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      The establishment and validation of a prediction model for traumatic intracranial injury patients: a reliable nomogram

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          Abstract

          Objective

          Traumatic brain injury (TBI) leads to death and disability. This study developed an effective prognostic nomogram for assessing the risk factors for TBI mortality.

          Method

          Data were extracted from an online database called “Multiparameter Intelligent Monitoring in Intensive Care IV” (MIMIC IV). The ICD code obtained data from 2,551 TBI persons (first ICU stay, >18 years old) from this database. R divided samples into 7:3 training and testing cohorts. The univariate analysis determined whether the two cohorts differed statistically in baseline data. This research used forward stepwise logistic regression after independent prognostic factors for these TBI patients. The optimal variables were selected for the model by the optimal subset method. The optimal feature subsets in pattern recognition improved the model prediction, and the minimum BIC forest of the high-dimensional mixed graph model achieved a better prediction effect. A nomogram-labeled TBI-IHM model containing these risk factors was made by nomology in State software. Least Squares OLS was used to build linear models, and then the Receiver Operating Characteristic (ROC) curve was plotted. The TBI-IHM nomogram model's validity was determined by receiver operating characteristic curves (AUCs), correction curve, Hosmer-Lemeshow test, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision-curve analysis (DCA).

          Result

          The eight features with a minimal BIC model were mannitol use, mechanical ventilation, vasopressor use, international normalized ratio, urea nitrogen, respiratory rate, and cerebrovascular disease. The proposed nomogram (TBI-IHM model) was the best mortality prediction model, with better discrimination and superior model fitting for severely ill TBI patients staying in ICU. The model's receiver operating characteristic curve (ROC) was the best compared to the seven other models. It might be clinically helpful for doctors to make clinical decisions.

          Conclusion

          The proposed nomogram (TBI-IHM model) has significant potential as a clinical utility in predicting mortality in TBI patients.

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          Most cited references35

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          Guidelines for the Management of Severe Traumatic Brain Injury, Fourth Edition.

          The scope and purpose of this work is 2-fold: to synthesize the available evidence and to translate it into recommendations. This document provides recommendations only when there is evidence to support them. As such, they do not constitute a complete protocol for clinical use. Our intention is that these recommendations be used by others to develop treatment protocols, which necessarily need to incorporate consensus and clinical judgment in areas where current evidence is lacking or insufficient. We think it is important to have evidence-based recommendations to clarify what aspects of practice currently can and cannot be supported by evidence, to encourage use of evidence-based treatments that exist, and to encourage creativity in treatment and research in areas where evidence does not exist. The communities of neurosurgery and neuro-intensive care have been early pioneers and supporters of evidence-based medicine and plan to continue in this endeavor. The complete guideline document, which summarizes and evaluates the literature for each topic, and supplemental appendices (A-I) are available online at https://www.braintrauma.org/coma/guidelines.
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            Guidelines for the Management of Severe Traumatic Brain Injury: 2020 Update of the Decompressive Craniectomy Recommendations

            Abstract When the fourth edition of the Brain Trauma Foundation's Guidelines for the Management of Severe Traumatic Brain Injury were finalized in late 2016, it was known that the results of the RESCUEicp (Trial of Decompressive Craniectomy for Traumatic Intracranial Hypertension) randomized controlled trial of decompressive craniectomy would be public after the guidelines were released. The guideline authors decided to proceed with publication but to update the decompressive craniectomy recommendations later in the spirit of “living guidelines,” whereby topics are updated more frequently, and between new editions, when important new evidence is published. The update to the decompressive craniectomy chapter presented here integrates the findings of the RESCUEicp study as well as the recently published 12-mo outcome data from the DECRA (Decompressive Craniectomy in Patients With Severe Traumatic Brain Injury) trial. Incorporation of these publications into the body of evidence led to the generation of 3 new level-IIA recommendations; a fourth previously presented level-IIA recommendation remains valid and has been restated. To increase the utility of the recommendations, we added a new section entitled Incorporating the Evidence into Practice. This summary of expert opinion provides important context and addresses key issues for practitioners, which are intended to help the clinician utilize the available evidence and these recommendations. The full guideline can be found at: https://braintrauma.org/guidelines/guidelines-for-the-management-of-severe-tbi-4th-ed#/.
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              Coagulopathy and haemorrhagic progression in traumatic brain injury: advances in mechanisms, diagnosis, and management.

              Normal haemostasis depends on an intricate balance between mechanisms of bleeding and mechanisms of thrombosis, and this balance can be altered after traumatic brain injury (TBI). Impaired haemostasis could exacerbate the primary insult with risk of initiation or aggravation of bleeding; anticoagulant use at the time of injury can also contribute to bleeding risk after TBI. Many patients with TBI have abnormalities on conventional coagulation tests at admission to the emergency department, and the presence of coagulopathy is associated with increased morbidity and mortality. Further blood testing often reveals a range of changes affecting platelet numbers and function, procoagulant or anticoagulant factors, fibrinolysis, and interactions between the coagulation system and the vascular endothelium, brain tissue, inflammatory mechanisms, and blood flow dynamics. However, the degree to which these coagulation abnormalities affect TBI outcomes and whether they are modifiable risk factors are not known. Although the main challenge for management is to address the risk of hypocoagulopathy with prolonged bleeding and progression of haemorrhagic lesions, the risk of hypercoagulopathy with an increased prothrombotic tendency also warrants consideration.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                25 May 2023
                2023
                : 14
                : 1165020
                Affiliations
                [1] 1Department of Critical Care Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine , Hangzhou, China
                [2] 2Department of Critical Care Medicine, Hangzhou Geriatric Hospital , Hangzhou, China
                [3] 3Department of Intensive Care Unit, The Affiliated Hospital of Hangzhou Normal University , Hangzhou, China
                Author notes

                Edited by: Robert Jeenchen Chen, Stanford University, United States

                Reviewed by: Masoom Desai, University of New Mexico, United States; Zhijie Zhao, Shanghai Jiao Tong University, China

                *Correspondence: Dong Cheng Liang liangdongcheng1222@ 123456163.com

                †These authors have contributed equally to this work

                Article
                10.3389/fneur.2023.1165020
                10249071
                37305757
                2c0304d2-39f8-41aa-8666-5edf2d090dac
                Copyright © 2023 Chen, Jin, Zeng, Ma, Chen, Gu, Qiu, Tian, Pan, Hu and Liang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 February 2023
                : 11 May 2023
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 35, Pages: 12, Words: 6833
                Funding
                This work was supported by the Construction Fund of Medical Key Disciplines of Hangzhou (Grant Number: OO20200485), the Project of Hangzhou Science and Technology (Grant Number: 20201203B198), and Hangzhou Health Science and Technology Plan (A20220388).
                Categories
                Neurology
                Original Research
                Custom metadata
                Neurocritical and Neurohospitalist Care

                Neurology
                traumatic brain injury,mortality,risk factors,nomogram,prediction model
                Neurology
                traumatic brain injury, mortality, risk factors, nomogram, prediction model

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