A novel method for patient-specific QTc--modeling QT-RR hysteresis

QT Corrections for Long QT Risk Assessment: Implications for the Preparticipation Examination

BACKGROUND

Because sudden cardiac death (SCD) in the young mainly occurs in individuals with structurally normal hearts, improved screening techniques for detecting inherited arrhythmic diseases are needed. The QT interval is an important screening measurement; however, the criteria for detecting an abnormal QT interval are based on Bazett formula and older populations.

OBJECTIVE

To define the normal upper limits for QT interval from the electrocardiograms (ECGs) of healthy young individuals, compare the major correction formula and propose new QT interval thresholds for detecting those at risk of SCD.

METHODS

Young active individuals underwent ECGs as part of routine preparticipation physical examinations for competitive sports or community screening. This was a nonfunded study using de-identified data with no follow-up.

RESULTS

There were 31 558 subjects: 2174 grade school (7%), 18 547 high school (59%), and 10 822 college (34%). Mean age was 17 (12-35 years), 45% were female, 67% white, and 11% of African descent. Bazett performed least favorably for removing the effect of heart rate (HR), whereas Fridericia performed the best. Fridericia correction also closely fit the raw data best (R of 0.65), and at percentile values applicable to screening. The recommended risk cut points using Bazetts correction identified less than half of the athletes in the 99th or 99.5th percentiles of the uncorrected QT by HR range. Use of Fridericia correction increased capture rates by over 50%.

CONCLUSION

Our results support the application of the Fridericia-corrected threshold of 460 for men and 470 milliseconds for women (and 485 milliseconds for marked prolongation) rather than Bazett correction for the preparticipation examination.

Value of the New Spline QTc Formula in Adjusting for Pacing-Induced Changes in Heart Rate

AIMS

To determine whether a new QTc calculation based on a Spline fit model derived and validated from a large population remained stable in the same individual across a range of heart rates (HRs). Second, to determine whether this formula incorporating QRS duration can be of value in QT measurement, compared to direct measurement of the JT interval, during ventricular pacing.

METHODS

Individuals (N=30; 14 males) aged 51.9 ± 14.3 years were paced with decremental atrial followed by decremental ventricular pacing.

RESULTS

The new QTc changed minimally with shorter RR intervals, poorly fit even a linear relationship, and did not fit a second-order polynomial. In contrast, the Bazett formula (QTcBZT) showed a steep and marked increase in QTc with shorter RR intervals. For atrial pacing data, QTcBZT was fit best by a second-order polynomial and demonstrated a dramatic increase in QTc with progressively shorter RR intervals. For ventricular pacing, the new QTc minus QRS duration did not meaningfully change with HR in contrast to the HR dependency of QTcBZT and JT interval.

CONCLUSION

The new QT correction formula is minimally impacted by HR acceleration induced by atrial or ventricular pacing. The Spline QTc minus QRS duration is an excellent method to estimate QTc in ventricular paced complexes.

Universal Correction for QT/RR Hysteresis

INTRODUCTION

Clinical pharmacology QT/QTc studies can be smaller if they more efficiently use the data generated.

OBJECTIVE

The aim was to use large sets of electrocardiograms (ECGs) deposited at the US Food and Drug Administration to investigate the implications of heart rate measurement on the accuracy of QTc data.

METHODS

Using the data of 80 thorough QT studies, we investigated whether placing study subjects in supine positions during short-term time points stabilizes heart rate (part I, based on 73 studies with 747,912 measured ECGs in 6786 healthy subjects) and whether heart rate measurements different from RR intervals captured simultaneously with QT intervals decrease QTc variability (part II, based on seven studies with 897,570 ECG measurements in 751 healthy subjects).

RESULTS

In the part I data, when subjects were placed in supine undisturbed positions, heart rate instability (max-min of repeatedly measured heart rates within the same study time point) exceeding 5 beats per minute (bpm) was observed 40 % of the time and exceeded 10 bpm 10 % of the time. In the part II data, even when including QT measurements preceded by variable heart rates, correction of QT durations for RR interval values derived through a simple QT/RR hysteresis model with 95 % adaptation in 120 s led to mean intra-subject standard deviation of QTc (Fridericia formula) of only 7.14 ± 1.98 and 6.38 ± 1.50 ms in women and men, respectively.

CONCLUSION

The QT/RR hysteresis model with 95 % adaptation in 120 s is universally applicable to healthy subjects, providing small QTc variability. Supine positions do not generally stabilize heart rates in healthy subjects. Universally applicable QT/RR hysteresis correction allows clinical QT/QTc studies to include variable heart rate episodes in the time points.

Optimizing QT Interval Measurement for the Preparticipation Screening of Young Athletes

PURPOSE

Sudden cardiac death is the leading cause of death in athletes. Long QT syndrome (LQTS) is one of the most common cardiogenetic diseases that can lead to sudden cardiac death and is identified by QT interval prolongation on an ECG. Recommendations for QT monitoring in athletes are adopted from nonathlete populations. To improve screening, ECG data of athletes are assessed to determine a more appropriate method for QT interval estimation.

METHODS

ECG (CardeaScreen) data were collected from June 2010 to March 2015. ECG data with HR greater than 100 bpm were excluded. Fiducial points of outliers were manually corrected if the QRS onset or the T wave offset was misidentified. A model of best fit was determined and compared across four QT correction factors. Classification analysis was used to compare the Bazett's corrected QT interval to the 99th percentile of uncorrected QT interval.

RESULTS

High school (n = 597), college (n = 1207), and professional athletes (n = 273) (N = 2077) were analyzed. Mean age was 19 ± 3.5 yr. QT interval varied by cohort (HS = 388 ± 30, Col = 410 ± 33, Pro = 407 ± 27, p < 0.0001). A nonlinear power function with a cubic exponent of -0.349 fit the data the best (R = 0.64). Of the four common correction factors, Fridericia had the lowest residual dependence to HR (m = -0.10). With standard screening, 75% of athletes within the top 1% for QT interval were not identified for further investigation for LQTS.

CONCLUSION

Up to 75% of athletes possessing an uncorrected QT interval greater than 99% of the population are not identified for investigation for LQTS using the recommended criteria. We propose a new method of risk stratification that replaces QT interval correction. Further study is needed to establish QT interval distributions and risk thresholds in athletes.

Categorization and theoretical comparison of quantitative methods for assessing QT/RR hysteresis

BACKGROUND

In the human electrocardiogram, there is a lag of adaptation of the QT interval to heart rate changes, usually termed QT/RR hysteresis (QT-hys). Subject-specific quantifiers of QT-hys have been proposed as potential biomarkers, but there is no consensus on the choice of the quantifier.

METHODS

A comprehensive literature search was conducted to identify original articles reporting quantifiers of repolarization hysteresis from the surface ECG in humans.

RESULTS

Sixty articles fulfilled our inclusion criteria. Reported biomarkers were grouped under four categories. A simple mathematical model of QT/RR loop was used to illustrate differences between the methods. Category I quantifiers use direct measurement of QT time course of adaptation. They are limited to conditions where RR intervals are under strict control. Category IIa and IIb quantifiers compare QT responses during consecutive heart rate acceleration and deceleration. They are relevant when a QT/RR loop is observed, typically during exercise and recovery, but are not robust to protocol variations. Category III quantifiers evaluate the optimum RR memory in dynamic QT/RR relationship modeling. They estimate an intrinsic memory parameter independent from the nature of RR changes, but their reliability remains to be confirmed when multiple memory parameters are estimated. Promising approaches include the differentiation of short-term and long-term memory and adaptive estimation of memory parameters.

CONCLUSION

Model-based approaches to QT-hys assessment appear to be the most versatile, as they allow separate quantification of QT/RR dependency and QT-hys, and can be applied to a wide range of experimental settings.

Use of continuous ECG for improvements in assessing the standing response as a positive control for QT prolongation

BACKGROUND

Standing invoked change in QT interval has been identified as a promising autonomic maneuver for the assessment of QT/QTc prolongation in patients with underlying heart abnormalities or as a positive control in healthy volunteers for drug studies. Criticism for its more widespread use is the high variability in reported results and the need for a more standardized methodology with defined normal ranges.

METHODS

Forty healthy male subjects underwent continuous ECG collection on the day before dosing in a double-blind, placebo-controlled, randomized, single ascending dose trial. A brisk supine to standing (3 minutes) response was conducted at three time points. Results were grouped by treatment cohort or assessed as a pooled group at each time point. Maximum time and median change from baseline (ΔTmax QTcF, ΔQTcF) were calculated for each individual over sequential 30-second periods staggered by 5 seconds.

RESULTS

Maximum ΔQTcF at all time points and in all groups was significant (i.e., the lower bound of 90% CI was > 5 milliseconds) which is the ICH E14 regulatory requirement for a positive control. Variability of the time to maximum response was also reduced 9-fold by the third time period.

CONCLUSIONS

Standing invoked ΔQTcF can be utilized to validate the sensitivity of a study for assessment of the QT interval effect of drugs in early development. The methodology may be used to further improve its diagnostic use of long QT syndromes by reducing the variability and allowing adequate definition of normal limits.