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A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome

Background: The aim of this study was to construct and validate a simple-to-use model to predict the survival of patients with acute respiratory distress syndrome. Methods: A total of 197 patients with acute respiratory distress syndrome were selected from the Dryad Digital Repository. All eligible...

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Autores principales: Liu, Yong, Liu, Jian, Huang, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921740/
https://www.ncbi.nlm.nih.gov/pubmed/33665197
http://dx.doi.org/10.3389/fmed.2021.604694
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author Liu, Yong
Liu, Jian
Huang, Liang
author_facet Liu, Yong
Liu, Jian
Huang, Liang
author_sort Liu, Yong
collection PubMed
description Background: The aim of this study was to construct and validate a simple-to-use model to predict the survival of patients with acute respiratory distress syndrome. Methods: A total of 197 patients with acute respiratory distress syndrome were selected from the Dryad Digital Repository. All eligible individuals were randomly stratified into the training set (n=133) and the validation set (n=64) as 2: 1 ratio. LASSO regression analysis was used to select the optimal predictors, and receiver operating characteristic and calibration curves were used to evaluate accuracy and discrimination of the model. Clinical usefulness of the model was also assessed using decision curve analysis and Kaplan-Meier analysis. Results: Age, albumin, platelet count, PaO(2)/FiO(2), lactate dehydrogenase, high-resolution computed tomography score, and etiology were identified as independent prognostic factors based on LASSO regression analysis; these factors were integrated for the construction of the nomogram. Results of calibration plots, decision curve analysis, and receiver operating characteristic analysis showed that this model has good predictive ability of patient survival in acute respiratory distress syndrome. Moreover, a significant difference in the 28-day survival was shown between the patients stratified into different risk groups (P < 0.001). For convenient application, we also established a web-based calculator (https://huangl.shinyapps.io/ARDSprognosis/). Conclusions: We satisfactorily constructed a simple-to-use model based on seven relevant factors to predict survival and prognosis of patients with acute respiratory distress syndrome. This model can aid personalized treatment and clinical decision-making.
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spelling pubmed-79217402021-03-03 A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome Liu, Yong Liu, Jian Huang, Liang Front Med (Lausanne) Medicine Background: The aim of this study was to construct and validate a simple-to-use model to predict the survival of patients with acute respiratory distress syndrome. Methods: A total of 197 patients with acute respiratory distress syndrome were selected from the Dryad Digital Repository. All eligible individuals were randomly stratified into the training set (n=133) and the validation set (n=64) as 2: 1 ratio. LASSO regression analysis was used to select the optimal predictors, and receiver operating characteristic and calibration curves were used to evaluate accuracy and discrimination of the model. Clinical usefulness of the model was also assessed using decision curve analysis and Kaplan-Meier analysis. Results: Age, albumin, platelet count, PaO(2)/FiO(2), lactate dehydrogenase, high-resolution computed tomography score, and etiology were identified as independent prognostic factors based on LASSO regression analysis; these factors were integrated for the construction of the nomogram. Results of calibration plots, decision curve analysis, and receiver operating characteristic analysis showed that this model has good predictive ability of patient survival in acute respiratory distress syndrome. Moreover, a significant difference in the 28-day survival was shown between the patients stratified into different risk groups (P < 0.001). For convenient application, we also established a web-based calculator (https://huangl.shinyapps.io/ARDSprognosis/). Conclusions: We satisfactorily constructed a simple-to-use model based on seven relevant factors to predict survival and prognosis of patients with acute respiratory distress syndrome. This model can aid personalized treatment and clinical decision-making. Frontiers Media S.A. 2021-02-16 /pmc/articles/PMC7921740/ /pubmed/33665197 http://dx.doi.org/10.3389/fmed.2021.604694 Text en Copyright © 2021 Liu, Liu and Huang. 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 Medicine
Liu, Yong
Liu, Jian
Huang, Liang
A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome
title A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome
title_full A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome
title_fullStr A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome
title_full_unstemmed A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome
title_short A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome
title_sort simple-to-use web-based calculator for survival prediction in acute respiratory distress syndrome
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921740/
https://www.ncbi.nlm.nih.gov/pubmed/33665197
http://dx.doi.org/10.3389/fmed.2021.604694
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