Heart Rate Correction Formula Research Articles

QTc intervals at rest and during exercise assessed by group correction formulas in survivors of childhood acute lymphoblastic leukemia

IntroductionEarly signs of subclinical cardiac damage must be identified before they turn into clinical manifestations. Tailoring a formula is relevant for precise QTc evaluation in childhood acute lymphoblastic leukemia (ALL) survivors considering they are at risk of long-term cardiac problems. Therefore, we aim to develop group heart rate correction formulas for QT intervals in childhood ALL survivors at rest and during exercise, and to assess the applicability of these methods across a variety of risk groups exposed to diverse chemotherapy dosages. MethodsTwo hundred and fifty childhood ALL survivors in the PETALE study were classified into 3 groups depending on their prognostic risk group. ECG measurements (QT and RR intervals) were made at rest and during a cardiopulmonary exercise test. QT correction for heart rate was applied using 5 different formulas, which included 2 previously published formulas and 3 group-specific formulas for each sex. ResultsThe QT/RR relation showed 2 different curves between rest and during exercise, which was worse for females. Group-specific QTc formulas allowed adequate heart rate-corrected QT interval, independently of the cumulative dose of doxorubicin received during treatment. Group-specific formulas showed significantly shorter QTc intervals than QTc from Bazett's formula. QTc (Bazett's formula) values surpassed the established clinical norm in 22 males (11%) and 22 females (11%), with a majority occurring during exercise, affecting 15 males (7.5%) and 10 females (5%). ConclusionThis study shows the applicability of personalized group correction of QT/RR data in childhood ALL survivors. Our comprehensive assessments (spanning rest, exercise, and recovery) is an effective approach for risk stratification of cardiac complications in childhood ALL survivors.

Importance of Formula-Specific Centile Thresholds for Evaluation of Heart Rate-Corrected QT Prolongation in Williams Syndrome

Patients with Williams syndrome (WS) have a 25- to 100-fold higher risk of sudden death and prolonged heart rate-corrected QT (QTc). A recent study using the Fridericia formula for QT correction suggested that prolongation is principally an issue of heart rate. We used multiple published heart rate correction formulas to reevaluate the prevalence of QTc prolongation in our original dataset from our 2010 study at the Children's Hospital of Philadelphia. The ninety-eighth centile for QTc and corrected JT Interval (JTc) of the control population for each formula were used to set the threshold for prolongation. Prevalence comparison was done with Fisher's exact test. Predictors of longer QTc/JTc were assessed using linear regression models adjusting for age, gender, and heart rate. Adjusted odds of QTc/JTc prolongation were evaluated with conditional logistic regression models matched based on age and heart rate. There were 482 electrocardiograms from 188 patients with WS and 1,522 from normal controls. Patients with WS were younger, with higher heart rates and shorter RR and QRS intervals. WS was associated with longer QTc/JTc compared with controls. There were higher odds of prolonged QTc/JTc in patients with WS than controls using both Bazett and Fridericia formulas. In conclusion, this study confirms the higher prevalence of QTc prolongation in WS compared with controls and highlights the importance of setting appropriate formula-specific upper thresholds for QTc prolongation for accurate diagnosis.

Assessment of the QT interval in right bundle branch block

Background Identifying prolonged QT interval in RBBB has been problematic. Methods Four approaches were compared to adjust for the QT prolongation in intermittent RBBB. The implications were assessed in a separate group of 200 persons with established RBBB. Results In 12 individuals, mean age 74.5 years with intermittent RBBB, the presence of RBBB significantly (p < 0.05) increased the QT interval in each of six different heart rate correction formulae by an amount ranging from 35.4 ms in the Hodges formula to 50.2 ms in the Bazett formula. Four different equations were tested to adjust the QT interval and one approach QTcRBBB = 0.945*QTcRBBB − 26 was the best method to adjust for the increased QT in RBBB as it produced a QT value that was not significantly different from the QT interval in the absence of RBBB in intermittent RBBB. Failure to adjust the QT interval in RBBB produces an overestimate of the QT interval which in some heart rate adjustment formulae was marked. For the Bazett heart rate adjustment approach QTc 450 ms was found in 73.9% of men and QTc over 460 ms was found in 60.6% of women. Conclusion These data suggest the implementation of a new approach to recalculate the QT intervals in RBBB. QTcRBBB = 0.945*QTcRBBB − 26 with an appropriate heart rate adjustment formula (other than the Bazett formula) accurately predicts the QT interval in the absence of RBBB.

Exercise-induced electrocardiographic changes after treadmill exercise testing in healthy children: A comprehensive study.

Background:Treadmill exercise testing is a crucial diagnostic tool for evaluating congenital and acquired heart disease in the pediatric population. This study aimed to perform a comprehensive evaluation of exercise-induced electrocardiographic (ECG) changes in children. Although there are numerous studies on exercise testing in various cardiac pathologies, studies on exercise-induced ECG changes in normal children with coverage of all ECG parameters of atrial and ventricular depolarization and repolarization are very scant, if any.Aims and Objectives:This study aimed to investigate the exercise-induced ECG changes in healthy children and evaluate the effects of gender and four different formulas of heart rate correction of Bazett, Fridericia, Framingham and Hodges on ventricular repolarization parameters pre-and post-exercise.Materials and Methods:Between April 2019 and April 2020, all children with normal electrocardiogram, echocardiogram and exercise test, high-quality ECG tracings and consent for participation were enrolled in this prospective study. Twenty electrocardiographic parameters were measured and 25 indices were calculated. P-value < 0.05 was considered significant.Results:Seventy-four healthy children were studied. Amplitudes of P, S, and T waves increased significantly after the exercise. All durations, except P wave time to peak and T peak -T end /QT (Tp-e/QT) interval decreased significantly with exercise. Generally, the parameters of ventricular repolarization were not statistically significant between males and females. There were significant differences among the heart-rate corrected values of intervals of QTc, QoTc, JTc, J point to peak T and Tp-e/QTc by various formulas. There was no U wave either at pre-exercise or post-exercise. QT interval was shortened by 24.6 % ± 12.1 % with exercise. The ECG-derived estimated duration of mechanical systole and diastole decreased with exercise. The percentage of decrease in diastole was more than systole (43.79 %± 13.31% versus 33.74% ±15.79 %, respectively, P-value < 0.001).Conclusion:Diastolic time decreased more than systolic time with exercise and systolic time to diastolic time increased with exercise. Hodges' and Fridericia's formulas resulted in the longest and shortest QT and QoT, JT, and JTP, respectively. Thus, using a single value as the cut-off for long QT syndrome can lead to under or over-diagnosis. Nomograms incorporating data on age, heart rate, and heart rate correction formula are indispensable for accurate long QT diagnosis. Furthermore, gender differences in ventricular repolarization parameters are not generally present in 5 to 14-year-old healthy children. The lack of U wave in this study may implicate the need for more careful investigation in the presence of U wave in the treadmill exercise testing of healthy children.

Assessment of the QT Interval in WPW: A New Approach to Calculating the QT Interval in Pre-excitation

Abstract Background The initial slurring of the QRS complex, in WPW increases the QT interval rendering it a less accurate assessment of repolarization. Objective The objective was to develop a method to calculate the underlying QT interval in WPW from the 12 lead ECG. Methods Patients with a diagnosis of intermittent WPW on a single ECG had measurements of QT interval, delta wave duration, QRS duration and JT interval. Seven different equations were evaluated in pre-excited compared to non-pre excited conduction with the latter considered the 'true' or underlying (intrinsic) QT interval. The best formulae were tested in a separate group of 100 patients with WPW. Results The QT interval of 'pre excited' QRS complexes (QTwpw) were significantly longer than the non-pre excited QT interval (QTi), in each of four different heart rate correction formulae. Three equations showed highly significant (p < 0.0001) correlations with QTi (r = 0.918 to 0.977) using either parametric or non-parametric testing and were better than subtracting delta wave duration from QTwpw an equations with the strongest correlation, highest F value, was selected. In a separate sample of 100 persons with pre excitation, QT heart rate dependency was not completely corrected by the Bazett formula and this formula produced unacceptably high estimates for QT prolongation. Three other heart rate correlation formulae showed a consistent and low prevalence of QT prolongation. Conclusion An accurate assessment of the underlying QT interval in pre-excitation is attained from the formula QTwpw - 0.462 (QRSwpw) + 18.26 followed by a heart rate correction formula other than the Bazett approach.

QT Interval and Its Prolongation - What Does It Mean?

The assessment of the QT interval has been an integral part of ECG interpretation since the first descriptions of long QT syndrome by Wolff in 1950 and by Jervell and Lange-Nielsen in 1957. The correct measurement of the QT interval as well as a correct interpretation of the causes and of the clinical consequences of a QT prolongation, however, may be difficult even for trained internists and cardiologists. In this review, we give an overview on physiological determinants of cardiac repolarization, its marker in the surface ECG - the QT interval -, methods to correctly assess QT interval duration, causes for pathologically prolonged QT intervals, and resulting clinical consequences. A correct measurement of the QT interval should be performed by using the "tangent method", excluding possible U waves. A heart rate correction formula should be employed to determine the heart rate corrected QT interval (QTc).Many factors, which may prolong the QT interval, should be checked whenever a QTc prolongation is observed. These include drugs, electrolyte imbalances, hormonal influence, and comorbidities. The correct management of a patient with (genetically determined) LQTS starts with a risk stratification based on genotype, ECG phenotype, clinical history, age, sex, concomitant diseases, drug therapies, and family history for syncope or sudden cardiac death. The therapeutic approaches for LQTS are multimodal. Prevention is the basis of the therapy and includes avoiding known risk factors / and potentially QT-prolonging drugs, and a pharmacological treatment with non-selective beta blockers. According to the risk profile and to the patient's lifestyle the implantation of an ICD or a pacemaker should be considered.

Normal Values of Corrected Heart-Rate Variability in 10-Second Electrocardiograms for All Ages.

Purpose: Heart-rate variability (HRV) measured on standard 10-s electrocardiograms (ECGs) has been associated with increased risk of cardiac and all-cause mortality, but age- and sex-dependent normal values have not been established. Since heart rate strongly affects HRV, its effect should be taken into account. We determined a comprehensive set of normal values of heart-rate corrected HRV derived from 10-s ECGs for both children and adults, covering both sexes.Methods: Five population studies in the Netherlands (Pediatric Normal ECG Study, Leiden University Einthoven Science Project, Prevention of Renal and Vascular End-stage Disease Study, Utrecht Health Project, Rotterdam Study) provided 10-s, 12-lead ECGs. ECGs were stored digitally and analyzed by well-validated analysis software. We included cardiologically healthy participants, 42% being men. Their ages ranged from 11 days to 91 years. After quality control, 13,943 ECGs were available. Heart-rate correction formulas were derived using an exponential model. Two time-domain HRV markers were analyzed: the corrected standard deviation of the normal-to-normal RR intervals (SDNNc) and corrected root mean square of successive RR-interval differences (RMSSDc).Results: There was a considerable age effect. For both SDNNc and RMSSDc, the median and the lower limit of normal decreased steadily from birth until old age. The upper limit of normal decreased until the age of 60, but increased markedly after that age. Differences of the median were minimal between men and women.Conclusion: We report the first comprehensive set of normal values for heart-rate corrected 10-s HRV, which can be of value in clinical practice and in further research.

Comparison of Heart Rate Correction Formulas for Accurate Detection of Repolarization Changes in Spontaneous Beating hiPSC-Cardiomyocytes

Comparison of Heart Rate Correction Formulas for Accurate Detection of Repolarization Changes in Spontaneous Beating hiPSC-Cardiomyocytes

QT interval variability index and QT interval duration during different sleep stages in patients with obstructive sleep apnea

ObjectivesThe aim of the study was to investigate the impact of obstructive sleep apnea (OSA) on the QT interval variability and duration in patients during different sleep stages. MethodsPolysomnographic recordings of 28 (13 male, 15 female) patients with OSA and 30 (15 male, 15 female) patients without OSA were analyzed. The QT interval variability index (QTVI) and the corrected QT interval (QTc) analyses were performed using two awake, 3–4 non-rapid eye movement (NREM) and three rapid eye movement (REM) sleep episodes (each 300 s). The Bazett formula, linear, and parabolic heart rate correction formulas with two separate α values were used. ResultsQTVI was statistically higher in OSA than in non-OSA patients for males while awake (awake −0.7 ± 0.3 vs −1.2 ± 0.2, p = 0.001; NREM ‒0.9 ± 0.4 vs −1.1 ± 0.3, p = 0.110; REM ‒1.1 ± 0.3 vs −1.3 ± 0.2, p = 0.667) and for females in all wake–sleep stages (awake −0.3 ± 0.7 vs −0.9 ± 0.5, p = 0.001; NREM ‒0.3 ± 0.5 vs −0.8 ± 0.4, p = 0.002; REM −0.3 ± 0.5 vs −1.0 ± 0.4, p < 0.001). QTVI was significantly higher during awake compared to sleep stages in OSA males (p < 0.05); no difference between wake–sleep stages was found in females (p > 0.05). Significant gender differences in QTVI existed in OSA patients during sleep (p < 0.05) but not while awake. No significant differences in QTc between patients groups were observed. ConclusionsOSA is associated with increased QT variability. REM sleep per se does not increase QTVI. In OSA patients, QTVI might be a more useful measure to detect ventricular repolarization abnormality than measures of QTc.

Newer QT Correction Formulae to Correct QT for Heart Rate Changes During Exercise

BackgroundThe QT interval is a marker for drug-induced cardiac toxicity, electrolyte abnormalities and genetic mutations with a high risk of sudden death. AimThe objective was to determine the optimal QT-heart rate correction when heart rate is increased. Materials and MethodsA total of 40 persons had QT interval measured before at the end of each stage of a Bruce protocol. Currently used heart rate correction formulae (QTc) were compared to recently proposed QTc formulae derived from large population studies. ResultsComparing the data at each stage of exercise found that QTc using the Bazett formula (QTcBZT) increased with exercise while the QTc proposed by Fridericia (QTcFRD) and by Framingham (QTcFRM) decreased with exercise. In contrast QTc proposed by Dmitrienko (QTcDMT) and Rautaharju (QTcRTHa) were relatively constant despite the increase in heart rate during exercise, whereas QTc proposed by Hodges (QTcHDG) was more variable. With exercise, the differences between QTcBZT or QTcFRD and the other correction formulae became greater and highly significant. Next, the slope of QTc or RR regression was calculated for each individual during the exercise test. The rank order of the slopes (from the smallest to largest absolute value) was QTcRTHa, QTcDMT, QTcBZT, QTcHDG, QTcFRD and QTcFRM. Furthermore the slope of the QT/heart rate relationship was significantly (P < 0.0001) different between the older formulae proposed by Bazett or Fridericia compared to the newer formulae QTcDMT or QTcRTHa. ConclusionThe 2 newer QT-heart rate correction formula should be used when evaluating QT interval at faster heart rates especially those associated with exercise.

Risk assessment of drug-induced QT prolongation.

Drugs can cause prolongation of the QT interval, alone or in combination, potentially leading to fatal arrhythmias such as torsades de pointes. When prescribing drugs that prolong the QT interval, the balance of benefit versus harm should always be considered. Readouts from automated ECG machines are unreliable. The QT interval should be measured manually. Changes in heart rate influence the absolute QT interval. Heart rate correction formulae are inaccurate, particularly for fast and slow heart rates. The QT nomogram, a plot of QT interval versus heart rate, can be used as a risk assessment tool to detect an abnormal QT interval.

Comparison of Formulas for Calculation of the Corrected QT Interval in Infants and Young Children

To compare 4 heart rate correction formulas for calculation of the rate corrected QT (QTc) interval among infants and young children. R-R and QT intervals were measured from digital electrocardiograms. QTc were calculated with the Bazett, Fridericia, Hodges, and Framingham formulas. QTc vs R-R graphs were plotted, and slopes of the regression lines compared. Slopes of QTc-R-R regression lines close to zero indicate consistent QT corrections over the range of heart rates. We reviewed electrocardiograms from 702 children, with 233 (33%) <1 year of age and 567 (81%) <2 years. The average heart rate was 122 ± 20 bpm (median 121 bpm). The slopes of the QTc-R-R regression lines for the 4 correction formulas were -0.019 (Bazett); 0.1028 (Fridericia); -0.1241 (Hodges); and 0.2748 (Framingham). With the Bazett formula, a QTc >460 ms was 2 SDs above the mean, compared with "prolonged" QTc values of 414, 443, and 353 ms for the Fridericia, Hodges, and Framingham formulas, respectively. The Bazett formula calculated the most consistent QTc; 460 ms is the best threshold for prolonged QTc. The study supports continued use of the Bazett formula for infants and children and differs from the use of the Fridericia correction during clinical trials of new medications.

Association between corrected QT interval and inflammatory cytokines in rheumatoid arthritis.

Corrected QT (QTc) interval predicts all-cause and cardiovascular mortality and may contribute to the increased mortality risk in rheumatoid arthritis (RA). Animal experiments have shown that proinflammatory cytokines [tumor necrosis factor (TNF)-α and interleukin 1 (IL-1)] can prolong cardiomyocyte action potential. We sought to determine whether elevations in circulating inflammatory cytokines were independently associated with QTc prolongation in patients with RA. One hundred twelve patients [median age 62 (interquartile range 17) yrs; 80 women (71%)] from a well-characterized RA cohort underwent baseline 12-lead electrocardiograms for QT interval measurement and contemporary blood sampling to assess concentrations of inflammatory markers including C-reactive protein (CRP), TNF-α, and interleukins (IL-1α, IL-1β, IL-6, IL-10). QTc was calculated using the Bazett (QTBAZ = QT ÷ √RR) and Framingham Heart Study (QTFHS = QT + 0.154 × [1 - RR]) heart rate correction formulas. Inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-10) were positively correlated with QTBAZ (Spearman rank correlation coefficient rho = 0.199, 0.210, 0.222, 0.333; all p < 0.05). In multivariable regression analysis, these associations were all confounded by age except IL-10, where higher tertile groups were independently and positively associated with QTBAZ (β = 0.202, p = 0.023) and QTFHS (β = 0.223, p = 0.009) when compared to the lower tertile. CRP (per unit increase) was independently associated with QTBAZ (β = 0.278, p = 0.001), but not QTFHS. To our knowledge, ours is the first study demonstrating a contemporary link between inflammatory cytokines and QT interval in humans. Our results suggest that a lower inflammatory burden may protect against QTc prolongation in patients with RA. However, further studies are required to confirm the effects of pro- and antiinflammatory cytokines on QTc interval.

QT Interval Variability Index and QT Interval Duration in Different Sleep Stages: Analysis of Polysomnographic Recordings in Nonapneic Male Patients.

The aim of the study was to determine whether different sleep stages, especially REM sleep, affect QT interval duration and variability in male patients without obstructive sleep apnea (OSA). Polysomnographic recordings of 30 patients were analyzed. Beat-to-beat QT interval variability was calculated using QTV index (QTVI) formula. For QTc interval calculation, in addition to Bazett's formula, linear and parabolic heart rate correction formulas with two separate α values were used. QTVI and QTc values were calculated as means of 2 awake, 3 NREM, and 3 REM sleep episodes; the duration of each episode was 300 sec. Mean QTVI values were not statistically different between sleep stages. Therefore, elevated QTVI values found in patients with OSA cannot be interpreted as physiological sympathetic impact during REM sleep and should be considered as a risk factor for potentially life-threatening ventricular arrhythmias. The absence of difference of the mean QTc interval values between NREM and REM stages seems to confirm our conclusion that sympathetic surges during REM stage do not induce repolarization variability. In patients without notable structural and electrical remodeling of myocardium, physiological elevation in sympathetic activity during REM sleep remains subthreshold concerning clinically significant increase of myocardial electrical instability.

Evaluation of differences in automated QT/QTc measurements between Fukuda Denshi and Nihon Koden systems.

BackgroundAutomatic measurement becomes a preference, and indeed a necessity, when analyzing 1000 s of ECGs in the setting of either drug-inducing QT prolongation screening or genome-wide association studies of QT interval. The problem is that individual manufacturers apply different computerized algorithms to measure QT interval. We conducted a comparative study to assess the outcomes with different automated measurements of QT interval between ECG machine manufacturers and validated the related heart rate correction methods.Methods and ResultsHerein, we directly compared these different commercial systems using 10,529 Fukuda Denshi ECGs and 72,754 Nihon Kohden ECGs taken in healthy Japanese volunteers. Log-transformed data revealed an equal optimal heart rate correction formula of QT interval for Fukuda Denshi and Nihon Kohden, in the form of QTc = QT/RR−0.347. However, with the raw data, the optimal heart rate correction formula of QT interval was in the form of QTc = QT+0.156×(1-RR) for Fukuda Denshi and QTc = QT+0.152×(1-RR) for Nihon Kohden. After optimization of heart rate correction of QT interval by the linear regression model using either log-transformed data or raw data, QTc interval was ∼10 ms longer in Nihon Kohden ECGs than in those recorded on Fukuda Denshi machines. Indeed, regression analysis revealed that differences in the ECG machine used had up to a two-fold larger impact on QT variation than gender difference. Such an impact is likely to be of considerable importance when ECGs for a given individual are recorded on different machines in the setting of multi-institutional joint research.ConclusionsWe recommend that ECG machines of the same manufacturer should be used to measure QT and RR intervals in the setting of multi-institutional joint research. It is desirable to unify the computer algorithm for automatic QT and RR measurements from an ECG.

The measurement of the QT interval.

The evaluation of every electrocardiogram should also include an effort to interpret the QT interval to assess the risk of malignant arrhythmias and sudden death associated with an aberrant QT interval. The QT interval is measured from the beginning of the QRS complex to the end of the T-wave, and should be corrected for heart rate to enable comparison with reference values. However, the correct determination of the QT interval, and its value, appears to be a daunting task. Although computerized analysis and interpretation of the QT interval are widely available, these might well over- or underestimate the QT interval and may thus either result in unnecessary treatment or preclude appropriate measures to be taken. This is particularly evident with difficult T-wave morphologies and technically suboptimal ECGs. Similarly, also accurate manual assessment of the QT interval appears to be difficult for many physicians worldwide. In this review we delineate the history of the measurement of the QT interval, its underlying pathophysiological mechanisms and the current standards of the measurement of the QT interval, we provide a glimpse into the future and we discuss several issues troubling accurate measurement of the QT interval. These issues include the lead choice, U-waves, determination of the end of the T-wave, different heart rate correction formulas, arrhythmias and the definition of normal and aberrant QT intervals. Furthermore, we provide recommendations that may serve as guidance to address these complexities and which support accurate assessment of the QT interval and its interpretation.

Peri-ictal QTc changes are not associated with hypoxemia

It has previously been suggested that abnormalities in cardiac repolarization (QTc lengthening and shortening) are more likely to accompany seizures with hypoxemia and may be involved in sudden unexpected death in epilepsy (SUDEP). Accordingly, we evaluated for associations between peri-ictal QTc changes and hypoxemia. We performed a reanalysis of cardiac and respiratory data gathered prospectively in our epilepsy monitoring units. The Bazett, Fridericia, Framingham, and Hodges heart rate correction formulas were utilized to calculate QTc in the pre-ictal, ictal, and post-ictal periods. Hypoxemia (defined as a drop in oxygen saturation below 90% for at least four contiguous seconds) was also examined during identical periods. Fifty-eight seizures from 29 patients were analyzed. Peri-ictal hypoxemia was not rare, occurring in 18/58 (31%) seizures. QTc lengthening was more commonly observed than shortening, with 11/58 (19%) seizures demonstrating peri-ictal QTc values≥500 using the Bazett formula. There was no significant difference between the minimum and maximum QTc values in seizures with and without peri-ictal hypoxemia, regardless of the correction formula utilized. All examined parameters of QTc lengthening and shortening were not associated with peri-ictal hypoxemia. This suggests that factors other than hypoxia result in peri-ictal cardiac repolarization abnormalities.

QT/RR curvatures in healthy subjects: sex differences and covariates

Data of a large clinical study were used to investigate how much are the QT/RR patterns in healthy subjects curved and whether these curvatures differ between women and men. Daytime drug-free 12-lead Holter recordings were repeated 4 times in each of 176 female healthy subjects and 176 male healthy subjects aged 32.7 ± 9.1 yr. In each of the subjects, up to 1,440 carefully verified QT interval measurements were obtained with QT/RR hysteresis-corrected RR intervals. Individual subject data were used to fit the following regression equation: QT = χ + (δ/γ)(1 - RR(γ)) + ε, where QT and RR are QT and RR measurements (in s), χ is regression intercept, δ is the QT/RR slope, γ is the QT/RR curvature and provides the lowest regression residual, and ε represents normally distributed zero-centered errors. The bootstrap technique showed the intrasubject reproducibility of QT/RR slopes and curvatures. In women and men, QT/RR curvatures were 0.544 ± 0.661 and 0.797 ± 0.706, respectively (P = 0.0006). The corresponding QT/RR slopes were 0.158 ± 0.030 and 0.139 ± 0.023, respectively (P < 0.0001). QT/RR curvatures were related to QT/RR slopes but not to individually corrected mean QTc intervals or individual QT/RR hysteresis profiles. The individual heart rate correction formula derived from the curvilinear regression provided a significantly lower intrasubject variability of QTc interval than individual optimisation of linear or log-linear QT/RR heart rate corrections. The QT/RR curvature can be reliable measured and expressed numerically. The corresponding heart rate correction formula provides more compact data than the previously proposed approaches. There are substantial sex differences in QT/RR patterns. Women have a QT/RR pattern that is not only steeper than men but also more curved.

Importance of subject-specific QT/RR curvatures in the design of individual heart rate corrections of the QT interval

ObjectiveA statistical modelling study investigated whether incorporating the curvatures of QT/RR patterns into the individual-specific QT heart rate correction increases QTc data accuracy. MethodsRepeated ECG readings were available from 4 different drug-free recordings made in 176+176 healthy female and male subjects (aged 32 ± 10 and 33 ± 8 years, respectively). In each subject, up to 1440 ECG readings were made of QT intervals and of the corresponding QT/RR hysteresis corrected RR intervals. The QT/RR patterns of each study participant was fitted with 12 different regression formulae that corresponded to differently curved physiologically plausible QT/RR profiles. In each subject, each of the regression fits was converted into a QT heart rate correction formula and the optimum model that fitted the data of the subject best was identified. Correction formulae were applied to modelled QT/RR data with RR intervals between 400 ms and 1600 ms. Differences in QTc intervals calculated by the correction formulae corresponding to the individually optimum QT/RR regression models and by the same type of regression in all study subjects were statistically summarised in females and males. ResultsCompared to the individually curvature optimised QTc heart rate correction formulae, formulae of the different regression models overestimated or underestimated the QTc values when applied on all study subjects. At RR of 500 ms, the model assuming linear QT/RR relationship led to errors of −5.01 ± 6.63 ms and of −4.80 ± 7.23 ms in females and males, respectively. At the same RR interval level, the model assuming the linear relationship between the logarithms of QT and RR intervals led to errors of +11.51 ± 6.36 ms and of +15.09 ± 7.61 ms in females and males, respectively. ConclusionThe differences in the curvatures of QT/RR patterns should be considered in the optimisation of subject-specific heart rate corrections. Forcing an arbitrary simple regression model on the QT/RR patterns of different subjects may lead to appreciable errors in QTc estimates. The frequently used linear and log-linear regression models were among the least precise if used without checking their appropriateness in individual subjects.

Graphical representation of QT rate correction formulae: an aid facilitating the use of a given formula and providing a visual comparison of the impact of different formulae

The QT interval on the electrocardiogram is an increasingly important measurement, especially in relation to drug action and interaction. The QT interval varies inversely as the heart rate and numerous rate correction formulae have been proposed. It is difficult to compare the effect of applying different formulae at different heart rates and for different measured QT intervals. A simple graphical display of the results from different formulae is proposed. This display is dependent on the concept of the absolute correction factor. This graphical presentation is useful (a) in comparing the effect of the application of different formulae and (b) in directly reading the correction produced by any individual formula.