{"id":30755,"date":"2025-10-20T18:10:34","date_gmt":"2025-10-20T18:10:34","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=30755"},"modified":"2025-10-20T18:10:35","modified_gmt":"2025-10-20T18:10:35","slug":"ai-can-better-predict-future-risks-in-heart-attack-patients","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/ai-can-better-predict-future-risks-in-heart-attack-patients\/","title":{"rendered":"AI Can Better Predict Future Risks in Heart Attack Patients"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">Researchers led by the University of Leicester have developed an AI-based tool, GRACE 3.0, that significantly enhances the prediction of heart attack patient outcomes, offering a leap forward in personalized cardiac care.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-0dfbf163 wp-block-group-is-layout-flex\"><div style=\"font-size:16px;\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<p>A new study spearheaded by researchers at the University of Leicester has revealed that artificial intelligence can significantly enhance the prediction of future risks in heart attack patients, paving the way for more precise and effective treatments.<\/p>\n\n\n\n<p>The study, <a href=\"https:\/\/www.thelancet.com\/journals\/landig\/article\/PIIS2589-7500(25)00089-5\/fulltext\" target=\"_blank\" rel=\"noopener\" title=\"\">published<\/a> in The Lancet Digital Health, was conducted by an international team led by Florian Wenzl, an honorary fellow in the Department of Cardiovascular Sciences at the University of Leicester, who worked closely with David Adlam, a professor in the Department of Cardiovascular Sciences. <\/p>\n\n\n\n<p>The research focuses on patients experiencing non-ST-elevation acute coronary syndrome (NSTE-ACS), a common heart attack type caused by partial arterial blockage.<\/p>\n\n\n\n<p>Traditionally, doctors rely on the GRACE score to determine the mortality risk and subsequent treatment strategies for heart attack patients. However, this method has its limitations, often failing to account for individual patient complexities.<\/p>\n\n\n\n<p>Enter GRACE 3.0, an advanced AI-driven risk assessment tool designed to predict both in-hospital and one-year mortality risks. This innovative system evaluates nine critical variables: age, sex, heart rate, systolic blood pressure, troponin level, ST-deviation, creatinine level, cardiac arrest and heart failure symptoms.<\/p>\n\n\n\n<p>\u201cGRACE 3.0 represents the next evolution of the GRACE score, bringing AI methods into one of the most widely used risk tools in cardiology,&#8221; Wenzl said in a news release. &#8220;It was trained and externally validated on data from hundreds of thousands of patients from multiple countries, which gives it a very strong evidence base. Unlike traditional risk scores, GRACE 3.0 captures complex and non-linear relationships that conventional approaches often miss.\u201d<\/p>\n\n\n\n<p>Another notable advancement of GRACE 3.0 is its sex-specific analysis, offering tailored risk assessments specifically for patients with partial arterial blockage, which sets it apart from broader approaches used for more severe heart attacks, according to Wenzl. <\/p>\n\n\n\n<p>\u201cIn addition, the GRACE 3.0 score enables physicians to better predict whether or not patients will benefit from early invasive treatment such as angioplasty (to open the artery with a balloon and typically place a stent),\u201d he added.<\/p>\n\n\n\n<p>Adlam, an interventional cardiologist working within the Leicester NIHR Biomedical Research Centre, underscored the clinical significance of the tool. <\/p>\n\n\n\n<p>\u201cThis newly developed score, using artificial intelligence, helps tailor treatment for patients by better detecting future risk and therefore guiding which health interventions they would benefit from,\u201d Adlam said in the news release.<\/p>\n\n\n\n<p>The adoption of GRACE 3.0 is a promising development for the medical community. Besides its growing incorporation into international guidelines, it holds potential for shaping future clinical trials, according to Adlam.<\/p>\n\n\n\n<div style=\"height:14px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><strong>Source: <\/strong><a href=\"https:\/\/le.ac.uk\/news\/2025\/october\/artificial-intelligence-heart-attack-predict\" target=\"_blank\" rel=\"noopener\" title=\"\">University of Leicester<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new study spearheaded by researchers at the University of Leicester has revealed that artificial intelligence can significantly enhance the prediction of future risks in heart attack patients, paving the way for more precise and effective treatments. The study, published in The Lancet Digital Health, was conducted by an international team led by Florian Wenzl, [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[46],"class_list":["post-30755","post","type-post","status-publish","format-standard","hentry","category-ai","tag-university-of-leicester"],"acf":[],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"The University Network","author_link":"https:\/\/www.tun.com\/home\/author\/funky_junkie\/"},"uagb_comment_info":0,"uagb_excerpt":"A new study spearheaded by researchers at the University of Leicester has revealed that artificial intelligence can significantly enhance the prediction of future risks in heart attack patients, paving the way for more precise and effective treatments. The study, published in The Lancet Digital Health, was conducted by an international team led by Florian Wenzl,&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/30755","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=30755"}],"version-history":[{"count":13,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/30755\/revisions"}],"predecessor-version":[{"id":30808,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/30755\/revisions\/30808"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=30755"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=30755"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=30755"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}