Can perioperative shifts in inflammatory indices predict maternal and neonatal outcomes following cervical cerclage?

BACKGROUND: Cervical insufficiency is a known risk factor for spontaneous preterm delivery and often leads to pregnancy loss in the second trimester. The aim of the study was to determine whether the Systemic Immune-Inflammation Index (SII), Systemic Inflammatory Response Index (SIRI) and Pan-Immune Inflammation Value (PIV) before and after cerclage, as well as alterations in these indices, can predict preterm birth and composite adverse perinatal outcomes (CAPOs). METHODS: This retrospective study included 104 singleton pregnancies in which cervical cerclage was performed between 12 and 24 weeks’ gestation. Inflammatory indices were calculated from complete blood counts obtained within 48 h before and after the cerclage. Delta scores were calculated as the difference between preoperative and postoperative inflammatory index values. Patients were categorized into term (≥ 37 weeks) and preterm (< 37 weeks) delivery groups. ROC analysis was performed to assess the predictive value of inflammatory indices for preterm birth and CAPOs. RESULTS: Higher pre-SII, post-SII and post-PIV scores were significantly associated with preterm delivery and CAPOs (p < 0.05). Delta-SII values were significantly lower in the preterm group and were associated with shorter cerclage-to-delivery intervals, increased cesarean rates, and CAPOs. ROC analysis showed that pre-SII (AUC: 0.657, 95% CI: 0.55–0.77, p = 0.006), post-SII (AUC: 0.721, 95% CI: 0.62–0.82, p < 0.001), delta-SII (AUC: 0.635, 95% CI: 0.53–0.74, p = 0.019) and post-PIV (AUC: 0.624, 95% CI: 0.51–0.74, p = 0.030) had a statistically significant predictive accuracy for preterm birth. Post-SII also predicted CAPOs with an AUC of 0.723 (95% CI: 0.62–0.82, p < 0.001). CONCLUSION: Systemic inflammatory indices, particularly the delta-SII, pre-SII, post-SII, and post-PIV, are promising biomarkers for predicting the outcome of cervical cerclage. Monitoring these indices may help clinicians identify high-risk patients and optimize prenatal care to improve maternal and neonatal outcomes.