Dynamic CD177/CD10 ratio for infection diagnosis and mortality risk stratification in critically ill patients: a...

Two crucial needs persist in delivering effective critical care: reliable differentiation of infectious vs non-infectious systemic inflammation and detection of impending sepsis before the occurrence of organ dysfunction. This prospective cohort study evaluates the clinical utility of the polymorphonuclear neutrophil (PMN) biomarker CD177/CD10 ratio to differentiate and monitor infections.

A total of 219 healthy volunteers and 145 patients were assigned to four clinically defined groups: healthy controls (HC), non-infectious inflammation (NI), non-septic infection (NS-I), and sepsis (S). Serial flow cytometric analysis of CD177 and CD10 expression in PMNs was conducted with longitudinal monitoring. Diagnostic efficacy was standardised against conventional biomarkers and organ dysfunction indices. A dynamic CD177/CD10 ratio-based subtyping system (rising/declining/stable pattern) was established for prognostic stratification.

The CD177/CD10 ratio exhibited superior diagnostic performance in infection identification. At a cut-off point (CFP) of 6.07, the area under the curve (AUC) value of the ratio to differentiate NS-I from S was 0.92, exceeding those of CRP (0.85) and PCT (0.85). Notably, this biomarker effectively differentiated NI (CFP = 0.67, AUC = 0.79) from NS-I (CFP = 0.98, AUC = 0.71). The dynamic CD177/CD10 ratio-based subtyping system showed robust prognostic efficacy: patients with the rising subtype exhibited a 7-day mortality rate of 62.5%, while those with decreasing and stable subtypes demonstrated survival rates of 85% and 92.59%, respectively.

The CD177/CD10 ratio can facilitate infection-specific differentiation and real-time therapeutic monitoring by quantifying the dynamic equilibrium between the extent of neutrophil activation and maturation. However, the CD177/CD10 ratio still requires validation through a multi-centre trial to confirm the generalisability of the established diagnostic and prognostic thresholds.

National Natural Science Foundation of China (No. U21A20370), Natural Science Foundation of Jiangsu Province (BK20240382), Science and Technology Innovation Project of Suzhou (SYW2024116).