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Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury
Traumatic brain injury (TBI) occurs frequently, and acute TBI requiring surgical treatment is closely related to patient survival. Models for predicting the prognosis of patients with TBI do not consider various factors of patient status; therefore, it is difficult to predict the prognosis more accu...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181160/ https://www.ncbi.nlm.nih.gov/pubmed/35683607 http://dx.doi.org/10.3390/jcm11113220 |
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author | Kim, Sol Bi Park, Youngjoon Ahn, Ju Won Sim, Jeongmin Park, Jeongman Kim, Yu Jin Hwang, So Jung Sung, Kyoung Su Lim, Jaejoon |
author_facet | Kim, Sol Bi Park, Youngjoon Ahn, Ju Won Sim, Jeongmin Park, Jeongman Kim, Yu Jin Hwang, So Jung Sung, Kyoung Su Lim, Jaejoon |
author_sort | Kim, Sol Bi |
collection | PubMed |
description | Traumatic brain injury (TBI) occurs frequently, and acute TBI requiring surgical treatment is closely related to patient survival. Models for predicting the prognosis of patients with TBI do not consider various factors of patient status; therefore, it is difficult to predict the prognosis more accurately. In this study, we created a model that can predict the survival of patients with TBI by adding hematologic parameters along with existing non-hematologic parameters. The best-fitting model was created using the Akaike information criterion (AIC), and hematologic factors including preoperative hematocrit, preoperative C-reactive protein (CRP), postoperative white blood cell (WBC) count, and postoperative hemoglobin were selected to predict the prognosis. Among several prediction models, the model that included age, Glasgow Coma Scale, Injury Severity Score, preoperative hematocrit, preoperative CRP, postoperative WBC count, postoperative hemoglobin, and postoperative CRP showed the highest area under the curve and the lowest corrected AIC for a finite sample size. Our study showed a new prediction model for mortality in patients with TBI using non-hematologic and hematologic parameters. This prediction model could be useful for the management of patients with TBI. |
format | Online Article Text |
id | pubmed-9181160 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91811602022-06-10 Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury Kim, Sol Bi Park, Youngjoon Ahn, Ju Won Sim, Jeongmin Park, Jeongman Kim, Yu Jin Hwang, So Jung Sung, Kyoung Su Lim, Jaejoon J Clin Med Article Traumatic brain injury (TBI) occurs frequently, and acute TBI requiring surgical treatment is closely related to patient survival. Models for predicting the prognosis of patients with TBI do not consider various factors of patient status; therefore, it is difficult to predict the prognosis more accurately. In this study, we created a model that can predict the survival of patients with TBI by adding hematologic parameters along with existing non-hematologic parameters. The best-fitting model was created using the Akaike information criterion (AIC), and hematologic factors including preoperative hematocrit, preoperative C-reactive protein (CRP), postoperative white blood cell (WBC) count, and postoperative hemoglobin were selected to predict the prognosis. Among several prediction models, the model that included age, Glasgow Coma Scale, Injury Severity Score, preoperative hematocrit, preoperative CRP, postoperative WBC count, postoperative hemoglobin, and postoperative CRP showed the highest area under the curve and the lowest corrected AIC for a finite sample size. Our study showed a new prediction model for mortality in patients with TBI using non-hematologic and hematologic parameters. This prediction model could be useful for the management of patients with TBI. MDPI 2022-06-05 /pmc/articles/PMC9181160/ /pubmed/35683607 http://dx.doi.org/10.3390/jcm11113220 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Sol Bi Park, Youngjoon Ahn, Ju Won Sim, Jeongmin Park, Jeongman Kim, Yu Jin Hwang, So Jung Sung, Kyoung Su Lim, Jaejoon Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury |
title | Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury |
title_full | Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury |
title_fullStr | Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury |
title_full_unstemmed | Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury |
title_short | Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury |
title_sort | potential of hematologic parameters in predicting mortality of patients with traumatic brain injury |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181160/ https://www.ncbi.nlm.nih.gov/pubmed/35683607 http://dx.doi.org/10.3390/jcm11113220 |
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