目的: 探讨高龄孕产妇发生不良妊娠风险的列线图模型建立。方法: 回顾性分析2018年8月-2019年2月于我院分娩的35~45岁的253例孕产妇的临床一般资料和妊娠合并症及并发症资料，使用Logistic回归分析筛选高龄孕产妇发生不良妊娠的独立危险因素。然后纳入筛选出的独立危险因素建立列线图预测模型，并对模型的预测性及准确度进行验证。结果:通过对两组患者临床一般资料和妊娠合并症及并发症资料做logistic回归分析可知，年龄（OR=4.479，95%CI：1.989～10.087 ）、凝血功能异常（OR=3.855，95%CI：1.435～10.361）、妊娠合并甲减（OR=6.041，95%CI：1.891～19.293）、GDM（OR=4.108，95%CI：1.640～10.287）、HDCP（OR=2.509，95%CI：1.067～5.900）、ICP（OR=11.071，95%CI：2.696～45.464）及胎盘前置（OR=5.114，95%CI：1.827～14.318）为高龄孕产妇发生不良妊娠的独立危险因素，具有统计学差异（P<0.05）,均与高龄孕产妇发生不良妊娠高度相关。基于年龄、凝血功能异常、妊娠合并甲减、GDM、HDCP、ICP及胎盘前置这7项高龄孕产妇发生不良妊娠的独立危险因素，建立预测高龄孕产妇发生不良妊娠的列线图模型，并对该模型进行验证，预测值同实测值基本一致，说明本研究的列线图预测模型具有较好的预测能力，同时本研究使用Bootstrap 内部验证法对高龄孕产妇发生不良妊娠的列线图模型进行验证，C-index指数高达0.807（95%CI：0.765-0.849），说明本研究列线图模型具有良好的精准度和区分度。结论:高龄孕发生不良妊娠的风险较高，年龄、凝血功能异常、妊娠合并甲减、GDM、HDCP、ICP及胎盘前置等因素是高龄孕产妇发生不良妊娠的独立危险因素，相关列线图预测模型的建立能够提高对高龄孕产妇发生不良妊娠的诊断效能，临床应用价值较高，值得进一步推广使用。

Objective: To explore the establishment of a nomogram model for the risk of adverse pregnancy in pregnant women. Methods: Retrospective analysis of clinical general data, pregnancy complications and complications of 253 pregnant women aged 35-45 years old from August 2018 to February 2019 in our hospital, and the use of logistic regression analysis to screen the occurrence of maternal maternal Independent risk factors for adverse pregnancy. Then, the independent risk factors selected are used to establish a nomogram prediction model, and the predictability and accuracy of the model are verified. Results: Logistic regression analysis of clinical data and pregnancy complications and complication data of the two groups showed that age (OR=4.479, 95% CI: 1.989-10.087) and abnormal coagulation function (OR=3.855, 95% CI) : 1.435～10.361), pregnancy with hypothyroidism (OR=6.041, 95% CI: 1.891～19.293), GDM (OR=4.108, 95% CI: 1.640～10.287), HDCP (OR=2.509, 95% CI: 1.067) ～5.900), ICP (OR=11.071, 95% CI: 2.696～45.464) and placenta preposition (OR=5.114, 95% CI: 1.827～14.318) are independent risk factors for adverse pregnancy in pregnant women with statistical significance. Differences (P<0.05) were highly correlated with adverse pregnancy in older pregnant women. Based on independent risk factors for age, coagulation dysfunction, pregnancy-induced hypothyroidism, GDM, HDCP, ICP, and placenta previa in 7 older maternal pregnant women, a nomogram model for predicting adverse pregnancy in older maternal women was established. The model is validated, and the predicted values are basically consistent with the measured values, indicating that the nomogram prediction model of this study has a good predictive ability. At the same time, this study uses the Bootstrap internal verification method to map the poor pregnancy of pregnant women. For verification, the C-index index is as high as 0.807 (95% CI: 0.765-0.849), indicating that the lining model of this study has good precision and discrimination. Conclusion: The risk of adverse pregnancy is higher in pregnant women. Age, coagulation abnormality, pregnancy with hypothyroidism, GDM, HDCP, ICP and placenta previa are independent risk factors for adverse pregnancy in older pregnant women. The establishment of predictive models can improve the diagnostic efficacy of adverse pregnancy in older pregnant women, and the clinical application value is higher, which is worth further promotion.