Errors of Fixed QT Heart Rate Corrections Used in the Assessment of Drug-Induced QTc Changes

Serial electrocardiogram recordings revealed a high prevalence of QT interval prolongation in patients with tuberculosis receiving fluoroquinolones

BACKGROUND

Fluoroquinolones, crucial components of treatment regimens for drug-resistant tuberculosis (TB), are associated with QT interval prolongation and risks of fatal cardiac arrhythmias. However, few studies have explored dynamic changes in the QT interval in patients receiving QT-prolonging agents.

METHODS

This prospective cohort study recruited hospitalized patients with TB who received fluoroquinolones. The study investigated the variability of the QT interval by using serial electrocardiograms (ECGs) recorded four times daily. This study analyzed the accuracy of intermittent and single-lead ECG monitoring in detecting QT interval prolongation.

RESULTS

This study included 32 patients. The mean age was 68.6 ± 13.2 years. The results revealed mild-to-moderate and severe QT interval prolongation in 13 (41%) and 5 (16%) patients, respectively. The incremental yields in sensitivity of one to four daily ECG recordings were 61.0%, 26.1%, 5.6%, and 7.3% in detecting mild-to-moderate QT interval prolongation, and 66.7%, 20.0%, 6.7%, and 6.7% in detecting severe QT interval prolongation. The sensitivity levels of lead II and V5 ECGs in detecting mild-to-moderate and severe QT interval prolongation exceeded 80%, and their specificity levels exceeded 95%.

CONCLUSION

This study revealed a high prevalence of QT interval prolongation in older patients with TB who receive fluoroquinolones, particularly those with multiple cardiovascular risk factors. Sparsely intermittent ECG monitoring, the prevailing strategy in active drug safety monitoring programs, is inadequate owing to multifactorial and circadian QT interval variability. Additional studies performing serial ECG monitoring are warranted to enhance the understanding of dynamic QT interval changes in patients receiving QT-prolonging anti-TB agents.

Development of an AI-Driven QT Correction Algorithm for Patients in Atrial Fibrillation

BACKGROUND

Prolongation of the QTc interval is associated with the risk of torsades de pointes. Determination of the QTc interval is therefore of critical importance. There is no reliable method for measuring or correcting the QT interval in atrial fibrillation (AF).

OBJECTIVES

The authors sought to evaluate the use of a convolutional neural network (CNN) applied to AF electrocardiograms (ECGs) for accurately estimating the QTc interval and ruling out prolongation of the QTc interval.

METHODS

The authors identified patients with a 12-lead ECG in AF within 10 days of a sinus ECG, with similar (±10 ms) QRS durations, between October 23, 2001, and November 5, 2021. A multilayered deep CNN was implemented in TensorFlow 2.5 (Google) to predict the MUSE (GE Healthcare) software-generated sinus QTc value from an AF ECG waveform, demographic characteristics, and software-generated features.

RESULTS

The study identified 6,432 patients (44% female) with an average age of 71 years. The CNN predicted sinus QTc values with a mean absolute error of 22.2 ms and root mean squared error of 30.6 ms, similar to the intrinsic variability of the sinus QTc interval. Approximately 84% and 97% of the model's predictions were contained within 1 SD (±30.6 ms) and 2 SD (±61.2 ms) from the sinus QTc interval. The model outperformed the AFQTc method, exhibiting narrower error ranges (mean absolute error comparison P < 0.0001). The model performed best for ruling out QTc prolongation (negative predictive value 0.82 male, 0.92 female; specificity 0.92 male, 0.97 female).

CONCLUSIONS

A CNN model applied to AF ECGs accurately predicted the sinus QTc interval, outperforming current alternatives and exhibiting a high negative predictive value.

The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review

INTRODUCTION

QTc prolongation is key in diagnosing long QT syndrome (LQTS), however 25%-50% with congenital LQTS (cLQTS) demonstrate a normal resting QTc. T wave morphology (TWM) can distinguish cLQTS subtypes but its role in acquired LQTS (aLQTS) is unclear.

METHODS

Electronic databases were searched using the terms "LQTS," "long QT syndrome," "QTc prolongation," "prolonged QT," and "T wave," "T wave morphology," "T wave pattern," "T wave biomarkers." Whole text articles assessing TWM, independent of QTc, were included.

RESULTS

Seventeen studies met criteria. TWM measurements included T-wave amplitude, duration, magnitude, Tpeak-Tend, QTpeak, left and right slope, center of gravity (COG), sigmoidal and polynomial classifiers, repolarizing integral, morphology combination score (MCS) and principal component analysis (PCA); and vectorcardiographic biomarkers. cLQTS were distinguished from controls by sigmoidal and polynomial classifiers, MCS, QTpeak, Tpeak-Tend, left slope; and COG x axis. MCS detected aLQTS more significantly than QTc. Flatness, asymmetry and notching, J-Tpeak; and Tpeak-Tend correlated with QTc in aLQTS. Multichannel block in aLQTS was identified by early repolarization (ERD_30% ) and late repolarization (LRD_30% ), with ERD reflecting hERG-specific blockade. Cardiac events were predicted in cLQTS by T wave flatness, notching, and inversion in leads II and V₅ , left slope in lead V₆ ; and COG last 25% in lead I. T wave right slope in lead I and T-roundness achieved this in aLQTS.

CONCLUSION

Numerous TWM biomarkers which supplement QTc assessment were identified. Their diagnostic capabilities include differentiation of genotypes, identification of concealed LQTS, differentiating aLQTS from cLQTS; and determining multichannel versus hERG channel blockade.

QT interval is correlated with and can predict the comorbidity of depression and anxiety: A cross-sectional study on outpatients with first-episode depression

Object

Patients with depression are at an increased risk for developing cardiovascular diseases. The associations between electrocardiogram (ECG) abnormalities and the severity of psychiatric disorders, such as depression and anxiety, have not been clearly elucidated. The present study aims to investigate the associations between depression and anxiety symptoms with ECG indices, and to predict the severity of depression and anxiety using ECG indicators.

Methods

61 outpatients with first-episode depression from the Shanghai Pudong New Area Mental Health Center were selected and met the diagnostic criteria of DSM-IV. All participants provided self-reported scores on the Zung Self-Rating Depression Scale (SDS) and Zung Self-Rating Anxiety Scale (SAS) and underwent the standard 12-lead ECG assessment.

Results

Among the 61 included outpatients (mean [standard deviation, SD] age: 37.84 [13.82] years; 41[67.2%] were female), there were 2 (3.3%) outpatients without depression symptoms, 16 (26.2%) with mild depression, 19 (31.1%) with moderate depression, and 24 (39.3%) with severe depression. Ten (16.4%) outpatients did not have anxiety symptoms, 19 (31.1%) exhibited mild anxiety, 20 (32.8%) exhibited moderate anxiety, and 12 (19.7%) exhibited severe anxiety. Only 1 (1.6%) outpatient exhibited neither depression nor anxiety, 9 (14.8%) and 1 (1.6%) outpatients only exhibited depression and anxiety, respectively, and most outpatients (50 [82.0%]) had comorbid depression and anxiety symptoms. In the correlation analysis, depression and anxiety severity levels were significantly positively correlated (r = 0.717, p &lt; 0.01). Moreover, categorical anxiety significantly differs in QT interval (p = 0.022), and continuous SAS scores were significantly correlated with QT interval (r = 0.263, p = 0.04). In addition, the correlations between ECG measurements and both categorical depression and continuous SDS scores were not statistically significant. The comorbidity of anxiety and depression was significantly correlated with heart rate (p = 0.039) and QT interval (p = 0.002). Disorder status significantly differed with different QT intervals (p = 0.021). In the prediction analysis, QT interval was the only significant predictor (p = 0.01, b = 0.058, Odds Ratio = 1.059) for comorbid anxiety and depression symptoms.

Conclusion

This study found that comorbid symptoms of depression and anxiety were significantly associated with QT interval and heart rate. Additionally, QT interval could predict the comorbidity of these two psychiatric disorders. Further prospective research in a larger and high-risk population is needed.

Sex and Rate Change Differences in QT/RR Hysteresis in Healthy Subjects

While it is now well-understood that the extent of QT interval changes due to underlying heart rate differences (i.e., the QT/RR adaptation) needs to be distinguished from the speed with which the QT interval reacts to heart rate changes (i.e., the so-called QT/RR hysteresis), gaps still exist in the physiologic understanding of QT/RR hysteresis processes. This study was designed to address the questions of whether the speed of QT adaptation to heart rate changes is driven by time or by number of cardiac cycles; whether QT interval adaptation speed is the same when heart rate accelerates and decelerates; and whether the characteristics of QT/RR hysteresis are related to age and sex. The study evaluated 897,570 measurements of QT intervals together with their 5-min histories of preceding RR intervals, all recorded in 751 healthy volunteers (336 females) aged 34.3 ± 9.5 years. Three different QT/RR adaptation models were combined with exponential decay models that distinguished time-based and interval-based QT/RR hysteresis. In each subject and for each modelling combination, a best-fit combination of modelling parameters was obtained by seeking minimal regression residuals. The results showed that the response of QT/RR hysteresis appears to be driven by absolute time rather than by the number of cardiac cycles. The speed of QT/RR hysteresis was found decreasing with increasing age whilst the duration of individually rate corrected QTc interval was found increasing with increasing age. Contrary to the longer QTc intervals, QT/RR hysteresis speed was faster in females. QT/RR hysteresis differences between heart rate acceleration and deceleration were not found to be physiologically systematic (i.e., they differed among different healthy subjects), but on average, QT/RR hysteresis speed was found slower after heart rate acceleration than after rate deceleration.

Energy Drinks and Their Acute Effects on Heart Rhythm and Electrocardiographic Time Intervals in Healthy Children and Teenagers: A Randomized Trial

Beyond their effect on blood pressure, the effect of energy drinks on heart rate in children and teenagers has not been evaluated until now. Thus, this study aimed to investigate the acute cardiovascular effects of energy drinks in healthy children and teenagers. Twenty-six children and adolescents (mean age 14.49 years) received a commercially available energy drink (ED) and placebo on two consecutive days based on the maximum caffeine dosage as proposed by the European Food Safety Authority. Heart rhythm and electrocardiographic time intervals were assessed in a prospective, randomized, double-blind, placebo-controlled, crossover clinical study design. ED consumption resulted in a significantly increased number of supraventricular extrasystoles (SVES) compared to the placebo, whereas supraventricular tachycardia or malignant ventricular arrhythmias were not observed. The mean heart rate (HR) was significantly lower following consumption of EDs. In contrast, QTc intervals were not affected by EDs. Being the first of its kind, this trial demonstrates the cardiovascular and rhythmological effects of EDs in minors. Interestingly, EDs were associated with adverse effects on heart rhythm. Whether higher dosages or consumption in children with preexisting conditions may cause potentially harmful disorders was beyond the scope of this pilot study and remains to be determined in future trials. Trial Registration Number (DRKS-ID): DRKS00027580.

Update on ICH E14/S7B Cardiac Safety Regulations: The Expanded Role of Preclinical Assays and the "Double-Negative" Scenario

For nearly 2 decades, regulators have adopted a harmonized approach to drug development, which has succeeded in bringing new pharmaceuticals to market without significant cardiac liability. Ushered in by technological advancements and better understanding of cellular electrophysiology, the initial paradigm detailed in the 2005 International Conference for Harmonization E14 and S7B documents has undergone evolutionary changes designed to streamline drug development and improve regulatory decision‐making and product labeling. The intent of this review is to summarize the new US Food and Drug Administration (FDA) Question and Answer update from August 2020 and key messaging from a subsequent FDA webinar describing best practices for preclinical and clinical data integration into a QT risk prediction model.

Influence of heart rate correction formulas on QTc interval stability

Monitoring of QTc interval is mandated in different clinical conditions. Nevertheless, intra-subject variability of QTc intervals reduces the clinical utility of QTc monitoring strategies. Since this variability is partly related to QT heart rate correction, 10 different heart rate corrections (Bazett, Fridericia, Dmitrienko, Framingham, Schlamowitz, Hodges, Ashman, Rautaharju, Sarma, and Rabkin) were applied to 452,440 ECG measurements made in 539 healthy volunteers (259 females, mean age 33.3 ± 8.4 years). For each correction formula, the short term (5-min time-points) and long-term (day-time hours) variability of rate corrected QT values (QTc) was investigated together with the comparisons of the QTc values with individually corrected QTcI values obtained by subject-specific modelling of the QT/RR relationship and hysteresis. The results showed that (a) both in terms of short-term and long-term QTc variability, Bazett correction led to QTc values that were more variable than the results of other corrections (p < 0.00001 for all), (b) the QTc variability by Fridericia and Framingham corrections were not systematically different from each other but were lower than the results of other corrections (p-value between 0.033 and < 0.00001), and (c) on average, Bazett QTc values departed from QTcI intervals more than the QTc values of other corrections. The study concludes that (a) previous suggestions that Bazett correction should no longer be used in clinical practice are fully justified, (b) replacing Bazett correction with Fridericia and/or Framingham corrections would improve clinical QTc monitoring, (c) heart rate stability is needed for valid QTc assessment, and (d) development of further QTc corrections for day-to-day use is not warranted.

Exposure-response modeling of the effect of glasdegib on cardiac repolarization in patients with cancer

PURPOSE

To characterize the effect of glasdegib on cardiac repolarization (QTc) in patients with advanced cancer.

METHODS

A concentration-QTc model was developed using data from two glasdegib single-agent, dose-escalation trials. Triplicate electrocardiogram was performed at pre-specified timepoints paired with pharmacokinetic blood collections after a single dose and at steady-state. Changes in QTc from baseline were predicted by model-based simulations at the clinical dose (100 mg QD) and in a supratherapeutic setting.

RESULTS

Glasdegib did not affect the heart rate, but had a positive effect on the corrected QT interval, described by a linear mixed-effects model with ΔQTcF (QTc using Fridericia's formula) as the dependent variable with glasdegib plasma concentrations from doses of 5-640 mg QD. The predicted mean QTcF change (upper bound of the 95% CI) was 5.30 (6.24) msec for the therapeutic 100-mg QD dose; at supratherapeutic concentrations (40% and 100% increase over the therapeutic C_max), it was 7.42 (8.74) and 12.09 (14.25) msec, respectively.

CONCLUSIONS

The relationship of glasdegib exposure and QTc was well characterized by the model. The effect of glasdegib on the QTc interval did not cross the threshold of clinical concern for an oncology drug.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT01286467 and NCT00953758.

T-wave peak-end interval and ratio of T-wave peak-end and QT intervals: novel arrhythmogenic and survival markers for dogs with myxomatous mitral valve disease

INTRODUCTION/OBJECTIVES

In the past few years, novel markers such as the interval between the peak and the end of T-wave (Tpte) and Tpte/QT ratio have been shown to have high sensitivity for ventricular arrhythmias and mortality. We analyzed these and other parameters of ventricular repolarization, such as QT interval, QT interval corrected for heart rate (QTc), and QT dispersion (QTd) in dogs with myxomatous mitral valve disease (MMVD). Additionally, we investigated their relationship with the progression of the disease, echocardiographic parameters, and ventricular arrhythmias and assessed their prognostic value with development of clinical signs or mortality as the final outcome.

ANIMALS, MATERIALS AND METHODS

Epidemiological, clinical, echocardiographic, and electrocardiographic data were obtained from 236 dogs with MMVD and 15 healthy dogs. Prognostic and survival information was also recorded for the MMVD group. All ventricular repolarization indices were measured in 10 lead electrocardiographic recordings.

RESULTS

With the exception of the QT interval, most repolarization markers increased along with the frequency of arrhythmias and with the progression of MMVD. The parameters that best identified ventricular arrhythmias (AUC > 0.7) were Tpte (aVR, rV2, average rV2-V10, average rV2-V4) and Tpte/QT (II, aVR, rV2). In survival analysis, statistically significant markers with the highest differences in median survival were Tpte (maximum of any lead, maximum rV2-V10), QTc aVR, and Tpte rV2.

CONCLUSION

Tpte and Tpte/QT are good non-invasive markers for clinical risk stratification in dogs with MMVD.

Problems with Bazett QTc correction in paediatric screening of prolonged QTc interval

Background

Bazett formula is frequently used in paediatric screening for the long QT syndrome (LQTS) and proposals exist that using standing rather than supine electrocardiograms (ECG) improves the sensitivity of LQTS diagnosis. Nevertheless, compared to adults, children have higher heart rates (especially during postural provocations) and Bazett correction is also known to lead to artificially prolonged QTc values at increased heart rates. This study assessed the incidence of erroneously increased QTc values in normal children without QT abnormalities.

Methods

Continuous 12-lead ECGs were recorded in 332 healthy children (166 girls) aged 10.7 ± 2.6 years while they performed postural manoeuvring consisting of episodes (in the following order) of supine, sitting, standing, supine, standing, sitting, and supine positions, each lasting 10 min. Detailed analyses of QT/RR profiles confirmed the absence of prolonged individually corrected QTc interval in each child. Heart rate and QT intervals were measured in 10-s ECG segments and in each segment, QTc intervals were obtained using Bazett, Fridericia, and Framingham formulas. In each child, the heart rates and QTc values obtained during supine, sitting and standing positions were averaged. QTc durations by the three formulas were classified to < 440 ms, 440–460 ms, 460–480 ms, and > 480 ms.

Results

At supine position, averaged heart rate was 77.5 ± 10.5 beat per minute (bpm) and Bazett, Fridericia and Framingham QTc intervals were 425.3 ± 15.8, 407.8 ± 13.9, and 408.2 ± 13.1 ms, respectively. At sitting and standing, averaged heart rate increased to 90.9 ± 10.1 and 100.9 ± 10.5 bpm, respectively. While Fridericia and Framingham formulas showed only minimal QTc changes, Bazett correction led to QTc increases to 435 ± 15.1 and 444.9 ± 15.9 ms at sitting and standing, respectively. At sitting, Bazett correction identified 51, 4, and 0 children as having the QTc intervals 440–460, 460–480, and > 480 ms, respectively. At sitting, these numbers increased to 118, 11, and 1, while on standing these numbers were 151, 45, and 5, respectively. Irrespective of the postural position, Fridericia and Framingham formulas identified only a small number (< 7) of children with QT interval between 440 and 460 ms and no children with longer QTc.

Conclusion

During screening for LQTS in children, the use of Bazett formula leads to a high number of false positive cases especially if the heart rates are increased (e.g. by postural manoeuvring). The use of Fridericia formula can be recommended to replace the Bazett correction not only for adult but also for paediatric ECGs.

Sources of QTc variability: Implications for effective ECG monitoring in clinical practice

Pharmaceuticals that prolong ventricular repolarization may be proarrhythmic in susceptible patients. While this fact is well recognized, schemes for sequential QTc interval monitoring in patients receiving QT‐prolonging drugs are frequently overlooked or, if implemented, underutilized in clinical practice. There are several reasons for this gap in day‐to‐day clinical practice. One of these is the perception that serially measured QTc intervals are subject to substantial variability that hampers the distinction between potential proarrhythmic signs and other sources of QTc variability. This review shows that substantial part of the QTc variability can be avoided if more accurate methodology for electrocardiogram collection, measurement, and interpretation is used. Four aspects of such a methodology are discussed. First, advanced methods for QT interval measurement are proposed including suggestion of multilead measurements in problematic recordings such as those in atrial fibrillation patients. Second, serial comparisons of T‐wave morphologies are advocated instead of simple acceptance of historical QTc measurements. Third, the necessity of understanding the pitfalls of heart rate correction is stressed including the necessity of avoiding the Bazett correction in cases of using QTc values for clinical decisions. Finally, the frequently overlooked problem of QT‐heart rate hysteresis is discussed including the possibility of gross QTc errors when correcting the QT interval for simultaneously measured short‐term heart rate.

Heart Rate Correction of the J-to-Tpeak Interval

Drug-induced changes of the J to T peak (JTp) and J to the median of area under the T wave (JT50) were reported to differentiate QT prolonging drugs that are predominant blockers of the delayed potassium rectifier current from those with multiple ion channel effects. Studies of drug-induced JTp/JT50 interval changes might therefore facilitate cardiac safety evaluation of new pharmaceuticals. It is not known whether formulas for QT heart rate correction are applicable to JTp and JT50 intervals. QT/RR, JTp/RR, and JT50/RR profiles were studied in 523 healthy subjects aged 33.5 ± 8.4 years (254 females). In individual subjects, 1,256 ± 220 electrocardiographic measurements of QT, JTp, and JT50 intervals were available including a 5-minute history of RR intervals preceding each measurement. Curvilinear, linear and log-linear regression models were used to characterize individual QT/RR, JTp/RR, and JT50/RR profiles both without and with correction for heart rate hysteresis. JTp/RR and JT50/RR hysteresis correction needs to be included but the generic universal correction for QT/RR hysteresis is also applicable to JTp/RR and JT50/RR profiles. Once this is incorporated, median regression coefficients of the investigated population suggest linear correction formulas JTpc = JTp + 0.150(1-RR) and JT50c = JT50 + 0.117(1-RR) where RR intervals of the underlying heart rate are hysteresis-corrected, and all measurements expressed in seconds. The established correction formulas can be proposed for future clinical pharmacology studies that show drug-induced heart rate changes of up to approximately 10 beats per minute.

Individually Rate Corrected QTc Intervals in Children and Adolescents

Accurate evaluation of the appearance of QTc sex differences during childhood and adolescence is intricate. Inter-subject differences of individual QT/RR patterns make generic heart rate corrections inaccurate because of fast resting heart rates in children. The study investigated 527 healthy children and adolescents aged 4–19 years (268 females, 50.9%). All underwent continuous ECG 12-lead monitoring while performing postural changes during a 70-min investigative protocol to obtain QT interval measurements at different heart rates. On average, more than 1200 ECG measurements (QT interval and its 5-min history of preceding RR intervals) were made in each subject. Curvilinear QT/RR regression involving intra-individual correction for QT/RR hysteresis were calculated in each subject. The projection of the QT/RR regressions to the heart rate of 60 beats per minute defined individually corrected QTc intervals. In males, gradual QTc shortening by about 15 ms appeared during the ages of 13–19 years synchronously with the incidence of secondary sex signs (p = 0.016). On the contrary, whilst gradual QTc prolongation by about 10 ms appeared in females, it occurred only during ages 16–19 years and was not related to the incidence of secondary sex signs (p = 0.18). The study also showed that in children and adolescents, linear QT/RR models fit the intra-subject data significantly more closely than the log-linear models (p < 0.001). The study speculates that hormonal shifts during puberty might be directly responsible for the QTc shortening in males but that QTc prolongation in females is likely more complex since it was noted to follow the appearance of secondary sex signs only after a considerable delay.