QT interval time lag in response to heart rate changes during stress test for Coronary Artery Disease diagnosis

Pérez, Cristina (Universidad de Zaragoza) ; Pueyo, Esther (Universidad de Zaragoza) ; Martínez, Juan Pablo (Universidad de Zaragoza) ; Viik, Jari ; Laguna, Pablo (Universidad de Zaragoza)

Resumen: Background: Slow adaptation of the QT interval to abrupt changes in heart rate (HR) can enhance ventricular heterogeneity and has been suggested as a marker of arrhythmic risk. Most investigations on QT rate adaptation lag have been performed in response to step-like HR changes. However, abrupt HR changes are difficult to induce or observe in ECG recordings under ambulatory conditions.

Objective: We aim to evaluate the power of indices related to the QT lag in response to ramp-like HR changes in stress test to assess CAD risk.

Methods: We quantified the lag between the actual QT series and the memoryless expected QT series, which was obtained by fitting a hyperbolic regression model to the instantaneous QT and HR measurements in stages where their behavior could be assumed stationary. The proposed methodology was applied to analyze ECG stress tests of a subset of 448 patients presenting different risk levels for Coronary Artery Disease (CAD). The QT lag was estimated separately in the exercise and recovery phases.

Results: An increase in the estimated QT lag during exercise (from 25 to 36 s) and a decrease during recovery (from 57 to 39 s) were associated with higher CAD risk. The difference between these lags showed significant capacity for CAD risk stratification.

Conclusion: The QT lag in response to HR changes can be quantified from a stress test. QT lag values in response to ramp-like HR changes are in ranges comparable to those quantified from abrupt HR changes and show clinical significance to stratify CAD risk.

Idioma: Inglés

DOI: 10.1016/j.bspc.2023.105056

Año: 2023

Publicado en: Biomedical Signal Processing and Control 86 (2023), 105056 [13 pp.]
ISSN: 1746-8094

Factor impacto JCR: 4.9 (2023)

Categ. JCR: ENGINEERING, BIOMEDICAL rank: 30 / 123 = 0.244 (2023) - Q1 - T1

Factor impacto CITESCORE: 9.8 - Biomedical Engineering (Q1) - Signal Processing (Q1) - Health Informatics (Q1)

Factor impacto SCIMAGO: 1.284 - Biomedical Engineering (Q1) - Signal Processing (Q1) - Health Informatics (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA-IIU/796-2019
Financiación: info:eu-repo/grantAgreement/ES/DGA/LMP94_21
Financiación: info:eu-repo/grantAgreement/ES/DGA/T39-23R
Financiación: info:eu-repo/grantAgreement/EUR/ERC-2014-StG-638284
Financiación: info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-104881RB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-105674RB-I00
Financiación: info:eu-repo/grantAgreement/EUR/MICINN/TED2021-130459B-I00

Tipo y forma: Article (Published version)

Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)