{"id":44278,"date":"2024-07-24T18:49:57","date_gmt":"2024-07-24T18:49:57","guid":{"rendered":"https:\/\/ibima.eu\/?p=44278"},"modified":"2025-09-30T12:43:08","modified_gmt":"2025-09-30T12:43:08","slug":"oracle","status":"publish","type":"post","link":"https:\/\/ibima.eu\/es\/oracle\/","title":{"rendered":"ORACLE"},"content":{"rendered":"<p>[et_pb_section fb_built=\u00bb1&#8243; disabled_on=\u00bboff|off|off\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bbrgba(0,0,0,0.14)\u00bb background_image=\u00bbhttps:\/\/ibima.eu\/wp-content\/uploads\/2024\/05\/929b21e7-96c2-4338-b236-e5e4aa52a653.jpg\u00bb background_position=\u00bbtop_center\u00bb background_vertical_offset=\u00bb24%\u00bb background_blend=\u00bboverlay\u00bb custom_padding=\u00bb160px||20px||false|false\u00bb locked=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_row _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb custom_padding=\u00bb80px||30px||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_column type=\u00bb4_4&#8243; _builder_version=\u00bb4.20.4&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb text_text_color=\u00bb#ffffff\u00bb header_text_color=\u00bb#FFFFFF\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"font-size: 46px; font-weight: bold; text-align: center;\"><span style=\"color: #ffffff;\">ORACLE<\/span><\/h2>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\u00bb1&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb custom_padding=\u00bb25px||||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_row _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb hover_enabled=\u00bb0&#8243; global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb locked=\u00bboff\u00bb custom_margin=\u00bb|20px|25px|175px|false|false\u00bb sticky_enabled=\u00bb0&#8243;][et_pb_column type=\u00bb4_4&#8243; _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb hover_enabled=\u00bb0&#8243; global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb sticky_enabled=\u00bb0&#8243;][et_pb_heading title=\u00bbOptimize risk prediction after myocardial infarction through artificial intelligence and multidimensional evaluation<br \/>\n\u00bb _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb title_font=\u00bb||||||||\u00bb title_text_align=\u00bbcenter\u00bb title_text_color=\u00bb#0C71C3&#8243; module_alignment=\u00bbcenter\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb custom_padding=\u00bb||0px|37px||\u00bb][\/et_pb_heading][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\u00bb3_5,2_5&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb width=\u00bb70%\u00bb locked=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_column type=\u00bb3_5&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb custom_padding=\u00bb0px|||||\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"text-align: center;\"><strong>ABSTRACT<\/strong><\/h2>\n<p style=\"text-align: justify;\">Myocardial infarction (MI) is a leading cause of death worldwide. After MI, long-term antithrombotic therapy is crucial to prevent recurrent events, but increases bleeding, that also impacts morbidity and mortality. Giving these competing risks prediction tools to forecast ischemic and bleeding are of paramount importance to inform clinical decisions, but their current precision is limited.<br \/>Improve events prediction, by discovering novel and innovative markers of risk would have a tremendous impact on therapeutic decisions and patients\u2019 outcome. I hypothesize that using innovative multidimensional information from wearable devices, biomarkers, behavioural patterns and non-invasive imaging, integrated through artificial intelligence computation, we may discover novel \u201ccomputational biomarkers\u201d of risk and improve current standards of risk prediction. In this project, I will enrol a large cohort of MI patients, whereby prospective collection of consolidated and innovative potential risk predictors will take place, in order to generate a comprehensive and multidimensional dataset. I will collect data from state-of-the-art non-invasive imaging, blood biomarkers, wearable medical devices of continuous heart electrical activity, sweat, mobility and behavioural patterns to create a large physiological time series allowing patients\u2019 deep phenotyping. We will therefore analyze data leveraging artificial intelligence computation to find relevant associations with clinical outcomes, and compare new algorithms with current risk prediction tools.<\/p>\n<p style=\"text-align: justify;\">This research will increase our knowledge on bleeding and ischemic risk factors, enabling enhanced capability predictions models. In the near future, we hypothesize that our clinically-guided Artificial Intelligence algorithm might be integrated in clinical practice, helping clinicians to inform treatment decisions, patients to better understand their risk profile, finally setting a common ground for shared patient\/physician decisions.<\/p>\n<p style=\"text-align: justify;\">\n<p>[\/et_pb_text][et_pb_text _builder_version=\u00bb4.27.0&#8243; _module_preset=\u00bbdefault\u00bb custom_margin=\u00bb10px||||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"text-align: center;\"><strong>OBJECTIVE<\/strong><\/h2>\n<div id=\"c-objective\" lang=\"en\" class=\"c-factsheet__section\">\n<p class=\"c-article__text\" style=\"text-align: justify;\">Myocardial infarction (MI) is a leading cause of death worldwide. After MI, long-term antithrombotic therapy is crucial to prevent recurrent events, but increases bleeding, that also impacts morbidity and mortality. Giving these competing risks prediction tools to forecast ischemic and bleeding are of paramount importance to inform clinical decisions, but their current precision is limited. Improve events prediction, by discovering novel and innovative markers of risk would have a tremendous impact on therapeutic decisions and patients\u2019 outcome. I hypothesize that using innovative multidimensional information from wearable devices, biomarkers, behavioral patterns and non-invasive imaging, integrated through artificial intelligence computation, we may discover novel \u201ccomputational biomarkers\u201d of risk and improve current standards of risk prediction. In this project, I will enroll a large cohort of MI patients, whereby prospective collection of consolidated and innovative potential risk predictors will take place, in order to generate a comprehensive and multidimensional dataset. I will collect data from state-of-the-art non-invasive imaging, blood biomarkers, wearable medical devices of continuous heart electrical activity, sweat, mobility and behavioral patterns to create a large physiological time series allowing patients\u2019 deep phenotyping. We will therefore analyze data leveraging artificial intelligence computation to find relevant associations with clinical outcomes, and compare new algorithms with current risk prediction tools. This research will increase our knowledge on bleeding and ischemic risk factors, enabling enhanced capability predictions models. In the near future, we hypothesize that our clinically-guided Artificial Intelligence algorithm might be integrated in clinical practice, helping clinicians to inform treatment decisions, patients to better understand their risk profile, finally setting a common ground for shared patient\/physician decisions.<\/p>\n<\/div>\n<div class=\"c-factsheet__section\"><\/div>\n<p style=\"text-align: justify;\">[\/et_pb_text][\/et_pb_column][et_pb_column type=\u00bb2_5&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_image src=\u00bbhttps:\/\/ibima.eu\/wp-content\/uploads\/2024\/05\/Logo-ORACLE.jpg\u00bb title_text=\u00bbLogo ORACLE\u00bb align=\u00bbcenter\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb max_width=\u00bb59%\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][\/et_pb_image][et_pb_text _builder_version=\u00bb4.27.0&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bbrgba(3,3,10,0.09)\u00bb custom_margin=\u00bb|72px||72px|false|false\u00bb custom_padding=\u00bb||0px|||\u00bb border_radii=\u00bbon|8px|8px|8px|8px\u00bb border_width_all=\u00bb2px\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"text-align: center;\"><\/h2>\n<h2 style=\"text-align: center;\"><span style=\"color: #000000;\"><strong><span style=\"text-decoration: underline;\">Project Information<\/span><\/strong><\/span><\/h2>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span style=\"color: #000000;\"><strong>Program<\/strong>:<\/span> <a href=\"https:\/\/cordis.europa.eu\/programme\/id\/HORIZON_ERC-2023-STG\/en\">ERC-2023-STG &#8211; ERC STARTING GRANTS<\/a><\/li>\n<li><b><span style=\"color: #000000;\">Project Reference:<\/span>\u00a0<\/b><a href=\"https:\/\/cordis.europa.eu\/project\/id\/101117469\">101128437<\/a><\/li>\n<li><span style=\"color: #000000;\"><b>Duration: <\/b>April 2024 to March 2029<\/span><\/li>\n<li><span><span style=\"color: #000000;\">Implementation Centre:<\/span> <a href=\"http:\/\/www.huvv.es\/\">Hospital Universitario Virgen de la Victoria<\/a><\/span><\/li>\n<li><span><a href=\"https:\/\/www.huvv.es\/\"><\/a><\/span><span style=\"color: #000000;\">Research group of IBIMA involved:<\/span> <a href=\"https:\/\/ibima.eu\/en\/project\/a-03\/\">Cardiovascular Research for Health<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>[\/et_pb_text][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb custom_margin=\u00bb-3px|||||\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<p style=\"text-align: center;\">\n<p style=\"text-align: center;\">\n<h2 style=\"text-align: center;\">Principal Investigator<\/h2>\n<p>[\/et_pb_text][et_pb_image src=\u00bbhttps:\/\/ibima.eu\/wp-content\/uploads\/2024\/05\/Foto-1-scaled.jpg\u00bb title_text=\u00bbFoto 1&#8243; align=\u00bbcenter\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb max_width=\u00bb73%\u00bb border_radii=\u00bbon|8px|8px|8px|8px\u00bb border_width_all=\u00bb2px\u00bb border_color_all=\u00bb#0C71C3&#8243; global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][\/et_pb_image][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<p style=\"text-align: center;\">\n<p style=\"text-align: center;\">\n<h2 style=\"text-align: center;\">Dr. Francesco Costa<\/h2>\n<p>[\/et_pb_text][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h3 style=\"text-align: center;\"><span>\ud83d\udce9app.oraclemi@gmail.com<\/span><\/h3>\n<p>[\/et_pb_text][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"text-align: center;\">Team<\/h2>\n<p>[\/et_pb_text][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb custom_margin=\u00bb|||50px|false|false\u00bb custom_padding=\u00bb|||0px||\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<ul>\n<li style=\"text-align: left;\">Prof. Andr\u00e9s Ortiz &#8211; Computational Scientist<\/li>\n<li style=\"text-align: left;\">Dr. Arancha Diaz Exposito &#8211; Investigador Clinico<\/li>\n<li style=\"text-align: left;\">Dr. Jorge Rodriguez-Capitan &#8211; Investigador Clinico<\/li>\n<li style=\"text-align: left;\">Dr. Jose Manuel Garcia Pinilla &#8211; Investigador Clinico<\/li>\n<li style=\"text-align: left;\">Dr. Cristobal Urbano Carrillo &#8211; Investigador Clinico<\/li>\n<li style=\"text-align: left;\">Dr. Juan Jose Gomez Doblas &#8211; Investigador Clinico<\/li>\n<li style=\"text-align: left;\">Prof. Manuel Jimenez-Navarro &#8211; Investigador Clinico<\/li>\n<\/ul>\n<p>[\/et_pb_text][et_pb_text _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<p style=\"text-align: center;\">\n<p style=\"text-align: center;\">\n<h2 style=\"text-align: center;\">Follow our social Networks<\/h2>\n<p>[\/et_pb_text][et_pb_image _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][\/et_pb_image][et_pb_social_media_follow _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb text_orientation=\u00bbcenter\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_social_media_follow_network social_network=\u00bbinstagram\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bb#ea2c59&#8243; custom_margin=\u00bb||||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb follow_button=\u00bboff\u00bb url_new_window=\u00bbon\u00bb]instagram[\/et_pb_social_media_follow_network][et_pb_social_media_follow_network social_network=\u00bbfacebook\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bb#3b5998&#8243; global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb follow_button=\u00bboff\u00bb url_new_window=\u00bbon\u00bb]facebook[\/et_pb_social_media_follow_network][et_pb_social_media_follow_network social_network=\u00bbtwitter\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bb#000000&#8243; global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb follow_button=\u00bboff\u00bb url_new_window=\u00bbon\u00bb]twitter[\/et_pb_social_media_follow_network][et_pb_social_media_follow_network social_network=\u00bblinkedin\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bb#007bb6&#8243; global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb follow_button=\u00bboff\u00bb url_new_window=\u00bbon\u00bb]linkedin[\/et_pb_social_media_follow_network][et_pb_social_media_follow_network social_network=\u00bbyoutube\u00bb _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb background_color=\u00bb#a82400&#8243; custom_margin=\u00bb|||-1px|false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb follow_button=\u00bboff\u00bb url_new_window=\u00bbon\u00bb]youtube[\/et_pb_social_media_follow_network][\/et_pb_social_media_follow][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb locked=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_column type=\u00bb4_4&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_text _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb custom_margin=\u00bb10px||||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"text-align: center;\"><strong><\/strong><\/h2>\n<h2 style=\"text-align: center;\"><strong><\/strong><\/h2>\n<h2 style=\"text-align: center;\"><strong>ORACLE MI<\/strong><\/h2>\n<div id=\"c-objective\" lang=\"en\" class=\"c-factsheet__section\">\n<div class=\"flex max-w-full flex-col flex-grow\">\n<div data-message-author-role=\"assistant\" data-message-id=\"fe5c3ad0-8f23-40f8-b5a1-8a740cc656b0\" dir=\"auto\" class=\"min-h-8 text-message flex w-full flex-col items-end gap-2 whitespace-normal break-words [.text-message+&amp;]:mt-5\" data-message-model-slug=\"gpt-4o\">\n<div class=\"flex w-full flex-col gap-1 empty:hidden first:pt-[3px]\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<p>The <strong>ORACLE MI mobile app<\/strong>, developed within the context of the ORACLE study, automatically determines patients&#8217; exposure to environmental pollutants, offering a unique opportunity to study how these factors may impact myocardial infarction patients in a personalized way, identify new risk factors, and improve prevention and treatment strategies. Additionally, the app sends quality-of-life and symptom surveys for precise follow-up, provides updates on secondary prevention of myocardial infarction and key research findings, and offers real-time air quality information to help patients make informed health decisions.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>[\/et_pb_text][et_pb_button button_url=\u00bbhttps:\/\/ibima.eu\/es\/oracle-mi-app\/\u00bb url_new_window=\u00bbon\u00bb button_text=\u00bbKnow More about ORACLE MI\u00bb button_alignment=\u00bbcenter\u00bb _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb custom_button=\u00bbon\u00bb button_text_size=\u00bb17px\u00bb button_text_color=\u00bb#ffffff\u00bb button_bg_color=\u00bb#235b78&#8243; button_border_width=\u00bb0px\u00bb button_border_radius=\u00bb12px\u00bb button_font=\u00bbPoppins||||||||\u00bb button_icon=\u00bb&#x39;||divi||400&#8243; custom_margin=\u00bb20px||42px||false|false\u00bb locked=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][\/et_pb_button][et_pb_text _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb custom_margin=\u00bb15px||23px||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n<h2 style=\"text-align: center;\">\u00a0<strong>NEWS ABOUT THE PROJECT<\/strong><\/h2>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\u00bb1&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_row _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_column type=\u00bb4_4&#8243; _builder_version=\u00bb4.25.1&#8243; _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_blog fullwidth=\u00bboff\u00bb include_categories=\u00bb2226&#8243; show_more=\u00bbon\u00bb show_author=\u00bboff\u00bb show_categories=\u00bboff\u00bb _builder_version=\u00bb4.27.4&#8243; _module_preset=\u00bbdefault\u00bb header_font=\u00bb||||||||\u00bb header_text_align=\u00bbcenter\u00bb header_font_size=\u00bb18px\u00bb header_letter_spacing=\u00bb1px\u00bb header_line_height=\u00bb1.4em\u00bb custom_css_free_form=\u00bbselector article {||  margin:10px!important;||}||||selector .et_pb_blog_grid .et_pb_post{||border-radius: 0px !important;||    overflow: hidden !important;||    border-color: #43a5d3 !important;||    border-right-width: 1px !important;||}||||selector .et_pb_post .entry-title a{||  font-size:30px !important;||}\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][\/et_pb_blog][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>ORACLEABSTRACT Myocardial infarction (MI) is a leading cause of death worldwide. After MI, long-term antithrombotic therapy is crucial to prevent recurrent events, but increases bleeding, that also impacts morbidity and mortality. Giving these competing risks prediction tools to forecast ischemic and bleeding are of paramount importance to inform clinical decisions, but their current precision is [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":38185,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[2191,2233],"tags":[],"class_list":["post-44278","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-proyectos-de-investigacion","category-proyectos-de-investigacion-investigador"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ORACLE - Ibima<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ibima.eu\/es\/oracle\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ORACLE - Ibima\" \/>\n<meta property=\"og:description\" content=\"ORACLEABSTRACT Myocardial infarction (MI) is a leading cause of death worldwide. After MI, long-term antithrombotic therapy is crucial to prevent recurrent events, but increases bleeding, that also impacts morbidity and mortality. 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