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Constructing of predictive model for the surgical effect of patients with cleft lip and palate

OBJECTIVE: To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery. METHODS: This study has been ethically reviewed and approved...

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Autores principales: Liu, Na, Yang, Jingyuan, Tan, Fang, Zhu, Haijian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313050/
https://www.ncbi.nlm.nih.gov/pubmed/37390058
http://dx.doi.org/10.1371/journal.pone.0286976
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author Liu, Na
Yang, Jingyuan
Tan, Fang
Zhu, Haijian
author_facet Liu, Na
Yang, Jingyuan
Tan, Fang
Zhu, Haijian
author_sort Liu, Na
collection PubMed
description OBJECTIVE: To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery. METHODS: This study has been ethically reviewed and approved by the Medical Ethics Committee of Guiyang Stomatological Hospital before the study began.A total of 997 cases of cleft lip and palate surgical treatment in Guiyang Stomatological Hospital from 2015 to 2020 were collected. Logistic regression analysis was used to analyze the factors influencing the surgical outcome, and a score system was established by assigning values to the influencing factors using the nomogram. Data of 110 patients were verified, and decision curve analysis was used to evaluate the predicted results. RESULTS: Logistic regression analysis showed that the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition during pregnancy and labor intensity during pregnancy were independent risk factors for poor surgical results (all P<0.05). The predictive model was built by including the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition and labor intensity during pregnancy into the predictive scoring system. The critical value was 273, the area under ROC curve (AUC) was 0.733(95%CI:0.704~0.76), the sensitivity was 89.57%, and the specificity was 48.14%.When the external validation data of 110 patients were brought into the score, the AUC of poor diagnostic value reached 74.5%, P<0.05, which was close to the modeling accuracy of 73.3%. CONCLUSION: This study constructed a predictive model of surgical effect for patients with cleft lip and palate, which can be used for the clinical prediction of cleft lip and palate patients in Guizhou Province.
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spelling pubmed-103130502023-07-01 Constructing of predictive model for the surgical effect of patients with cleft lip and palate Liu, Na Yang, Jingyuan Tan, Fang Zhu, Haijian PLoS One Research Article OBJECTIVE: To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery. METHODS: This study has been ethically reviewed and approved by the Medical Ethics Committee of Guiyang Stomatological Hospital before the study began.A total of 997 cases of cleft lip and palate surgical treatment in Guiyang Stomatological Hospital from 2015 to 2020 were collected. Logistic regression analysis was used to analyze the factors influencing the surgical outcome, and a score system was established by assigning values to the influencing factors using the nomogram. Data of 110 patients were verified, and decision curve analysis was used to evaluate the predicted results. RESULTS: Logistic regression analysis showed that the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition during pregnancy and labor intensity during pregnancy were independent risk factors for poor surgical results (all P<0.05). The predictive model was built by including the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition and labor intensity during pregnancy into the predictive scoring system. The critical value was 273, the area under ROC curve (AUC) was 0.733(95%CI:0.704~0.76), the sensitivity was 89.57%, and the specificity was 48.14%.When the external validation data of 110 patients were brought into the score, the AUC of poor diagnostic value reached 74.5%, P<0.05, which was close to the modeling accuracy of 73.3%. CONCLUSION: This study constructed a predictive model of surgical effect for patients with cleft lip and palate, which can be used for the clinical prediction of cleft lip and palate patients in Guizhou Province. Public Library of Science 2023-06-30 /pmc/articles/PMC10313050/ /pubmed/37390058 http://dx.doi.org/10.1371/journal.pone.0286976 Text en © 2023 Liu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Liu, Na
Yang, Jingyuan
Tan, Fang
Zhu, Haijian
Constructing of predictive model for the surgical effect of patients with cleft lip and palate
title Constructing of predictive model for the surgical effect of patients with cleft lip and palate
title_full Constructing of predictive model for the surgical effect of patients with cleft lip and palate
title_fullStr Constructing of predictive model for the surgical effect of patients with cleft lip and palate
title_full_unstemmed Constructing of predictive model for the surgical effect of patients with cleft lip and palate
title_short Constructing of predictive model for the surgical effect of patients with cleft lip and palate
title_sort constructing of predictive model for the surgical effect of patients with cleft lip and palate
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313050/
https://www.ncbi.nlm.nih.gov/pubmed/37390058
http://dx.doi.org/10.1371/journal.pone.0286976
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