| Autor: |
Abhishek Jagdishchander Arora, Ramamurthy S. Komatlapalli, Rajani Thakur |
| Rok vydání: |
2021 |
| Předmět: |
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| Popis: |
Context: Quantitative and semi-quantitative indicators of lung involvement in COVID-19 could help to stratify the patients and thus help in triaging and speeding up the entire workflow in hospitals as patients with higher severity scores require early therapeutic intervention and critical care.Objective: To calculate Computed Tomography (CT) severity score for COVID-19 infection based on lobar involvement of the disease and correlate the score with oxygen saturation levels (SpO2) of the patient and further predict oxygen therapy requirement.Settings and Design: Prospective study.Methods and Material: This is a prospective study of 154 proven novel coronavirus (SARS-CoV-2) infected (COVID-19) patients. SpO2 values of all the patients were obtained within 6 hours of scan. All the scans were reviewed and semi-quantitative CT score was calculated based on the extent of lobar involvement Statistical analysis used: Scatter plot correlation and ROC curve analysis were performed. Results: CT score and SpO2 values of patients were plotted in scatter plot chart and Pearson correlation co-efficient (r) was calculated, which was -0.836 suggesting a strong negative correlation. Forty-six patients were given oxygen therapy and they had oxygen saturation value ≤ 94% with CT score ranging from 10-22. ROC curve analysis was performed to determine and reach an optimum cut off value of 11 for oxygen therapy requirement with sensitivity and specificity of 95.83% and 95.58% respectively. Conclusions: CT score in COVID-19 patients has strong negative correlation with oxygen saturation and it definitely helped to predict the requirement of the oxygen therapy in our study. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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