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作者:

Sun, Ge (Sun, Ge.) | Xu, Qi (Xu, Qi.) | Zhang, Song (Zhang, Song.) | Yang, Lin (Yang, Lin.) | Liu, Guoli (Liu, Guoli.) | Meng, Yu (Meng, Yu.) | Chen, Aiqing (Chen, Aiqing.) | Yang, Yimin (Yang, Yimin.) | Li, Xuwen (Li, Xuwen.) | Hao, Dongmei (Hao, Dongmei.) | Liu, Xiaohong (Liu, Xiaohong.) | Shao, Jing (Shao, Jing.)

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摘要:

BACKGROUND: Placental growth factor (PlGF), one of the biomarkers, has a certain predictive effect on hypertensive disorders in pregnancy (HDP). OBJECTIVE: To study the HDP prediction effect of different methods for variable selection and modeling for models containing PlGF. METHODS: For the model containing PlGF, the appropriate range of PlGF parameters needed to be selected. Step-logistic regression and lasso were used to compare the model effect of twice range selection. The PlGF model with good predictive effect and appropriate detecting gestational age was selected for the final prediction. RESULTS: The effect of the model containing PlGF tested at 15-16 weeks was better than the PlGF value without comprehensive screening. The sensitivity of both methods was over 92%. By comprehensive comparison, the final model of lasso method in this study was more effective. CONCLUSIONS: In this study, a variety of methods were used to screen models containing PlGF parameters. According to clinical needs and model effects, the optimal HDP prediction model with PlGF parameters in the second trimester of 15-26 weeks of pregnancy was finally selected.

关键词:

variable selection model parameters Placental growth factor

作者机构:

  • [ 1 ] [Sun, Ge]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 2 ] [Zhang, Song]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 3 ] [Yang, Lin]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 4 ] [Meng, Yu]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 5 ] [Yang, Yimin]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 6 ] [Li, Xuwen]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 7 ] [Hao, Dongmei]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China
  • [ 8 ] [Sun, Ge]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 9 ] [Zhang, Song]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 10 ] [Yang, Lin]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 11 ] [Meng, Yu]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 12 ] [Yang, Yimin]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 13 ] [Li, Xuwen]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 14 ] [Hao, Dongmei]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China
  • [ 15 ] [Xu, Qi]Peking Univ Peoples Hosp, Beijing 100044, Peoples R China
  • [ 16 ] [Liu, Guoli]Peking Univ Peoples Hosp, Beijing 100044, Peoples R China
  • [ 17 ] [Chen, Aiqing]Beijing Yes Med Devices Co Ltd, Beijing 100152, Peoples R China
  • [ 18 ] [Liu, Xiaohong]Beijing Yes Med Devices Co Ltd, Beijing 100152, Peoples R China
  • [ 19 ] [Shao, Jing]Beijing Yes Med Devices Co Ltd, Beijing 100152, Peoples R China

通讯作者信息:

  • [Yang, Lin]Beijing Univ Technol, Fac Environm & Life Sci, Beijing 100124, Peoples R China;;[Yang, Lin]Beijing Int Sci & Technol Cooperat Base Intellige, Beijing 100124, Peoples R China;;[Liu, Guoli]Peking Univ Peoples Hosp, Beijing 100044, Peoples R China

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来源 :

TECHNOLOGY AND HEALTH CARE

ISSN: 0928-7329

年份: 2021

卷: 29

页码: S427-S432

1 . 6 0 0

JCR@2022

ESI学科: MOLECULAR BIOLOGY & GENETICS;

ESI高被引阀值:127

JCR分区:4

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WoS核心集被引频次: 0

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