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Heart surgeons know patient age matters for coronary artery bypass grafting (CABG) outcomes. But a new tool uses artificial intelligence on pre-op ECGs to estimate "physiological age."
Researchers studied 13,808 isolated CABG patients with ECGs taken within 30 days of surgery. They calculated AI ECG age via neural networks, then found the age gap: AI age minus real age. Median real age was 68 years; AI age 67 years. Average gap was -1 year, but 44% had older AI age and 21% over 5 years ahead. Teams checked links to health issues, surgery problems, and long-term survival. The results were published in the Journal of Thoracic and Cardiovascular Surgery.
Bigger Age Gaps Mean Sicker Patients Pre-Op
Patients with AI age over 5 years ahead showed more troubles upfront. They had higher rates of kidney failure, heart failure, past heart attacks, bigger BMI, and weaker pump function. Real age 65 but AI age 72? Expect extra burdens. This gap flags hidden wear-and-tear beyond years lived. Surgeons face tougher cases here—more meds, frailer bodies.
Short-Term Surgery Hits Harder with Advanced AI Age
Post-op woes piled up for big-gap patients. Atrial fibrillation risk rose 15% (OR 1.15, P=0.042). Ventilation lasted longer (OR 1.2, P=0.047). Blood needs jumped 15% (OR 1.15, P=0.017). Kidney function dipped (creatinine up 0.15, P<0.001). Hospital stays stretched 0.7 days (P=0.001). These add costs, recovery time. Check ECG AI age. Counsel high-gap patients on risks.
Long-Term Survival Takes a Hit Too
Over years, survival dropped for those with gaps over 5 years (HR 1.4, P<0.001). Physiology trumps calendar. Models adjusted for age, sex, diabetes, and more—link held strong. AI spots early vascular aging, fibrosis signals invisible to eye.
Easy Add-On for Cath Lab Workflow
No new tests are needed because existing ECGs can be used with software that runs fast and integrates easily with PACS systems. In the pre-op clinic, physicians can tell patients, "Your heart acts 10 years older than your actual age, so let's optimize your treatment plan." This approach flags patients who require tighter control of beta-blockers and statins.

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Key highlights
  • AI ECG estimates physiological age from routine pre-op ECGs in CABG patients, with 44% showing older heart age than real age.
  • Age gap over 5 years links to more pre-op issues like kidney failure, heart failure, and low ejection fraction.
  • Patients with larger AI age gaps face higher post-op risks of atrial fibrillation, long ventilation, transfusions, kidney worsening, and longer stays.
  • Long-term survival drops 40% in patients with AI ECG age more than 5 years ahead, even after risk adjustments.
  • AI ECG age gap provides independent prognostic value beyond chronological age for CABG outcomes.
Source

Sawma T, Arghami A, Schaff HV, et al. Risk stratification of coronary artery bypass patients using an artificial intelligence electrocardiogram-derived age. J Thorac Cardiovasc Surg. 2026 Jan;171(1):201-209.e3. doi: https://doi.org/10.1016/j.jtcvs.2025.06.037 

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AI on pre-op ECGs predicts worse CABG outcomes—44% show older "heart age," with gaps over 5 years raising surgery risks and cutting long-term survival.

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