AI-ECG Model Outperforms STEMI Criteria for Identifying ACS Patients With Occlusions

13 Dec 2023 • An artificial intelligence algorithm for ECG interpretation (AI-ECG) is superior to conventional, guideline-recommended STEMI criteria for identifying patients with chest pain who have an occluded culprit coronary artery that requires immediate revascularization, a study suggests.

Researchers developed this AI-ECG model, dubbed “Queen of Hearts” - which acts on a single 12-lead ECG - using 18,616 ECGs from 10,543 patients with suspected ACS.

  • For the current study, the investigators tested the model on 3,254 ECGs from 2,222 patients who underwent invasive coronary angiography.
  • Overall, 21.6% were diagnosed with occlusion MI, meaning they had an acutely occluded or flow-limiting culprit artery requiring emergent revascularization.
  • The AI-ECG model identified these patients with an accuracy of 90.9%, a sensitivity of 80.6%, and a specificity of 93.7%.

The short-term impact of the AI-ECG model is expected to be in reducing false-positive cath lab activations, which would be financially beneficial for health systems.

Source: tctMD | Read full story

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