Integrated Hematological, Biochemical and Radiological Markers Associated with Disease Severity and Mortality in Patients with Acute Respiratory Diseases: A Cross-Sectional Study

Abstract

Background: Early recognition of deterioration in acute respiratory disease requires rapidly available and biologically interpretable information. This study evaluated hematological and biochemical markers, together with structured chest computed tomography (CT) status, in relation to disease severity and mortality.
Methods: A secondary analytical cross-sectional analysis used the iCTCF resource. Severity analysis included 894 laboratory-confirmed COVID-19 pneumonia cases (620 mild/regular and 274 severe/critical), while mortality analysis included 719 patients with known outcomes (662 cured and 57 deceased). Group differences were assessed using nonparametric or categorical tests with Benjamini-Hochberg correction. Biomarker-specific logistic models adjusted for age, sex, underlying disease and hospital. Repeated five-fold cross-validation evaluated clinical, hematological, biochemical and integrated logistic models.
Results: Severe/critical cases were older, more often male and more frequently had underlying disease. Higher neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), lactate dehydrogenase (LDH), blood urea nitrogen and interleukin-6, together with lower lymphocyte count and albumin, characterized worse outcomes. Mortality associations were strongest for LDH (OR 3.76 per 1-SD increase; 95% CI 2.29-6.17), CRP (OR 3.33; 95% CI 1.46-7.62) and NLR (OR 2.85; 95% CI 2.11-3.85). Mean cross-validated ROC-AUC increased from 0.743 to 0.802 for severe/critical disease and from 0.819 to 0.888 for mortality when moving from clinical-only to integrated models.
Conclusion: Multidomain biomarker information improved discrimination beyond clinical variables alone. NLR, LDH, lymphocyte count and albumin were particularly informative. The structured CT variable should be interpreted as radiological evidence status rather than a quantitative CT severity score, and external validation is required before clinical implementation.