New Chest X-Ray Scoring System Can Be Used to Predict Outcome of COVID-19 Patients

Three cardiothoracic radiologists and three diagnostic radiology residents then independently scored their admission CXRs, based on extent and severity of COVID-19 pneumonia. Demographic variables, clinical characteristics, and admission laboratory values were collected, while interrater reliability among attending, resident, and the combined group of graders was assessed.

Of the 240 patients (142 males, 98 females; median age, 65 years) who met the inclusion criteria, interrater reliability for CXR scoring was high (mean, 0.686) among the attending, residents, and combination of graders. Furthermore, there was no difference in outcomes across gender, race, ethnicity, or those with either a history of lung cancer or chronic obstructive pulmonary disease. Although CXR severity proved an independent predictor of death (p < 0.001), CXR severity was a non-independent predictor of CRRT (p = 0.007) and intubation (p < 0.001) but not extracorporeal membrane oxygenation.

"We developed an accurate and reliable tool for classifying COVID-19 severity, which can be used both at the attending chest radiologist and junior resident level. This study identifies the laboratory, clinical and radiographic data that predict important patient outcomes such as death, intubation, and the need for chronic renal replacement therapy (CRRT)," wrote first author Russell Reeves of Thomas Jefferson University in Philadelphia, PA.

"These findings are supported by prior work, validating the utility of CXR for patient prognostication, while adding new insight into COVID-19 infection during the initial presentation," the authors of the ARRS Annual Meeting E-Poster concluded.

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