Qing Liu, Minghui Gong, Zhuolin Su, Huiran Xu, Ziwei Zhao, Ying Zhang, Yinong Jiang, Wei Song
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The performance of the nomogram was evaluated by an internal validation. In total, 207 (30.1%) patients developed CHT after delivery. Maternal age, highest systolic blood pressure (SBP), highest diastolic blood pressure (DBP), peak alkaline phosphatase (ALP) levels, peak uric acid (UA) levels, and urine protein during pregnancy were independent predictors of the nomogram. Area under the curve (AUC) of the training set was 0.819 (95% CI: 0.778–0.860, <i>p</i> < 0.001) and 0.800 (95% CI: 0.739–0.862, <i>p</i> < 0.001) in the validation set. A good consistency between the nomogram model and standard diagnostic criteria was obtained (<i>p</i> > 0.05). Decision curve analysis (DCA) also showed a net benefit in the nomogram when the risk thresholds were 10%–90%. In conclusion, we developed a novel clinical nomogram to predict CHT risk in women with HDP, which was a useful and easy tool to identify high-risk individuals and performed well on internal validation.</p>","PeriodicalId":50237,"journal":{"name":"Journal of Clinical Hypertension","volume":"27 7","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jch.70094","citationCount":"0","resultStr":"{\"title\":\"Development and Validation of a Nomogram for Predicting the Probability of Postpartum Chronic Hypertension in Women With Hypertensive Disorders of Pregnancy: A Multicenter, Cross-Sectional Study\",\"authors\":\"Qing Liu, Minghui Gong, Zhuolin Su, Huiran Xu, Ziwei Zhao, Ying Zhang, Yinong Jiang, Wei Song\",\"doi\":\"10.1111/jch.70094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Women with hypertensive disorders of pregnancy (HDP) have a higher risk of developing chronic hypertension (CHT) postpartum, which can lead to increased cardiovascular events. Therefore, we aimed to develop and validate a nomogram to predict the probability of CHT in HDP women by analyzing traditional characteristics and pregnancy-related indices. A total of 688 HDP women who delivered at the three designated hospitals in China, during the period of January 2011 to June 2021, were randomly divided into 70% (<i>n</i> = 482) as the training set and the remaining 30% (<i>n</i> = 206) as the validation set. Predictors for CHT were extracted to establish a nomogram based on multivariate logistic analysis of the training set. The performance of the nomogram was evaluated by an internal validation. In total, 207 (30.1%) patients developed CHT after delivery. Maternal age, highest systolic blood pressure (SBP), highest diastolic blood pressure (DBP), peak alkaline phosphatase (ALP) levels, peak uric acid (UA) levels, and urine protein during pregnancy were independent predictors of the nomogram. 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引用次数: 0
摘要
患有妊娠期高血压疾病(HDP)的妇女产后发生慢性高血压(CHT)的风险更高,这可能导致心血管事件增加。因此,我们旨在通过分析HDP妇女的传统特征和妊娠相关指标,建立并验证一个预测HDP妇女发生CHT概率的nomogram。选取2011年1月至2021年6月在中国三家指定医院分娩的688名HDP妇女,随机分为70% (n = 482)作为训练集,其余30% (n = 206)作为验证集。基于训练集的多变量逻辑分析,提取了CHT的预测因子,建立了一个nomogram。通过内部验证来评价图的性能。207例(30.1%)患者在分娩后发生CHT。妊娠期产妇年龄、最高收缩压(SBP)、最高舒张压(DBP)、碱性磷酸酶(ALP)峰值水平、尿酸(UA)峰值水平和尿蛋白是nomogram独立预测因子。训练集曲线下面积(AUC)为0.819 (95% CI: 0.778-0.860, p <;0.001)和0.800 (95% CI: 0.739-0.862, p <;0.001)。nomogram模型与标准诊断标准具有良好的一致性(p >;0.05)。当风险阈值为10%-90%时,决策曲线分析(DCA)也显示出nomogram净收益。总之,我们开发了一种新的临床nomogram来预测HDP女性的CHT风险,这是一种有效且简单的识别高风险个体的工具,并且在内部验证中表现良好。
Development and Validation of a Nomogram for Predicting the Probability of Postpartum Chronic Hypertension in Women With Hypertensive Disorders of Pregnancy: A Multicenter, Cross-Sectional Study
Women with hypertensive disorders of pregnancy (HDP) have a higher risk of developing chronic hypertension (CHT) postpartum, which can lead to increased cardiovascular events. Therefore, we aimed to develop and validate a nomogram to predict the probability of CHT in HDP women by analyzing traditional characteristics and pregnancy-related indices. A total of 688 HDP women who delivered at the three designated hospitals in China, during the period of January 2011 to June 2021, were randomly divided into 70% (n = 482) as the training set and the remaining 30% (n = 206) as the validation set. Predictors for CHT were extracted to establish a nomogram based on multivariate logistic analysis of the training set. The performance of the nomogram was evaluated by an internal validation. In total, 207 (30.1%) patients developed CHT after delivery. Maternal age, highest systolic blood pressure (SBP), highest diastolic blood pressure (DBP), peak alkaline phosphatase (ALP) levels, peak uric acid (UA) levels, and urine protein during pregnancy were independent predictors of the nomogram. Area under the curve (AUC) of the training set was 0.819 (95% CI: 0.778–0.860, p < 0.001) and 0.800 (95% CI: 0.739–0.862, p < 0.001) in the validation set. A good consistency between the nomogram model and standard diagnostic criteria was obtained (p > 0.05). Decision curve analysis (DCA) also showed a net benefit in the nomogram when the risk thresholds were 10%–90%. In conclusion, we developed a novel clinical nomogram to predict CHT risk in women with HDP, which was a useful and easy tool to identify high-risk individuals and performed well on internal validation.
期刊介绍:
The Journal of Clinical Hypertension is a peer-reviewed, monthly publication that serves internists, cardiologists, nephrologists, endocrinologists, hypertension specialists, primary care practitioners, pharmacists and all professionals interested in hypertension by providing objective, up-to-date information and practical recommendations on the full range of clinical aspects of hypertension. Commentaries and columns by experts in the field provide further insights into our original research articles as well as on major articles published elsewhere. Major guidelines for the management of hypertension are also an important feature of the Journal. Through its partnership with the World Hypertension League, JCH will include a new focus on hypertension and public health, including major policy issues, that features research and reviews related to disease characteristics and management at the population level.