QTc-prolonging Drugs Research Articles

Determining sensitivity and specificity of risk scores for QTc interval prolongation in hemato-oncology patients prescribed systemic antifungal therapy: a retrospective cross-sectional study.

QTc interval prolongation can result in potentially lethal arrhythmias. One risk factor is QTc-prolonging drugs, including some antifungals often used in hemato-oncology patients. Screening tools for patients at risk have not yet been investigated in this patient population. Our aim was to evaluate the sensitivity and specificity of five QTc risk scores in hemato-oncology patients receiving systemic antifungal therapy. Data were retrieved from an internal study database including adult hemato-oncology patients prescribed systemic antifungal therapy. Data on QTc-prolonging medication, risk factors for QTc prolongation, and electrocardiograms (ECG) were collected retrospectively for a period of 12months. The QTc risk scores according to Tisdale, Vandael, Berger, Bindraban, and Aboujaoude as well as their sensitivity and specificity were calculated. During the evaluated period, 77 patients were prescribed systemic antifungals resulting in 187 therapy episodes. Regarding therapy episodes, median age was 56years (IQR 44-68), 41% (77) were female, and a median of 3 QTc-prolonging drugs were prescribed (range 0-6). ECGs were available for 45 (24%) of the therapy episodes 3-11days after initiation of the antifungal therapy, 22 of which showed QTc prolongation. Regarding these 45 therapy episodes, sensitivity and specificity of the risk scores were calculated as follows: Tisdale 86%/22%, Vandael 91%/35%, Berger 32%/83%, Bindraban 50%/78%, Aboujaoude 14%/87%. The QTc risk scores according to Tisdale and Vandael showed sufficient sensitivity for risk stratification in the studied patient population. In contrast, risk scores according to Berger, Bindraban, and Aboujaoude cannot be considered suitable due to poor sensitivity.

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.

Developing a Model for Quantifying QTc-Prolongation Risk to Enhance Medication Safety Assessment: A Retrospective Analysis.

There are currently no established methods to predict quantitatively whether the start of a drug with the potential to prolong the QTc interval poses patients at risk for relevant QTc prolongation. Therefore, this retrospective study aimed to pave the way for the development of models for estimating QTc prolongation in patients newly exposed to medications with QTc-prolonging potential. Data of patients with a documented QTc prolongation after initiation of a QTc-prolonging drug were extracted from hospital charts. Using a standard model-building approach, general linear mixed models were identified as the best models for predicting both the extent of QTc prolongation and its absolute value after the start of a QTc-time-prolonging drug. The cohort consisted of 107 adults with a mean age of 64.2 years. Patients were taking an average of 2.4 drugs associated with QTc prolongation, with amiodarone, propofol, pipamperone, ondansetron, and mirtazapine being the most frequently involved. There was a significant but weak correlation between measured and predicted absolute QTc values under medication (r2 = 0.262, p < 0.05), as well as for QTc prolongation (r2 = 0.238, p < 0.05). As the developed models are based on a relatively small number of subjects, further research is necessary to ensure their applicability and reliability in real-world scenarios. Overall, this research contributes to the understanding of QTc prolongation and its association with medications, providing insight into the development of predictive models. With improvements, these models could potentially aid healthcare professionals in assessing the risk of QTc prolongation before adding a new drug and in making informed decisions in clinical settings.

The QTc-Bazett Interval in Former Very Preterm Infants in Adolescence and Young Adulthood is Not Different from Term-Born Controls.

Although relevant for precision pharmacovigilance, there are conflicting data on whether former preterm birth is associated with QTc-Bazett prolongation in later life. To explore QTc-Bazett interval differences between former preterm and/or extremely low birth weight (ELBW) cases and term-born controls in adolescence and young adulthood, we analyzed pooled individual data after a structured search on published cohorts. To test the absence of a QTc-Bazett difference, a non-inferiority approach was applied (one-sided, upper limit of the 95% confidence interval [CI] mean QTc-Bazett difference, 5 and 10 ms). We also investigated the impact of characteristics, either perinatal or at assessment, on QTc-Bazett in the full dataset (cases and controls). Data were reported as median and range. The pooled dataset contained 164 former preterm and/or ELBW (cases) and 140 controls born full-term from three studies. The median QTc-Bazett intervals were 409 (335-490) and 410 (318-480) ms in cases and controls. The mean QTc-Bazett difference was 1 ms, with an upper 95% CI of 6 ms (p>0.05 and p<0.01 for 5 and 10 ms, respectively). In the full dataset, females had a significantly longer QTc-Bazett than males (415 vs. 401 ms; p<0.0001). QTc-Bazett intervals are not significantly different between former preterm and/or ELBW cases and term-born controls, and we rejected a potential prolongation > 10 ms in cases. When prescribing QTc-prolonging drugs, pharmacovigilance practices in this subpopulation should be similar to the general public (NCT05243537).

PO-04-209 A NOVEL MACHINE LEARNING (ML) ALGORITHM TO MEASURE THE CORRECTED QT INTERVAL FROM MOBILE ECGS WITH HIGH ACCURACY AND PRECISION

The heart rate-corrected QT interval (QTc) is an important feature of the electrocardiogram (ECG), as it is an important prognosticator for ventricular arrhythmia and sudden cardiac death. The 12-lead (12L) ECG is used most often for assessment of QTc, and algorithms that have extended QTc detection to mobile ECGs with fewer than 12 leads are prone to wide sample size deviation. For clinical applications requiring serial QTc monitoring, such as titration of QTc-prolonging drugs, both accuracy and precision are critical. The aim was to develop a novel machine-learning (ML) algorithm that measures QTc from mobile ECG data formats with high accuracy as well as precision. The acceptance criteria was defined as error and standard deviation within 20 milliseconds (ms), the human interobserver variability observed for manual ECG measurements (gold standard). The ML algorithm was trained using a database of 13,000 cardiologist-annotated 12L ECG heartbeats, including the following steps: 1) pre-processing including resampling to 300 Hz, 2) normalization of amplitudes using min-max scaling 3) noisy beats with excessive baseline wander were discarded, and 4) applying TabNet and XGBoost models for detection of the end of T-Wave. This ML model for detection of the T-wave endpoint was merged with a signal processing method for detection of the Q-point. The algorithm was then validated on a subset of 1,239 cardiologist-annotated heartbeats, sufficient to assess strong agreement between software and manual methods (95% CI ± 0.2 std, Bland-Altman approach). Results showed high AUC, sensitivity, and specificity for detecting QTc above clinically meaningful thresholds. Mean QTc error was 5.24±7.22 ms, meeting predefined acceptance criteria. The ML algorithm was then applied to a dataset of 150 6L mECGs (AliveCor; Mountain View, CA), which comprise an all-comer population of a combination of healthy (∼40%), outpatient clinic (30%), and hospitalized patients (30%), with error 13.7±7.78 ms, again meeting acceptance criteria. Algorithm validation surpassed the defined acceptance criteria and demonstrated that the algorithm can provide and potentially surpass human QTc measurement capabilities. By enabling automated, dynamic QTc analysis, the algorithm offered the precision required for outpatient use.

Determinants of severe QTc prolongation in a real-world gerontopsychiatric setting.

QTc prolongation carries the risk of ventricular tachyarrhythmia (Torsades de Pointes) and sudden cardiac death. Psychotropic drugs can affect ventricular repolarization and thus prolong the QTc interval. The present study sought to investigate the risk factors (pharmacological and non-pharmacological) of severe QTc prolongation in gerontopsychiatric patients. Electrocardiograms of patients on a gerontopsychiatric ward were screened for QTc prolongation. Medication lists were examined utilizing the AzCERT classification. Potential drug interactions were identified with the electronic drug interaction program mediQ. The overall prevalence of QTc prolongation was 13.6%, with 1.9% displaying severe QTc prolongation (≥ 500 ms). No statistically significant differences between patients with moderate and severe QTc prolongation were identified; however, patients with severe QTc prolongation tended to take more drugs (p = 0.063). 92.7% of patients with QTc prolongation took at least one AzCERT-listed drug, most frequently risperidone and pantoprazole. Risperidone and pantoprazole, along with pipamperone, were also most frequently involved in potential drug interactions. All patients displayed additional risk factors for QTc prolongation, particularly cardiac diseases. In addition to the use of potentially QTc-prolonging drugs, other risk factors, especially cardiac diseases, appear to be relevant for the development of QTc prolongation in gerontopsychiatric patients. Pantoprazole was frequently involved in potential drug interactions and should generally not be used for more than 8 weeks in geriatric populations. As clinical consequences of QTc prolongation were rare, potentially QTc-prolonging drugs should not be used overcautiously; their therapeutic benefit should be considered as well. It is paramount to perform diligent benefit-risk analyses prior to the initiation of potentially QTc-prolonging drugs and to closely monitor their clinical (side) effects.

Effect of hyperglycaemia in combination with moxifloxacin on cardiac repolarization in male and female patients with type I diabetes

BackgroundPatients with Type 1 diabetes mellitus have been shown to be at a two to ten-fold higher risk of sudden cardiac death (SCD) (Svane et al., Curr Cardiol 2020; 22:112) than the general population, but the underlying mechanism is unclear. Hyperglycaemia is a recognised cause of QTc prolongation; a state patients with type 1 diabetes are more prone to, potentially increasing their risk of ventricular arrhythmia. Understanding the QTc prolongation effect of both hyperglycaemia and the concomitant additive risk of commonly prescribed QTc-prolonging drugs such as Moxifloxacin may help to elucidate the mechanism of sudden cardiac death in this cohort. This single-blinded, placebo-controlled study investigated the extent to which hyperglycaemia prolongs the QTc in controlled conditions, and the potential additive risk of QTc-prolonging medications.Methods21 patients with type 1 diabetes mellitus were enrolled to a placebo-controlled crossover study at a single clinical trials unit. Patients underwent thorough QTc assessment throughout the study. A ‘hyperglycaemic clamp’ of oral and intravenous glucose was administered with a target blood glucose of > 25 mM and maintained for 2 h on day 1 and day 3, alongside placebo on day 1 and moxifloxacin on day 3. Day 2 served as a control day between the two active treatment days.Thorough QTc assessment was conducted at matched time points over 3 days, and regular blood sampling was undertaken at matched time intervals for glucose levels and moxifloxacin exposure.ResultsConcentration-effect modelling showed that acute hyperglycaemia prolonged the QTc interval in female and male volunteers with type 1 diabetes by a peak mean increase of 13 ms at 2 h. Peak mean QTc intervals after the administration of intravenous Moxifloxacin during the hyperglycaemic state were increased by a further 9 ms at 2 h, to 22 ms across the entire study population. Regression analysis suggested this additional increase was additive, not exponential.Hyperglycaemia was associated with a significantly greater mean QTc-prolonging effect in females, but the mean peak increase with the addition of moxifloxacin was the same for males and females. This apparent sex difference was likely due to the exclusive use of basal insulin in the male patients, which provided a low level of exogenous insulin during the study assessments thereby mitigating the effects of hyperglycaemia on QTc. This effect was partially overcome by Moxifloxacin administration, suggesting both hyperglycaemia and moxifloxacin prolong QTc by different mechanisms, based on subinterval analysis.ConclusionsHyperglycaemia was found to be a significant cause of QTc prolongation and the additional effect of a QTc-prolonging positive control (moxifloxacin) was found to be additive. Given the high risk of sudden cardiac death in type 1 diabetes mellitus, extra caution should be exercised when prescribing any medication in this cohort for QTc effects, and further research needs to be undertaken to elucidate the exact mechanism underlying this finding and explore the potential prescribing risk in diabetes.Trial RegistrationNCT number: NCT01984827.Graphical abstract

Dear Doctor Letters regarding citalopram and escitalopram: guidelines vs real-world data

Dear Doctor Letters (DDLs, Direct Healthcare Professional Communications) from 2011 provided guidance regarding QTc-prolonging effects with risk of torsade de pointes during treatment with citalopram and escitalopram. This study examines the DDLs’ effects on prescription behavior. Data from 8842 inpatients treated with citalopram or escitalopram with a primary diagnosis of major depressive disorder (MDD) were derived from a European pharmacovigilance study (Arzneimittelsicherheit in der Psychiatrie, AMSP) from 2001 to 2017. It was examined to what extent new maximum doses were adhered to and newly contraindicated combinations with QTc-prolonging drugs were avoided. In addition, the prescriptions of psychotropic drugs before and after DDLs were compared in all 43,480 inpatients with MDD in the data set. The proportion of patients dosed above the new limit decreased from 8 to 1% in patients ≤ 65 years and from 46 to 23% in patients > 65 years old for citalopram versus 14–5% and 47–31% for escitalopram. Combinations of es-/citalopram with other QTc-prolonging psychotropic drugs reduced only insignificantly (from 35.9 to 30.9%). However, the proportion of patients with doses of quetiapine > 150 mg/day substantially decreased within the combinations of quetiapine and es-/citalopram (from 53 to 35%). After the DDLs, prescription of citalopram decreased and of sertraline increased. The DDLs’ recommendations were not entirely adhered to, particularly in the elderly and concerning combination treatments. This might partly be due to therapeutic requirements of the included population. Official warnings should consider clinical needs.

Prevalence of QTc Prolongation in Patients with Parkinson's Disease. Assessment of the Effects of Drugs, Clinical Risk Factors and Used Correction Formula.

Background: Parkinson’s disease (PD) is a possible risk factor for corrected QT interval (QTc) prolongation. PD patients frequently take QTc-prolonging drugs. The aim of the study was to assess the prevalence of QTc prolongation in PD and the influence of drugs and other potential risk factors on the QTc length in PD. Methods: 101 patients with PD and a good quality ECG were included in the study. The prolonged QTc was defined as ≥450 ms for men and ≥460 ms for women. Bazett’s (QTcB) and Framingham (QTcF) formulas were utilized to calculate QTc. Data about sex, age, PD duration, disease’s severity, comorbidities and QTc-prolonging drugs were collected. Multiple linear regressions with backward elimination were used to assess factors influencing the QTc. Results: A long QTc was presented in 13 patients (12.9%) for QTcB and 4 patients (4%) for QTcF. Longer QTc in PD patients was associated with older age, male sex and QTc-prolonging drugs regardless of the used formula. The QTcB was also significantly affected by the heart rate (HR). Conclusion: QTc prolongation is common in PD. Age, drugs and male gender are potential risk factors for QTc prolongation in PD.

Bedaquiline for multidrug-resistant tuberculosis and QTc prolongation in California

BackgroundBedaquiline (BDQ) is recommended for the treatment of multidrug-resistant tuberculosis (MDR TB), however, it has the potential to prolong QTc interval. We assessed the frequency and severity of QTc prolongation in patients receiving BDQ in California. MethodsBased on chart review for patients receiving BDQ as part of MDR TB therapy from January 2013–May 2019, we analyzed QTc values at six pre-specified time points during BDQ therapy (baseline, 2, 4, 8, 12, and 24 weeks), as well as peak QTc, time to peak QTc, and the clinical characteristics of patients who had QTc elevation >500 milliseconds (ms) during therapy. ResultsA total of 37 patients were treated with BDQ during the analysis period, with a total of 449 QTc measurements available for analysis. Most patients (89%) received at least one QTc-prolonging drug in addition to BDQ. Median QTc values at all pre-specified time points were <450 ms. Median peak QTc was 455 ms (interquartile range [IQR]: 437–486) and median time to peak was 57 days (IQR: 19–156). Four patients (11%) had a non-transient elevation in QTc to >500 ms, including one patient with profound hypokalemia and one receiving concurrent chemotherapy, but none had cardiac arrhythmia. Less than 10% of patient in our cohort had ECGs performed at all six pre-specified time points. DiscussionBDQ was generally well-tolerated in a cohort of patients treated for MDR TB in California, with 11% of patients experiencing a non-transient QTc elevation >500 ms, and no episodes of arrhythmia. Frequent ECG monitoring during BDQ therapy presents a challenge for TB clinicians, even in well-resourced countries.

Translational Models and Tools to Reduce Clinical Trials and Improve Regulatory Decision Making for QTc and Proarrhythmia Risk (ICH E14/S7B Updates).

After multiple drugs were removed from the market secondary to drug‐induced torsade de pointes (TdP) risk, the International Council for Harmonisation (ICH) released guidelines in 2005 that focused on the nonclinical (S7B) and clinical (E14) assessment of surrogate biomarkers for TdP. Recently, Vargas et al. published a pharmaceutical‐industry perspective making the case that “double‐negative” nonclinical data (negative in vitro hERG and in vivo heart‐rate corrected QT (QTc) assays) are associated with such low probability of clinical QTc prolongation and TdP that potentially all double‐negative drugs would not need detailed clinical QTc evaluation. Subsequently, the ICH released a new E14/S7B Draft Guideline containing Questions and Answers (Q&As) that defined ways that double‐negative nonclinical data could be used to reduce the number of “Thorough QT” (TQT) studies and reach a low‐risk determination when a TQT or equivalent could not be performed. We review the Vargas et al. proposal in the context of what was contained in the ICH E14/S7B Draft Guideline and what was proposed by the ICH E14/S7B working group for a “stage 2” of updates (potential expanded roles for nonclinical data and details for assessing TdP risk of QTc‐prolonging drugs). Although we do not agree with the exact probability statistics in the Vargas et al. paper because of limitations in the underlying datasets, we show how more modest predictive value of individual assays could still result in low probability for TdP with double‐negative findings. Furthermore, we expect that the predictive value of the nonclinical assays will improve with implementation of the new ICH E14/S7B Draft Guideline.

The use of a clinical decision support tool to assess the risk of QT drug-drug interactions in community pharmacies.

Introduction:The handling of drug–drug interactions regarding QTc-prolongation (QT-DDIs) is not well defined. A clinical decision support (CDS) tool will support risk management of QT-DDIs. Therefore, we studied the effect of a CDS tool on the proportion of QT-DDIs for which an intervention was considered by pharmacists.Methods:An intervention study was performed using a pre- and post-design in 20 community pharmacies in The Netherlands. All QT-DDIs that occurred during a before- and after-period of three months were included. The impact of the use of a CDS tool to support the handling of QT-DDIs was studied. For each QT-DDI, handling of the QT-DDI and patient characteristics were extracted from the pharmacy information system. Primary outcome was the proportion of QT-DDIs with an intervention. Secondary outcomes were the type of interventions and the time associated with handling QT-DDIs. Logistic regression analysis was used to analyse the primary outcome.Results:Two hundred and forty-four QT-DDIs pre-CDS tool and 157 QT-DDIs post-CDS tool were included. Pharmacists intervened in 43.0% and 35.7% of the QT-DDIs pre- and post-CDS tool respectively (odds ratio 0.74; 95% confidence interval 0.49–1.11). Substitution of interacting agents was the most frequent intervention. Pharmacists spent 20.8 ± 3.5 min (mean ± SD) on handling QT-DDIs pre-CDS tool, which was reduced to 14.9 ± 2.4 min (mean ± SD) post-CDS tool. Of these, 4.5 ± 0.7 min (mean ± SD) were spent on the CDS tool.Conclusion:The CDS tool might be a first step to developing a tool to manage QT-DDIs via a structured approach. Improvement of the tool is needed in order to increase its diagnostic value and reduce redundant QT-DDI alerts.Plain Language Summary The use of a tool to support the handling of QTc-prolonging drug interactions in community pharmacies Introduction: Several drugs have the ability to cause heart rhythm disturbances as a rare side effect. This rhythm disturbance is called QTc-interval prolongation. It may result in cardiac arrest. For health care professionals, such as physicians and pharmacists, it is difficult to decide whether or not it is safe to proceed treating a patient with combinations of two or more of these QT-prolonging drugs. Recently, a tool was developed that supports the risk management of these QT drug–drug interactions (QT-DDIs).Methods: In this study, we studied the effect of this tool on the proportion of QT-DDIs for which an intervention was considered by pharmacists. An intervention study was performed using a pre- and post-design in 20 community pharmacies in The Netherlands. All QT-DDIs that occurred during a before- and after-period of 3 months were included.Results: Two hundred and forty-four QT-DDIs pre-implementation of the tool and 157 QT-DDIs post-implementation of the tool were included. Pharmacists intervened in 43.0% of the QT-DDIs before the tool was implemented and in 35.7% after implementation of the tool. Substitution of one of the interacting agents was the most frequent intervention. Pharmacists spent less time on handling QT-DDIs when the tool was used.Conclusion: The clinical decision support tool might be a first step to developing a tool to manage QT-DDIs via a structured approach.

A case study on escitalopram induced QTc prolongation and adverse drug reaction

Antagonistic medication response (ADR) can be characterized as any toxic change which is suspected to be because of a medication, happens at dosages ordinarily utilized in man, requires treatment or decline in portion or shows alert later on the utilization of similar medication. Escitalopram is a medication which goes under the classification of particular serotonin reuptake inhibitors (SSRIs) (antidepressants). It is the S-enantiomer of the racemic subsidiary of citalopram, which specifically restrains the reuptake of serotonin with practically no impact on norepinephrine or dopamine reuptake. Practically all the antidepressants and antipsychotics have been connected to QT prolongation. In a patient with previously diagnosed congenital QTS, we present a drug-induced QT extension owing to the escitalopram overdose. A 15-year-old Caucasian woman was presented with an escalopram overdose after a suicide attempt. The patient has a lengthy QT period of torsade de point incidents. The patient was received and monitored in the telemetry facility. She proceeded to exhibit the persistently extended QT period after the resolution of torsades de punes. She was diagnosed with a congenital QT condition by the cardiology clinic. In this situation, an escitalopram overdose is seen to trigger an immediate QT extension for a patient who has congenital LQTS and the value of an electrocardiogram before SSRIs are started, particularly for those at high risk of QT prolongation.

Abstract 15615: Association of Covid-19 With QTc Prolongation: A Need for Routine Ecg Screening

Introduction: Coronavirus Disease 2019 (COVID-19) has a high risk of death due to respiratory and cardiac complications. Internalization of the virus in the heart may derange myocyte functions such as repolarization, manifesting as QT prolongation on surface electrocardiograms (ECGs). Long QT is associated with cardiac arrhythmias, including sudden arrhythmic death. Previous studies of corrected QT (QTc) in Covid-19 have not controlled for other QTc prolonging comorbidities. Hypothesis: This study investigates whether COVID-19 is associated with prolonged QTc independent of other causes of QTc prolongation. Methods: QTc values were taken from ECGs of 36 patients with COVID-19 admitted to intensive care and 70 healthy age- and gender-matched control subjects. Patients were excluded if they received QTc-prolonging drugs, had hypokalemia, hypocalcemia, or hypomagnesemia, or history of excessive alcohol use. QTc values of COVID-19 patients were compared against normal control subjects. Results: The COVID-19 group included 15 females and 21 males with hypertension (n=11) and diabetes mellitus (n=5) as the most common comorbidities. Electrolytes were normal (K, 3.97 ± 0.41 mEq/L; Mg, 2.41 ± 0.38 mg/dL; and corrected Ca, 10.60 ± 0.60 mg/dL). QTc (msec) was significantly prolonged in COVID-19 compared with control subjects (total 469 ± 36.1 vs 418 ± 17.8; females, 475±29.2 vs 424 ± 11.4, and males 465 ± 40.5 vs 416 ± 19.9; all p&lt;0.001). Conclusions: COVID-19 alone, without an associated QT prolonging etiology, is associated with QTc prolongation. Ventricular arrhythmias may be more likely to affect women with COVID-19 than men with the disease. Therefore, it is recommended that, in COVID-19 patients, electrolytes be maintained within normal limits and QT prolonging drugs be avoided.

Comparison of two algorithms to support medication surveillance for drug-drug interactions between QTc-prolonging drugs

BackgroundQTc-prolongation is an independent risk factor for developing life-threatening arrhythmias. Risk management of drug-induced QTc-prolongation is complex and digital support tools could be of assistance. Bindraban et al. and Berger et al. developed two algorithms to identify patients at risk for QTc-prolongation. ObjectiveThe main aim of this study was to compare the performances of these algorithms for managing QTc-prolonging drug-drug interactions (QT-DDIs). Materials and MethodsA retrospective data analysis was performed. A dataset was created from QT-DDI alerts generated for in- and outpatients at a general teaching hospital between November 2016 and March 2018. ECGs recorded within 7 days of the QT-DDI alert were collected. Main outcomes were the performance characteristics of both algorithms. QTc-intervals of > 500 ms on the first ECG after the alert were taken as outcome parameter, to which the performances were compared. Secondary outcome was the distribution of risk scores in the study cohort. ResultsIn total, 10,870 QT-DDI alerts of 4987 patients were included. ECGs were recorded in 26.2 % of the QT-DDI alerts. Application of the algorithms resulted in area under the ROC-curves of 0.81 (95 % CI 0.79–0.84) for Bindraban et al. and 0.73 (0.70–0.75) for Berger et al. Cut-off values of ≥ 3 and ≥ 6 led to sensitivities of 85.7 % and 89.1 %, and specificities of 60.8 % and 44.3 % respectively. ConclusionsBoth algorithms showed good discriminative abilities to identify patients at risk for QTc-prolongation when using ≥ 2 QTc-prolonging drugs. Implementation of digital algorithms in clinical decision support systems could support the risk management of QT-DDIs.

Time for a Fully Integrated Nonclinical-Clinical Risk Assessment to Streamline QT Prolongation Liability Determinations: A Pharma Industry Perspective.

Defining an appropriate and efficient assessment of drug‐induced corrected QT interval (QTc) prolongation (a surrogate marker of torsades de pointes arrhythmia) remains a concern of drug developers and regulators worldwide. In use for over 15 years, the nonclinical International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) S7B and clinical ICH E14 guidances describe three core assays (S7B: in vitro hERG current & in vivo QTc studies; E14: thorough QT study) that are used to assess the potential of drugs to cause delayed ventricular repolarization. Incorporating these assays during nonclinical or human testing of novel compounds has led to a low prevalence of QTc‐prolonging drugs in clinical trials and no new drugs having been removed from the marketplace due to unexpected QTc prolongation. Despite this success, nonclinical evaluations of delayed repolarization still minimally influence ICH E14‐based strategies for assessing clinical QTc prolongation and defining proarrhythmic risk. In particular, the value of ICH S7B‐based “double‐negative” nonclinical findings (low risk for hERG block and in vivo QTc prolongation at relevant clinical exposures) is underappreciated. These nonclinical data have additional value in assessing the risk of clinical QTc prolongation when clinical evaluations are limited by heart rate changes, low drug exposures, or high‐dose safety considerations. The time has come to meaningfully merge nonclinical and clinical data to enable a more comprehensive, but flexible, clinical risk assessment strategy for QTc monitoring discussed in updated ICH E14 Questions and Answers. Implementing a fully integrated nonclinical/clinical risk assessment for compounds with double‐negative nonclinical findings in the context of a low prevalence of clinical QTc prolongation would relieve the burden of unnecessary clinical QTc studies and streamline drug development.

Development and validation of a tool to assess the risk of QT drug-drug interactions in clinical practice

BackgroundThe exact risk of developing QTc-prolongation when using a combination of QTc-prolonging drugs is still unknown, making it difficult to interpret these QT drug-drug interactions (QT-DDIs). A tool to identify high-risk patients is needed to support healthcare providers in handling automatically generated alerts in clinical practice. The main aim of this study was to develop and validate a tool to assess the risk of QT-DDIs in clinical practice.MethodsA model was developed based on risk factors associated with QTc-prolongation determined in a prospective study on QT-DDIs in a university medical center inthe Netherlands. The main outcome measure was QTc-prolongation defined as a QTc interval > 450 ms for males and > 470 ms for females. Risk points were assigned to risk factors based on their odds ratios. Additional risk factors were added based on a literature review. The ability of the model to predict QTc-prolongation was validated in an independent dataset obtained from a general teaching hospital against QTc-prolongation as measured by an ECG as the gold standard. Sensitivities, specificities, false omission rates, accuracy and Youden’s index were calculated.ResultsThe model included age, gender, cardiac comorbidities, hypertension, diabetes mellitus, renal function, potassium levels, loop diuretics, and QTc-prolonging drugs as risk factors. Application of the model to the independent dataset resulted in an area under the ROC-curve of 0.54 (95% CI 0.51–0.56) when QTc-prolongation was defined as > 450/470 ms, and 0.59 (0.54–0.63) when QTc-prolongation was defined as > 500 ms. A cut-off value of 6 led to a sensitivity of 76.6 and 83.9% and a specificity of 28.5 and 27.5% respectively.ConclusionsA clinical decision support tool with fair performance characteristics was developed. Optimization of this tool may aid in assessing the risk associated with QT-DDIs.Trial registrationNo trial registration, MEC-2015-368.

Incidence and determinants of QT interval prolongation in COVID-19 patients treated with hydroxychloroquine and azithromycin.

Combined use of hydroxychloroquine and azithromycin was globally adopted, in part due to paucity and high cost of alternative therapies. However the utility of these medications has been questioned; and thus safety becomes a major concern given clinical equipoise regarding efficacy. Both hydroxychloroquine and azithromycin continue to be administered in US clinical trials examining their potential role in prevention of infection, treatment of mild infection in ambulatory patients, and in combination with other medical regimens in treatment of patients with severe disease. These drugs also continue to be clinically utilized in hospitalized patients around the globe, often without continuous telemetry due to lack of resources. Concern regarding use of hydroxychloroquine without adequate rhythm monitoring in clinical trials has been recently expressed.1 A review of clinicaltrials.gov at the time of submission of this correspondence reveals actively recruiting trials of combined hydroxychloroquine/azithromycin with or without additional COVID-19 therapies, for both ambulatory and hospitalized patients within and outside the US. The potential for hydroxychloroquine and azithromycin to cause QT prolongation is counterbalanced by very low risk of pro-arrhythmia in the general population, and emerging evidence of relatively low risk of Torsades de Pointes (TdP) in COVID-19 patients.2,3,4,5 Thus delineation of the determinants of significant QTc prolongation and pro-arrhythmic risk for hydroxychloroquine/azithromycin is very important, especially given mounting evidence of inefficacy in COVID-19 treatment.

Use of Chloroquine and Hydroxychloroquine in COVID-19 and Cardiovascular Implications: Understanding Safety Discrepancies to Improve Interpretation and Design of Clinical Trials.

Author(s): Oren, Ohad; Yang, Eric H; Gluckman, Ty J; Michos, Erin D; Blumenthal, Roger S; Gersh, Bernard J

Preventable patient acute mortality after EMR-generated QTc alerts.

e19359 Background: EMR generated QTc prolongation alerts are ubiquitous in cancer patients. Their significance and impact on mortality is unknown. Methods: From 2006-2018, 19,223 adult cancer patients at UT-Southwestern hospitals had EMR generated QTc prolongation drug alerts. We collected information on cancer site, demographics and alert details. Deaths ≤10 days from a first QTc alert (acute mortality) were considered more attributable to QTc prolongation. We analyzed overall patient survival through multivariable Kaplan-Meier analysis and Cox regression with the two-outcomes (dead/alive) using a ≤10 days cutoff and followed patients for 365 days from their 1st alert. Results: Analysis of mortality from 1st QTc alert demonstrated statistically significant (p = &lt; 0.05) higher risk of ≤10-day mortality in: patients age &gt; 70 yrs, hazard ratio (HR) = 2.32; black, HR = 1.26 or other/unknown race, HR = 1.29; and increasing number of QTc alerts, particularly patients with 6-10, HR = 1.67 or &gt; 11 HR = 1.88 alerts. Females had lower mortality compared to males, HR = 0.83. Compared to a head and neck cancer patient baseline, significantly increased ≤10-day mortality was seen in: GI, HR = 2.16; lung, HR = 1.94; blood, HR = 1.46; soft tissue, HR = 2.26; and female genital, HR = 1.55 cancers. Male genital, HR = 0.39; breast, HR = 0.57; and endocrine, HR = 0.48 cancers had significantly decreased ≤10-day mortality. In patients with EKG’s recorded: 34 males who died ≤10-days of their 1st alert had significantly longer QTc intervals compared the 5465 who survived to day 11 (469 vs 450 msec, p = &lt; 0.0001). There was no QTc prolongation in the 24 females who died ≤10-days compared to the 4392 who survived to Day 11. Deaths ≤10 days after a QTc alert were rare (total 149/19,223; range 0.01 for male genital to 2.5% for GI), while the majority of deaths within 1 year of a patient’s 1st alert occurred between 11-180 days (range 1.03% for endocrine to 11.05% for lung). Most patients were alive &gt; 1 year after their 1st alert: 63.77% (lung)-95.9% (endocrine). Conclusions: Patients with EKG-proven prolongation of QTc intervals after QTc alerts likely represent a segment of the population where intervention may reduce acute mortality. It is unclear whether the QTc interval prolongation is the actual cause of death or if the EMR alerts identify patients with co-morbidities associated with high risk of acute mortality.