Abstract：
OBJECTIVE: The aim of this study was to investigate the predictive value of inflammation parameters and indices measured in the first trimester for the detection of preeclampsia.
METHODS: In this retrospective analysis, we examined the medical records of 276 eligible pregnancies at a tertiary referral center from 2022 to 2023. The cases were categorized into the Control group (n = 171), the Mild Preeclampsia group (n = 63), and the Severe Preeclampsia group (n = 42). We examined the demographic characteristics and perinatal outcomes of all participants. Additionally, we analyzed laboratory parameters, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune inflammation index (SII) (neutrophil*platelet/lymphocyte), systemic inflammation response index (SIRI) (neutrophil*monocyte/lymphocyte), pan-immune inflammation value (PIV) (neutrophil*platelet*monocyte/lymphocyte), and the β-hCG to PAPP-A ratio in the first trimester. Receiver operating characteristic curve (ROC) analysis was conducted to identify the optimal cut-off levels for inflammatory markers in predicting preeclampsia.
RESULTS: SIRI and PIV exhibited statistical significance in differentiating between the preeclampsia and control groups for predicting preeclampsia. The determined cut-off value for SIRI was 1.5, providing a sensitivity of 56.2% and a specificity of 55.6% (p = 0.012). Likewise, the cut-off value for PIV was 394.4, with a sensitivity of 55.2% and a specificity of 55% (p = 0.013). NLR, PLR, MLR, SII, and β-hCG to PAPP-A ratio could not predict preeclampsia.
CONCLUSIONS: This study suggests that SIRI and PIV hold promise as potential tools for predicting the risk of preeclampsia during the first trimester.
METHODS: In this retrospective analysis, we examined the medical records of 276 eligible pregnancies at a tertiary referral center from 2022 to 2023. The cases were categorized into the Control group (n = 171), the Mild Preeclampsia group (n = 63), and the Severe Preeclampsia group (n = 42). We examined the demographic characteristics and perinatal outcomes of all participants. Additionally, we analyzed laboratory parameters, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune inflammation index (SII) (neutrophil*platelet/lymphocyte), systemic inflammation response index (SIRI) (neutrophil*monocyte/lymphocyte), pan-immune inflammation value (PIV) (neutrophil*platelet*monocyte/lymphocyte), and the β-hCG to PAPP-A ratio in the first trimester. Receiver operating characteristic curve (ROC) analysis was conducted to identify the optimal cut-off levels for inflammatory markers in predicting preeclampsia.
RESULTS: SIRI and PIV exhibited statistical significance in differentiating between the preeclampsia and control groups for predicting preeclampsia. The determined cut-off value for SIRI was 1.5, providing a sensitivity of 56.2% and a specificity of 55.6% (p = 0.012). Likewise, the cut-off value for PIV was 394.4, with a sensitivity of 55.2% and a specificity of 55% (p = 0.013). NLR, PLR, MLR, SII, and β-hCG to PAPP-A ratio could not predict preeclampsia.
CONCLUSIONS: This study suggests that SIRI and PIV hold promise as potential tools for predicting the risk of preeclampsia during the first trimester.
摘要：
目的：本研究的目的是探讨孕早期测量的炎症参数和指标对检测先兆子痫的预测价值。
方法：在本回顾性分析中，从2022年至2023年,我们在三级转诊中心检查了276例符合条件的妊娠患者的医疗记录.病例分为对照组（n=171），轻度子痫前期组（n=63），和重度子痫前期组（n=42）。我们检查了所有参与者的人口统计学特征和围产期结局。此外,我们分析了实验室参数，包括中性粒细胞与淋巴细胞比率（NLR），血小板与淋巴细胞比率（PLR），单核细胞与淋巴细胞比率（MLR），全身免疫炎症指数（SII）（中性粒细胞*血小板/淋巴细胞），全身炎症反应指数（SIRI）（中性粒细胞*单核细胞/淋巴细胞），泛免疫炎症值（PIV）（中性粒细胞*血小板*单核细胞/淋巴细胞），以及孕早期β-hCG与PAPP-A的比值。进行受试者工作特征曲线（ROC）分析以确定预测先兆子痫的炎性标志物的最佳截止水平。
结果：SIRI和PIV在区分子痫前期组和对照组预测子痫前期方面表现出统计学意义。确定的SIRI的截断值为1.5,提供56.2%的灵敏度和55.6%的特异性(p=0.012)。同样，PIV的临界值为394.4,敏感性为55.2%,特异性为55%(p=0.013).NLR,PLR,MLR,SII,β-hCG与PAPP-A的比值不能预测先兆子痫。
结论：这项研究表明，SIRI和PIV有望作为预测孕早期先兆子痫风险的潜在工具。
方法：在本回顾性分析中，从2022年至2023年,我们在三级转诊中心检查了276例符合条件的妊娠患者的医疗记录.病例分为对照组（n=171），轻度子痫前期组（n=63），和重度子痫前期组（n=42）。我们检查了所有参与者的人口统计学特征和围产期结局。此外,我们分析了实验室参数，包括中性粒细胞与淋巴细胞比率（NLR），血小板与淋巴细胞比率（PLR），单核细胞与淋巴细胞比率（MLR），全身免疫炎症指数（SII）（中性粒细胞*血小板/淋巴细胞），全身炎症反应指数（SIRI）（中性粒细胞*单核细胞/淋巴细胞），泛免疫炎症值（PIV）（中性粒细胞*血小板*单核细胞/淋巴细胞），以及孕早期β-hCG与PAPP-A的比值。进行受试者工作特征曲线（ROC）分析以确定预测先兆子痫的炎性标志物的最佳截止水平。
结果：SIRI和PIV在区分子痫前期组和对照组预测子痫前期方面表现出统计学意义。确定的SIRI的截断值为1.5,提供56.2%的灵敏度和55.6%的特异性(p=0.012)。同样，PIV的临界值为394.4,敏感性为55.2%,特异性为55%(p=0.013).NLR,PLR,MLR,SII,β-hCG与PAPP-A的比值不能预测先兆子痫。
结论：这项研究表明，SIRI和PIV有望作为预测孕早期先兆子痫风险的潜在工具。
