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A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III
OBJECTIVE: To develop a nomogram for predicting the occurrence of sepsis-associated delirium (SAD). MATERIALS AND METHODS: Data from a total of 642 patients were retrieved from the Medical Information Mart for Intensive Care (MIMIC III) database to build a prediction model. Multivariate logistic reg...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503010/ https://www.ncbi.nlm.nih.gov/pubmed/37715189 http://dx.doi.org/10.1186/s12911-023-02282-5 |
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author | Gu, Qiong Yang, Shucong Fei, DanTing Lu, Yuting Yu, Huijie |
author_facet | Gu, Qiong Yang, Shucong Fei, DanTing Lu, Yuting Yu, Huijie |
author_sort | Gu, Qiong |
collection | PubMed |
description | OBJECTIVE: To develop a nomogram for predicting the occurrence of sepsis-associated delirium (SAD). MATERIALS AND METHODS: Data from a total of 642 patients were retrieved from the Medical Information Mart for Intensive Care (MIMIC III) database to build a prediction model. Multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of SAD. The performance of the nomogram was assessed in terms of discrimination and calibration by bootstrapping with 1000 resamples. RESULTS: Multivariate logistic regression identified 4 independent predictors for patients with SAD, including Sepsis-related Organ Failure Assessment(SOFA) (p = 0.004; OR: 1.131; 95% CI 1.040 to 1.231), mechanical ventilation (P < 0.001; OR: 3.710; 95% CI 2.452 to 5.676), phosphate (P = 0.047; OR: 1.165; 95% CI 1.003 to 1.358), and lactate (P = 0.023; OR: 1.135; 95% CI 1.021 to 1.270) within 24 h of intensive care unit (ICU) admission. The area under the curve (AUC) of the predictive model was 0.742 in the training set and 0.713 in the validation set. The Hosmer − Lemeshow test showed that the model was a good fit (p = 0.471). The calibration curve of the predictive model was close to the ideal curve in both the training and validation sets. The DCA curve also showed that the predictive nomogram was clinically useful. CONCLUSION: We constructed a nomogram for the personalized prediction of delirium in sepsis patients, which had satisfactory performance and clinical utility and thus could help clinicians identify patients with SAD in a timely manner, perform early intervention, and improve their neurological outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02282-5. |
format | Online Article Text |
id | pubmed-10503010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105030102023-09-16 A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III Gu, Qiong Yang, Shucong Fei, DanTing Lu, Yuting Yu, Huijie BMC Med Inform Decis Mak Research OBJECTIVE: To develop a nomogram for predicting the occurrence of sepsis-associated delirium (SAD). MATERIALS AND METHODS: Data from a total of 642 patients were retrieved from the Medical Information Mart for Intensive Care (MIMIC III) database to build a prediction model. Multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of SAD. The performance of the nomogram was assessed in terms of discrimination and calibration by bootstrapping with 1000 resamples. RESULTS: Multivariate logistic regression identified 4 independent predictors for patients with SAD, including Sepsis-related Organ Failure Assessment(SOFA) (p = 0.004; OR: 1.131; 95% CI 1.040 to 1.231), mechanical ventilation (P < 0.001; OR: 3.710; 95% CI 2.452 to 5.676), phosphate (P = 0.047; OR: 1.165; 95% CI 1.003 to 1.358), and lactate (P = 0.023; OR: 1.135; 95% CI 1.021 to 1.270) within 24 h of intensive care unit (ICU) admission. The area under the curve (AUC) of the predictive model was 0.742 in the training set and 0.713 in the validation set. The Hosmer − Lemeshow test showed that the model was a good fit (p = 0.471). The calibration curve of the predictive model was close to the ideal curve in both the training and validation sets. The DCA curve also showed that the predictive nomogram was clinically useful. CONCLUSION: We constructed a nomogram for the personalized prediction of delirium in sepsis patients, which had satisfactory performance and clinical utility and thus could help clinicians identify patients with SAD in a timely manner, perform early intervention, and improve their neurological outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02282-5. BioMed Central 2023-09-15 /pmc/articles/PMC10503010/ /pubmed/37715189 http://dx.doi.org/10.1186/s12911-023-02282-5 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 Gu, Qiong Yang, Shucong Fei, DanTing Lu, Yuting Yu, Huijie A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III |
title | A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III |
title_full | A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III |
title_fullStr | A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III |
title_full_unstemmed | A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III |
title_short | A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III |
title_sort | nomogram for predicting sepsis-associated delirium: a retrospective study in mimic iii |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503010/ https://www.ncbi.nlm.nih.gov/pubmed/37715189 http://dx.doi.org/10.1186/s12911-023-02282-5 |
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