Chest Radiograph Scoring Alone or Combined with Other Risk Scores for Predicting Outcomes in COVID-19

Abstract

Key Results1. Among a 787-patient cohort with confirmed COVID-19, three chest radiograph scores (BRIXIA, RALE, and percent opacification) all had good interrater reliability with intraclass correlations of 0.87, 0.86, and 0.72 respectively.2. Radiograph scores predicted intensive care unit (ICU) admission or death after COVID-19 diagnosis. A 50%-75% opacification (compared to 0%-25%) associated with a 2.2-fold increase in these outcomes among those eligible for ICU care after adjustment for clinical risk scoring. SummaryBRIXIA, RALE, and percent opacification produced reliable and reproducible COVID-19 chest radiograph severity scores that improved accuracy for predicting adverse outcomes when incorporated into ISARIC-4C mortality and NEWS2 clinical scoring systems. I n p r e s s ResultsAdmission chest radiographs of 50 patients (mean age, 74 years +/-16 [sd], 28 men) were scored by all 3 radiologists, with good inter-rater reliability for all scores (ICCs (95% CIs) of for RALE 0.87 (0.80, 0.92), BRIXIA 0.86 (0.76, 0.92), and percentage opacification 0.72 (0.48, 0.85)). Of 751 patients with chest radiograph, those with >75% opacification had a median time to ICU admission or death of just 1-2 days. Among 628 patients with data (median age 76 years (IQR 61 -84), and 344 were men), 50-75% opacification increased risk of ICU admission or death by twofold (1.6 -2.8), and over 75% opacification by 4 fold (3.4 -4.7), compared to a 0-25% opacification when adjusted for NEWS2 score. ConclusionBRIXIA, RALE, and percent opacification scores all reliably predicted adverse outcomes in SARS-CoV-2.

Brixia and qSOFA Scores, Coagulation Factors and Blood Values in Spring versus Autumn 2021 Infection in Pregnant Critical COVID-19 Patients: A Preliminary Study

“…We cannot confirm that, because our median admittance (A) Brixia score was over 11.3 in spring and over 8 in autumn patients; from there, it went higher to the Brixia H (highest) score. Balbi [ 43 ], d’Souza [ 44 ] and Au-Yong [ 45 ] correlated the Brixia A score with outcomes in COVID-19 patients. Setiawati [ 46 ] found that severe cases of COVID-19 pneumonia had a Brixia score over 6, Gatti [ 47 ] over 7 upon admission and Boari [ 48 ] over 8, but the first and last authors did not specify which Brixia score they used: A, H or E. Similarly, Hoang [ 49 ] and Gurtoo [ 50 ] also correlated Brixia score with the outcomes in COVID-19 patients but did not specify which Brixia score they used in calculations—either A, H or E score—or if there was more than one chest X-ray taken of each patient.…”

Visual classification of three computed tomography lung patterns to predict prognosis of COVID-19: a retrospective study

“…2 ). Further CT findings included consolidation, linear opacities, reversed halo sign, and crazy-paving sign [ 5 , 6 , 8 – 10 , 13 ]. The definitions of these CT findings were based on the uniform terms for thoracic imaging by the Fleishner society [ 16 ].…”

“…Numerous clinical and imaging markers of disease severity have been reported. Among imaging markers, computed tomography (CT) provides the most sensitive radiological technique for the diagnosis of COVID-19, revealing diffuse lung alterations, ranging from ground-glass opacity to consolidation [ 5 – 10 ]. In addition, different radiological lung patterns are manifested over the course of the disease.…”

“…In addition, different radiological lung patterns are manifested over the course of the disease. Research using quantitative methods to evaluate lung CT images to derive various image analysis scores has suggested the possibility of predicting the severity of the disease [ 10 – 14 ]. However, there are limited opportunities in clinical practice to use these quantitative image analysis approaches [ 11 , 12 , 14 ].…”

Chest Radiograph Severity Scores, Comorbidity Prevalence, and Outcomes of Patients with Coronavirus Disease Treated at the King Abdullah University Hospital in Jordan: A Retrospective Study

“…The severity of CXR helps to predict COVID-19 outcomes, especially with the presence of CXR reporting systems, such as Brixia, and Radiographic Assessment of Lung Edema (RALE), 23 which helped to predict the negative outcomes of the disease, reliably. In addition, using the CXR severity score may help in decision-making regarding the most suitable admission department.…”