• Yusuf Aydemir, Yasemin Gündüz, Mehmet Köroğlu, Oğuz Karabay, Hamad Dheir, Aysun Şengül, Selçuk Yaylacı, Havva Kocayiğit, Ali Fuat Erdem, Özlem Aydemir, Ertuğrul Güçlü, and Yusuf Yürümez.
• Department of Pulmonology, Faculty of Medicine, Sakarya University, Sakarya, Turkey
• Turk J Med Sci. 2021 Jun 28; 51 (3): 1012-1020.

Background/AimIt is very important for the efficient use of limited capacity and the success of treatment to predict patients who may need ICU with high mortality rate in the Covid-19 outbreak. In our study, it was aimed to investigate the value of the radiological involvement on initial CT in demonstrating the ICU transfer and mortality rate of patients.Materials And MethodsAll PCR-positive patients were included in the study, whose CT, PCR, and laboratory values were obtained simultaneously at the time of first admission. Patients were divided into 4 groups in terms of the extent of radiological lesions. These groups were compared in terms of intensive care transfer needs and Covid-related mortality rates.ResultsA total of 477 patients were included in the study. Ninety of them were group 0 (no lung involvement), 162 were group 1 (mild lesion), 89 were group 2 (moderate lesion), and 136 were group 3 (severe lung involvement). A significant relationship was found between the extensiveness of the radiological lesion on CT and admission to intensive care and mortality rate. As the initial radiological involvement amounts increased, the rate of ICU transfer and mortality increased. The mortality rates of the groups were 0%, 3%, 12.3%, and 12.5%, respectively, and the difference was significant (p < 0.001). Similarly, the ICU transfer rates of the groups were 2.2%, 5.6%, 13.5%, and 17.7%, respectively, and the difference was significant (p < 0.001).ConclusionIn conclusion, in our study, the strong relationship between the initial radiological extent assessment and the need for intensive care and mortality rates has been demonstrated, and we believe that our results will make a significant contribution to increase the success of the health system in predicting patients who may progress, helping clinicians and managing pandemics.This work is licensed under a Creative Commons Attribution 4.0 International License.

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