The Correlation Between Chest CT Severity and Clinical Data Of Patients with COVID-19
DOI:
https://doi.org/10.54361/LJMR.19.2.21Keywords:
COVID-19, Chest CT Severity, RT-PCR, ICU Admission, Chronic IllnessAbstract
Purpose: The study aims to examine the correlation between clinical laboratory data, including RT-PCR results, and the severity of chest CT findings in COVID-19 patients. Early detection of severe cases can help reduce ICU admissions and improve patient outcomes. Data were collected from the laboratory at Tobruk Medical Center (TMC) and non-contrast high-resolution chest CT scans by a professional team. Materials and Methods: A retrospective analysis was conducted on 94 COVID-19 patients treated at The Medical Center of Tobruk in 2021. The study population included 58 males and 35 females, covering both young and elderly patients with and without chronic illnesses. Epidemiological, demographic, clinical, and outcome data—including ICU admissions and mortality—were analyzed using Microsoft Excel 2010. RT-PCR test results were obtained from the accredited Department of Laboratory Medicine at Tobruk Medical Center, which is responsible for PCR testing in the Tobruk region. The case definition followed the World Health Organization (WHO) interim guidance. Results: The results showed that 58% of the patients were male, while 35% were female. Patients were divided into two age groups: those below 40 years and those above 40 years. Among them, 4% of females and 7% of males were under 40, while 9% of females and 54% of males were above 40. The study also analyzed the presence of chronic illnesses: 27 patients had hypertension (BP), 5 had both hypertension and diabetes (DM), 1 had cerebrovascular accident (CVA), 18 had diabetes only, and 40 had no chronic diseases. Conclusion: This study highlights the significant correlation between chest CT severity and clinical data, particularly in older patients and those with chronic illnesses. Males exhibited a higher severity rate. The findings emphasize the importance of integrating laboratory and imaging data for early detection, which can aid in reducing ICU admissions and improving patient management.
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Copyright (c) 2025 Nagwa. R. Bochwal , Huda M. Ibrahim , Wfa A. Nweh , Muhammad .Y.Alsawy, Ghanem .M. Jamal , Abdullh .A.Ali , Hamza. F. Atia , Fared .R. Fared (Author)
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