{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:19:53Z","timestamp":1753885193384,"version":"3.41.2"},"reference-count":12,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Eur J Clin Investigation"],"published-print":{"date-parts":[[2022,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>With the spread of COVID\u201019 pandemic, there have been reports on its impact on incident myocardial infarction (MI) emanating from studies with small to modest sample sizes. We therefore examined the incidence of MI in a very large population health cohort with COVID\u201019 using a methodology which integrates the dynamicity of prior comorbid history. We used two approaches, i.e. main effect modelling and a machine learning (ML) methodology, accounting for the complex dynamic relationships among comorbidity and other variables.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We studied a very large prospective 18\u201390\u2010year US population, including 4,289,481 patients from medical databases in a 12\u2010month investigation of those with\/without newly incident COVID\u201019 cases together with a 2\u2010year comorbid profile in the baseline period. Incident MI outcomes were examined in relationship to diverse multimorbid conditions, COVID\u201019\u00a0status and demographic variables\u2014with ML accounting for the dynamic nature of changing multimorbidity risk factors.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Multimorbidity, defined as a composite of cardiometabolic\/noncardiometabolic comorbid profile, significantly contributed to the onset of confirmed COVID\u201019 cases. Furthermore, a main effect model (C\u2010index value 0.932; 95%CI 0.930\u20130.934) had medium to large effect sizes with incident MI outcomes in a COVID\u201019 cohort for the classic multimorbid conditions in medical history profile which includes prior coronary artery disease (OR 4.61 95%CI 4.49\u20134.73); hypertension (OR 3.55 95%CI 3.55\u20133.83); congestive heart failure (2.31 95%CI 2.24\u20132.37); valvular disease (1.43 95%CI 1.39\u20131.47); stroke (1.30 95%CI 1.26\u20131.34); and diabetes (1.26 95%CI 1.23\u20131.34). COVID\u201019\u00a0status (1.86 95%CI 1.79\u20131.93) contributed an independent large size risk effect for incident MI. The ML algorithm demonstrated better discriminatory validity than the main effect model (training: C\u2010index 0.949, 95%CI 0.948\u20130.95; validation: C\u2010index 0.949, 95%CI 0.948\u20130.95). Calibration of the ML\u2010based formulation was satisfactory and better than the main effect model. Decision curve analysis demonstrated that the ML clinical utility was better than the \u2018treat all\u2019 strategy and the main effect model. The ML logistic regression model was better than the neural network algorithm.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The very large investigation conducted herein confirmed the importance of cardiometabolic and noncardiometabolic multimorbidity in increasing vulnerabilities to a higher risk of COVID\u201019 infections. Furthermore, the presence of COVID\u201019 infections increased incident MI complications both in terms of independent effects and interactions with the multimorbid profile and age.<\/jats:p><\/jats:sec>","DOI":"10.1111\/eci.13760","type":"journal-article","created":{"date-parts":[[2022,2,13]],"date-time":"2022-02-13T16:54:02Z","timestamp":1644771242000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Effects of multimorbidity on incident COVID\u201019 events and its interplay with COVID\u201019 event status on subsequent incident myocardial infarction (MI)"],"prefix":"10.1111","volume":"52","author":[{"given":"Gregory Y. H.","family":"Lip","sequence":"first","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool and Liverpool Heart &amp; Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5336-6941","authenticated-orcid":false,"given":"Ash","family":"Genaidy","sequence":"additional","affiliation":[{"name":"Anthem Inc  Indianapolis Indiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George","family":"Tran","sequence":"additional","affiliation":[{"name":"IngenioRX  Indianapolis Indiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia","family":"Marroquin","sequence":"additional","affiliation":[{"name":"Anthem Inc  Indianapolis Indiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cara","family":"Estes","sequence":"additional","affiliation":[{"name":"Anthem Inc  Indianapolis Indiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sue","family":"Sloop","sequence":"additional","affiliation":[{"name":"Anthem Inc  Indianapolis Indiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,2,28]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehaa409"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMc2015630"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.120.050809"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMc2009020"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCINTERVENTIONS.120.009438"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clim.2020.108651"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/all.14657"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1183\/16000617.0139-2019"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00125-018-4796-7"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1177\/2235042X20961676"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12933-020-01140-2"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1003321"}],"container-title":["European Journal of Clinical Investigation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/eci.13760","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/eci.13760","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/eci.13760","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,24]],"date-time":"2023-08-24T10:05:06Z","timestamp":1692871506000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/eci.13760"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,28]]},"references-count":12,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,5]]}},"alternative-id":["10.1111\/eci.13760"],"URL":"https:\/\/doi.org\/10.1111\/eci.13760","archive":["Portico"],"relation":{},"ISSN":["0014-2972","1365-2362"],"issn-type":[{"type":"print","value":"0014-2972"},{"type":"electronic","value":"1365-2362"}],"subject":[],"published":{"date-parts":[[2022,2,28]]},"assertion":[{"value":"2021-11-16","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-02-04","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-02-28","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e13760"}}