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Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching
BACKGROUND: The predictive value of red blood cell distribution width (RDW) for mortality in patients with sepsis-induced acute kidney injury (SI-AKI) remains unclear. The present study aimed to investigate the potential association between RDW at admission and outcomes in patients with SI-AKI. METH...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391576/ https://www.ncbi.nlm.nih.gov/pubmed/37533812 http://dx.doi.org/10.1016/j.jointm.2023.02.005 |
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author | Lai, Honghao Wu, Guosheng Zhong, Yu Chen, Guangping Zhang, Wei Shi, Shengjun Xia, Zhaofan |
author_facet | Lai, Honghao Wu, Guosheng Zhong, Yu Chen, Guangping Zhang, Wei Shi, Shengjun Xia, Zhaofan |
author_sort | Lai, Honghao |
collection | PubMed |
description | BACKGROUND: The predictive value of red blood cell distribution width (RDW) for mortality in patients with sepsis-induced acute kidney injury (SI-AKI) remains unclear. The present study aimed to investigate the potential association between RDW at admission and outcomes in patients with SI-AKI. METHODS: The Medical Information Mart for Intensive Care (MIMIC)-IV (version 2.0) database, released in June of 2022, provides medical data of SI-AKI patients to conduct our related research. Based on propensity score matching (PSM) method, the main risk factors associated with mortality in SI-AKI were evaluated using Cox proportional hazards regression analysis to construct a predictive nomogram. The concordance index (C-index) and decision curve analysis were used to validate the predictive ability and clinical utility of this model. Patients with SI-AKI were classified into the high- and low-RDW groups according to the best cut-off value obtained by calculating the maximum value of the Youden index. RESULTS: A total of 7574 patients with SI-AKI were identified according to the filter criteria. Compared with the low-RDW group, the high-RDW group had higher 28-day (9.49% vs. 31.40%, respectively, P <0.001) and 7-day (3.96% vs. 13.93%, respectively, P <0.001) mortality rates. Patients in the high-RDW group were more prone to AKI progression than those in the low-RDW group (20.80% vs. 13.60%, respectively, P <0.001). Based on matched patients, we developed a nomogram model that included age, white blood cells, RDW, combined hypertension and presence of a malignant tumor, treatment with vasopressor, dialysis, and invasive ventilation, sequential organ failure assessment, and AKI stages. The C-index for predicting the probability of 28-day survival was 0.799. Decision curve analysis revealed that the model with RDW offered greater net benefit than that without RDW. CONCLUSION: The present findings demonstrated the importance of RDW, which improved the predictive ability of the nomogram model for the probability of survival in patients with SI-AKI. |
format | Online Article Text |
id | pubmed-10391576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103915762023-08-02 Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching Lai, Honghao Wu, Guosheng Zhong, Yu Chen, Guangping Zhang, Wei Shi, Shengjun Xia, Zhaofan J Intensive Med Original Article BACKGROUND: The predictive value of red blood cell distribution width (RDW) for mortality in patients with sepsis-induced acute kidney injury (SI-AKI) remains unclear. The present study aimed to investigate the potential association between RDW at admission and outcomes in patients with SI-AKI. METHODS: The Medical Information Mart for Intensive Care (MIMIC)-IV (version 2.0) database, released in June of 2022, provides medical data of SI-AKI patients to conduct our related research. Based on propensity score matching (PSM) method, the main risk factors associated with mortality in SI-AKI were evaluated using Cox proportional hazards regression analysis to construct a predictive nomogram. The concordance index (C-index) and decision curve analysis were used to validate the predictive ability and clinical utility of this model. Patients with SI-AKI were classified into the high- and low-RDW groups according to the best cut-off value obtained by calculating the maximum value of the Youden index. RESULTS: A total of 7574 patients with SI-AKI were identified according to the filter criteria. Compared with the low-RDW group, the high-RDW group had higher 28-day (9.49% vs. 31.40%, respectively, P <0.001) and 7-day (3.96% vs. 13.93%, respectively, P <0.001) mortality rates. Patients in the high-RDW group were more prone to AKI progression than those in the low-RDW group (20.80% vs. 13.60%, respectively, P <0.001). Based on matched patients, we developed a nomogram model that included age, white blood cells, RDW, combined hypertension and presence of a malignant tumor, treatment with vasopressor, dialysis, and invasive ventilation, sequential organ failure assessment, and AKI stages. The C-index for predicting the probability of 28-day survival was 0.799. Decision curve analysis revealed that the model with RDW offered greater net benefit than that without RDW. CONCLUSION: The present findings demonstrated the importance of RDW, which improved the predictive ability of the nomogram model for the probability of survival in patients with SI-AKI. Elsevier 2023-04-20 /pmc/articles/PMC10391576/ /pubmed/37533812 http://dx.doi.org/10.1016/j.jointm.2023.02.005 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Lai, Honghao Wu, Guosheng Zhong, Yu Chen, Guangping Zhang, Wei Shi, Shengjun Xia, Zhaofan Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching |
title | Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching |
title_full | Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching |
title_fullStr | Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching |
title_full_unstemmed | Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching |
title_short | Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching |
title_sort | red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: a retrospective analysis from mimic-iv database using propensity score matching |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391576/ https://www.ncbi.nlm.nih.gov/pubmed/37533812 http://dx.doi.org/10.1016/j.jointm.2023.02.005 |
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