Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
15 10 2022
15 10 2022
Historique:
received:
27
10
2021
accepted:
09
09
2022
entrez:
15
10
2022
pubmed:
16
10
2022
medline:
19
10
2022
Statut:
epublish
Résumé
We investigated the association between a wide range of comorbidities and COVID-19 in-hospital mortality and assessed the influence of multi morbidity on the risk of COVID-19-related death using a large, regional cohort of 6036 hospitalized patients. This retrospective cohort study was conducted using Patient Administration System Admissions and Discharges data. The International 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,1.64-4.74), metastatic cancer (OR, 2.17; 95% CI,1.25-3.77), solid tumour without metastasis (OR, 1.67; 95% CI,1.16-2.41), liver disease (OR: 2.50, 95% CI,1.53-4.07), congestive heart failure (OR, 1.69; 95% CI,1.32-2.15), chronic obstructive pulmonary disease (OR, 1.43; 95% CI,1.18-1.72), obesity (OR, 5.28; 95% CI,2.92-9.52), renal disease (OR, 1.81; 95% CI,1.51-2.19), and dementia (OR, 1.44; 95% CI,1.17-1.76) 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,0.42-0.86). Individuals with two (OR, 1.79; 95% CI, 1.47-2.20; P < 0.001), and three or more comorbidities (OR, 1.80; 95% CI, 1.43-2.27; P < 0.001) 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.
Identifiants
pubmed: 36243878
doi: 10.1038/s41598-022-20176-w
pii: 10.1038/s41598-022-20176-w
pmc: PMC9568958
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
17313Informations de copyright
© 2022. The Author(s).
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