Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, and Shanghai Key Laboratory of Gynecologic Oncology, Shanghai, China.
Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, and Shanghai Institute of Rheumatology, Shanghai, China.
Arthritis Care Res (Hoboken). 2020 Nov;72(11):1602-1610. doi: 10.1002/acr.24265.
To screen for a high risk of preeclampsia in women with systemic lupus erythematosus (SLE).
A total of 513 antenatal care records of pregnant patients with SLE were obtained, and the data were randomly assigned to either a development set (n = 342) or a validation set (n = 171). Preeclampsia predictors were identified with stepwise regression, and a coefficient B of each variable was used to establish a prediction model and risk scoring system. Goodness-of-fit was assessed by the Hosmer-Lemeshow and Omnibus tests, and the area under the receiver operating characteristic curve (area under the curve) was used to assess discrimination. Validation was performed using the validation set.
The preeclampsia incidence was 14.4% in the pregnant patients with SLE. A mean arterial pressure (MAP) ≥96.5 mm Hg (odds ratio [OR] 213.15 [95% confidence interval (95% CI) 24.39-999.99]), prepregnancy hypertension (OR 18.19 [95% CI 2.67-125.01]), a hematologic disorder (OR 4.13 [95% CI 1.03-16.67]), positive IgM anticardiolipin antibodies (aCLs) (OR 19.85 [95% CI 1.11-333.33]), serum albumin <31.5 grams/liter (OR 9.88 [95% CI 2.07-47.62]), serum uric acid ≥303 μmoles/liter (OR 5.58 [95% CI 1.40-22.22]), and 24-hour urinary protein ≥0.286 grams (OR 14.39 [95% CI 2.43-83.33]) were selected for the preeclampsia prediction model. The area under the curve was 0.975. Preeclampsia prediction model scores >4 indicated a high risk of preeclampsia. For the validation set, the preeclampsia prediction accuracy was 93.6% (sensitivity 88.5%, specificity 94.5%).
A model for predicting the risk of preeclampsia in pregnant patients with SLE was established on the basis of MAP, prepregnancy hypertension, hematologic disorders, IgM aCLs, albumin, uric acid, and 24-hour urinary protein. The model had good predictive efficiency and can help clinicians improve pregnancy outcomes in high-risk women with early interventions.
筛查系统性红斑狼疮（SLE）孕妇子痫前期高危人群。
收集 513 例 SLE 孕妇产前检查记录，随机分为开发集（n=342）和验证集（n=171）。采用逐步回归法识别子痫前期预测因素，用各变量的系数 B 建立预测模型和风险评分系统。采用 Hosmer-Lemeshow 和 Omnibus 检验评估拟合优度，采用接收者操作特征曲线下面积（曲线下面积）评估判别能力。采用验证集进行验证。
SLE 孕妇子痫前期发生率为 14.4%。平均动脉压（MAP）≥96.5mmHg（比值比[OR]213.15[95%置信区间（95%CI）24.39-999.99]）、孕前高血压（OR 18.19[95%CI 2.67-125.01]）、血液系统疾病（OR 4.13[95%CI 1.03-16.67]）、IgM 抗心磷脂抗体（aCL）阳性（OR 19.85[95%CI 1.11-333.33]）、血清白蛋白＜31.5g/L（OR 9.88[95%CI 2.07-47.62]）、血清尿酸≥303μmol/L（OR 5.58[95%CI 1.40-22.22]）、24 小时尿蛋白≥0.286g（OR 14.39[95%CI 2.43-83.33]）纳入子痫前期预测模型。曲线下面积为 0.975。预测模型评分＞4 分提示子痫前期风险高。验证集预测子痫前期的准确率为 93.6%（敏感度 88.5%，特异度 94.5%）。
基于 MAP、孕前高血压、血液系统疾病、IgM aCL、白蛋白、尿酸和 24 小时尿蛋白，建立了预测 SLE 孕妇子痫前期风险的模型。该模型具有较好的预测效能，有助于临床医生对高危孕妇进行早期干预，改善妊娠结局。
