Development and validation of a risk prediction model of delayed onset of lactogenesis among mothers with gestational diabetes mellitus: a prospective multicenter study.

IF 3.5
Frontiers in clinical diabetes and healthcare Pub Date : 2026-03-26 eCollection Date: 2026-01-01 DOI:10.3389/fcdhc.2026.1721649
Yu-Ting Luo, Min Xu, Zhi-Dong Guo, Yun-Xia Liu, Li Liu
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Abstract

Objective: The aim of this study is to develop and validate a prediction model of delayed onset of lactogenesis among mothers with gestational diabetes mellitus.

Methods: This was a prospective study. A total of 511 mothers with GDM hospitalized at seven tertiary (grade 3A) hospitals in five cities of Guangdong Province, China, between October 10, 2023, and December 8, 2024, were enrolled in the study using convenience sampling. Univariate regression, LASSO regression and logistic regression were used to construct and validation risk prediction model. Logistic regression and R language was used to draw the nomogram. Model performance was evaluated using the area under the receiver operator characteristic curve (AUC), Hosmer-Lemeshow goodness-of fit test, and clinical decision curve analysis, assessing the discrimination ability, calibration, and clinical utility of the model.

Results: Based on logistic regression analysis, we identified several significant delayed onset of lactogenesis risk factors for mothers with gestational diabetes mellitus: pre-delivery BMI, Edinburgh Postnatal Depression Scale score, serum albumin levels, LATCH score, blood glucose control during pregnancy. The AUC was 0.828, (95%CI:0.779~0.877),with a sensitivity of 70.9%, a specificity of 83.7%,optimal cut-off point of 0.341, a maximum Youden index of 0.546. The Hosmer-Lemeshow test yielded a χ 2 value of 7.226 and p = 0.546.The internal verification showed the AUC was 0.806(95%CI:0.728, 0.884), indicating the model's high discrimination ability. Calibration curves showed good agreement between predicted and observed values, confirming good calibration. The clinical decision curve analysis further supported the model's clinical utility.

Conclusion: The prediction model constructed and verified in this study was to predict delayed onset of lactogenesis risk for mothers with gestational diabetes mellitus, providing an effective evaluation tool for healthcare professionals.

妊娠期糖尿病母亲迟发性乳发生风险预测模型的建立和验证:一项前瞻性多中心研究。
目的:建立并验证妊娠期糖尿病母亲迟发性乳发生的预测模型。方法:前瞻性研究。采用方便抽样的方法,于2023年10月10日至2024年12月8日在中国广东省5个城市的7家三级(三甲)医院住院的511名GDM母亲被纳入研究。采用单因素回归、LASSO回归和logistic回归构建风险预测模型并进行验证。采用逻辑回归和R语言绘制nomogram。采用接收算子特征曲线下面积(AUC)、Hosmer-Lemeshow拟合优度检验和临床决策曲线分析来评估模型的性能,评估模型的辨别能力、校准能力和临床效用。结果:基于logistic回归分析,我们确定了妊娠期糖尿病母亲的几个显著延迟性乳发生危险因素:产前BMI、爱丁堡产后抑郁量表评分、血清白蛋白水平、LATCH评分、妊娠期间血糖控制。AUC为0.828,(95%CI:0.779~0.877),敏感性70.9%,特异性83.7%,最佳截断点0.341,最大约登指数0.546。Hosmer-Lemeshow检验的χ 2值为7.226,p = 0.546。内部验证显示AUC为0.806(95%CI:0.728, 0.884),表明该模型具有较高的判别能力。校正曲线预测值与实测值吻合较好,证实校正效果良好。临床决策曲线分析进一步支持了模型的临床实用性。结论:本研究构建并验证的预测模型能够预测妊娠期糖尿病母亲迟发性产乳风险,为医护人员提供有效的评估工具。
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