{"id":1918,"date":"2022-09-15T00:00:00","date_gmt":"2022-09-15T04:00:00","guid":{"rendered":"https:\/\/icesontario.wpengine.com\/journal-articles\/derivation-and-external-validation-of-a-clinical-model-to-predict-heart-failure-onset-in-patients-with-incident-diabetes\/"},"modified":"2023-06-14T19:57:42","modified_gmt":"2023-06-14T23:57:42","slug":"derivation-and-external-validation-of-a-clinical-model-to-predict-heart-failure-onset-in-patients-with-incident-diabetes","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/derivation-and-external-validation-of-a-clinical-model-to-predict-heart-failure-onset-in-patients-with-incident-diabetes\/","title":{"rendered":"Derivation and external validation of a clinical model to predict heart failure onset in patients with incident diabetes"},"content":{"rendered":"<p><strong>Objective<\/strong> &#x2014; Heart failure (HF) often develops in patients with diabetes and is recognized for its role in increased cardiovascular morbidity and mortality in this population. Most existing models predict risk in patients with prevalent rather than incident diabetes and fail to account for sex differences in HF risk factors. We derived sex-specific models in Ontario, Canada to predict HF at diabetes onset and externally validated these models in the U.K.<\/p>\n<p><span class=\"bold\">Research Design and Methods<\/span> &#x2014; Retrospective cohort study using international population-based data. Our derivation cohort comprised all Ontario residents aged &#x2265;18 years who were diagnosed with diabetes between 2009 and 2018. Our validation cohort comprised U.K. patients aged &#x2265;35 years who were diagnosed with diabetes between 2007 and 2017. Primary outcome was incident HF. Sex-stratified multivariable Fine and Gray subdistribution hazard models were constructed, with death as a competing event.<\/p>\n<p><strong>Results<\/strong> &#x2014; A total of 348,027 Ontarians (45% women) and 54,483 U.K. residents (45% women) were included. At 1, 5, and 9 years, respectively, in the external validation cohort, the C-statistics were 0.81 (95% CI 0.79-0.84), 0.79 (0.77-0.80), and 0.78 (0.76-0.79) for the female-specific model; and 0.78 (0.75-0.80), 0.77 (0.76-0.79), and 0.77 (0.75-0.79) for the male-specific model. The models were well-calibrated. Age, rurality, hypertension duration, hemoglobin, HbA1c, and cardiovascular diseases were common predictors in both sexes. Additionally, mood disorder and alcoholism (heavy drinker) were female-specific predictors, while income and liver disease were male-specific predictors.<\/p>\n<p><strong>Conclusions<\/strong> &#x2014; Our findings highlight the importance of developing sex-specific models and represent an important step toward personalized lifestyle and pharmacologic prevention of future HF development.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Objective &#x2014; Heart failure (HF) often develops in patients with diabetes and is recognized for its role in increased cardiovascular morbidity and mortality in this population. Most existing models predict risk in patients with prevalent rather than incident diabetes and fail to account for sex differences in HF risk factors. We derived sex-specific models in [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[],"migration-helper-qa-sample-set":[],"class_list":["post-1918","journal_article","type-journal_article","status-publish","hentry"],"acf":{"citation":"Sun LY, Zghebi SS, Eddeen AB, Liu PP, Lee DS, Tu K, Tobe SW, Kontopantelis E, Mamas MA. <em>Diabetes Care<\/em>. 2022; 45(11):2737-45. Epub 2022 Sep 15.","source_url":"https:\/\/doi.org\/10.2337\/dc22-0894","ices_scientist":[1350,1290],"site":[6734],"research_program":[6742],"news_release":[],"journal_article":[],"atlas":[],"research_report":[],"infographic":[],"video":[],"downloads":null,"links":null,"sitecore_item_id":"321813D6-139A-45EC-8F73-B3152B55472B","sitecore_item_name":"Derivation-and-external-validation-of-a-clinical-model-to-predict-heart-failure-onset-in-patients","sitecore_field_values":"{\n  \"Title\": \"Derivation and external validation of a clinical model to predict heart failure onset in patients with incident diabetes\",\n  \"Short title\": \"Derivation and external validation of a\",\n  \"Summary\": \"This study derived sex-specific models in Ontario, Canada to predict heart failure at diabetes onset and externally validated these models in the U.K.\",\n  \"Citation\": \"<p>Sun LY, Zghebi SS, Eddeen AB, Liu PP, Lee DS, Tu K, Tobe SW, Kontopantelis E, Mamas MA. <em>Diabetes Care<\/em>. 2022; 45(11):2737-45. Epub 2022 Sep 15. DOI: <a href=\"https:\/\/doi.org\/10.2337\/dc22-0894\" title=\"opens external link\">https:\/\/doi.org\/10.2337\/dc22-0894<\/a><\/p>\",\n  \"Abstract\": \"<p><strong>Objective<\/strong> &mdash; Heart failure (HF) often develops in patients with diabetes and is recognized for its role in increased cardiovascular morbidity and mortality in this population. Most existing models predict risk in patients with prevalent rather than incident diabetes and fail to account for sex differences in HF risk factors. We derived sex-specific models in Ontario, Canada to predict HF at diabetes onset and externally validated these models in the U.K.<\/p>n<p><span class=\"bold\">Research Design and Methods<\/span> &mdash; Retrospective cohort study using international population-based data. Our derivation cohort comprised all Ontario residents aged &ge;18 years who were diagnosed with diabetes between 2009 and 2018. Our validation cohort comprised U.K. patients aged &ge;35 years who were diagnosed with diabetes between 2007 and 2017. Primary outcome was incident HF. Sex-stratified multivariable Fine and Gray subdistribution hazard models were constructed, with death as a competing event.<\/p>n<p><strong>Results<\/strong> &mdash; A total of 348,027 Ontarians (45% women) and 54,483 U.K. residents (45% women) were included. At 1, 5, and 9 years, respectively, in the external validation cohort, the C-statistics were 0.81 (95% CI 0.79-0.84), 0.79 (0.77-0.80), and 0.78 (0.76-0.79) for the female-specific model; and 0.78 (0.75-0.80), 0.77 (0.76-0.79), and 0.77 (0.75-0.79) for the male-specific model. The models were well-calibrated. Age, rurality, hypertension duration, hemoglobin, HbA1c, and cardiovascular diseases were common predictors in both sexes. Additionally, mood disorder and alcoholism (heavy drinker) were female-specific predictors, while income and liver disease were male-specific predictors.<\/p>n<p><strong>Conclusions<\/strong> &mdash; Our findings highlight the importance of developing sex-specific models and represent an important step toward personalized lifestyle and pharmacologic prevention of future HF development.<\/p>\",\n  \"Research Programs\": \"{BEC72DE0-BA8C-42B8-ACE5-EE29FFB2CB3B}\",\n  \"ICES Locations\": \"{0AD77E2C-C883-4E93-8B9A-40B82D50E3A5}\",\n  \"ICES Scientists\": \"{A8AB3D1C-BAB5-4AD8-90EF-12C9E0E07A9A}|{CEEE13AD-C7DE-455F-ACF8-AAD7D27BB178}\",\n  \"Posted Date\": \"20220915T000000\",\n  \"Show on Publications Landing Page\": \"1\"\n}","previous_url":"https:\/\/www.ices.on.ca\/Publications\/Journal-Articles\/2022\/September\/Derivation-and-external-validation-of-a-clinical-model-to-predict-heart-failure-onset-in-patients"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | Derivation and external validation of a clinical model to predict heart failure onset in patients with incident diabetes<\/title>\n<meta name=\"description\" content=\"Objective &#x2014; 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