Abstract
Background: Chest High-Resolution Computed Tomography (HRCT) is mandatory for patients with confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and a high Respiratory Rate (RR) because sublobar consolidation is the likely pathological pattern in addition to Ground Glass Opacities (GGOs).
Objective: The present study determined the correlation between the percentage extent of typical pulmonary lesions on HRCT, as a representation of severity, and the RR and peripheral oxygen saturation level (SpO2), as measured through pulse oximetry, in patients with Reverse Transcriptase Polymerase Chain Reaction (RT-PCR)-confirmed primary (noncomplicated) SARS-CoV-2 pneumonia.
Methods: The present retrospective study was conducted in 332 adult patients who presented with dyspnea and hypoxemia and were admitted to Prince Mohammed bin Abdulaziz Hospital, Riyadh, Saudi Arabia between May 15, 2020 and December 15, 2020. All the patients underwent chest HRCT. Of the total, 198 patients with primary noncomplicated SARS-CoV-2 pneumonia were finally selected based on the typical chest HRCT patterns. The main CT patterns, GGO and sublobar consolidation, were individually quantified as a percentage of the total pulmonary involvement through algebraic summation of the percentage of the 19 pulmonary segments affected. Additionally, the statistical correlation strength between the total percentage pulmonary involvement and the age, initial RR, and percentage SpO2 of the patients was determined.
Results: The mean ± Standard Deviation (SD) age of the 198 patients was 48.9 ± 11.4 years. GGO magnitude alone exhibited a significant weak positive correlation with patients’ age (r = 0.2; p = 0.04). Sublobar consolidation extent exhibited a relatively stronger positive correlation with RR than GGO magnitude (r = 0.23; p = 0.002). A relatively stronger negative correlation was observed between the GGO extent and SpO2 (r = - 0.38; p = 0.002) than that between sublobar consolidation and SpO2 (r = - 0.2; p = 0.04). An increase in the correlation strength was demonstrated with increased case segregation with GGO extent (r = - 0.34; p = 0.01).
Conclusion: The correlation between the magnitudes of typical pulmonary lesion patterns, particularly GGO, which exhibited an incremental correlation pattern on chest HRCT, and the SpO2 percentage, may allow the establishment of an artificial intelligence program to differentiate primary SARS-CoV-2 pneumonia from other complications and associated pathology influencing SpO2.
Keywords: Artificial intelligence, chest high-resolution computed tomography, ground glass opacities, primary SARS-CoV-2 pneumonia, respiratory rate, HRCT.
Graphical Abstract
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