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Jan 30, 2024Article Details
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Main Article Content
Risk stratification of hospital admissions for COVID-19 pneumonia by chest radiographic scoring in a Johannesburg tertiary hospital
Abstract
Background. Chest radiographic scoring systems for COVID-19 pneumonia have been developed. However, little is published on the utility of these scoring systems in low- and middle-income countries.
Objectives. To perform risk stratification of COVID-19 pneumonia in Johannesburg, South Africa (SA), by comparing the Brixia score with clinical parameters, disease course and clinical outcomes. To assess inter-rater reliability and developing predictive models of the clinical outcome using the Brixia score and clinical parameters.
Methods. Retrospective investigation was conducted of adult participants with established COVID-19 pneumonia admitted at a tertiary institution from 1 May to 30 June 2020. Two radiologists, blinded to clinical data, assigned Brixia scores. Brixia scores were compared with clinical parameters, length of stay and clinical outcomes (discharge/death). Inter-rater agreement was determined. Multivariable logistic regression extracted variables predictive of in-hospital demise.
Results. The cohort consisted of 263 patients, 51% male, with a median age of 47 years (interquartile range (IQR) = 20; 95% confidence interval (CI) 46.5 - 49.9). Hypertension (38.4%), diabetes (25.1%), obesity (19.4%) and HIV (15.6%) were the most common comorbidities. The median length of stay for 258 patients was 7.5 days (IQR = 7; 95% CI 8.2 - 9.7) and 6.5 days (IQR = 8; 95% CI 6.5 - 12.5) for intensive care unit stay. Fifty (19%) patients died, with a median age of 55 years (IQR = 23; 95% CI 50.5 - 58.7) compared with survivors, of median age 46 years (IQR = 20; 95% CI 45 - 48.6) (p=0.01). The presence of one or more comorbidities resulted in a higher death rate (23% v. 9.2%; p=0.01) than without comorbidities. The median Brixia score for the deceased was higher (14.5) than for the discharged patients (9.0) (p<0.001). Inter-rater agreement for Brixia scores was good (intraclass correlation coefficient 0.77; 95% CI 0.6 - 0.85; p<0.001). A model combining Brixia score, age, male gender and obesity (sensitivity 84%; specificity 63%) as well as a model with Brixia score and C-reactive protein (CRP) count (sensitivity 81%; specificity 63%) conferred the highest risk for in-hospital mortality.
Conclusion. We have demonstrated the utility of the Brixia scoring system in a middle-income country setting and developed the first SA risk stratification models incorporating comorbidities and a serological marker. When used in conjunction with age, male gender, obesity and CRP, the Brixia scoring system is a promising and reliable risk stratification tool. This may help inform the clinical decision pathway in resource-limited settings like ours during future waves of COVID-19.
