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C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram
To develop a C-reactive protein-to-albumin ratio (CAR)-based nomogram for predicting the risk of in-hospital death in sepsis patients. Sepsis patients were selected from the MIMIC-IV database. Independent predictors were determined by multiple Cox analysis and then integrated to predict survival. Th...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504378/ https://www.ncbi.nlm.nih.gov/pubmed/37714898 http://dx.doi.org/10.1038/s41598-023-42601-4 |
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author | Zhou, Xin Fu, Shouzhi Wu, Yisi Guo, Zhenhui Dian, Wankang Sun, Huibin Liao, Youxia |
author_facet | Zhou, Xin Fu, Shouzhi Wu, Yisi Guo, Zhenhui Dian, Wankang Sun, Huibin Liao, Youxia |
author_sort | Zhou, Xin |
collection | PubMed |
description | To develop a C-reactive protein-to-albumin ratio (CAR)-based nomogram for predicting the risk of in-hospital death in sepsis patients. Sepsis patients were selected from the MIMIC-IV database. Independent predictors were determined by multiple Cox analysis and then integrated to predict survival. The performance of the model was evaluated using the concordance index (C-index), receiver operating characteristic curve (ROC) analysis, and calibration curve. The risk stratifications analysis and subgroup analysis of the model in overall survival (OS) were assessed by Kaplan–Meier (K–M) curves. A total of 6414 sepsis patients were included. C-index of the CAR-based model was 0.917 [standard error (SE): 0.112] for the training set and 0.935 (SE: 0.010) for the validation set. The ROC curve analysis showed that the area under the curve (AUC) of the nomogram was 0.881 in the training set and 0.801 in the validation set. And the calibration curve showed that the nomogram performs well in both the training and validation sets. K–M curves indicated that patients with high CAR had significantly higher in-hospital mortality than those with low CAR. The CAR-based model has considerably high accuracy for predicting the OS of sepsis patients. |
format | Online Article Text |
id | pubmed-10504378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105043782023-09-17 C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram Zhou, Xin Fu, Shouzhi Wu, Yisi Guo, Zhenhui Dian, Wankang Sun, Huibin Liao, Youxia Sci Rep Article To develop a C-reactive protein-to-albumin ratio (CAR)-based nomogram for predicting the risk of in-hospital death in sepsis patients. Sepsis patients were selected from the MIMIC-IV database. Independent predictors were determined by multiple Cox analysis and then integrated to predict survival. The performance of the model was evaluated using the concordance index (C-index), receiver operating characteristic curve (ROC) analysis, and calibration curve. The risk stratifications analysis and subgroup analysis of the model in overall survival (OS) were assessed by Kaplan–Meier (K–M) curves. A total of 6414 sepsis patients were included. C-index of the CAR-based model was 0.917 [standard error (SE): 0.112] for the training set and 0.935 (SE: 0.010) for the validation set. The ROC curve analysis showed that the area under the curve (AUC) of the nomogram was 0.881 in the training set and 0.801 in the validation set. And the calibration curve showed that the nomogram performs well in both the training and validation sets. K–M curves indicated that patients with high CAR had significantly higher in-hospital mortality than those with low CAR. The CAR-based model has considerably high accuracy for predicting the OS of sepsis patients. Nature Publishing Group UK 2023-09-15 /pmc/articles/PMC10504378/ /pubmed/37714898 http://dx.doi.org/10.1038/s41598-023-42601-4 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/) . |
spellingShingle | Article Zhou, Xin Fu, Shouzhi Wu, Yisi Guo, Zhenhui Dian, Wankang Sun, Huibin Liao, Youxia C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram |
title | C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram |
title_full | C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram |
title_fullStr | C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram |
title_full_unstemmed | C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram |
title_short | C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram |
title_sort | c-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel lasso-cox based prognostic nomogram |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504378/ https://www.ncbi.nlm.nih.gov/pubmed/37714898 http://dx.doi.org/10.1038/s41598-023-42601-4 |
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