Literature DB >> 31055833

Cluster analysis identifying clinical phenotypes of preterm birth and related maternal and neonatal outcomes from the Brazilian Multicentre Study on Preterm Birth.

Renato T Souza1, Jose G Cecatti1, Renato Passini1, Rodolfo C Pacagnella1, Paulo F Oliveira2, Cleide M Silva2.   

Abstract

OBJECTIVE: To explore a conceptual framework of clinical conditions associated with preterm birth (PTB) by cluster analysis, assessing determinants for different PTB subtypes and related maternal and neonatal outcomes.
METHODS: Secondary analysis of the Brazilian Multicentre Study on Preterm Birth of 33 740 births in 20 maternity hospitals between April 2011 and July 2012. In accordance with a prototype concept based on maternal, fetal, and placental conditions, an adapted k-means model and fuzzy algorithm were used to identify clusters using predefined conditions. The mains outcomes were phenotype clusters and maternal and neonatal outcomes.
RESULTS: Among 4150 PTBs, three clusters of PTB phenotypes were identified: women who had PTB without any predefined conditions; women with mixed conditions; and women who had pre-eclampsia, eclampsia, HELLP syndrome and fetal growth restriction. The prevalence of different preterm subtypes differed significantly in the three clusters, varying from 80.95% of provider-initiated PTBs in cluster 3-6.62% in cluster 1 (P<0.001). Although some maternal characteristics differed among the clusters, maternal and neonatal outcomes did not.
CONCLUSIONS: The analysis identified three clusters with distinct phenotypes. Women from the different clusters had different subtypes of PTB and maternal and pregnancy characteristics.
© 2019 The Authors. International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.

Entities:  

Keywords:  Cluster; Maternal outcomes; Neonatal outcomes; Phenotypes; Preterm birth; k-means

Mesh:

Year:  2019        PMID: 31055833     DOI: 10.1002/ijgo.12839

Source DB:  PubMed          Journal:  Int J Gynaecol Obstet        ISSN: 0020-7292            Impact factor:   3.561


  5 in total

1.  Using cluster analysis to describe phenotypical heterogeneity in extremely preterm infants: a retrospective whole-population study.

Authors:  Theodore Dassios; Emma E Williams; Christopher Harris; Anne Greenough
Journal:  BMJ Open       Date:  2022-02-28       Impact factor: 2.692

2.  Vaginal Birth After Cesarean Section (VBAC) Model using Fuzzy Analytic Hierarch Process.

Authors:  Stavroula Barbounaki; Kleanthi Gourounti; Antigoni Sarantaki
Journal:  Acta Inform Med       Date:  2021-12

3.  Construction and validation of a preterm birth risk assessment model using fuzzy analytic hierarchy process.

Authors:  Stavroula Barbounaki; Antigoni Sarantaki
Journal:  Bosn J Basic Med Sci       Date:  2022-04-01       Impact factor: 3.363

Review 4.  Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review.

Authors:  Ferdinand Dhombres; Jules Bonnard; Kévin Bailly; Paul Maurice; Aris T Papageorghiou; Jean-Marie Jouannic
Journal:  J Med Internet Res       Date:  2022-04-20       Impact factor: 7.076

5.  The role of maternal infection in preterm birth: evidence from the Brazilian Multicentre Study on Preterm Birth (EMIP).

Authors:  Ricardo P Tedesco; Rafael B Galvão; Jose Paulo Guida; Renato Passini-Júnior; Giuliane J Lajos; Marcelo L Nomura; Patricia M Rehder; Tabata Z Dias; Renato T Souza; Jose G Cecatti
Journal:  Clinics (Sao Paulo)       Date:  2020-03-23       Impact factor: 2.365

  5 in total

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