Differentiating Multisystem Inflammatory Syndrome in Children (MIS-C) from Acute COVID-19 Using Biomarkers: Toward a Practical Clinical Scoring Model

Background/Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)infection in children presents with a heterogeneous clinical spectrum, whereasmultisystem inflammatory syndrome in children (MIS-C) is a distinct immunologicalentity characterized by a hyperinflammatory phenotype and a distinct biologicalarchitecture. Identifying routine biomarkers with early discriminatory utility is essentialfor rapid differentiation between MIS-C and coronavirus disease 2019 (COVID-19).Methods: We conducted a retrospective comparative study of 144 pediatric patients withCOVID-19 or MIS-C admitted to a single specialized medical center. The analysesintegrated classical statistical methods, Benjamini–Hochberg false discovery ratecorrection (FDR), penalized regression models, and machine learning algorithms toidentify biomarkers with discriminative value, using only routine laboratory tests.Results: MIS-C was associated with an intense inflammatory profile, characterized byincreases in C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and plateletto-lymphocyte ratio (PLR), lymphopenia, and selective electrolyte disturbances,highlighting a coherent biological architecture. In contrast, COVID-19 showed limitedassociations with traditional inflammatory markers. Predictive models identified a stablecore of biomarkers with excellent performance in Random Forest analysis (area under thecurve, AUC = 0.95), and reproducible thresholds (CRP ~3.7 mg/dL, NLR ~3.3, PLR ~376;potassium ~4.2 mmol/L). These findings were independently confirmed using penalizedRidge regression, where the reduced model achieved superior discrimination comparedto the full 13-variable model (AUC = 0.93 vs. 0.89) and maintained stable performanceunder internal cross-validation, reinforcing the clinical relevance of this compactbiomarker panel. Conclusions: MIS-C is clearly distinguished from COVID-19 by aspecific and reproducible immunological signature. The identified biomarkers mayrepresent a potential foundation for the development of simple clinical algorithms forpediatric triage and risk stratification, opening the prospect of a simplified scoring toolapplicable in emergency settings.