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C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study
BACKGROUND: It is not clear whether there are valuable inflammatory markers for prognosis judgment in the intensive care unit (ICU). We therefore conducted a multicenter, prospective, observational study to evaluate the prognostic role of inflammatory markers. METHODS: The clinical and laboratory da...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680994/ https://www.ncbi.nlm.nih.gov/pubmed/33225902 http://dx.doi.org/10.1186/s12871-020-01207-3 |
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author | Qu, Rong Hu, Linhui Ling, Yun Hou, Yating Fang, Heng Zhang, Huidan Liang, Silin He, Zhimei Fang, Miaoxian Li, Jiaxin Li, Xu Chen, Chunbo |
author_facet | Qu, Rong Hu, Linhui Ling, Yun Hou, Yating Fang, Heng Zhang, Huidan Liang, Silin He, Zhimei Fang, Miaoxian Li, Jiaxin Li, Xu Chen, Chunbo |
author_sort | Qu, Rong |
collection | PubMed |
description | BACKGROUND: It is not clear whether there are valuable inflammatory markers for prognosis judgment in the intensive care unit (ICU). We therefore conducted a multicenter, prospective, observational study to evaluate the prognostic role of inflammatory markers. METHODS: The clinical and laboratory data of patients at admission, including C-reactive protein (CRP), were collected in four general ICUs from September 1, 2018, to August 1, 2019. Multivariate logistic regression was used to identify factors independently associated with nonsurvival. The area under the receiver operating characteristic curve (AUC-ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate the effect size of different factors in predicting mortality during ICU stay. 3 -knots were used to assess whether alternative cut points for these biomarkers were more appropriate. RESULTS: A total of 813 patients were recruited, among whom 121 patients (14.88%) died during the ICU stay. The AUC-ROC values of PCT and CRP for discriminating ICU mortality were 0.696 (95% confidence interval [CI], 0.650–0.743) and 0.684 (95% CI, 0.633–0.735), respectively. In the multivariable analysis, only APACHE II score (odds ratio, 1.166; 95% CI, 1.129–1.203; P = 0.000) and CRP concentration > 62.8 mg/L (odds ratio, 2.145; 95% CI, 1.343–3.427; P = 0.001), were significantly associated with an increased risk of ICU mortality. Moreover, the combination of APACHE II score and CRP > 62.8 mg/L significantly improved risk reclassification over the APACHE II score alone, with NRI (0.556) and IDI (0.013). Restricted cubic spline analysis confirmed that CRP concentration > 62.8 mg/L was the optimal cut-off value for differentiating between surviving and nonsurviving patients. CONCLUSION: CRP markedly improved risk reclassification for prognosis prediction. |
format | Online Article Text |
id | pubmed-7680994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76809942020-11-23 C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study Qu, Rong Hu, Linhui Ling, Yun Hou, Yating Fang, Heng Zhang, Huidan Liang, Silin He, Zhimei Fang, Miaoxian Li, Jiaxin Li, Xu Chen, Chunbo BMC Anesthesiol Research Article BACKGROUND: It is not clear whether there are valuable inflammatory markers for prognosis judgment in the intensive care unit (ICU). We therefore conducted a multicenter, prospective, observational study to evaluate the prognostic role of inflammatory markers. METHODS: The clinical and laboratory data of patients at admission, including C-reactive protein (CRP), were collected in four general ICUs from September 1, 2018, to August 1, 2019. Multivariate logistic regression was used to identify factors independently associated with nonsurvival. The area under the receiver operating characteristic curve (AUC-ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate the effect size of different factors in predicting mortality during ICU stay. 3 -knots were used to assess whether alternative cut points for these biomarkers were more appropriate. RESULTS: A total of 813 patients were recruited, among whom 121 patients (14.88%) died during the ICU stay. The AUC-ROC values of PCT and CRP for discriminating ICU mortality were 0.696 (95% confidence interval [CI], 0.650–0.743) and 0.684 (95% CI, 0.633–0.735), respectively. In the multivariable analysis, only APACHE II score (odds ratio, 1.166; 95% CI, 1.129–1.203; P = 0.000) and CRP concentration > 62.8 mg/L (odds ratio, 2.145; 95% CI, 1.343–3.427; P = 0.001), were significantly associated with an increased risk of ICU mortality. Moreover, the combination of APACHE II score and CRP > 62.8 mg/L significantly improved risk reclassification over the APACHE II score alone, with NRI (0.556) and IDI (0.013). Restricted cubic spline analysis confirmed that CRP concentration > 62.8 mg/L was the optimal cut-off value for differentiating between surviving and nonsurviving patients. CONCLUSION: CRP markedly improved risk reclassification for prognosis prediction. BioMed Central 2020-11-23 /pmc/articles/PMC7680994/ /pubmed/33225902 http://dx.doi.org/10.1186/s12871-020-01207-3 Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://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 Article Qu, Rong Hu, Linhui Ling, Yun Hou, Yating Fang, Heng Zhang, Huidan Liang, Silin He, Zhimei Fang, Miaoxian Li, Jiaxin Li, Xu Chen, Chunbo C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
title | C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
title_full | C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
title_fullStr | C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
title_full_unstemmed | C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
title_short | C-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
title_sort | c-reactive protein concentration as a risk predictor of mortality in intensive care unit: a multicenter, prospective, observational study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680994/ https://www.ncbi.nlm.nih.gov/pubmed/33225902 http://dx.doi.org/10.1186/s12871-020-01207-3 |
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