 92.85% of the potential DDIs were "contraindicated" or "major," only 18.46% had a "good" or "excellent" strength of evidence. The risk of psychotropic polypharmacy (OR:0.73, 95% CI 0.59-0.92; p:0.006) and DDIs (OR:0.69, 95% CI 0.35-0.76; p:0.033) was significantly higher in patients without primary psychiatric disorders. When the total number of drugs and the total number of potential DDIs were compared amongst all inpatient units, significant differences were found between paediatric hematology-general paediatrics (mean difference: 2.002; P<.001) and paediatric hematology-paediatric ICU (mean difference: 1.650; P=.012), respectively. Psychotropic drug-related DDI is a major problem in the paediatric population and the clinical significance of the potential DDIs' risk should be determined in patient-centred care and managed by the multidisciplinary team.

Abstract PS7-59: Presence of comorbidities and use of concomitant medications associated with QTC prolongation/torsades de pointes in patients with HR+/HER2- advanced breast cancer

Abstract BACKGROUND: Corrected QT (QTc) prolongation is a cardiac condition that may increase the risk of ventricular arrhythmias, including Torsades de Pointes (TdP), and cardiac-related death. QTc prolongation is a notable concern in oncology as drug-induced QTc prolongation is a documented side effect of several anticancer therapies. Moreover, patient-specific risk factors for QTc prolongation such as increased age and a history of cardiovascular disease/events can be common among patients with metastatic breast cancer, which puts this population at an increased baseline risk for QTc prolongation. Female sex is a risk factor itself. The objective of this study was to characterize the presence of comorbidities and use of concomitant medications associated with QTc prolongation/TdP among patients receiving first-line (1L) treatment for HR+/HER2- locally advanced or metastatic breast cancer (aBC).METHODS: Oncologists in France, Germany, Israel, Italy, Spain and the United States abstracted clinical characteristics and medication data from the medical records of patients, aged ≥18, who received 1L treatment for HR+/HER2- aBC between 10/2019 and 02/2020. The presence of comorbidities (e.g., congestive heart failure, myocardial infarction, history of atrial arrythmias) and utilization of concomitant medications (excluding anti-cancer therapies) with known, possible, or conditional risk for QTc prolongation/TdP were summarized. The list of comorbidity risk factors was compiled from a targeted literature search and clinician review. The list of concomitant medications was obtained from crediblemeds.org.RESULTS: A total of 1164 patients with aBC were sampled across the six countries. Among them, 99% were female and the mean age was 62 years. The majority of patients had metastatic disease (85%); 15% had locally advanced disease. Among those with metastatic disease, 47% had visceral metastasis and 34% had bone-only metastasis. At 1L initiation, 84% of patients had an ECOG score of 0/1. Comorbidities associated with risk of QTc prolongation/TdP were observed in 8% of patients; the most frequently observed were congestive heart failure (3%) and history of myocardial infarction (2%) (Table 1). The proportion of patients who received at least one medication associated with risk of QTc prolongation/TdP was 39%. Overall, 42% of patients had at least one comorbidity or medication associated with risk of QTc prolongation/TdP. CONCLUSIONS: Approximately 2 out of 5 patients receiving 1L treatment for HR+/HER2- aBC had a comorbidity or utilized a concomitant medication that could increase risk of QTc prolongation/TdP. As cardiovascular toxicity is a known side effect associated with several anticancer therapies, the high prevalence of coexisting risk factors among patients receiving 1L treatment underscores the importance of assessing patients’ existing risk when selecting treatments for advanced breast cancer. Table 1. Presence of Comorbidities and Use of Concomitant Medications with known, possible, or conditional risk for QTc prolongation/TdP in Patients Who Received First-Line Therapy for HR+/HER2- Advanced Breast CancerN%Total Patients1164100ComorbiditiesMyocardial infarction202Congestive heart failure323Moderate or severe liver disease3&amp;lt;1History of QT prolongation3&amp;lt;1Bradyarrhythmia3&amp;lt;1History of atrial arrhythmias282History of ventricular arrhythmias1&amp;lt;1Hypo/hyperkalemia81Hypo/Hypercalcemia81Disorders of magnesium metabolism81Disorders of phosphorus metabolism2&amp;lt;1Unstable angina4&amp;lt;1Presence of comorbidity QTc risk factor948Mean (SD) number of conditions per patient1.3 (.4)Received medication considered a risk factor for QTc prolongation45039Presence of QTc risk factor condition or medication49042 Citation Format: Reshma Mahtani, Katie Lewis, Emily Clayton, Matthew Last, Debanjali Mitra, Samantha Kurosky. Presence of comorbidities and use of concomitant medications associated with QTC prolongation/torsades de pointes in patients with HR+/HER2- advanced breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-59.

Factors that Contribute to the QTc Interval Prolongation in DR-TB Patients on STR Regimen

Introduction: QTc interval prolongation is one of the adverse drug reaction of several drugs used in DR-TBpatients treated with STR regimen. Drug-induced QTc prolongation can predispose patient to develop lifethreatening arrhythmia, increasing hospital length of stay and mortality. This study aims to determine factorsthat contribute to QTc prolongation in DR-TB patients on STR regimen.Methods. This was an observational retrospective study using medical records of DR-TB patients whoreceived STR regimen from August 2017 to March 2019 in tertiary hospital DR Soetomo, Surabaya,Indonesia. QTc interval was calculated by Fredericia formula. The influence of risk factors (age, bodyweight (BW), Body Mass Index (BMI), gender, comorbid, potassium, sodium and QTc baseline) with QTcprolongation was analyzed using multiple regression. The relationship between Moxifloxacin dosage andQTc was analyzed using Chi-Square test.Results Out of the 113 DR-TB patients who received the STR therapy regimen, 98 patients were eligible forthis study. They consist of 62 (%) male; 36 (%) female. Thirty-five (35,7%) of them had Diabetes Mellitusas a comorbid disease. The mean age of the patients was 44±11 years, with the mean of BMI was 20.20±3.73. Potassium and Sodium levels at the baseline were 4.192 ± 0.58 and 138.05 ± 4.562 respectively. TheQTc baseline before receiving STR regimen was 431.9±30,617ms. Patients received a dose of moxifloxacin400 mg (5.1%) , 600 mg (59,2%), and 800 mg (35,7%) according to body weight. There were no correlationbetween age, BW, gender, comorbid, and sodium baseline with QTc. There were correlation betweenpotassium (p=0,001), BMI (p=0,006) and QTc baseline (p &lt;0,001) with QTc.Conclusion QTc baseline and potassium level are factors that contribute to the prolongation of the QTcinterval.

Use of Disproportionality Analysis to Identify Previously Unknown Drug-Associated Causes of Cardiac Arrhythmias Using the Food and Drug Administration Adverse Event Reporting System (FAERS) Database

Drug-induced QTc-prolongation is a well-known adverse drug reaction (ADR), however there is limited knowledge of other drug-induced arrhythmias. The objective of this study is to determine the drugs reported to be associated with arrhythmias other than QTc-prolongation using the FAERS database, possibly identifying potential drug causes that have not been reported previously. FAERS reports from 2004 quarter 1 through 2019 quarter 1 were combined to create a dataset of approximately 11.6 million reports. Search terms for arrhythmias of interest were selected from the Standardized MedDRA Queries (SMQ) Version 12.0. Frequency of the cardiac arrhythmias were determined for atrial fibrillation, atrioventricular block, bradyarrhythmia, bundle branch block, supraventricular tachycardia, and ventricular fibrillation and linked to the reported causal medications. Reports were further categorized by prior evidence associations using package inserts and established drug databases. A reporting odds ratio (ROR) and confidence interval (CI) were calculated for the ADRs for each drug and each of the 6 cardiac arrhythmias. Of the 11.6 million reports in the FAERS database, 68,989 were specific to cardiac arrhythmias of interest. There were 61 identified medication-reported arrhythmia pairs for the 6 arrhythmia groups with 33 found to have an unknown reported association. Rosiglitazone was the most frequently medication reported across all arrhythmias [ROR 6.02 (CI: 5.82-6.22)]. Other medications with significant findings included: rofecoxib, digoxin, alendronate, lenalidomide, dronedarone, zoledronic acid, adalimumab, dabigatran, and interferon beta-1b. Upon retrospective analysis of the FAERS database, the majority of drug-associated arrhythmias reported were unknown suggesting new potential drug causes. Cardiac arrhythmias other than QTc prolongation are a new area of focus for pharmacovigilance and medication safety. Consideration of future studies should be given to using the FAERS database as a timely pharmacovigilance tool to identify unknown adverse events of medications.

Mechanisms of QT prolongation by buprenorphine cannot be explained by direct hERG channel block.

Buprenorphine is a μ-opioid receptor (MOR) partial agonist used to manage pain and addiction. QTC prolongation that crosses the 10 msec threshold of regulatory concern was observed at a supratherapeutic dose in two thorough QT studies for the transdermal buprenorphine product BUTRANS®. Because QTC prolongation can be associated with Torsades de Pointes (TdP), a rare but potentially fatal ventricular arrhythmia, these results have led to further investigation of the electrophysiological effects of buprenorphine. Drug-induced QTC prolongation and TdP are most commonly caused by acute inhibition of hERG current (IhERG) that contribute to the repolarizing phase of the ventricular action potentials (APs). Concomitant inhibition of inward late Na+ (INaL) and/or L-type Ca2+ (ICaL) current can offer some protection against proarrhythmia. Therefore, we characterized the effects of buprenorphine and its major metabolite norbuprenorphine on cardiac hERG, Ca2+, and Na+ ion channels, as well as cardiac APs. For comparison, methadone, a MOR agonist associated with QTC prolongation and high TdP risk, and naltrexone and naloxone, two opioid receptor antagonists, were also studied. Whole cell recordings were performed at 37°C on cells stably expressing hERG, CaV1.2, and NaV1.5 proteins. Microelectrode array (MEA) recordings were made on human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The results showed that buprenorphine, norbuprenorphine, naltrexone, and naloxone had no effect on IhERG, ICaL, INaL, and peak Na+ current (INaP) at clinically relevant concentrations. In contrast, methadone inhibited IhERG, ICaL, and INaL. Experiments on iPSC-CMs showed a lack of effect for buprenorphine, norbuprenorphine, naltrexone, and naloxone, and delayed repolarization for methadone at clinically relevant concentrations. The mechanism of QTC prolongation is opioid moiety-specific. This remains undefined for buprenorphine, while for methadone it involves direct hERG channel block. There is no evidence that buprenorphine use is associated with TdP. Whether this lack of TdP risk can be generalized to other drugs with QTC prolongation not mediated by acute hERG channel block warrants further study.