Background COVID-19 is a worldwide pandemic and has placed significant demand for acute and critical care services on hospitals in many countries. Objectives To determine the predictors of severe COVID-19 disease requiring admission to an ICU by comparing patients who were ICU admitted to non-ICU groups. Methods A cohort study was conducted for the laboratory-confirmed COVID-19 patients who were admitted to six Saudi Ministry of Health’s hospitals in Alahsa, between March 1, 2020, and July 30, 2020, by reviewing patient’s medical records retrospectively. Results This cohort included 1014 patients with an overall mean age of 47.2 ± 19.3 years and 582 (57%) were males. A total of 205 (20%) of the hospitalized patients were admitted to the ICU. Hypertension, diabetes and obesity were the most common comorbidities in all study patients (27.2, 19.9, and 9%, respectively). The most prevalent symptoms were cough (47.7%), shortness of breath (35.7%) and fever (34.3%). Compared with non-ICU group, ICU patients had older age ( p ≤ 0.0005) and comprised a higher proportion of the current smokers and had higher respiratory rates ( p ≤ 0.0005), and more percentage of body temperatures in the range of 37.3–38.0 °C ( p ≥ 0.0005); and had more comorbidities including diabetes ( p ≤ 0.0005), hypertension ( p ≥ 0.0005), obesity ( p = 0.048), and sickle cell disease ( p = 0.039). There were significant differences between the non-ICU and ICU groups for fever, shortness of breath, cough, fatigue, vomiting, dizziness; elevated white blood cells, neutrophils, alanine aminotransferase and alkaline aminotransferase, lactate dehydrogenase, and ferritin, and decreased hemoglobin; and proportion of abnormal bilateral chest CT images ( p < 0.05). Significant differences were also found for multiple treatments ( p < 0.05). ICU patients group had a much higher mortality rate than those with non-ICU admission ( p ≤ 0.0005). Conclusion Identifying key clinical characteristics of COVID-19 that predict ICU admission and high mortality can be useful for frontline healthcare providers in making the right clinical decision under time-sensitive and resource-constricted environment.
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