Baseline demographic, clinical and laboratory risk factors for predicting admission to intensive care unit in patients diagnosed with COVID-19 in the emergency department

Abstract

Aim: The COVID-19 pandemic has caused very significant morbidity and mortality throughout the world. Predicting the need for intensive care in these patients is important in terms of proper planning of health services and developing cost-effective management strategies. In this study, we sough to investigate the predictability of whether patients with COVID-19 would need intensive care by looking at some clinical, hematological and biochemical parameters. Material and Method: All of the patients who applied to the adult emergency department of our hospital with the diagnosis of COVID-19 and were hospitalized were included in the study. The age, physical examination findings, comorbidities, and first laboratory parameters of the patients admitted to our hospital between March 2020 and June 2020 were retrospectively analyzed. A multivarible logistic regression model was constructed to determine the significant predictors of admission to ICU. Results: A total of 1,005 patients were included in the study. Logistic regression analyses revealed that age (OR: 1.094, p<0.001), chronic renal failure (OR: 4.735, p=0.036), cancer diagnosis (OR: 3.957, p=0.021), higher levels of lactate dehydrogenase (OR: 1.006, p<0.001), and ferritin (OR: 1.001, p=0.001), and lower levels of lymphocyte count (OR: 0.879, p=0.021) were the independent risk factors in predicting the intensive care unit admission of the patients Conclusion: Age, chronic renal failure, cancer, higher levels of LDH and ferritin, and lower levels of lymphocyte are found to be independent risk factors in predicting intensive care admission for patients admitted to the emergency department with the diagnosis of COVID-19.

Keywords

• age
• cancer
• chronic renal failure
• covid-19
• emergency department
• ferritin
• intensive care
• LDH
• lymphocyte

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