RESUMO
Background: Chest computed tomography (CT) scans play an important role in the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to describe the quantitative CT parameters in COVID-19 patients according to disease severity and build decision trees for predicting respiratory outcomes using the quantitative CT parameters. Methods: Patients hospitalized for COVID-19 were classified based on the level of disease severity: (1) no pneumonia or hypoxia, (2) pneumonia without hypoxia, (3) hypoxia without respiratory failure, and (4) respiratory failure. High attenuation area (HAA) was defined as the quantified percentage of imaged lung volume with attenuation values between -600 and -250 Hounsfield units (HU). Decision tree models were built with clinical variables and initial laboratory values (model 1) and including quantitative CT parameters in addition to them (model 2). Results: A total of 387 patients were analyzed. The mean age was 57.8 years, and 50.3% were women. HAA increased as the severity of respiratory outcome increased. HAA showed a moderate correlation with lactate dehydrogenases (LDH) and C-reactive protein (CRP). In the decision tree of model 1, the CRP, fibrinogen, LDH, and gene Ct value were chosen as classifiers whereas LDH, HAA, fibrinogen, vaccination status, and neutrophil (%) were chosen in model 2. For predicting respiratory failure, the decision tree built with quantitative CT parameters showed a greater accuracy than the model without CT parameters. Conclusions: The decision tree could provide higher accuracy for predicting respiratory failure when quantitative CT parameters were considered in addition to clinical characteristics, PCR Ct value, and blood biomarkers.
RESUMO
BACKGROUND: There have been various efforts to identify less costly but still accurate methods for monitoring the response to HIV treatment. We evaluated a pooling method to determine if this could improve screening efficiency and reduce costs while maintaining accuracy in Seoul, South Korea. METHODS: We conducted the first prospective study of pooled nucleic acid testing (NAT) using a 5 minipool + algorithm strategy versus individual viral load testing for patients receiving antiretroviral therapy (ART) between November 2011 and August 2012 at an urban hospital in Seoul, South Korea. The viral load assay used has a lower level of detection of 20 HIV RNA copies/ml, and the cost per assay is US$ 136. The 5 minipool +algorithm strategy was applied and 43 pooled samples were evaluated. The relative efficiency and accuracy of the pooled NAT were compared with those of individual testing. RESULTS: Using the individual viral load assay, 15 of 215 (7%) plasma samples had more than 200 HIV RNA copies/ml. The pooled NAT using the 5 minipool + algorithm strategy was applied to 43 pooled samples; 111 tests were needed to test all samples when virologic failure was defined at HIV RNA ≥ 200 copies/ml. Therefore, 104 tests were saved over individual testing, with a relative efficiency of 0.48. When evaluating costs, a total of US$ 14,144 was saved for 215 individual samples during 10 months. The negative predictive value was 99.5% for all samples with HIV RNA ≥ 200 copies/ml. CONCLUSIONS: The pooled NAT with 5 minipool + algorithm strategy seems to be a very promising approach to effectively monitor patients receiving ART and to save resources.