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A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract
The aim of this study was to identify predictive factors and develop a model to assess individualized risk of postnatal surgical intervention in patients with antenatal hydronephrosis. This is a retrospective cohort study of 694 infants with prenatally detected congenital anomalies of kidney and uri...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454042/ https://www.ncbi.nlm.nih.gov/pubmed/31001505 http://dx.doi.org/10.3389/fped.2019.00120 |
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author | Vasconcelos, Mariana A. Oliveira, Eduardo A. Simões e Silva, Ana Cristina Dias, Cristiane S. Mak, Robert H. Fonseca, Carolina C. Campos, Ana Paula M. Steyerberg, Ewout W. Vergouwe, Yvonne |
author_facet | Vasconcelos, Mariana A. Oliveira, Eduardo A. Simões e Silva, Ana Cristina Dias, Cristiane S. Mak, Robert H. Fonseca, Carolina C. Campos, Ana Paula M. Steyerberg, Ewout W. Vergouwe, Yvonne |
author_sort | Vasconcelos, Mariana A. |
collection | PubMed |
description | The aim of this study was to identify predictive factors and develop a model to assess individualized risk of postnatal surgical intervention in patients with antenatal hydronephrosis. This is a retrospective cohort study of 694 infants with prenatally detected congenital anomalies of kidney and urinary tract with a median follow-up time of 37 months. The main event of interest was postnatal surgical intervention. A predictive model was developed using Cox model with internal validation by bootstrap technique. Of 694 patients, 164 (24%) infants underwent surgical intervention in a median age of 7.8 months. Predictors of the surgical intervention in the model were: baseline glomerular filtration rate, associated hydronephrosis, presence of renal damage and the severity of renal pelvic dilatation. The optimism corrected c statistic for the model was 0.84 (95%CI, 0.82–0.87). The predictive model may contribute to identify infants at high risk for surgical intervention. Further studies are necessary to validate the model in patients from other settings. |
format | Online Article Text |
id | pubmed-6454042 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64540422019-04-18 A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract Vasconcelos, Mariana A. Oliveira, Eduardo A. Simões e Silva, Ana Cristina Dias, Cristiane S. Mak, Robert H. Fonseca, Carolina C. Campos, Ana Paula M. Steyerberg, Ewout W. Vergouwe, Yvonne Front Pediatr Pediatrics The aim of this study was to identify predictive factors and develop a model to assess individualized risk of postnatal surgical intervention in patients with antenatal hydronephrosis. This is a retrospective cohort study of 694 infants with prenatally detected congenital anomalies of kidney and urinary tract with a median follow-up time of 37 months. The main event of interest was postnatal surgical intervention. A predictive model was developed using Cox model with internal validation by bootstrap technique. Of 694 patients, 164 (24%) infants underwent surgical intervention in a median age of 7.8 months. Predictors of the surgical intervention in the model were: baseline glomerular filtration rate, associated hydronephrosis, presence of renal damage and the severity of renal pelvic dilatation. The optimism corrected c statistic for the model was 0.84 (95%CI, 0.82–0.87). The predictive model may contribute to identify infants at high risk for surgical intervention. Further studies are necessary to validate the model in patients from other settings. Frontiers Media S.A. 2019-04-02 /pmc/articles/PMC6454042/ /pubmed/31001505 http://dx.doi.org/10.3389/fped.2019.00120 Text en Copyright © 2019 Vasconcelos, Oliveira, Simões e Silva, Dias, Mak, Fonseca, Campos, Steyerberg and Vergouwe. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pediatrics Vasconcelos, Mariana A. Oliveira, Eduardo A. Simões e Silva, Ana Cristina Dias, Cristiane S. Mak, Robert H. Fonseca, Carolina C. Campos, Ana Paula M. Steyerberg, Ewout W. Vergouwe, Yvonne A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract |
title | A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract |
title_full | A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract |
title_fullStr | A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract |
title_full_unstemmed | A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract |
title_short | A Predictive Model of Postnatal Surgical Intervention in Children With Prenatally Detected Congenital Anomalies of the Kidney and Urinary Tract |
title_sort | predictive model of postnatal surgical intervention in children with prenatally detected congenital anomalies of the kidney and urinary tract |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454042/ https://www.ncbi.nlm.nih.gov/pubmed/31001505 http://dx.doi.org/10.3389/fped.2019.00120 |
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