Acta Medica International (Jan 2021)
Correlation of chest radiographic findings and coagulation abnormality with disease severity in COVID-19 positive patients
Abstract
Introduction: The pandemic of coronavirus disease 19 (COVID-19) has engulfed most of the world and has constrained already overburdened health care systems, especially in developing countries. There is an urgent need of a rapid investigation to assess disease severity in suspected patients and the baseline chest radiograph may serve as a triage tool. The aim is to correlate chest radiographic findings and coagulation abnormality with disease severity in COVID-19 positive patients. Materials and Methods: This was a retrospective observational study which comprised 100 reverse transcription-polymerase chain reaction positive COVID-19 cases which were clinically stratified into three groups based on clinical parameters. Baseline chest radiograph and serum D-dimer levels at the time of admission for all the patients were reviewed. A radiographic severity score (Radiographic Assessment of Lung Edema [RALE]) was determined for all four quadrants of both lungs. The scores of each quadrant were added to yield the final severity score. Results: Baseline chest radiograph was abnormal in 75% of patients, whereas 25% of patients had normal chest radiograph. Most frequent radiographic abnormality was ground-glass opacity (GGO) (n = 31, 41.3%) followed by lung consolidation (n = 19, 25.3%), while 7 patients (9.3%) had both GGO and consolidation. The most common pattern of disease distribution was bilateral 34 (57.7%) and peripheral in 58 (69%). The optimal cut-off RALE score for identifying symptomatic patients was ≥3 (area under the curve [AUC] 0.760) and for identifying severe cases was ≥7 (AUC 0.870). Similarly, the optimal cut-off D-Dimer value for identifying symptomatic patients was ≥567 ng/ml (AUC 0.836) and for diagnosing severe disease was ≥1200 ng/ml (AUC 0.99). Conclusions: Radiographic RALE score and elevated serum D-Dimer levels correlate strongly with disease severity in COVID-19 patients and can be utilized for early identification of high-risk cases which can ultimately reduce mortality and morbidity.
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