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This retrospective cohort study was conducted using Patient Administration System Admissions and Discharges data. The\u00a0International Classification of Diseases 10th edition (ICD-10) diagnosis codes were used to identify common comorbidities and the outcome measure. Individuals with lymphoma (odds ratio [OR], 2.78;95% CI,1.64\u20134.74), metastatic cancer (OR, 2.17; 95% CI,1.25\u20133.77), solid tumour without metastasis (OR, 1.67; 95% CI,1.16\u20132.41), liver disease (OR: 2.50, 95% CI,1.53\u20134.07), congestive heart failure (OR, 1.69; 95% CI,1.32\u20132.15), chronic obstructive pulmonary disease (OR, 1.43; 95% CI,1.18\u20131.72), obesity (OR, 5.28; 95% CI,2.92\u20139.52), renal disease (OR, 1.81; 95% CI,1.51\u20132.19), and dementia (OR, 1.44; 95% CI,1.17\u20131.76) were at increased risk of COVID-19 mortality. Asthma was associated with a lower risk of death compared to non-asthma controls (OR, 0.60; 95% CI,0.42\u20130.86). Individuals with two (OR, 1.79; 95% CI, 1.47\u20132.20; <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001), and three or more comorbidities (OR, 1.80; 95% CI, 1.43\u20132.27; <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) were at increasingly higher risk of death when compared to those with no underlying conditions. Furthermore, multi morbidity patterns were analysed by identifying clusters of conditions in hospitalised COVID-19 patients using k-mode clustering, an unsupervised machine learning technique. Six patient clusters were identified, with recognisable co-occurrences of COVID-19 with different combinations of diseases, namely, cardiovascular (100%) and renal (15.6%) diseases in patient Cluster 1; mental and neurological disorders (100%) with metabolic and endocrine diseases (19.3%) in patient Cluster 2; respiratory (100%) and cardiovascular (15.0%) diseases in patient Cluster 3, cancer (5.9%) with genitourinary (9.0%) as well as metabolic and endocrine diseases (9.6%) in patient Cluster 4; metabolic and endocrine diseases (100%) and cardiovascular diseases (69.1%) in patient Cluster 5; mental and neurological disorders (100%) with cardiovascular diseases (100%) in patient Cluster 6. The highest mortality of 29.4% was reported in Cluster 6.<\/jats:p>","DOI":"10.1038\/s41598-022-20176-w","type":"journal-article","created":{"date-parts":[[2022,10,15]],"date-time":"2022-10-15T09:02:55Z","timestamp":1665824575000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19"],"prefix":"10.1038","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8417-1602","authenticated-orcid":false,"given":"Magda","family":"Bucholc","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Declan","family":"Bradley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Damien","family":"Bennett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lynsey","family":"Patterson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel","family":"Spiers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Gibson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hugo","family":"Van Woerden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony J.","family":"Bjourson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,15]]},"reference":[{"issue":"18","key":"20176_CR1","doi-asserted-by":"publisher","first-page":"1708","DOI":"10.1056\/NEJMoa2002032","volume":"382","author":"WJ Guan","year":"2020","unstructured":"Guan, W. 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