Time-of-Day-Associated Variation in Serum CO2 Patient-Result Distribution and Its Impact on PBRTQC Performance

Background: Patient-based real-time quality control (PBRTQC) is now widely used in clinical labs, yet the impact of time-dependent variation on its performance remains understudied, particularly with regard to serum carbon dioxide (CO2). This study explores how time-of-day-associated variation in the serum CO2 patient-result distribution affects PBRTQC outcomes and clinical acidosis classification, and an optimization strategy is evaluated. Methods: We analyzed 168,957 serum CO2 results collected over one year (2025) using three biochemical analyzers. Moving average-based PBRTQC was compared between peak (10:00–13:00) and off-peak periods, using either conventional unified limits or time-stratified separate limits. Results: Serum CO2 patient-result distribution shifted significantly toward higher values during the peak period (23.6 vs. 23.0 mmol/L, p < 0.001). A unified control strategy led to a marked rise in false-positive rates (0.955% vs. 0.062%). In a simulated category-transition analysis, 92 of 1212 samples (7.59%) were reclassified, of which 88 were acidosis-to-normal shifts. The time-stratified model reduced peak false positives to 0.069% while maintaining efficient detection of error. Conclusions: Time-of-day-associated variation in the distribution of patients’ serum CO2 impairs PBRTQC specificity during peak hours. Time-stratified control limits reduce false-positive rates while maintaining error detection, offering a practical solution for reliable serum CO2 monitoring. These findings should be interpreted as descriptive, given the cross-sectional design and the potential influence of patient case mix.