Sex influences on ventricular repolarization duration in normal subjects and in type 1, 2 and 3 long QT syndrome patients: Different effect in acquired and congenital type 2 LQTS

Extremely dangerous hypopituitarism related long QT syndrome and transient ST-segment elevation: A case report

Acquired long QT syndrome caused by hypopituitarism and transient ST-segment elevation has not been reported in cardiac arrest patients. We report a case of extremely dangerous acquired long QT syndrome and transient ST-segment elevation. A 44-year-old Chinese woman with renal failure experienced sudden cardiac arrest in the haemodialysis room. Subsequent electrocardiogram showed QT prolongation and transient ST-segment elevation. This patient's medical history, subsequent laboratory results and pituitary magnetic resonance imaging suggested hypopituitarism. Transient ST-segment elevation on the electrocardiogram was considered to be caused by repeated direct current shocks. The patient was diagnosed with acquired long QT syndrome and was not taking any antiarrhythmic drugs. Her corrected QT interval normalized after hormone replacement therapy. This case highlights the importance of the awareness of hypopituitarism; early identification and intervention can prevent the occurrence of this life-threatening arrhythmia. ST-segment elevation is not always due to acute myocardial infarction, and a variety of other causes, especially electrical cardioversion, should be considered.

OUP accepted manuscript

Current exercise recommendations make it difficult for long QT syndrome (LQTS) patients to adopt a physically active and/or athletic lifestyle. The purpose of this review is to summarize the current evidence, identify knowledge gaps, and discuss research perspectives in the field of exercise and LQTS. The first aim is to document the influence of exercise training, exercise stress, and postural change interventions on ventricular repolarization in LQTS patients, while the second aim is to describe electrophysiological measurements used to study the above. Studies examining the effects of exercise on congenital or acquired LQTS in human subjects of all ages were included. Systematic searches were performed on 1 October 2021, through PubMed (NLM), Ovid Medline, Ovid All EBM Reviews, Ovid Embase, and ISI Web of Science, and limited to articles written in English or French. A total of 1986 LQTS patients and 2560 controls were included in the 49 studies. Studies were mainly case-control studies (n = 41) and examined exercise stress and/or postural change interventions (n = 48). One study used a 3-month exercise training program. Results suggest that LQTS patients have subtype-specific repolarization responses to sympathetic stress. Measurement methods and quality were found to be very heterogeneous, which makes inter-study comparisons difficult. In the absence of randomized controlled trials, the current recommendations may have long-term risks for LQTS patients who are discouraged from performing physical activity, rendering its associated health benefits out of range. Future research should focus on discovering the most appropriate levels of exercise training that promote ventricular repolarization normalization in LQTS.

Deep learning analysis of electrocardiogram for risk prediction of drug-induced arrhythmias and diagnosis of long QT syndrome

AIMS

Congenital long-QT syndromes (cLQTS) or drug-induced long-QT syndromes (diLQTS) can cause torsade de pointes (TdP), a life-threatening ventricular arrhythmia. The current strategy for the identification of drugs at the high risk of TdP relies on measuring the QT interval corrected for heart rate (QTc) on the electrocardiogram (ECG). However, QTc has a low positive predictive value.

METHODS AND RESULTS

We used convolutional neural network (CNN) models to quantify ECG alterations induced by sotalol, an IKr blocker associated with TdP, aiming to provide new tools (CNN models) to enhance the prediction of drug-induced TdP (diTdP) and diagnosis of cLQTS. Tested CNN models used single or multiple 10-s recordings/patient using 8 leads or single leads in various cohorts: 1029 healthy subjects before and after sotalol intake (n = 14 135 ECGs); 487 cLQTS patients (n = 1083 ECGs: 560 type 1, 456 type 2, 67 type 3); and 48 patients with diTdP (n = 1105 ECGs, with 147 obtained within 48 h of a diTdP episode). CNN models outperformed models using QTc to identify exposure to sotalol [area under the receiver operating characteristic curve (ROC-AUC) = 0.98 vs. 0.72, P ≤ 0.001]. CNN models had higher ROC-AUC using multiple vs. single 10-s ECG (P ≤ 0.001). Performances were comparable for 8-lead vs. single-lead models. CNN models predicting sotalol exposure also accurately detected the presence and type of cLQTS vs. healthy controls, particularly for cLQT2 (AUC-ROC = 0.9) and were greatest shortly after a diTdP event and declining over time (P ≤ 0.001), after controlling for QTc and intake of culprit drugs. ECG segment analysis identified the J-Tpeak interval as the best discriminator of sotalol intake.

CONCLUSION

CNN models applied to ECGs outperform QTc measurements to identify exposure to drugs altering the QT interval, congenital LQTS, and are greatest shortly after a diTdP episode.