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Abstract：
This study analyzes the levels of peripheral blood placental growth factor (PLGF), body mass index (BMI), decorin (DCN), lactate dehydrogenase (LDH), uric acid (UA), and clinical indicators of patients with preeclampsia (PE), and establishes a predictive risk model of PE, which can provide a reference for early and effective prediction of PE.
81 cases of pregnant women with PE who had regular prenatal checkups and delivered in Jinshan Branch of Shanghai Sixth People\'s Hospital from June 2020 to December 2022 were analyzed, and 92 pregnant women with normal pregnancies who had their antenatal checkups and delivered at the hospital during the same period were selected as the control group. Clinical data and peripheral blood levels of PLGF, DCN, LDH, and UA were recorded, and the two groups were subjected to univariate screening and multifactorial logistic regression analysis. Based on the screening results, the diagnostic efficacy of PE was evaluated using the receiver operating characteristic (ROC) curve. Risk prediction nomogram model was constructed using R language. The Bootstrap method (self-sampling method) was used to validate and produce calibration plots; the decision curve analysis (DCA) was used to assess the clinical benefit rate of the model.
There were statistically significant differences in age, pre-pregnancy BMI, gestational weight gain, history of PE or family history, family history of hypertension, gestational diabetes mellitus, and history of renal disease between the two groups (P < 0.05). The results of multifactorial binary logistic stepwise regression revealed that peripheral blood levels of PLGF, DCN, LDH, UA, and pre-pregnancy BMI were independent influences on the occurrence of PE (P < 0.05). The area under the curve of PLGF, DCN, LDH, UA levels and pre-pregnancy BMI in the detection of PE was 0.952, with a sensitivity of 0.901 and a specificity of 0.913, which is better than a single clinical diagnostic indicator. The results of multifactor analysis were constructed as a nomogram model, and the mean absolute error of the calibration curve of the modeling set was 0.023, suggesting that the predictive probability of the model was generally compatible with the actual value. DCA showed the predictive model had a high net benefit in the range of 5% to 85%, suggesting that the model has clinical utility value.
The occurrence of PE is related to the peripheral blood levels of PLGF, DCN, LDH, UA and pre-pregnancy BMI, and the combination of these indexes has a better clinical diagnostic value than a single index. The nomogram model constructed by using the above indicators can be used for the prediction of PE and has high predictive efficacy.
81 cases of pregnant women with PE who had regular prenatal checkups and delivered in Jinshan Branch of Shanghai Sixth People\'s Hospital from June 2020 to December 2022 were analyzed, and 92 pregnant women with normal pregnancies who had their antenatal checkups and delivered at the hospital during the same period were selected as the control group. Clinical data and peripheral blood levels of PLGF, DCN, LDH, and UA were recorded, and the two groups were subjected to univariate screening and multifactorial logistic regression analysis. Based on the screening results, the diagnostic efficacy of PE was evaluated using the receiver operating characteristic (ROC) curve. Risk prediction nomogram model was constructed using R language. The Bootstrap method (self-sampling method) was used to validate and produce calibration plots; the decision curve analysis (DCA) was used to assess the clinical benefit rate of the model.
There were statistically significant differences in age, pre-pregnancy BMI, gestational weight gain, history of PE or family history, family history of hypertension, gestational diabetes mellitus, and history of renal disease between the two groups (P < 0.05). The results of multifactorial binary logistic stepwise regression revealed that peripheral blood levels of PLGF, DCN, LDH, UA, and pre-pregnancy BMI were independent influences on the occurrence of PE (P < 0.05). The area under the curve of PLGF, DCN, LDH, UA levels and pre-pregnancy BMI in the detection of PE was 0.952, with a sensitivity of 0.901 and a specificity of 0.913, which is better than a single clinical diagnostic indicator. The results of multifactor analysis were constructed as a nomogram model, and the mean absolute error of the calibration curve of the modeling set was 0.023, suggesting that the predictive probability of the model was generally compatible with the actual value. DCA showed the predictive model had a high net benefit in the range of 5% to 85%, suggesting that the model has clinical utility value.
The occurrence of PE is related to the peripheral blood levels of PLGF, DCN, LDH, UA and pre-pregnancy BMI, and the combination of these indexes has a better clinical diagnostic value than a single index. The nomogram model constructed by using the above indicators can be used for the prediction of PE and has high predictive efficacy.
摘要：
■本研究分析了外周血胎盘生长因子（PLGF）的水平，体重指数（BMI），decorin(DCN)，乳酸脱氢酶（LDH），尿酸（UA），和子痫前期（PE）患者的临床指标，建立了PE的预测风险模型,为早期有效预测PE提供参考。
■分析了2020年6月至2022年12月在上海市第六人民医院金山分院定期进行产前检查并分娩的81例PE孕妇，选择同期进行产前检查并在医院分娩的92例正常妊娠孕妇作为对照组。临床资料及外周血PLGF水平,DCN,LDH,和UA被记录下来，并对两组进行单因素筛选和多因素logistic回归分析。根据筛选结果,采用受试者工作特征(ROC)曲线评价PE的诊断效能.使用R语言构建风险预测列线图模型。Bootstrap方法（自采样方法）用于验证和产生校准图；决策曲线分析（DCA）用于评估模型的临床受益率。
■年龄差异有统计学意义，孕前BMI,妊娠期体重增加,体育史或家族史，高血压家族史,妊娠期糖尿病,2组之间有肾脏疾病史(P<0.05)。多因素二元Logistic逐步回归结果显示，外周血PLGF水平，DCN,LDH,UA,孕前BMI是PE发生的独立影响因素(P<0.05)。PLGF曲线下面积,DCN,LDH,UA水平和孕前BMI在PE检测中为0.952,敏感性为0.901,特异性为0.913,优于单一临床诊断指标。多因素分析的结果被构造为列线图模型，模型集校准曲线的平均绝对误差为0.023，表明模型的预测概率与实际值大体相符。DCA显示预测模型在5%到85%的范围内具有很高的净收益，表明该模型具有临床应用价值。
■PE的发生与外周血PLGF水平有关，DCN,LDH,UA和孕前BMI，这些指标的组合比单一指标具有更好的临床诊断价值。利用上述指标构建的列线图模型可用于PE的预测,具有较高的预测效能。
■分析了2020年6月至2022年12月在上海市第六人民医院金山分院定期进行产前检查并分娩的81例PE孕妇，选择同期进行产前检查并在医院分娩的92例正常妊娠孕妇作为对照组。临床资料及外周血PLGF水平,DCN,LDH,和UA被记录下来，并对两组进行单因素筛选和多因素logistic回归分析。根据筛选结果,采用受试者工作特征(ROC)曲线评价PE的诊断效能.使用R语言构建风险预测列线图模型。Bootstrap方法（自采样方法）用于验证和产生校准图；决策曲线分析（DCA）用于评估模型的临床受益率。
■年龄差异有统计学意义，孕前BMI,妊娠期体重增加,体育史或家族史，高血压家族史,妊娠期糖尿病,2组之间有肾脏疾病史(P<0.05)。多因素二元Logistic逐步回归结果显示，外周血PLGF水平，DCN,LDH,UA,孕前BMI是PE发生的独立影响因素(P<0.05)。PLGF曲线下面积,DCN,LDH,UA水平和孕前BMI在PE检测中为0.952,敏感性为0.901,特异性为0.913,优于单一临床诊断指标。多因素分析的结果被构造为列线图模型，模型集校准曲线的平均绝对误差为0.023，表明模型的预测概率与实际值大体相符。DCA显示预测模型在5%到85%的范围内具有很高的净收益，表明该模型具有临床应用价值。
■PE的发生与外周血PLGF水平有关，DCN,LDH,UA和孕前BMI，这些指标的组合比单一指标具有更好的临床诊断价值。利用上述指标构建的列线图模型可用于PE的预测,具有较高的预测效能。
