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<p>Early prediction of gestational diabetes mellitus (GDM) is particularly important. The role of neutrophil to high-density lipoprotein cholesterol (HDL-C) ratio (NHR) in GDM is unclear. This study aims to explore the predictive value of early pregnancy NHR in GDM. A case-control study was conducted involving 1421 pregnant women, randomly divided into a training dataset and a validation set. Routine clinical and laboratory information were collected. Logistic regression was performed and nomogram was established to determine the diagnostic efficacy of NHR for GDM. We evaluated nomogram through receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Compared with non-GDM, early pregnancy NHR was significantly elevated in GDM. Logistic regression indicated that NHR was an independent risk factor for GDM. A nomogram model was constructed using NHR, age, body mass index, glycated hemoglobin, and fasting blood glucose as factors to predict GDM in early pregnancy. The calibration curve and DCA demonstrated strong predictive ability. The DCA result indicated that the model has clinical application value. In GDM subjects, NHR levels significantly increase in early pregnancy and are closely related to the occurrence of GDM. NHR has good predictive diagnostic performance.</p>

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The predictive value of neutrophil to high-density lipoprotein cholesterol ratio in early pregnancy for gestational diabetes based on nomogram

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月18日

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  • Yuehan Ma,
  • Jianbing Sun,
  • Ning Yuan,
  • Sixu Xin,
  • Dan Zhao,
  • Xiaomei Zhang

摘要

Early prediction of gestational diabetes mellitus (GDM) is particularly important. The role of neutrophil to high-density lipoprotein cholesterol (HDL-C) ratio (NHR) in GDM is unclear. This study aims to explore the predictive value of early pregnancy NHR in GDM. A case-control study was conducted involving 1421 pregnant women, randomly divided into a training dataset and a validation set. Routine clinical and laboratory information were collected. Logistic regression was performed and nomogram was established to determine the diagnostic efficacy of NHR for GDM. We evaluated nomogram through receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Compared with non-GDM, early pregnancy NHR was significantly elevated in GDM. Logistic regression indicated that NHR was an independent risk factor for GDM. A nomogram model was constructed using NHR, age, body mass index, glycated hemoglobin, and fasting blood glucose as factors to predict GDM in early pregnancy. The calibration curve and DCA demonstrated strong predictive ability. The DCA result indicated that the model has clinical application value. In GDM subjects, NHR levels significantly increase in early pregnancy and are closely related to the occurrence of GDM. NHR has good predictive diagnostic performance.