A Non-Faradaic Impedimetric Label-Free Immunosensor Integrated with PCCODE Logic for Stratified Monitoring of Post-COVID Conditions

The COVID-19 pandemic has presented significant challenges for the effectiveness of existing diagnostic tools in detecting and monitoring infections. Currently, there is an increased emphasis on the potential challenges faced by individuals during their postrecovery phase. The impact of post-COVID conditions (PCC) has substantially influenced perspectives on disease management, fostering a positive trend toward personal healthcare. Here, we report a ZnO-modified, non-Faradaic impedimetric biosensor for the rapid detection of TRAIL and D-dimer across clinically relevant ranges. The dual-analyte platform demonstrated great sensitivity (LOD: 3.4 pg/mL for TRAIL, 8.9 ng/mL for D-dimer), with high specificity in human plasma. Optimized surface chemistry and impedance analysis enabled reliable signal acquisition from 5 μL samples in 5 min. Beyond detection, we introduce the PCCODE (Post-COVID Co-dysregulation Evaluator) threshold-based classifier model using quantified concentration output values-TRAIL <50 pg/mL, D-dimer >1000 ng/mL-to encode biomarker signals in four binary states. This logic-driven system was constructed using exogenously spiked plasma samples and validated through signal-mapped heatmaps, allowing stratification of healthy, inflammation, immune dysregulation, and post-COVID categories. Together, the biosensor and classifier framework enable real-time, mechanism-informed stratification of PCC, marking a significant advance toward point-of-care diagnostics.