Echocardiography-Guided Risk Stratification for Long QT Syndrome. Sugrue A, van Zyl M, Enger N, Mancl K, Eidem BW, Oh JK, Bos JM, Asirvatham SJ, Ackerman MJ. J Am Coll Cardiol. 2020 Dec 15;76(24):2834-2843. doi: 10.1016/j.jacc.2020.10.024.
Take Home Points:
- Echocardiography can be used to assess for risk of cardiac events in patients with Long QT syndrome (LQTS)
- A simple and reliable echocardiographic measure, electromechanical window (EMW), was proven to be a better predictor of symptomatic LQTS compared to QTc interval.
- A negative EMW is associated with LQTS (-25±34 msec vs +15±20 in controls)
- A more negative EMW is associated with symptomatic LQTS (-52±38 vs -18±29 in asymptomatic LQTS)
- EMW < -40 ms was identified as the optimal threshold for LQTS risk prediction (Sensitivity: 86%; Specificity: 61%).
Commentary by Dr. Akash Patel (San Francisco, Ca, USA) Congenital and Pediatric Cardiac EP section editor: Long QT syndrome (LQTS) is associated with sudden cardiac death and identification of patients prior to these sentinel events is critical. Our current methods for risk stratification depend on a variety of factors including genotype and phenotype characteristics such specific genetic mutation, age, gender, prior cardiac events, T wave abnormalities, and QTc intervals. As phenotypic expression is variable, additional strategies are needed to help identify those at risk. This study examined the use of echocardiography to assess risk for cardiac events in LQTS with a particular focus on electromechanical dysfunction as measured by the electromechanical window (EMW).
This was a retrospective single center study at the Mayo Clinic of 997 genotype-confirmed LQTS patients who underwent an echocardiogram. A total of 346 patients were excluded due to non-digitized images for analysis (n=212) or poor quality ECG tracings (n=134). A total of 651 (65%) patients were analyzed with complete clinical, electrocardiographic and echocardiographic data. The primary outcome measure was the presence of symptomatic LQTS defined as arrhythmogenic syncope, generalized seizure, aborted cardiac arrest, appropriate ICD shock, or sudden cardiac death.
The EMW was obtained by blinded review of a continuous-wave doppler image in the apical long-axis view with concurrent ECG tracing. The EMW was calculated as the difference between the interval from QRS onset to aortic valve closure (midline) (QAoC interval) and the QT interval from the ECG, for the same beat (EMW= QAoC interval – QT interval). See figure below. Interobserver and intraobserver reliability of physicians and sonographers was also assessed on a subset of patients.
The cohort had a mean age of 26±17 years of whom 60% were female. The group included a representative distribution of Long QT Syndromes- LQTS1 (51%), LQT2 (33%), LQT3 (11%), and multiple mutations (5%). The mean QTc was 469±41 msec. There was symptomatic LQTS seen in 24% of this cohort. This was comprised of predominately syncope/seizure (74%) followed by other (15%) and cardiac arrest (11%). See figure below.
The EMW was predominately positive in normal controls (15±20 msec) and significantly negative in nearly all patients with LQTS (-25±34 msec) (p<0.0001). In addition, patients with symptomatic LQTS demonstrated a significantly more negative EMW compared to asymptomatic patients (-52±38msec vs -18 ±29 msec, p<0.0001). See figures below.
Of note, there was no significant differences in EMW between LQTS1, LQTS2, and LQTS3. However, multiple mutations were noted to have a significantly more negative EMW (-58±49 msec) compared to single mutation LQTS genotypes 1, 2, and 3 (p=0.0001). See figure below. This finding may be due to multiple mutation patients having longer QT and QTc intervals compared to the single mutation LQTS patients, though not reported in the study.
Overall, there was weak to moderate correlation between EMW and QTc interval (r=
-0.36 and r2 =0.13, p < 0.0001). Of note, there was no subgroup analyses of the QAoC interval, QT interval, and QTc interval based on LQTS genotype groups to determine which factor, if any effected the correlation between EMW and QTc. See figure below.
There was a significant portion of symptomatic LQTS patients in this cohort (24%). Based on multivariate analysis only age, EMW per 10msec, QTc per 10 msec, female gender, and LQTS3 were associated with symptoms. Interestingly, EMW per 10 msec was more significantly associated with symptoms (OR 1.37, p<0.0001) compared to the QTc interval per 10 msec (OR 1.07, p<0.006). Also, EMW per change in SD was associated with a 3-fold increase in symptoms (OR per SD, 3.00, CI: 2.34 – 3.91, p<0.0001). Of note, there was no interaction between Bazett QTc and EMW (p= 0.50). See figure below.
ROC analysis also revealed that EMW was superior to Bazett QTc in identifying symptomatic LQTS patients (AUC for EMW= 0.78 (95% CI: 0.74 to 0.81) vs. AUC of Bazett QTc = 0.70 (95% CI: 0.67 to 0.74); p=0.01). The ROC analysis did not reveal a difference between LTQ1 (AUC=0.79, 95% CI: 0.74 to 0.83) and LQT2 (AUC=0.83, 95% CI: 0.77 to 0.88 ) but was reduced with LQT3 (AUC=0.54) and multiple mutations (AUC=0.54). See figures below.
The optimal EMW cut off to determine symptomatic LQTS was considered < -40 msec which resulted in a sensitivity of 86% and specificity of 61%.
Finally, the interobserver and intraobserver variability was considered excellent after appropriate training. The interobserver reliability between reviewers for EMW (average measures ICC: 0.93; 95% CI: 0.89 to 0.96) was excellent. Intraobserver reliability for QT (average measures ICC: 0.98; 95% CI: 0.97 to 0.99), QAoC (average measures ICC: 0.97; 95% CI: 0.96 to 0.98) and EMW (average, measures ICC: 0.95; 95% CI: 0.86 to 0.99) was excellent. Based on this, EMW reporting has been consider standard clinical practice at this center since December 2019.
Overall, this study demonstrates a novel echocardiographic measure (EMW) for risk stratification in patients with LQTS. The EMW was previously identified as a risk factor in LQTS by Ter Bekke et al in 2014 across 3 centers in a smaller cohort with similar findings. This study validated these findings in larger cohort and demonstrated the feasibility to incorporate this measure into clinical practice.
The authors discuss that EMW represents the time between the end of electrical and mechanical systole. In healthy adults, this should be positive as electrical systole ends the before closure of the aortic valve. In patients with LQTS, there is a mismatch due to prolongation of electrical systole resulting in a negative EMW. The mechanism for why there is increased arrhythmias in this setting is unknown but thought to be due to abnormalities in cellular calcium handling, heterogenous mechanical /electrical ventricular dispersion, impaired relaxation, and/or modulations of cardiac mechanoreceptors. Interestingly a negative EMW in animal models of LQTS has been associated with increased lability for torsade de pointes.
The impact for treatment on the EMW was not evaluated in this study. Presumptively, some if not all of these patients were on beta-blocker at the time of their imaging and thus the impact of therapy on EMW and outcomes is unclear. However, the authors conducted a pilot study on patients who underwent left cardiac sympathetic denervation that is used to reduce events in high risk patients. They showed a reduction in EMW by 35±57 msec.
Most importantly, this study demonstrated that an echocardiographic marker of electromechanical dysfunction (EMW) was a better predictor of events in LQTS overall and in particular in LQTS1 and LQTS2 than the QTc interval. In addition, this study demonstrated that this measure could be obtained reliably and accurately with appropriate training of staff.
This study does have some limitations that may impact its generalizability. First, all clinical analysis and evaluation was done at single center by a single provider with expertise in LQTS. Second, the assessment of the QT interval on echocardiogram can be challenging as demonstrated by a removal of 13% of the cohort and the learning curve needed by sonographers/physicians to obtain accurate measures. This was due to the inability to precisely determine the end of the T-wave due to small T-wave amplitude, biphasic T-wave, or noise. Third, the lead positioning and beat-to beat HR variation impact on the QTc interval was not addressed. Finally, the authors highlight that additional markers or alternative techniques (i.e. strain, tissue doppler, etc.) for electromechanical dysfunction may prove to be superior.
Risk stratification in LQTS is critically important to minimize the risk of morbidity and mortality. This has been mainly driven by genotype, gender, age, QTc interval, and prior clinical events. This study identifies a new measure that can be incorporated in the risk assessment of patients with LQTS to better inform clinical decisions. Validation of this data in a prospective trial and/or multicenter study will aid in the generalizability of these findings.