Tomas Robyns

Which QT Correction Formulae to Use for QT Monitoring

Background Drug safety precautions recommend monitoring of the corrected QT interval. To determine which QT correction formula to use in an automated QT‐monitoring algorithm in our electronic medical record, we studied rate correction performance of different QT correction formulae and their impact on risk assessment for mortality. Methods and Results All electrocardiograms (ECGs) in patients >18 years with sinus rhythm, normal QRS duration and rate <90 beats per minute (bpm) in the University Hospitals of Leuven (Leuven, Belgium) during a 2‐month period were included. QT correction was performed with Bazett, Fridericia, Framingham, Hodges, and Rautaharju formulae. In total, 6609 patients were included (age, 59.8±16.2 years; 53.6% male and heart rate 68.8±10.6 bpm). Optimal rate correction was observed using Fridericia and Framingham; Bazett performed worst. A healthy subset showed 99% upper limits of normal for Bazett above current clinical standards: men 472 ms (95% CI, 464–478 ms) and women 482 ms (95% CI 474–490 ms). Multivariate Cox regression, including age, heart rate, and prolonged QTc, identified Framingham (hazard ratio [HR], 7.31; 95% CI, 4.10–13.05) and Fridericia (HR, 5.95; 95% CI, 3.34–10.60) as significantly better predictors of 30‐day all‐cause mortality than Bazett (HR, 4.49; 95% CI, 2.31–8.74). In a point‐prevalence study with haloperidol, the number of patients classified to be at risk for possibly harmful QT prolongation could be reduced by 50% using optimal QT rate correction. Conclusions Fridericia and Framingham correction formulae showed the best rate correction and significantly improved prediction of 30‐day and 1‐year mortality. With current clinical standards, Bazett overestimated the number of patients with potential dangerous QTc prolongation, which could lead to unnecessary safety measurements as withholding the patient of first‐choice medication.

Inferior and anterior QRS fragmentation have different prognostic value in patients who received an implantable defibrillator in primary prevention of sudden cardiac death

AIMS QRS fragmentation (fQRS) has been proposed as a predictor of sudden cardiac death (SCD) and all-cause mortality in ischemic (ICM) and non-ischemic cardiomyopathy patients. However the value of fQRS in patients with a LVEF <35% is a matter of debate. METHODS All consecutive patients with an indication for an ICD in primary prevention of SCD were included in a retrospective registry from 1996 until 2013. Twelve lead electrocardiograms before implant were analyzed for the presence of fQRS in different regions. Adjusted Cox regression analysis for first appropriate ICD shock (AS) and all-cause mortality was performed. RESULTS In total 407 patients were included with a mean follow-up of 4.2±3.3y (age 60.6±11.9y, 15.7% female and 52.8% ICM). fQRS was present in 46.7% of patients, predominantly inferior (30.7%) followed by anterior (21.4%) and lateral (11.1%) coronary artery territories. fQRS was significantly more prevalent in ICM (p=0.004). Inferior fQRS was an independent predictor of a first AS within 1y (HR 2.55, 95%CI 1.28-5.07) and 3y (HR 1.90, 95%CI 1.14-3.18) after implantation. Whereas, anterior fQRS was an independent predictor of all-cause mortality within 1y (HR 4.58, 95%CI 1.29-16.19), 3y (HR 3.92, 95%CI 1.77-8.65) and the complete follow-up (HR 2.22, 95%CI 1.33-3.69). Lateral fQRS was only a predictor of late (>3y of follow-up) all-cause mortality (HR 2.04, 95%CI 1.09-3.81). CONCLUSIONS fQRS in a specific coronary artery territory might be promising to discriminate arrhythmic from mortality risk. Inferior fQRS was a predictor of early arrhythmia, while anterior fQRS was related to mortality.

Individualized corrected QT interval is superior to QT interval corrected using the Bazett formula in predicting mutation carriage in families with long QT syndrome

BACKGROUND Long QT syndrome (LQTS) is characterized by reduced penetrance and variable QT prolongation over time, resulting in an estimate of 25% carriers of a pathogenic mutation with a normal corrected QT (QTc) interval on the resting electrocardiogram (ECG). OBJECTIVE The purpose of this study was to test the hypothesis that an individualized corrected QT interval derived from 24-hour Holter data more accurately predicts carriage of a pathogenic LQTS mutation than did QT derived from a standard 12-lead ECG and corrected using the Bazett formula (QTc interval). METHODS Carriers of a pathogenic LQTS mutation and their genotype-negative family members who had both resting ECG and Holter recordings available were included. Automated and manual measurements of QTc were performed. QTi was derived from 24-hour Holter recordings and defined as the QT value at the intersection of an RR interval of 1000 ms, with the linear regression line fitted through QT-RR data points of each individual patient. RESULTS In total, 69 patients with LQTS (23 long QT type 1, 39 long QT type 2, and 7 long QT type 3) and 55 controls were selected. Demographic characteristics were comparable. A comparison of the receiver operating characteristic curves indicates that the test added diagnostic value compared to manual measurement (P = .02) or automated measurement (P = .005). The diagnostic accuracy of manually measured QTc using conventional cutoff criteria was 72%, while it was 92% using a sex-independent QTi cutoff of 445 ms. This was caused by a 39% increase in sensitivity without compromising the specificity. CONCLUSION QTi derived from Holter recordings is superior to conventional QTc measured from a standard 12-lead ECG in predicting the mutation carrier state in families with LQTS.

Response of Robyns to the Tse's letter to editor

Dear Editor, We would like to thank Gary Tse and Bryan P. Yan for their interest in our research regarding the index of electrophysiological balance (iCEB), a novel marker of arrhythmic risk (Lu, Yan, & Gallacher, 2013; Robyns et al., 2016). We illustrated that QT/QRS is a simple surrogate for cardiac wavelength that otherwise can only be measured from invasive recordings. Cardiac wavelength plays an important role in arrhythmogenesis, and therefore, an ECG surrogate of wavelength is an interesting tool with potential large interest for clinical practice. We showed that iCEB is reduced in conditions with increased propensity for nontorsadogenic ventricular fibrillation (patients with Brugada syndrome and flecainide use) and that iCEB is increased in conditions with increased risk for torsadogenic ventricular fibrillation (long QT syndrome and sotalol use). In their letter to the editor, Tse and Yan highlight their description of novel markers in a recent issue of europace and present two additional novel risk markers (Tse & Yan, 2017, 2016). The similarity between iCEB and these novel markers is that they are based on inclusion of both a repolarization and a depolarization parameter. The first two markers (TpTe/QRS and TpTe/(QT × QRS)) include TpTe instead of QT, based on the fact that TpTe is probably a better marker for increased risk of sudden death compared to the QT interval (Tse & Yan, 2017). The markers they propose in their letter to the editor include the addition of QRS dispersion in their formula. Again, based on the fact that QRS dispersion is a marker of conduction velocity dispersion which might be a better marker for increased risk compared to QRS (Yamada et al., 2004). We do agree that these are interesting markers to evaluate; however, our main antagonism is that, compared to iCEB, it is not based on any pathophysiological background such as cardiac wavelength. Indeed, TpTe is related to transmural or global dispersion of repolarization (Izumi et al., 2012; Yan & Antzelevitch, 1998). Replacing QT by TpTe therefore moves away from the idea to measure cardiac wavelength from the surface ECG. Furthermore, as Tse and Yan correctly underline, none of these parameters have been clinically evaluated. Therefore, we tested in our described cohort of patients with long QT syndrome and Brugada syndrome and individuals started on either flecainide or sotalol whether the parameters including TpTe show any signal. Similar to iCEB, the two parameters proposed by Tse are decreased in Brugada syndrome and increased in long QT syndrome (Table 1). However, the overlap between controls and patients with BrS is larger with TpTe/QRS compared to iCEB (post hoc pvalue only .12 for TpTe/QRS compared to <.001 for iCEB). In individuals started on flecainide or sotalol on the other hand, there is no significant difference in the parameters proposed by Tse in contrast to iCEB (Table 2). To conclude, in our population of patients with arrhythmogenic heart disease, the parameters proposed by Tse including TpTe are similarly altered as iCEB, while they do not show any signal in patients started on drugs with potential proarrhythmic effect. Further evaluation of these parameters in large patient cohorts with endpoints of sudden death is required to establish their role in risk stratification.

Targeted capture sequencing in a large LQTS family reveals a new pathogenic mutation c.2038delG in KCNH2 initially missed due to allelic dropout.

We present a new mutation in KCNH2 (c.2038delG) resulting in a frameshift and premature truncation of the IKr channel protein in a large LQTS family with several sudden death cases. This mutation was initially missed by mutation scanning with DHPLC due to allelic dropout and only retrieved after repeat genetic testing with targeted capture and massive parallel sequencing. There was full penetrance of this mutation, only if an individualized QT correction derived from 24-hour Holter data was used. This case again underscores the importance of repeat genetic testing in robust cases of LQTS that remained genotype negative with mutation scanning techniques.

QT correction across the heart rate spectrum, in atrial fibrillation and ventricular conduction defects

Incorporation of QTc in clinical decision support systems requires accurate QT‐interval correction, also during common electrocardiogram abnormalities as ventricular conduction defects (VCD). We compared the performance and predictive value of QT correction formulas to design a patient‐specific QT correction algorithm (QTcA).

Combining noninvasive risk stratification parameters improves the prediction of mortality and appropriate ICD shocks

Sudden cardiac death (SCD) results from a complex interplay of abnormalities in autonomic function, myocardial substrate and vulnerability. We studied whether a combination of noninvasive risk stratification tests reflecting these key players could improve risk stratification.

Genotype-phenotype relationship and risk stratification in loss-of-function SCN5A mutation carriers

Loss‐of‐function (LoF) mutations in the SCN5A gene cause multiple phenotypes including Brugada Syndrome (BrS) and a diffuse cardiac conduction defect. Markers of increased risk for sudden cardiac death (SCD) in LoF SCN5A mutation carriers are ill defined. We hypothesized that late potentials and fragmented QRS would be more prevalent in SCN5A mutation carriers compared to SCN5A‐negative BrS patients and evaluated risk markers for SCD in SCN5A mutation carriers.

The impact of changes in LVEF and renal function on the prognosis of ICD patients after elective device replacement

A proportion of patients with an implantable cardioverter‐defibrillator (ICD) in prevention of sudden cardiac death will only receive their first appropriate ICD therapy (AT) after device replacement. Clinical reassessment at the time of replacement could be helpful to guide the decision to replace or not in the future.

Inter- and intra-observer variability of visual fragmented QRS scoring in ischemic and non-ischemic cardiomyopathy

BACKGROUND Fragmented QRS (fQRS) on a 12-lead ECG has been linked with adverse outcome. However, the visual scoring of ECGs is prone to inter- and intra-observer variability. METHODS Five observers, two experienced and three novel, assessed fQRS in 712 digital ECGs, 100 were re-evaluated to assess intra-observer variability. Fleiss and Cohens Kappa were calculated and compared between subgroups. RESULTS The inter-observer variability for assessing fQRS in all leads combined was substantial with a Kappa of 0.651. Experienced observers only had a better agreement with a Kappa of 0.823. Intra-observer variability ranged from 0.736 to 0.880. In the subgroup with ventricular pacing the inter-observer variability was even significantly larger when compared to ECGs with normal QRS duration (Kappa 0.493 vs 0.664, p<0.001). CONCLUSION The visual assessment of QRS fragmentation is prone to inter- and intra-observer variability, mainly influenced by the experience of the observers, the underlying rhythm and QRS morphology.