Background: Electromechanical window (EMW) defines the difference between the end of mechanical systole and the termination of electrical repolarisation [EMW= QAoC – QT]. A negative EMW has been established in patients with long QT syndrome (LQTS) when compared with controls, with marked EMW negativity in symptomatic LQTS. EMW negativity has been shown to be a better risk-stratification tool compared with the existing methods.
Aims: To validate the findings of EMW negativity in LQTS and determine whether a negative EMW exists in other inherited arrhythmia syndromes (IAS) such as Brugada syndrome (BrS) and arrhythmogenic cardiomyopathy (ACM).
Method: This was a retrospective study at Royal Papworth Hospital, over a 10-year period (2011–2021), investigating a convenient sample size of LQTS (n=28), BrS (n=27), ACM (n=34) and control (normal; n=64). EMW was calculated as the difference between aortic valve closure QAoC and QT-interval measured using transthoracic echocardiography.
Results: A negative EMW was found in LQTS (-40 ± 50; p<0.001) and ACM (-10 ± 40; p<0.001) compared with controls. However, this was not true for the BrS cohort (17 ± 30; p=0.204). EMW was more negative in the symptomatic compared with the asymptomatic LQTS cohort. Both findings validate previous literature specifically that of a negative EMW (-43 ± 46 ms; p<0.0001) in LQTS compared with controls. LQTS type 3 had a marked EMW negativity compared with other LQTS types. A correlation existed between EMW negativity and a prolonged QT-interval. Excellent inter-rater reliability was established via the ICC calculation; average ICC was 0.97 with a confidence interval of 0.94–0.99.
Conclusions: LQTS and ACM cohorts had a negative EMW compared with controls, and EMW negativity was more pronounced in symptomatic LQTS. However, this was not the case in the BrS cohort. EMW has proven to outperform the traditionally used QTc and can be used when Bazett’s correction formula and wide QRS limit the use of QTc. Therefore, EMW negativity could be a useful measure of risk stratification in IAS.