The use of biomarkers to predict maternal postpartum infection in a post-cesarean population

To evaluate whether specific maternal serum biomarkers, identified through a prior systematic review are associated with and predict subsequent surgical site infections (SSIs) after unplanned cesarean delivery (CD). Nested case-control study of participants in a multicenter RCT of adjunctive azithromycin for CD after labor or membrane rupture ≥ 4 hours. Serum was collected and frozen (-80oF) at delivery or within 24 hours of delivery and participants were followed for 6 weeks to identify SSIs (wound infection, endometritis or abdominal/pelvic abscess). Among participants in the RCT, we included 80: 40 cases selected from among 181 with SSIs; and 40 controls selected randomly from 1832 without SSIs. Exposures were four candidate inflammatory biomarkers: STREM-1, procalcitonin, TNF-alpha, IL-6, assayed using ELISA and Charge Coupled Device (CCD) technology. Mean concentration levels were compared between cases and controls and evaluated at p< 0.05 level. Receiver operator characteristics curves (ROC) were used to assess the predictive efficiency of biomarkers for the composite outcome. Cases had higher BMI (38.2 vs. 33.9 kg/m2) and were more likely to be Black (60% vs. 25%; p: 0.02) compared with controls. Among the 4 preselected biomarkers, mean levels of TNF alpha and IL-6 were significantly different between cases and controls (Table). TNF-alpha (AUC 0.964 [95% CI 0.929-0.999]) and IL6 (AUC 0.960 [95% CI 0.922-0.997) had outstanding predictive efficiency for SSIs individually as well as when combined (AUC 0.983 [0.964-< 1.000] Fig). IL-6 and TNF alpha in serum were significantly elevated in patients who subsequently developed SSI. These markers appear promising to predict future post cesarean infection, and may provide an opportunity for earlier intervention to decrease morbidity.View Large Image Figure ViewerDownload Hi-res image Download (PPT)