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Predicting fetal distress and admission to neonatal intensive care unit in patients with fetal growth restriction by nomogram: A retrospective cohort study in China
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  • Xiaobin Chen,
  • Yuan Chen,
  • Ying Jiang,
  • tian dong,
  • Juan Li,
  • Mengmeng Yang,
  • baihui zhao,
  • Qiong Luo
Xiaobin Chen
Zhejiang University School of Medicine Women's Hospital
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Yuan Chen
Zhejiang University School of Medicine Women's Hospital
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Ying Jiang
Zhejiang University School of Medicine Women's Hospital
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tian dong
Zhejiang University School of Medicine Women's Hospital
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Juan Li
Zhejiang University School of Medicine Women's Hospital
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Mengmeng Yang
Zhejiang University School of Medicine Women's Hospital
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baihui zhao
Zhejiang University School of Medicine Women's Hospital
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Qiong Luo
Zhejiang University School of Medicine Women's Hospital
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Abstract

Objective: The purpose of this research was to establish prediction model of fetal distress risk and admission to neonatal intensive care unit(NICU) risk of patients with fetal growth restriction(FGR). Design: Case-control study, a retrospective analysis. Setting: Women’s Hospital, School of Medicine, Zhejiang University in China. Population: 930 patients who were diagnosed with FGR were selected, and using fetal distress and admission to NICU as outcome.. Methods: Using lasso regression and multivariable logistic regression analysis established the nomogram prediction model of fetal distress risk and admission to NICU risk. Discrimination, calibration and clinical usability of the predicting model were respectively adopted. Internal validation was assessed using the bootstrapping validation. Main Outcome Measures: Nomograms were established for Predicting fetal distress and admission to neonatal intensive care unit in patients with FGR. Results: We found that six identified factors associated with fetal distress of patients with FGR. Four independent predictors were selected for admission to NICU of patients with FGR. The delivery method of cesarean section increased the above risks. Two nomograms were developed and verified accordingly. The two models had good discrimination and good calibration respectively. The decision curve analysis performed that the clinical usability and benefits of the nomograms were the range of 3%-75% and 17%-95%. Conclusion: Two nomograms were the first to predict fetal distress and admission to NICU of patients with FGR. Establishing effective predictive models based on independent predictors could help early diagnosis and evaluation of fetal distress and admission to NICU in patients with FGR.