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Research Article | Volume 13 Issue:2 (, 2023) | Pages 1747 - 1753
Mean CT Severity Score – an effective parameter to predict development of post-covid syndrome
Under a Creative Commons license
Open Access
DOI : 10.5083/ejcm
Published
July 3, 2023
Abstract

Context: A significant proportion of survivors from COVID-19 infection have shown residual pulmonary abnormalities including lung fibrosis which if not managed at appropriate time can cause disastrous effects, even requiring lung transplantation in few patients.  Aims: To evaluate the usefulness of Mean CT Severity Score of initial scans done during acute illness in predicting Post-COVID Syndrome. Settings and Design:  A prospective observational study was conducted in a tertiary care centre comprising of 2000 patients, among which 650 patients showed residual lung abnormalities. Methods and Material: HRCT Scan was performed to calculate Mean CT Severity Score during acute illness and after an interval period of 1 month, 3 months and 6 months respectively to detect residual lung abnormalities. Statistical analysis used: SPSS software used for calculation of mean and standard deviation. A chi-square test was used for the comparison of categorical variables. (P-value <0.05, significant) Results- At cut off score of 7 of Mean CT Severity Score calculated at initial scan, high sensitivity and specificity of Mean CT Severity Score was found in predicting Post Covid Syndrome. Moreover, the study found significant association between the lesions including ground-glass opacities, reticular opacities and consolidation separately with high initial CTSS score with their persistence in post COVID follow up scan. (P value- <0.001) Conclusion – Mean CT Severity Score can act as an effective parameter in predicting long term pulmonary outcome of COVID-19 illness and can guide towards appropriate management of the patient’s allowing intervention at an early stage in post-COVID syndrome.

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