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Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention

BACKGROUND: This study focused on congenital heart disease (CHD) patients complicated with airway stenosis (AS) without airway intervention and aimed to identify the patients with potential risks. METHODS: Patients diagnosed with CHD and AS were enrolled in this retrospective study. The primary outc...

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Autores principales: He, Qiyu, Liu, Yuze, Dou, Zheng, Ma, Kai, Li, Shoujun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337114/
https://www.ncbi.nlm.nih.gov/pubmed/37438689
http://dx.doi.org/10.1186/s12887-023-04160-5
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author He, Qiyu
Liu, Yuze
Dou, Zheng
Ma, Kai
Li, Shoujun
author_facet He, Qiyu
Liu, Yuze
Dou, Zheng
Ma, Kai
Li, Shoujun
author_sort He, Qiyu
collection PubMed
description BACKGROUND: This study focused on congenital heart disease (CHD) patients complicated with airway stenosis (AS) without airway intervention and aimed to identify the patients with potential risks. METHODS: Patients diagnosed with CHD and AS were enrolled in this retrospective study. The primary outcome was defined as a postoperative mechanical ventilation duration of more than two weeks. We constructed a prediction model to predict the risk of prolonged mechanical ventilation (PMV). RESULTS: A total of 185 patients diagnosed with CHD and AS in Fuwai Hospital from July 2009 to December 2022 were included in the study. Weight at CHD surgery, cardiopulmonary bypass (CPB) duration, complex CHD and comorbid tracheobronchomalacia were identified as risk factors and included in the model. The ROC curve showed a good distinguishing ability, with an AUC of 0.847 (95% CI: 0.786–0.908). According to the optimal cut-off value of the ROC curve, patients were divided into high- and low-risk groups, and the subsequent analysis showed significant differences in peri-operative characteristics and in-hospital deaths. CONCLUSIONS: With the predictive model, several factors could be used to assess the risky patients with PMV. More attention should be paid to these patients by early identification and routine surveillance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12887-023-04160-5.
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spelling pubmed-103371142023-07-13 Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention He, Qiyu Liu, Yuze Dou, Zheng Ma, Kai Li, Shoujun BMC Pediatr Research BACKGROUND: This study focused on congenital heart disease (CHD) patients complicated with airway stenosis (AS) without airway intervention and aimed to identify the patients with potential risks. METHODS: Patients diagnosed with CHD and AS were enrolled in this retrospective study. The primary outcome was defined as a postoperative mechanical ventilation duration of more than two weeks. We constructed a prediction model to predict the risk of prolonged mechanical ventilation (PMV). RESULTS: A total of 185 patients diagnosed with CHD and AS in Fuwai Hospital from July 2009 to December 2022 were included in the study. Weight at CHD surgery, cardiopulmonary bypass (CPB) duration, complex CHD and comorbid tracheobronchomalacia were identified as risk factors and included in the model. The ROC curve showed a good distinguishing ability, with an AUC of 0.847 (95% CI: 0.786–0.908). According to the optimal cut-off value of the ROC curve, patients were divided into high- and low-risk groups, and the subsequent analysis showed significant differences in peri-operative characteristics and in-hospital deaths. CONCLUSIONS: With the predictive model, several factors could be used to assess the risky patients with PMV. More attention should be paid to these patients by early identification and routine surveillance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12887-023-04160-5. BioMed Central 2023-07-12 /pmc/articles/PMC10337114/ /pubmed/37438689 http://dx.doi.org/10.1186/s12887-023-04160-5 Text en © The Author(s) 2023 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
He, Qiyu
Liu, Yuze
Dou, Zheng
Ma, Kai
Li, Shoujun
Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
title Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
title_full Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
title_fullStr Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
title_full_unstemmed Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
title_short Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
title_sort congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337114/
https://www.ncbi.nlm.nih.gov/pubmed/37438689
http://dx.doi.org/10.1186/s12887-023-04160-5
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