{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:45:06Z","timestamp":1760489106499,"version":"3.41.2"},"reference-count":22,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"15","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Rates, causes, and predictors of readmission in patients with ST\u2010segment\u2013elevation myocardial infarction (STEMI) during COVID\u201019 pandemic are unknown.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results<\/jats:title>\n            <jats:p xml:lang=\"en\">\n              All hospitalizations for STEMI were selected from the US Nationwide Readmissions Database 2020 and were stratified by the presence of COVID\u201019. Primary outcome was 30\u2010day readmission. Multivariable hierarchical generalized logistic regression analysis was performed to compare 30\u2010day readmission between patients with STEMI with and without COVID\u201019 and to identify the predictors of 30\u2010day readmissions in patients with STEMI and COVID\u201019. The rate of 30\u2010day all\u2010cause readmission was 11.4% in patients with STEMI who had COVID\u201019 and 10.6% in those without COVID\u201019, with the adjusted odds ratio (OR) not being significantly different between the two groups (OR, 0.88 [95% CI, 0.73\u20131.07],\n              <jats:italic>P<\/jats:italic>\n              =0.200). Of all 30\u2010day readmissions in patients with STEMI and COVID\u201019, 41% were for cardiac causes. Among the cardiac causes, 56% were secondary to acute coronary syndrome, while among the noncardiac causes, infections were the most prevalent. Among the causes of 30\u2010day readmissions, infectious causes were significantly higher for patients with STEMI who had COVID\u201019 compared with those without COVID\u201019 (29.9% versus 11.3%,\n              <jats:italic>P<\/jats:italic>\n              =0.001). In a multivariable model, congestive heart failure, chronic kidney disease, low median household income, and length of stay \u22655\u2009days were found to be associated with an increased risk of 30\u2010day readmission.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p xml:lang=\"en\">Post\u2010STEMI, 30\u2010day readmission rates were similar between patients with and without COVID\u201019. Cardiac causes were the most common causes for 30\u2010day readmissions, and infections were the most prevalent noncardiac causes.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/jaha.123.029738","type":"journal-article","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T11:38:51Z","timestamp":1690285131000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":5,"title":["Causes and Predictors of 30\u2010Day Readmission in Patients With COVID\u201019 and ST\u2010Segment\u2013Elevation Myocardial Infarction in the United States: A Nationwide Readmission Database Analysis"],"prefix":"10.1161","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2712-0670","authenticated-orcid":false,"given":"Kunal N.","family":"Patel","sequence":"first","affiliation":[{"name":"Department of Internal Medicine Saint Peter\u2019s University Hospital New Brunswick NJ USA"},{"name":"Now with Department of Cardiovascular Medicine West Virginia University Medicine Heart and Vascular Institute Morgantown WV USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5389-5878","authenticated-orcid":false,"given":"Monil","family":"Majmundar","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine University of Kansas Medical Center Kansas City KS USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0276-0989","authenticated-orcid":false,"given":"Tasveer","family":"Khawaja","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine Case Western Reserve University, University Hospitals Cleveland OH USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5618-2750","authenticated-orcid":false,"given":"Rajkumar","family":"Doshi","sequence":"additional","affiliation":[{"name":"Department of Cardiology St. Joseph\u2019s University Medical Center Paterson NJ USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7627-1064","authenticated-orcid":false,"given":"Avleen","family":"Kaur","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine Maimonides Medical Center Brooklyn NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2136-4183","authenticated-orcid":false,"given":"Harsh","family":"Mehta","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine University of Kansas Medical Center Kansas City KS USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2440-9033","authenticated-orcid":false,"given":"Kamal","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine University of Kansas Medical Center Kansas City KS USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"276","reference":[{"doi-asserted-by":"publisher","key":"e_1_3_2_2_2","DOI":"10.1016\/j.cpcardiol.2022.101547"},{"doi-asserted-by":"publisher","key":"e_1_3_2_3_2","DOI":"10.3390\/jcm11113024"},{"volume-title":"Overview of the Nationwide Readmissions Database (NRD)","author":"Healthcare Cost and Utilization Project (HCUP)","unstructured":"Healthcare Cost and Utilization Project (HCUP) . 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Methods applying AHRQ quality indicators to Healthcare Cost and Utilization Project (HCUP) data for the 2022 National Healthcare Quality and Disparities Report (NHQDR). Agency for Healthcare Research and Quality; 2022. 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