Long QT syndrome (LQTS) presents a group of inheritable channelopathies with prolonged ventricular repolarization, leading to syncope, ventricular tachycardia, and sudden death. Differentiating LQTS genotypes is crucial for targeted management and treatment, yet conventional genetic testing remains costly and time-consuming. This study aims to improve the distinction between LQTS genotypes, particularly LQT3, through a novel electrocardiogram (ECG)-based approach. Patients with LQT3 are at elevated risk due to arrhythmia triggers associated with rest and sleep. Employing a database of genotyped long QT syndrome E-HOL-03-0480-013 ECG signals, we introduced two innovative parameterization techniques-area under the ECG curve and wave transformation into the unit circle-to classify LQT3 against LQT1 and LQT2 genotypes. Our methodology utilized single-lead ECG data with a 200 Hz sampling frequency. The support vector machine (SVM) model demonstrated the ability to discriminate LQT3 with a recall of 90% and a precision of 81%, achieving an F1-score of 0.85. This parameterization offers a potential substitute for genetic testing and is practical for low frequencies. These single-lead ECG data could enhance smartwatches' functionality and similar cardiovascular monitoring applications. The results underscore the viability of ECG morphology-based genotype classification, promising a significant step towards streamlined diagnosis and improved patient care in LQTS.

• Klíčová slova
• LQT3 discrimination, electrocardiogram classification, electrocardiogram parameterization, long QT syndrome, support vector machine classification,
• MeSH
• dospělí MeSH
• elektrokardiografie * metody   MeSH
• genotyp MeSH
• lidé MeSH
• strojové učení * MeSH
• support vector machine MeSH
• syndrom dlouhého QT * genetika   diagnóza   patofyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• srovnávací studie MeSH

BACKGROUND: The patients with the long QT syndrome type-1 (LQT-1) have an impaired adaptation of the QT interval to heart rate changes. Yet, the description of the dynamic QT-RR coupling in genotyped LQT-1 has never been thoroughly investigated. METHOD: We propose a method to model the dynamic QT-RR coupling by defining a transfer function characterizing the relationship between a QT interval and its previous RR intervals measured from ambulatory Holter recordings. Three parameters are used to characterize the QT-RR coupling: a fast gain (Gain(F) ), a slow gain (Gain(L) ), and a time constant (τ). We investigated the values of these parameters across genders, and in genotyped LQT-1 patients with normal QTc interval duration (QTc < 470 ms). RESULTS: The QT-RR dynamic profiles are significantly different between LQT-1 patients (97) and controls (154): LQT-1 have longer QTc interval (453 ± 35 vs. 384 ± 26 ms, P < 0.0001), and an increased dependency of the QT interval to previous RR changes revealed by a larger Gain(L) (0.22 ± 0.06 vs. 0.18 ± 0.07, P < 0.0001) and Gain(F) (0.05 ± 0.02 vs. 0.03 ± 0.01, P < 0.0001). Importantly, LQT-1 patients have a faster QT dynamic response to previous RR changes described by τ: 122 ± 44 vs. 172 ± 92 beats (P < 0.0001). This faster QT dynamic response of the QT-RR dynamic coupling remained in LQT-1 patients with QTc in a normal range (<430 ms). CONCLUSIONS: The measurement of QT-RR dynamic coupling could be used in patients suspected to carry a concealed form of the LQT-1 syndrome, or to provide insights into the types of arrhythmogenic triggers a patient may be prone to.

• MeSH
• cirkadiánní rytmus MeSH
• dospělí MeSH
• elektrokardiografie ambulantní metody   statistika a číselné údaje   MeSH
• fyziologická adaptace MeSH
• kohortové studie MeSH
• lidé MeSH
• mladý dospělý MeSH
• referenční hodnoty MeSH
• srdeční frekvence MeSH
• syndrom dlouhého QT diagnóza   patofyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH