Evaluation of MSCT severity scoring for prediction of mortality among patients with COVID-19

Abstract

Abstract Background Lung CT imaging may reveal COVID-19 abnormalities earlier than RTPCR. CT may be more sensitive than RT-PCR for diagnosing COVID-19-related pneumonia. Aim This study assesses the accuracy of multi-slice computed tomography (MSCT) grading in predicting COVID-19 mortality. Methods COVID-19 RT-PCR. For severity scores, all patients’ clinical examinations, history, and chest MSCT data were collected. Results According to the chest MSCT score, 102 (51.5%), 70 (35%), and 28 (14%) patients had mild, moderate, and severe illness. Out of the patients, 62 (31%) died, and 69% survived. Patients with severe MSCT scores showed a considerably greater mean age than other groups (P < 0.001). Moreover, this group had a considerably higher mean BMI (P < 0.001), and a majority (57.1%) were obese (P < 0.001). Compared to the mild group, the moderate and severe groups had significantly increased rates of diabetes, hypertension, and liver disease (P < 0.001). The moderate group had a greater rate of no comorbidities (P < 0.001). A severe MSCT score was linked to increased leucocytes, C-reactive protein, ESR, ferritin, d-dimer, HbA1c, and fasting blood sugar, as well as decreased mean lymphocytes (P < 0.001). Severe MSCT scores were linked to increased ICU admissions (P < 0.001) and increased demand for advanced mechanical ventilation and oxygen assistance (P < 0.001). A severe MSCT score was associated with the highest death rate, followed by a moderate MSCT score. Low mortality rates were observed in mild MSCT-scored patients (P < 0.001). Conclusion MSC T score severity is a reliable and noninvasive way to predict COVID-19 mortality