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Systemic Immune-Inflammation Index as a Predictive Biomarker for Pre-Eclampsia
Dimitris Baroutis1, Eleni Katsianou2, Aikaterini-Gavriela Giannakaki1
11st Department of Obstetrics and Gynecology, Alexandra Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece.
Journal of Clinical Medicine
|May 27, 2026
Summary
The Systemic Immune-Inflammation Index (SII) shows inconsistent results for predicting pre-eclampsia, a serious pregnancy condition. Current evidence does not support its clinical use due to varied findings and methodological limitations.
Area of Science:
- Obstetrics and Gynecology
- Hematology
- Immunology
Background:
- Pre-eclampsia is a leading cause of maternal and perinatal morbidity globally.
- The Systemic Immune-Inflammation Index (SII) reflects neutrophil, lymphocyte, and platelet counts, implicated in pre-eclampsia.
- Existing research on SII in pre-eclampsia presents conflicting findings.
Purpose of the Study:
- To review current evidence on the Systemic Immune-Inflammation Index (SII) in pre-eclampsia.
- To evaluate the biological rationale, clinical findings, and diagnostic performance of SII.
- To assess the potential clinical utility and limitations of SII for pre-eclampsia.
Main Methods:
- Narrative review synthesizing evidence from major scientific databases (PubMed/MEDLINE, Scopus, Web of Science, Google Scholar).
- Literature search included all available records up to January 2026.
- Analysis of studies examining SII association with pre-eclampsia and its diagnostic performance.
Main Results:
- Substantial heterogeneity observed in the association between SII and pre-eclampsia (elevated vs. decreased).
- Diagnostic performance of SII varies significantly across different populations.
- A meta-analysis reported non-significant pooled results for the pre-eclampsia subgroup.
Conclusions:
- Methodological limitations (retrospective designs, lack of standardized thresholds) and inconsistent results preclude current clinical implementation of SII.
- SII's cost-effectiveness and accessibility are advantageous but insufficient for adoption.
- Future research requires prospective validation and mechanistic studies for potential integration into multiparametric prediction models.
