Predictors of Mortality in COVID-19 Patients in Southern California - Retrospective Multicenter Study
| Autor: | Adrian Torbela, Rakesh K. Gupta, Mahendra Aseri, Chukwuemeka A. Umeh, Harpreet Kaur, Sumanta Chaudhuri, Stella Maguwudze, Shadi Kazourra, Rahul Gupta, Shipra Saigal |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Statin Multivariate analysis Pulmonology medicine.drug_class Infectious Disease remdesivir Disease law.invention law Internal medicine Diabetes mellitus medicine Internal Medicine lactate dehydrogenase (ldh) creatine phosphokinase (cpk) california business.industry General Engineering Retrospective cohort study intensive care unit (icu) medicine.disease Intensive care unit mortality covid-19 Cohort business Body mass index |
| Zdroj: | Cureus |
| ISSN: | 2168-8184 |
| Popis: | Introduction The majority of patients infected with coronavirus disease 2019 (COVID-19) recover from the illness after suffering mild to moderate symptoms, while approximately 20% progress to severe or critical disease, which may result in death. Understanding the predictors of severe disease and mortality in COVID-19 patients will help to risk stratify patients and improve clinical decision making. US data to inform this understanding are, however, scarce. We studied predictors of COVID-19 mortality in a cohort of 1,116 hospitalized patients in Southern California in the United States. Methods We conducted a retrospective cohort study of COVID-19 patients admitted at two hospitals in Southern California United States between March 2020 and March 2021. Bivariate and multivariate analyses of the relationship between mortality and other variables such as demographics, comorbidities, and laboratory values were performed, with a p-value of 0.05 considered as significant. Results The analysis involved 1,116 COVID-19 patients, of which 51.5% were males and 48.5% were females. Of the 1,116 patients, 81.6% were whites, 7.2% were blacks, and 11.2% were other races. After adjusting for co-variables, age (p |
| Databáze: | OpenAIRE |
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