ABSTRACT
Severe acute respiratory syndrome-associated coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), which has been considered a pandemic by the World Health Organization (WHO). Clinical manifestations of COVID-19 disease may differ, most cases are mild, but a significant minority of patients may develop moderate to severe respiratory symptoms, with the most severe cases requiring intensive care and/or mechanical ventilatory support. In this study, we aimed to identify validity of our modified scoring system for foreseeing the approach to the COVID-19 patient and the disease, the treatment plan, the severity of morbidity and even the risk of mortality from the clinician's point of view. In this single center study, we examined the patients hospitalized with the diagnosis of COVID-19 between 01/04/2020 and 01/06/2020, of the 228 patients who were between 20 and 90 years of age, and whose polymerase chain reaction (PCR) tests of nasal and pharyngeal swab samples were positive. We evaulated 228 (92 male and 136 female) PCR (+) patients. Univariate analysis showed that advanced age (p < 0.001), hemoglobin (p < 0.001), troponin-I (p < 0.001), C-reactive protein (CRP) (p < 0.001), fibrinogen (p < 0.001), HT (p = 0.01), CAD (p = 0.001), DM (p < 0.001), history of malignancy (p = 0.008), along with m-sPESI scores (p < 0.001) were significantly higher in patients that needed intensive care due to COVID-19 infection. In the multivariable logistic regression analysis, only the m-sPESI score higher than ≥ 2 was found to be highly significant in terms of indicating the need for ICU admission (AUC 0.948; 84.6% sensitivity and 94.6% specificity) (p < 0.001). With an increasing number of hospitalized patients, healthcare providers are confronting a deluge of lab results in the process of caring for COVID-19 patients. It is imperative to identify risk factors for mortality and morbidity development. The modified sPESI scoring system, which we put forward, is successful in predicting the course of the disease at the presentation of the patient with COVID-19 disease and predicting the need for intensive care with high specificity and sensitivity, can detect the need for intensive care with high specificity and sensitivity.