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Clinical validation of a model predicting the risk of preterm delivery
OBJECTIVES: To validate a model predicting the risk of threatened preterm delivery and to establish the optimal threshold for this risk scoring system. MATERIALS AND METHODS: Two cohorts were studied: one of singleton pregnancies without preterm premature rupture of membranes (PPROM) and no cervical...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5300233/ https://www.ncbi.nlm.nih.gov/pubmed/28182768 http://dx.doi.org/10.1371/journal.pone.0171801 |
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author | Dabi, Yohann Nedellec, Sophie Bonneau, Claire Trouchard, Blandine Rouzier, Roman Benachi, Alexandra |
author_facet | Dabi, Yohann Nedellec, Sophie Bonneau, Claire Trouchard, Blandine Rouzier, Roman Benachi, Alexandra |
author_sort | Dabi, Yohann |
collection | PubMed |
description | OBJECTIVES: To validate a model predicting the risk of threatened preterm delivery and to establish the optimal threshold for this risk scoring system. MATERIALS AND METHODS: Two cohorts were studied: one of singleton pregnancies without preterm premature rupture of membranes (PPROM) and no cervical cerclage (cohort 1) and one of twin pregnancies without PPROM and no cervical cerclage (cohort 2). Patients were included from January 1(st) 2013 until December 31(st) 2013 by the Regional Perinatal Network of Ile de France with patients transferred because of threatened preterm delivery at 22 to 32 weeks of gestation. The individual probability of delivery within 48 hours of admission was calculated using the nomogram for every patient. Discrimination and calibration of the nomogram as well as the optimal threshold were determined using R studio. RESULTS: The nomogram accurately predicted obstetric outcome. Discrimination and calibration were excellent, with an area under the curve (AUC) of 0.88 (95% CI 0.86–0.90) for cohort 1 and 0.73 (95% CI 0.66–0.80) for cohort 2. The optimal threshold would be 15% for cohort 1 and 10% for cohort 2. Using these thresholds, the performance characteristics of the nomogram were: sensitivity 80% (cohort 1) and 69% (cohort 2), negative predictive value 94.8% (cohort 1) and 91.3% (cohort 2). Use of the nomogram would avoid 253 unnecessary transfers in cohort 1. CONCLUSIONS: The nomogram was efficient and clinically relevant in our high risk population. A threshold set at 15% would help minimize the risk of preterm deliveries in singleton pregnancies and should reduce unnecessary, costly and stressful in utero transfer. |
format | Online Article Text |
id | pubmed-5300233 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53002332017-02-28 Clinical validation of a model predicting the risk of preterm delivery Dabi, Yohann Nedellec, Sophie Bonneau, Claire Trouchard, Blandine Rouzier, Roman Benachi, Alexandra PLoS One Research Article OBJECTIVES: To validate a model predicting the risk of threatened preterm delivery and to establish the optimal threshold for this risk scoring system. MATERIALS AND METHODS: Two cohorts were studied: one of singleton pregnancies without preterm premature rupture of membranes (PPROM) and no cervical cerclage (cohort 1) and one of twin pregnancies without PPROM and no cervical cerclage (cohort 2). Patients were included from January 1(st) 2013 until December 31(st) 2013 by the Regional Perinatal Network of Ile de France with patients transferred because of threatened preterm delivery at 22 to 32 weeks of gestation. The individual probability of delivery within 48 hours of admission was calculated using the nomogram for every patient. Discrimination and calibration of the nomogram as well as the optimal threshold were determined using R studio. RESULTS: The nomogram accurately predicted obstetric outcome. Discrimination and calibration were excellent, with an area under the curve (AUC) of 0.88 (95% CI 0.86–0.90) for cohort 1 and 0.73 (95% CI 0.66–0.80) for cohort 2. The optimal threshold would be 15% for cohort 1 and 10% for cohort 2. Using these thresholds, the performance characteristics of the nomogram were: sensitivity 80% (cohort 1) and 69% (cohort 2), negative predictive value 94.8% (cohort 1) and 91.3% (cohort 2). Use of the nomogram would avoid 253 unnecessary transfers in cohort 1. CONCLUSIONS: The nomogram was efficient and clinically relevant in our high risk population. A threshold set at 15% would help minimize the risk of preterm deliveries in singleton pregnancies and should reduce unnecessary, costly and stressful in utero transfer. Public Library of Science 2017-02-09 /pmc/articles/PMC5300233/ /pubmed/28182768 http://dx.doi.org/10.1371/journal.pone.0171801 Text en © 2017 Dabi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Dabi, Yohann Nedellec, Sophie Bonneau, Claire Trouchard, Blandine Rouzier, Roman Benachi, Alexandra Clinical validation of a model predicting the risk of preterm delivery |
title | Clinical validation of a model predicting the risk of preterm delivery |
title_full | Clinical validation of a model predicting the risk of preterm delivery |
title_fullStr | Clinical validation of a model predicting the risk of preterm delivery |
title_full_unstemmed | Clinical validation of a model predicting the risk of preterm delivery |
title_short | Clinical validation of a model predicting the risk of preterm delivery |
title_sort | clinical validation of a model predicting the risk of preterm delivery |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5300233/ https://www.ncbi.nlm.nih.gov/pubmed/28182768 http://dx.doi.org/10.1371/journal.pone.0171801 |
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