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Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage
BACKGROUND: Postoperative pneumonia (POP) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) associated with increased mortality rates, prolonged hospitalization, and high medical costs. It is currently understood that identifying pneumonia early and implementing aggressive tre...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513064/ https://www.ncbi.nlm.nih.gov/pubmed/37745673 http://dx.doi.org/10.3389/fneur.2023.1251570 |
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author | Jin, Xiao Wang, Shijia Zhang, Chengwei Yang, Song Lou, Lejing Xu, Shuyao Cai, Chang |
author_facet | Jin, Xiao Wang, Shijia Zhang, Chengwei Yang, Song Lou, Lejing Xu, Shuyao Cai, Chang |
author_sort | Jin, Xiao |
collection | PubMed |
description | BACKGROUND: Postoperative pneumonia (POP) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) associated with increased mortality rates, prolonged hospitalization, and high medical costs. It is currently understood that identifying pneumonia early and implementing aggressive treatment can significantly improve patients' outcomes. The primary objective of this study was to explore risk factors and develop a logistic regression model that assesses the risks of POP. METHODS: An internal cohort of 613 inpatients with aSAH who underwent surgery at the Neurosurgical Department of First Affiliated Hospital of Wenzhou Medical University was retrospectively analyzed to develop a nomogram for predicting POP. We assessed the discriminative power, accuracy, and clinical validity of the predictions by using the area under the receiver operating characteristic curve (AUC), the calibration curve, and decision curve analysis (DCA). The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. RESULTS: Among patients in our internal cohort, 15.66% (n = 96/613) of patients had POP. The least absolute shrinkage and selection operator (LASSO) regression analysis identified the Glasgow Coma Scale (GCS), mechanical ventilation time (MVT), albumin, C-reactive protein (CRP), smoking, and delayed cerebral ischemia (DCI) as potential predictors of POP. We then used multivariable logistic regression analysis to evaluate the effects of these predictors and create a final model. Eighty percentage of patients in the internal cohort were randomly assigned to the training set for model development, while the remaining 20% of patients were allocated to the internal validation set. The AUC values for the training, internal, and external validation sets were 0.914, 0.856, and 0.851, and the corresponding Brier scores were 0.084, 0.098, and 0.143, respectively. CONCLUSION: We found that GCS, MVT, albumin, CRP, smoking, and DCI are independent predictors for the development of POP in patients with aSAH. Overall, our nomogram represents a reliable and convenient approach to predict POP in the patient population. |
format | Online Article Text |
id | pubmed-10513064 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105130642023-09-22 Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage Jin, Xiao Wang, Shijia Zhang, Chengwei Yang, Song Lou, Lejing Xu, Shuyao Cai, Chang Front Neurol Neurology BACKGROUND: Postoperative pneumonia (POP) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) associated with increased mortality rates, prolonged hospitalization, and high medical costs. It is currently understood that identifying pneumonia early and implementing aggressive treatment can significantly improve patients' outcomes. The primary objective of this study was to explore risk factors and develop a logistic regression model that assesses the risks of POP. METHODS: An internal cohort of 613 inpatients with aSAH who underwent surgery at the Neurosurgical Department of First Affiliated Hospital of Wenzhou Medical University was retrospectively analyzed to develop a nomogram for predicting POP. We assessed the discriminative power, accuracy, and clinical validity of the predictions by using the area under the receiver operating characteristic curve (AUC), the calibration curve, and decision curve analysis (DCA). The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. RESULTS: Among patients in our internal cohort, 15.66% (n = 96/613) of patients had POP. The least absolute shrinkage and selection operator (LASSO) regression analysis identified the Glasgow Coma Scale (GCS), mechanical ventilation time (MVT), albumin, C-reactive protein (CRP), smoking, and delayed cerebral ischemia (DCI) as potential predictors of POP. We then used multivariable logistic regression analysis to evaluate the effects of these predictors and create a final model. Eighty percentage of patients in the internal cohort were randomly assigned to the training set for model development, while the remaining 20% of patients were allocated to the internal validation set. The AUC values for the training, internal, and external validation sets were 0.914, 0.856, and 0.851, and the corresponding Brier scores were 0.084, 0.098, and 0.143, respectively. CONCLUSION: We found that GCS, MVT, albumin, CRP, smoking, and DCI are independent predictors for the development of POP in patients with aSAH. Overall, our nomogram represents a reliable and convenient approach to predict POP in the patient population. Frontiers Media S.A. 2023-09-04 /pmc/articles/PMC10513064/ /pubmed/37745673 http://dx.doi.org/10.3389/fneur.2023.1251570 Text en Copyright © 2023 Jin, Wang, Zhang, Yang, Lou, Xu and Cai. https://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 | Neurology Jin, Xiao Wang, Shijia Zhang, Chengwei Yang, Song Lou, Lejing Xu, Shuyao Cai, Chang Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
title | Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
title_full | Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
title_fullStr | Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
title_full_unstemmed | Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
title_short | Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
title_sort | development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513064/ https://www.ncbi.nlm.nih.gov/pubmed/37745673 http://dx.doi.org/10.3389/fneur.2023.1251570 |
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