Dataset Information

Artificial intelligence-derived cardiac ageing is associated with cardiac events post-heart transplantation.

ABSTRACT:

Aims

An artificial intelligence algorithm detecting age from 12-lead electrocardiogram (ECG) has been suggested to reflect 'physiological age'. An increased physiological age has been associated with a higher risk of cardiac mortality in the non-transplant population. We aimed to investigate the utility of this algorithm in patients who underwent heart transplantation (HTx).

Methods and results

A total of 540 patients were studied. The average ECG ages within 1 year before and after HTx were used to represent pre- and post-HTx ECG ages. Major adverse cardiovascular event (MACE) was defined as any coronary revascularization, heart failure hospitalization, re-transplantation, and mortality. Recipient pre-transplant ECG age (mean 63 ± 11 years) correlated significantly with recipient chronological age (mean 49 ± 14 years, R = 0.63, P < 0.0001), while post-transplant ECG age (mean 54 ± 10 years) correlated with both the donor (mean 32 ± 13 years, R = 0.45, P < 0.0001) and the recipient ages (R = 0.38, P < 0.0001). During a median follow-up of 8.8 years, 307 patients experienced MACE. Patients with an increase in ECG age post-transplant showed an increased risk of MACE [hazard ratio (HR): 1.58, 95% confidence interval (CI): (1.24, 2.01), P = 0.0002], even after adjusting for potential confounders [HR: 1.58, 95% CI: (1.19, 2.10), P = 0.002].

Conclusion

Electrocardiogram age-derived cardiac ageing after transplantation is associated with a higher risk of MACE. This study suggests that physiological age change of the heart might be an important determinant of MACE risk post-HTx.

SUBMITTER: Ozcan I

PROVIDER: S-EPMC9779895 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Artificial intelligence-derived cardiac ageing is associated with cardiac events post-heart transplantation.

Ozcan Ilke I Toya Takumi T Cohen-Shelly Michal M Park Hyun Woong HW Ahmad Ali A Ozcan Alp A Noseworthy Peter A PA Kapa Suraj S Lerman Lilach O LO Attia Zachi I ZI Kushwaha Sudhir S SS Friedman Paul A PA Lerman Amir A

European heart journal. Digital health 20220916 4

<h4>Aims</h4>An artificial intelligence algorithm detecting age from 12-lead electrocardiogram (ECG) has been suggested to reflect 'physiological age'. An increased physiological age has been associated with a higher risk of cardiac mortality in the non-transplant population. We aimed to investigate the utility of this algorithm in patients who underwent heart transplantation (HTx).<h4>Methods and results</h4>A total of 540 patients were studied. The average ECG ages within 1 year before and aft ...[more]

PMID: 36710906

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Dataset Information

Artificial intelligence-derived cardiac ageing is associated with cardiac events post-heart transplantation.

Aims

Methods and results

Conclusion

Publications

Artificial intelligence-derived cardiac ageing is associated with cardiac events post-heart transplantation.

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