Abstract
Background: We aimed to predict the efficacy of the systemic immune-inflammatory index (SII) in predicting missed abortions. Methods: In this retrospective study, we analyzed the data of women diagnosed with a missed abortion between gestational weeks 7–12 at our clinic from January 2018 to December 2021. The control group consisted of women in healthy pregnancies who were at the same gestational weeks. The demographic characteristics of participants, SII (neutrophil count x platelet count/lymphocyte count), platelet-lymphocyte ratio (PLR), and neutrophil-lymphocyte ratio (NLR) values were evaluated in both groups. Results: A total of 142 missed abortion group and 142 control group were included. SII was found to be statistically significantly higher in the missed abortion group than in the control group (917.1 ± 549.7 and 557.1 ± 193.7, respectively; p < 0.001). In the logistic regression model, SII was found to be an independent predictor of a missed abortion (odds ratio = 2.85, 95% confidence interval: 1.34–4.15, p < 0.001). We found that the diagnostic value of SII (area under the curve [AUC]: 0.765) was higher than PLR (AUC: 0.711) or NLR (AUC: 0.703) alone in patients with a missed abortion. We determined that an SII value of >709.75 predicted the development of a missed abortion with 64.0% sensitivity and 80.9% specificity. Discussion: In recent years, complete blood count parameters have been increasingly used as an indicator of systemic inflammation. Although there are many studies in the literature investigating the relationship of a missed abortion with PLR and NLR, there is limited research evaluating the relationship of this clinical condition with SII. We determined that SII obtained from the combination of lymphocyte, platelet, and neutrophil counts was more valuable than evaluating these parameters by dividing them separately. Conclusion: Our results show that there is a significant relationship between SII and a missed abortion, and therefore SII can be used as a predictive marker of this clinical condition.
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