El-Menyar A. Letter to the Editor: Do we need an artificial intelligence-assisted electrocardiographic tool to diagnose diabetes mellitus or to predict its unseen cardiovascular consequences? World J Cardiol 2026; 18(6): 119266 [DOI: 10.4330/wjc.119266]
Corresponding Author of This Article
Ayman El-Menyar, MS (cardiology), FRCP, FESC, FACC, Department of Surgery, Hamad Medical Corporation, Al-Rayyan Street, Doha 3050, Qatar. aymanco65@yahoo.com
Research Domain of This Article
Cardiac & Cardiovascular Systems
Article-Type of This Article
letter
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El-Menyar A. Letter to the Editor: Do we need an artificial intelligence-assisted electrocardiographic tool to diagnose diabetes mellitus or to predict its unseen cardiovascular consequences? World J Cardiol 2026; 18(6): 119266 [DOI: 10.4330/wjc.119266]
World J Cardiol. Jun 26, 2026; 18(6): 119266 Published online Jun 26, 2026. doi: 10.4330/wjc.119266
Letter to the Editor: Do we need an artificial intelligence-assisted electrocardiographic tool to diagnose diabetes mellitus or to predict its unseen cardiovascular consequences?
Ayman El-Menyar
Ayman El-Menyar, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar
Author contributions: El-Menyar A conceptualization, methodology, writing, and review of the manuscript.
Conflict-of-interest statement: The author declared that he has no conflict of interest.
Corresponding author: Ayman El-Menyar, MS (cardiology), FRCP, FESC, FACC, Department of Surgery, Hamad Medical Corporation, Al-Rayyan Street, Doha 3050, Qatar. aymanco65@yahoo.com
Received: January 23, 2026 Revised: February 2, 2026 Accepted: February 24, 2026 Published online: June 26, 2026 Processing time: 147 Days and 1 Hours
Core Tip
Core Tip: Diabetes mellitus (DM) has a significant negative impact on the global health. The most dramatic complications of diabetes include the microvascular damage that can start years before the diagnosis of type 2 diabetes (T2DM) is made; therefore, early screening is of utmost value. Moreover, subclinical electrocardiographic (ECG) changes are common in patients with T2DM without evident cardiac disease. A simple, easily accessible tool for early detection or prediction of cardiac dysfunction in DM or in people at risk is more valuable than merely distinguishing healthy individuals from those with diabetes or type 1 diabetes from T2DM. A single-lead ECG, especially with artificial intelligence, can red-flagging risk and help bridge some gaps in predicting event risk. However, this study needs validation with a precise aim to predict high-risk diabetics and not only to diagnose DM.
