168383 20260204153543.0 doi 10.1109/TBME.2025.3607144 sideral 147832 ART-2025-147832 eng Pérez, Cristina Universidad de Zaragoza Sudden cardiac death risk prediction from QT–RR adaptation time lag computed from exercise stress test ECG 2025 Objetive: This study aims to evaluate the QT adaptation time following gradual heart rate changes estimated from exercise stress test (EST) ECGs as a marker of sudden cardiac death (SCD) risk. The predicted risk value for any cardiovascular death (CVD) is also evaluated. Methods: Three ECG-derived markers related to QT-RR adaptation time were estimated during the exercise phase of EST, τe, during the recovery phase, τr, and as the difference between them, Δτ. The values were computed from patients with coronary artery disease (CAD) from ARTEMIS study (N=1472; median follow-up of 8.9 years). These markers are calculated as the delay between the observed RR interval series and a patient-specific memoryless RR series computed from the QT interval (RR-based strategy). Alternatively, the estimates were calculated as the delay between the observed QT intervals and a patient-specific instantaneous QT series computed from the RR intervals (QT-based strategy). The relation between the markers and CAD or SCD was evaluated. Results: The marker τr is more robustly estimateed with the RR-based strategy and is able to stratify survivors and victims of either SCD or CVD (p-value equal to 0.022 and 0.065, respectively). Multivariable regression models for predicting SCD and CVD include the QT-RR adaptation time estimated in the recovery phase of EST using the RR-based strategy. Conclusion: A prolonged QT-RR adaptation time during the recovery phase of the EST ECG, calculated with the RR-based strategy, can predict SCD and CVD, providing complementary information to other clinical markers Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/AEI/PID2021-128972OA-I00 info:eu-repo/grantAgreement/ES/AEI/PID2023-148975OB-I00 info:eu-repo/grantAgreement/ES/DGA-FEDER/T39-23R-BSICoS info:eu-repo/grantAgreement/ES/DGA/LMP 94-21 info:eu-repo/grantAgreement/ES/MICINN/CNS2023-143599 info:eu-repo/grantAgreement/ES/MICINN/PID2022-140556OB-I00 info:eu-repo/grantAgreement/ES/MICINN/RYC2021-031413-I info:eu-repo/grantAgreement/EUR/MICINN/TED2021-130459B-I00 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Martínez, Juan Pablo Universidad de Zaragoza (orcid)0000-0002-7503-3339 Ramírez, Julia Universidad de Zaragoza (orcid)0000-0003-4130-5866 Kenttä, Tuomas Junttila, Juhani Kiviniemi, Antti Perkiömäki, Juha Huikuri, Heikki Pueyo, Esther Universidad de Zaragoza (orcid)0000-0002-1960-407X Laguna, Pablo Universidad de Zaragoza (orcid)0000-0003-3434-9254 1007 610 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Medicina 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. (2025), 1-12 IEEE trans. biomed. eng. IEEE Transactions on Biomedical Engineering 0018-9294 1246166 http://zaguan.unizar.es/record/168383/files/texto_completo.pdf Versión publicada 3698615 http://zaguan.unizar.es/record/168383/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:168383 articulos driver 2026-02-04-13:14:56 ARTICLE