Descriptive Analysis of Chest Computed Tomography Scan in Coronavirus Disease 2019 Pneumonia: Correlation with Reverse Transcription-polymerase Chain Reaction and Clinical Features
Keywords:Computed tomography scan, Coronavirus disease 2019, Reverse transcription-polymerase chain reaction; Sensitivity, Specificity
BACKGROUND: Reverse transcriptase-polymerase chain reaction (RT-PCR) is the primary diagnostic tool to confirm coronavirus disease 2019 (COVID-2019) due to its high specificity. However, it has relatively low sensitivity and time consuming. In contrast, chest computed tomography (CT) has high sensitivity and achieves quick results. It may, therefore, play a critical role in screening and diagnosing COVID-19. A cross-sectional study was done in 212 patients with confirmed cases and patients under surveillance for COVID-19 tested for RT-PCR and chest CT scan. Statistical analysis was performed using SPSS Version 23 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA).
AIM: We aim to investigate the diagnostic value of chest CT in correlation to RT-PCR in Indonesia.
METHODS: A cross-sectional study was done in 212 patients with confirmed cases and patients under surveillance for COVID-19 tested for RT-PCR and chest CT scan. Statistical analysis was performed using SPSS Version 23 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA).
RESULTS: From a total of 212 patients, 92% of them were diagnosed as confirmed cases of COVID-19. It was found that the sensitivity of CT scan for COVID-19 patients was 72.3% (65.5% and 78.5%) with positive predictive value (PPV) of 93.9% (90.9% and 96.0%) and the sensitivity and PPV improve in symptomatic patients. Typical chest CT scan lesions were 8.0 times which were more likely (3.9–16.4; p <0.001) to be detected in symptomatic patients while patients with severe CT scan findings were 4.4 times more likely (3.0–6.5; p <0.001) to be admitted to the intensive care unit.CONCLUSION: A high PPV suggests that a chest CT scan can detect COVID-19 lesions, but the absence of the lesions would not exclude the disease’s presence.
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Copyright (c) 2020 Rusli Muljadi, Mira Yuniarti, Ricardo Tan, Teodorus Alfons Pratama, Ignatius Bima Prasetya, Allen Widysanto, Gilbert Sterling Octavius (Author)
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