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Predictions of Preterm Birth from Early Pregnancy Characteristics: Born in Guangzhou Cohort Study.
He, Jian-Rong; Ramakrishnan, Rema; Lai, Yu-Mian; Li, Wei-Dong; Zhao, Xuan; Hu, Yan; Chen, Nian-Nian; Hu, Fang; Lu, Jin-Hua; Wei, Xue-Ling; Yuan, Ming-Yang; Shen, Song-Ying; Qiu, Lan; Chen, Qiao-Zhu; Hu, Cui-Yue; Cheng, Kar Keung; Mol, Ben Willem J; Xia, Hui-Min; Qiu, Xiu.
Afiliação
  • He JR; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. jianrong.he@bigcs.org.
  • Ramakrishnan R; Department of Obstetrics and Gynecology, Guangzhou Women and Children Medical Center, Guangzhou Medical University, Guangzhou 510623, China. jianrong.he@bigcs.org.
  • Lai YM; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford OX3 9DU, UK. jianrong.he@bigcs.org.
  • Li WD; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford OX3 9DU, UK. rema.ramakrishnan@wrh.ox.ac.uk.
  • Zhao X; Department of Obstetrics and Gynecology, Guangzhou Women and Children Medical Center, Guangzhou Medical University, Guangzhou 510623, China. yumian.lai@bigcs.org.
  • Hu Y; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. weidong.li@bigcs.org.
  • Chen NN; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. weidong.li@bigcs.org.
  • Hu F; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. xuan.zhao@bigcs.org.
  • Lu JH; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. xuan.zhao@bigcs.org.
  • Wei XL; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. yan.hu@bigcs.org.
  • Yuan MY; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. yan.hu@bigcs.org.
  • Shen SY; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. niannian.chen@bigcs.org.
  • Qiu L; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. niannian.chen@bigcs.org.
  • Chen QZ; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. fang.hu@bigcs.org.
  • Hu CY; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. fang.hu@bigcs.org.
  • Cheng KK; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. jinhua.lu@bigcs.org.
  • Mol BWJ; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. jinhua.lu@bigcs.org.
  • Xia HM; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. xueling.wei@bigcs.org.
  • Qiu X; Department of Woman and Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. xueling.wei@bigcs.org.
J Clin Med ; 7(8)2018 Jul 27.
Article em En | MEDLINE | ID: mdl-30060450
ABSTRACT
Preterm birth (PTB, <37 weeks) is the leading cause of death in children <5 years of age. Early risk prediction for PTB would enable early monitoring and intervention. However, such prediction models have been rarely reported, especially in low- and middle-income areas. We used data on a number of easily accessible predictors during early pregnancy from 9044 women in Born in Guangzhou Cohort Study, China to generate prediction models for overall PTB and spontaneous, iatrogenic, late (34⁻36 weeks), and early (<34 weeks) PTB. Models were constructed using the Cox proportional hazard model, and their performance was evaluated by Harrell's c and D statistics and calibration plot. We further performed a systematic review to identify published models and validated them in our population. Our new prediction models had moderate discrimination, with Harrell's c statistics ranging from 0.60⁻0.66 for overall and subtypes of PTB. Significant predictors included maternal age, height, history of preterm delivery, amount of vaginal bleeding, folic acid intake before pregnancy, and passive smoking during pregnancy. Calibration plots showed good fit for all models except for early PTB. We validated three published models, all of which were from studies conducted in high-income countries; the area under receiver operating characteristic for these models ranged from 0.50 to 0.56. Based on early pregnancy characteristics, our models have moderate predictive ability for PTB. Future studies should consider inclusion of laboratory markers for the prediction of PTB.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Clin Med Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Clin Med Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND