Values of Intensive Care Scores in Predicting Morbidity and Mortality in Patients Treated for COVID-19 Pneumonia

Year 2022, Volume: 39 Issue: 4, 1175 - 1183, 29.10.2022

Hale Kefeli Çelik , Zahide Doğanay , Ramazan Burak Ferli

Abstract

Some of the patients with COVID-19 pneumonia are followed up in intensive care units (ICU).This study aims to determine the success of intensive care scores used in patients followed up in the ICU with the diagnosis of COVID-19 pneumonia in predicting morbidity and mortality. This retrospective study included patients who were treated with the diagnosis of COVID-19 pneumonia in the ICUs of … Training and Research Hospital. The demographic characteristics, vital signs, arterial blood gas values, radiological imaging, and laboratory data of the patients were used by using the hospital database and patient files. Group I patients were determined as alive patients and Group II as dead patients. A total of 75 patients were included in the study, of which 34 (45.3%) were female and 41 (54.7%) were male.The median length of intensive care stay was 8 (5-15) days in Group I patients and 5 (2-8) days in Group II patients, which was found to be higher in alive patients (p=0.004).Radiological involvement was present in 93.3% (n=70) of the patients included in the study and involvement was seen in both lungs in 77.3% (n=58). Complications were observed in 54.7% (n=41) of the patients included in the study whereas the incidence of complications was 20% in Group I and 72% in Group II, which was statistically significant (p<0.001).APACHE II, PSI, SOFA, qSOFA, SMART-COP, CURB65, A-DROP and NEWS2 scores were statistically significantly higher in patients who died whereas APACHE II, SOFA, qSOFA, and SMART-COP scores were more successful in predicting morbidity. It is important to predict the mortality risk early in patients with COVID-19 pneumonia followed up in the intensive care unit.Among the scoring systems, APACHE II, PSI, SOFA, qSOFA, SMART-COP, CURB65, A-DROP, and NEWS2 can be used safely to predict mortality.

Keywords

COVID-19, intensive care unit, mortality, pneumonia, score

References

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