Establishment and validation of a nomogram model for adverse outcomes of early onset severe preeclampsia in pregnant women of advanced maternal age
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摘要:目的
调查伴早发型重度子痫前期(SPE)高龄孕妇的近期院内不良结局的发生率和危险因素，并构建定量列线图预测模型指导临床实践。
方法将2016年1月—2020年1月南通大学附属海安医院妇产科确诊的早发型SPE高龄孕妇316例作为训练集，根据院内结局不同将其分为不良组52例和良好组264例。另选择2020年2月—2022年5月90例早发型SPE高龄孕妇作为验证集，其中16例出现不良结局。对训练集不良组与良好组患者的临床资料和血液生化指标进行单因素分析，采用套索算法(LASSO)和多因素Logistic回归分析筛选最优预测因素, R软件建立列线图，采用受试者工作特征(ROC)曲线计算模型在训练集与验证集内预测不良结局的曲线下面积(AUC)。
结果不良组症状数量、收缩压、凝血酶原时间(PT)、丙氨酸转氨酶(ALT)、尿酸、乳酸脱氢酶(LDH)、尿素氮(BUN)和肌酐、胎儿脐动脉收缩期最大血流速度与舒张期末期血流速度的比值(S/D)和阻力指数(RI)高于或长于良好组，而血小板计数、PT活动度(PTA)和白蛋白低于良好组，差异有统计学意义(P < 0.05)。LASSO筛选出6个非共线性指标。Logistic回归分析显示，症状数量≥1个、BUN≥5 mmol/L、PT≥10 s、LDH≥250 U/L、血小板计数 < 100×109/L和白蛋白 < 30 g/L是不良结局的独立预测因子。对训练集进行内部验证，列线图预测不良结局的AUC为0.895, Hosmer-Lemeshow检验显示其拟合优度良好(χ2=12.325, P=0.548), 校正曲线显示一致性较好; 对验证集进行外部验证，列线图预测不良结局的AUC为0.846, Hosmer-Lemeshow检验显示其拟合优度良好(χ2=9.627, P=0.324), 校正曲线显示一致性较好。
结论本研究开发的列线图模型可视化强、操作简便，可用于指导临床早期识别早发型SPE高龄孕妇的院内不良结局，有较好的预测效能，对中国区域性早发型SPE高龄孕妇的临床预后有重要应用价值。
Abstract:ObjectiveTo investigate the occurrence and risk factors of short-term adverse hospital outcomes in pregnant women of advanced maternal age with early-onset severe preeclampsia (SPE), and to construct a quantitative nomogram prediction model to guide clinical practice.
MethodsFrom January 2016 to January 2020, 316 pregnant women of advanced maternal age with early-onset SPE diagnosed by the Department of Obstetrics and Gynecology of Hai'an Hospital Affiliated to Nantong University were selected as training sets. They were divided into poor group(52 cases) and good group(264 cases) according to the different outcomes in the hospital. In addition, 90 pregnant women of advanced maternal age with early-onset SPE from February 2020 to May 2022 were selected as the validation set, and 16 of them had adverse outcomes. Single factor analysis was performed on the clinical data and blood biochemical indexes of the patients in the poor and good groups of the training set. The lasso algorithm (LASSO) and multifactor Logistic regression analysis were used to screen the best predictors. R software was used to establish a nomogram. The area under the curve(AUC) of the patient′s receiver operating characteristic(ROC) curve was calculated to predict the adverse outcome in the training set and the validation set.
ResultsThe number of symptoms, systolic blood pressure, prothrombin time (PT), alanine transaminase (ALT), uric acid, lactate dehydrogenase (LDH), urea nitrogen (BUN) and creatinine, ratio of maximum systolic flow velocity to end-diastolic flow velocity (S/D) in fetal umbilical artery and resistance index (RI) in the poor group were higher or longer than those in the good group, while the blood plate count, PT activity (PTA) and albumin in the poor group were lower than those in the good group (P < 0.05). LASSO screened 6 non-collinear indicators. Logistic regression analysis showed that the number of symptoms ≥1, BUN≥5 mmol/L, PT≥10 s, LDH≥250 U/L, platelet count < 100×109/L and albumin < 30 g/L were independent predictors of adverse outcomes. The internal validation of the training set showed that the AUC of the nomogram predicting the adverse outcome was 0.895, and the Hosmer-Lemeshow test showed that its goodness of fit was good(χ2=12.325, P=0.548), the calibration curve showed good consistency. External validation was performed on the validation set. The AUC of the nomogram predicting adverse outcomes was 0.846. The Hosmer-Lemeshow test showed that its goodness of fit was good(χ2=9.627, P=0.324), the calibration curve showed a good consistency.
ConclusionThis study has developed a nomograph model with strong visualization and simple operation for guiding clinical early identification of adverse outcomes in hospital of advanced-aged pregnant women with early-onset SPE, which has a good predictive effect, and important potential for clinical prognosis of regional advanced-aged pregnant women with early-onset SPE in China.
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Keywords:
- advanced age /
- preeclampsia /
- adverse outcome /
- nomogram /
- LASSO algorithm /
- Logistic regression analysis
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表 1 良好组和不良组临床资料和血液生化指标的单因素比较(x±s)[n(%)]
项目 分类 良好组(n=264) 不良组(n=52) t/χ2 P 年龄/岁 38.6±3.7 38.5±3.6 0.569 0.501 孕周/周 31.8±2.2 31.5±2.4 0.424 0.632 经产妇 106(40.2) 19(36.5) 0.237 0.626 既往史 高血压 79(29.9) 14(26.9) 0.188 0.664 妊娠期高血压 64(24.2) 10(19.2) 0.608 0.435 PE或子痫 21(8.0) 3(5.8) 0.296 0.587 临床症状 头痛或头晕 50(18.9) 12(23.1) 0.472 0.492 恶心或呕吐 31(11.7) 10(19.2) 2.157 0.142 下肢水肿 52(19.7) 13(25.0) 0.748 0.387 视力模糊 22(8.3) 8(15.4) 2.514 0.113 胸痛或呼吸困难 4(1.5) 2(3.8) 1.267 0.260 症状数量/个 0.8±0.2 1.6±0.3 3.659 0.013 体质量指数/(kg/m2) 24.1±2.1 24.5±2.3 0.768 0.269 收缩压/mmHg 159.7±14.6 168.5±15.3 10.235 < 0.001 舒张压/mmHg 100.4±9.3 102.3±8.6 0.767 0.359 生化指标 白细胞计数/(×109/L) 12.4±3.2 13.5±3.6 1.056 0.128 血红蛋白/(g/L) 119.6±9.8 115.9±7.4 0.859 0.354 血小板计数/(×109/L) 198.7±54.2 132.3±39.7 21.325 < 0.001 D-二聚体/(mg/L) 2.5±1.3 2.8±1.2 0.648 0.401 PT/s 9.2±1.3 10.9±1.6 4.021 0.008 PTA/% 94.6±18.5 86.5±12.3 5.968 0.001 纤维蛋白原/(g/L) 5.5±1.4 5.8±1.6 0.854 0.263 APTT/s 34.8±8.5 32.6±6.5 0.569 0.521 蛋白尿 33(12.5) 9(17.3) 0.871 0.351 白蛋白/(g/L) 41.2±7.9 34.5±6.6 5.657 0.001 ALT/(U/L) 42.3±8.7 55.6±9.2 5.021 0.003 尿酸/(μmol/L) 401.2±88.6 456.9±102.3 20.235 < 0.001 总胆固醇/(mmol/L) 4.6±1.4 4.5±1.3 0.295 0.741 低密度脂蛋白/(mmol/L) 2.4±0.4 2.3±0.3 0.565 0.423 LDH/(U/L) 234.4±40.2 266.4±45.8 31.269 < 0.001 BUN/(mmol/L) 4.3±2.1 5.6±2.2 4.968 0.001 肌酐/(μmol/L) 201.4±74.5 245.6±89.5 24.524 < 0.001 双顶径/cm 7.7±1.1 7.6±0.9 0.458 0.623 头围/cm 29.6±5.8 28.8±4.5 0.965 0.123 羊水指数/cm 11.9±1.8 12.2±1.9 0.854 0.256 胎儿心率/(次/min) 148.7±16.5 152.6±15.9 1.012 0.152 脐动脉S/D 2.6±0.6 2.9±0.8 4.021 0.007 RI 0.57±0.08 0.65±0.09 4.526 0.009 PT: 凝血酶原时间; PTA: PT活动度; APTT: 活化部分凝血酶原时间; ALT: 丙氨酸转氨酶; LDH: 乳酸脱氢酶;
BUN: 尿素氮; S/D: 收缩期最大血流速度与舒张期末期血流速度的比值; RI: 阻力指数。
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表 2 不良结局的Logistic回归分析
因素 B SE Wald P OR 95%CI 症状数量≥1个 0.702 0.314 4.998 0.011 2.018 1.090~3.734 BUN≥5 mmol/L 0.996 0.388 6.590 < 0.001 2.707 1.266~5.792 PT≥10 s 0.529 0.207 6.531 < 0.001 1.697 1.131~2.547 LDH≥250 U/L 1.634 0.537 9.259 < 0.001 5.124 1.789~14.690 血小板计数 < 100×109/L 1.468 0.629 5.447 0.003 4.341 1.126~14.892 白蛋白 < 30 g/L 0.813 0.402 4.090 0.016 2.255 1.025~4.958
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