{"id":5239,"date":"2025-10-27T10:34:23","date_gmt":"2025-10-27T08:34:23","guid":{"rendered":"https:\/\/cvja.co.za\/journal\/?p=5239"},"modified":"2026-05-05T14:41:23","modified_gmt":"2026-05-05T12:41:23","slug":"cvja-2025-069","status":"publish","type":"post","link":"https:\/\/cvja.co.za\/journal\/cvja-2025-069\/","title":{"rendered":"Rapid AI-assisted Poincar\u00e9 plot analysis for early detection of subclinical left ventricular dysfunction in hypertensive patients admitted to the emergency department: A prospective observational study"},"content":{"rendered":"    <div id=\"article\">                                                                                                                        \r\n        <div id=\"title-container\">                                                                                                    \r\n        <div id=\"authors-title\">                                                                                                            \r\n        <!--Aurthors under Title-->                                                                                                            \r\n            \r\nErhan Ar\u0131kan, Faik \u00d6zel, Ramazan Aslan, Murat \u00d6zmen, Ahmet Ardahanl\u0131, \u0130sa Ardahanl\u0131\r\n        <\/div>        \r\n<\/div>                                                                                                                            \r\n            <div id=\"copyright\">\r\n        <strong>Copyright:<\/strong> Clinics Cardive Publishing (Pty) Ltd. publisher\r\n        of Cardiovascular Journal of Africa.<\/div>\r\n    <div style=\"clear: both;\"><\/div>                                                                                                                                \r\n        <div id=\"article-abstract\">                                                                                                            \r\n            <div id=\"abstract-title\">                                                                                                        \r\n                    Abstract                                                                                                                \r\n                <\/div>                                                                                                                        \r\n                                                                                                                                \r\n            <div id=\"abstract-content\">                                                                                                        \r\n            <!--Content of Abstract Article-->                                                                                                \r\n            <!--<strong>\"Abstract titles\":<\/strong>-->                                                                                        \r\n            <!--<br\/> at the end of each section!!-->                                                                                        \r\n                                                                                                                                            \r\n        <strong>Introduction:<\/strong>                                                                                                    \r\n                                                                                                                                                    \r\nEarly detection of subclinical left ventricular (LV) dysfunction in hypertensive patients presenting to the emergency department (ED) is of critical importance. We aimed to evaluate the performance of artificial intelligence (AI)-assisted Poincar\u00e9 plot analysis of electrocardiogram (ECGs) to identify subclinical LV dysfunction rapidly.\r\n<br \/>                                                                                                                            \r\n                                                                                                                                                \r\n        <strong>Methods:<\/strong>                                                                                                    \r\n                                                                                                                                                    \r\n60 hypertensive patients and 55 normotensive controls were prospectively enrolled in the ED. After stabilisation, all participants underwent 5-minute ECG recordings. Heart rate variability (HRV) measurements were calculated, and Poincar\u00e9 plots were generated. A convolutional neural network (CNN) model was trained to classify the Poincar\u00e9 plot images. Transthoracic echocardiography was performed within 24 hours to measure left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS). Subclinical dysfunction was defined as GLS > -18% with preserved LVEF.\r\n<br \/>        \r\n                \r\n                <strong>Results:<\/strong>                                                                                                    \r\nThe CNN model detected subclinical LV dysfunction by achieving an area under the curve (AUC) of 0.91 (95% CI: 0.84-0.96). Conventional HRV measurements showed a moderate correlation with GLS (r = 0.48), while AI-based Poincar\u00e9 plot analysis had a stronger correlation (r = 0.70). The time from ECG acquisition to automatic analysis was less than 5 minutes.\r\n<br \/>\r\n                                                                                                                                                                                                                                                                        \r\n                                                                                                                                                \r\n        <strong>Conclusion:<\/strong>                                                                                                    \r\n                                                                                                                                                    \r\nAl-assisted Poincar\u00e9 plot analysis enables rapid and non-invasive detection of subclinical LV dysfunction in hypertensive patients in the ED, supporting early risk stratification.\r\n<br \/>    \r\n                                                                                                        \r\n\r\n                                                                                                                                                \r\n            <\/div>                                                                                                                            \r\n        <\/div>                                                                                                                                    \r\n                                                                                                                                        \r\n                                                                                                                                                \r\n        <div id=\"keywords\">                                                                                                                    \r\n                                                                                                                                            \r\n            <strong>Keywords:<\/strong>                                                                                                        \r\n                                                                                                                                            \r\n            <strong>hypertension, subclinical left ventricular dysfunction, Poincar\u00e9 plot, heart rate variability, artificial intelligence, emergency department, electrocardiogram<\/strong>                                                                                                                                                                                                                    \r\n                                                                                                                                                \r\n        <\/div>                                                                                                                                    \r\n                                                                                                                                                \r\n    <div id=\"publish-info\">                                                                                                                    \r\n                                                                                                                                \r\n    <strong>Submitted:<\/strong> April 30, 2025; <!--Month day, year; -->    \r\n    <strong>Accepted:<\/strong> June 5, 2025; <!--Month day, year; -->                                                                            \r\n    <strong>Published:<\/strong> October 27, 2025<!--Month day, year; -->                                                                                                                            <br \/>                                                            \r\n        <em>Cardiovasc J Afr 2025; <b>36<\/b>: 480-487<!--pg no. till pg no. \"eg. 4-7\"--><\/em>\r\n        <br \/><strong>Volume 36, Issue 4<\/strong> <br \/>                                                                            \r\n        <\/div>                                                                                                                            \r\n                                                                                                                                        \r\n    <div id=\"DOI\">                                                                                                                    \r\n            DOI Citation Reference: dx.doi.org\/10.5830\/CVJA-2025-069<!--DOI number-->                                                                \r\n        <\/div>                                                                                                                            \r\n                \r\n                <div id=\"author-affiliation\">                                                                                                \r\n\r\n<strong>Department of Emergency Medicine, Seyh Edebali University School of Medicine, Bilecik, Turkey\r\n<\/strong>    <br \/>                                                                            \r\nErhan Ar\u0131kan\r\n\r\n<br \/><br \/>\r\n\r\n<strong>Department of Internal Medicine, Seyh Edebali University School of Medicine, Bilecik, Turkey\r\n<\/strong>    <br \/>                                                                            \r\nFaik \u00d6zel\r\n\r\n<br \/><br \/>\r\n\r\n<strong>Department of Cardiology, Bilecik Training and Research Hospital, Bilecik, Turkey\r\n<\/strong>    <br \/>                                                                            \r\nRamazan Aslan\r\n\r\n<br \/><br \/>\r\n\r\n<strong>Department of Cardiology, Health Sciences University Erzurum Faculty of Medicine, Erzurum, Turkey\r\n<\/strong>    <br \/>                                                                            \r\nMurat \u00d6zmen\r\n\r\n<br \/><br \/>\r\n\r\n<strong>Department of Computer Engineering, Kafkas University Faculty of Engineering, Kars, Turkey\r\n<\/strong>    <br \/>                                                                            \r\nAhmet Ardahanl\u0131\r\n\r\n<br \/><br \/>\r\n\r\n<strong>Department of Cardiology, Seyh Edebali University School of Medicine, Bilecik, Turkey\r\n<\/strong>    <br \/>                                                                            \r\n\u0130sa Ardahanl\u0131\r\n\r\n<br \/><br \/>\r\n                                                                                                                                                                                                                                        \r\n\r\n                [soshsc hide=\"logged\"]\r\n                <strong>You need to be <a style=\"color: #c80c44;\" href=\"https:\/\/cvja.co.za\/journal\/member-login\/\" target=\"_blank\" rel=\"noopener\">logged in to view and download<\/a> the full text PDF version. <a style=\"color: #c80c44;\" href=\"https:\/\/cvja.co.za\/journal\/register\/\" target=\"_blank\" rel=\"noopener\">Register for a free account?<\/a><\/strong> <br \/><br \/>[\/soshsc]\r\n                \r\n                \r\n                \r\n                <\/div>\r\n    \r\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Early detection of subclinical left ventricular (LV) dysfunction in hypertensive patients presenting to the emergency department (ED) is of critical importance. We aimed to evaluate the performance of artificial intelligence (AI)-assisted Poincar\u00e9 plot analysis of electrocardiogram (ECGs) to identify subclinical LV dysfunction rapidly.<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[44,108],"tags":[],"class_list":["post-5239","post","type-post","status-publish","format-standard","hentry","category-cardiovascular-topics","category-volume-36-issue-4"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Rapid AI-assisted Poincar\u00e9 plot analysis for early detection of subclinical left ventricular dysfunction in hypertensive patients admitted to the emergency department: A prospective observational study - Cardiovascular Journal of Africa<\/title>\n<meta name=\"description\" content=\"Early detection of subclinical left ventricular (LV) dysfunction in hypertensive patients presenting to the emergency department (ED) is of critical importance. 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