ArticleLaboratory medicine2021
Laboratory Predictors of COVID-19 Pneumonia in Patients with Mild to Moderate Symptoms.
Article in Laboratory medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Pneumonia and Pulmonary Thromboembolism Classification Using Electronic Health Records.Diagnostics (Basel, Switzerland) · 2022Article
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8 authors.
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Abstract
objectiveThis research aims to develop a laboratory model that can accurately distinguish pneumonia from nonpneumonia in patients with COVID-19 and to identify potential protective factors against lung infection.
methodsWe recruited 50 patients diagnosed with COVID-19 infection with or without pneumonia. We selected candidate predictors through group comparison and punitive least absolute shrinkage and selection operator (LASSO) analysis. A stepwise logistic regression model was used to distinguish patients with and without pneumonia. Finally, we used a decision-tree method and randomly selected 50% of the patients 1000 times from the same specimen to verify the effectiveness of the model.
resultsWe found that the percentage of eosinophils, a high-fluorescence-reticulocyte ratio, and creatinine had better discriminatory power than other factors. Age and underlying diseases were not significant for discrimination. The model correctly discriminated 77.1% of patients. In the final validation step, we observed that the model had an overall predictive rate of 81.3%.
conclusionWe developed a laboratory model for COVID-19 pneumonia in patients with mild to moderate symptoms. In the clinical setting, the model will be able to predict and differentiate pneumonia vs nonpneumonia before any lung computed tomography findings. In addition, the percentage of eosinophils, a high-fluorescence-reticulocyte ratio, and creatinine were considered protective factors against lung infection in patients without pneumonia.
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