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A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation
BACKGROUND: Etiopathogenesis of preterm birth (PTB) is multifactorial, with a universe of risk factors interplaying between the mother and the environment. It is of utmost importance to identify the most informative factors in order to estimate the degree of PTB risk and trace an individualized prof...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8052693/ https://www.ncbi.nlm.nih.gov/pubmed/33863296 http://dx.doi.org/10.1186/s12884-021-03654-3 |
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author | Della Rosa, Pasquale Anthony Miglioli, Cesare Caglioni, Martina Tiberio, Francesca Mosser, Kelsey H.H. Vignotto, Edoardo Canini, Matteo Baldoli, Cristina Falini, Andrea Candiani, Massimo Cavoretto, Paolo |
author_facet | Della Rosa, Pasquale Anthony Miglioli, Cesare Caglioni, Martina Tiberio, Francesca Mosser, Kelsey H.H. Vignotto, Edoardo Canini, Matteo Baldoli, Cristina Falini, Andrea Candiani, Massimo Cavoretto, Paolo |
author_sort | Della Rosa, Pasquale Anthony |
collection | PubMed |
description | BACKGROUND: Etiopathogenesis of preterm birth (PTB) is multifactorial, with a universe of risk factors interplaying between the mother and the environment. It is of utmost importance to identify the most informative factors in order to estimate the degree of PTB risk and trace an individualized profile. The aims of the present study were: 1) to identify all acknowledged risk factors for PTB and to select the most informative ones for defining an accurate model of risk prediction; 2) to verify predictive accuracy of the model and 3) to identify group profiles according to the degree of PTB risk based on the most informative factors. METHODS: The Maternal Frailty Inventory (MaFra) was created based on a systematic review of the literature including 174 identified intrauterine (IU) and extrauterine (EU) factors. A sample of 111 pregnant women previously categorized in low or high risk for PTB below 37 weeks, according to ACOG guidelines, underwent the MaFra Inventory. First, univariate logistic regression enabled p-value ordering and the Akaike Information Criterion (AIC) selected the model including the most informative MaFra factors. Second, random forest classifier verified the overall predictive accuracy of the model. Third, fuzzy c-means clustering assigned group membership based on the most informative MaFra factors. RESULTS: The most informative and parsimonious model selected through AIC included Placenta Previa, Pregnancy Induced Hypertension, Antibiotics, Cervix Length, Physical Exercise, Fetal Growth, Maternal Anxiety, Preeclampsia, Antihypertensives. The random forest classifier including only the most informative IU and EU factors achieved an overall accuracy of 81.08% and an AUC of 0.8122. The cluster analysis identified three groups of typical pregnant women, profiled on the basis of the most informative IU and EU risk factors from a lower to a higher degree of PTB risk, which paralleled time of birth delivery. CONCLUSIONS: This study establishes a generalized methodology for building-up an evidence-based holistic risk assessment for PTB to be used in clinical practice. Relevant and essential factors were selected and were able to provide an accurate estimation of degree of PTB risk based on the most informative constellation of IU and EU factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12884-021-03654-3). |
format | Online Article Text |
id | pubmed-8052693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80526932021-04-19 A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation Della Rosa, Pasquale Anthony Miglioli, Cesare Caglioni, Martina Tiberio, Francesca Mosser, Kelsey H.H. Vignotto, Edoardo Canini, Matteo Baldoli, Cristina Falini, Andrea Candiani, Massimo Cavoretto, Paolo BMC Pregnancy Childbirth Research BACKGROUND: Etiopathogenesis of preterm birth (PTB) is multifactorial, with a universe of risk factors interplaying between the mother and the environment. It is of utmost importance to identify the most informative factors in order to estimate the degree of PTB risk and trace an individualized profile. The aims of the present study were: 1) to identify all acknowledged risk factors for PTB and to select the most informative ones for defining an accurate model of risk prediction; 2) to verify predictive accuracy of the model and 3) to identify group profiles according to the degree of PTB risk based on the most informative factors. METHODS: The Maternal Frailty Inventory (MaFra) was created based on a systematic review of the literature including 174 identified intrauterine (IU) and extrauterine (EU) factors. A sample of 111 pregnant women previously categorized in low or high risk for PTB below 37 weeks, according to ACOG guidelines, underwent the MaFra Inventory. First, univariate logistic regression enabled p-value ordering and the Akaike Information Criterion (AIC) selected the model including the most informative MaFra factors. Second, random forest classifier verified the overall predictive accuracy of the model. Third, fuzzy c-means clustering assigned group membership based on the most informative MaFra factors. RESULTS: The most informative and parsimonious model selected through AIC included Placenta Previa, Pregnancy Induced Hypertension, Antibiotics, Cervix Length, Physical Exercise, Fetal Growth, Maternal Anxiety, Preeclampsia, Antihypertensives. The random forest classifier including only the most informative IU and EU factors achieved an overall accuracy of 81.08% and an AUC of 0.8122. The cluster analysis identified three groups of typical pregnant women, profiled on the basis of the most informative IU and EU risk factors from a lower to a higher degree of PTB risk, which paralleled time of birth delivery. CONCLUSIONS: This study establishes a generalized methodology for building-up an evidence-based holistic risk assessment for PTB to be used in clinical practice. Relevant and essential factors were selected and were able to provide an accurate estimation of degree of PTB risk based on the most informative constellation of IU and EU factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12884-021-03654-3). BioMed Central 2021-04-16 /pmc/articles/PMC8052693/ /pubmed/33863296 http://dx.doi.org/10.1186/s12884-021-03654-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Della Rosa, Pasquale Anthony Miglioli, Cesare Caglioni, Martina Tiberio, Francesca Mosser, Kelsey H.H. Vignotto, Edoardo Canini, Matteo Baldoli, Cristina Falini, Andrea Candiani, Massimo Cavoretto, Paolo A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
title | A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
title_full | A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
title_fullStr | A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
title_full_unstemmed | A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
title_short | A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
title_sort | hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8052693/ https://www.ncbi.nlm.nih.gov/pubmed/33863296 http://dx.doi.org/10.1186/s12884-021-03654-3 |
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