A Novel Model for Predicting the Death Risk of Severe Traumatic Brain Injury during Hospitalization

BACKGROUND: Patients with severe traumatic brain injury (sTBI) often presents with extracranial injuries, which may contribute to fatal outcome. The aim of this study was to construct the best death prediction model for sTBI and provide a feasible basis for early prognosis. METHODS: A retrospective study from the First Affiliated Hospital of Guangxi Medical University from January 2012 to September 2020 was performed. Relevant risk factors at admission and record survival were collected at discharge. Logistic regression was used to establish a death prediction model. The performance of the model was predicted by fitting goodness test and calculating the area under the ROC curve (AUC). The DCA curve was used to show the net benefit rate of patients. RESULTS: Of the 190 patients with sTBI, 91 died during hospitalization, with a mortality rate of 47.8 percent. Pupillary dilation, occipital lobe injury, SAH, cerebral hernia, and APACHE II score could predict the probability of death alone, with AUC of 0.636, 0.595, 0.611, 0.599 and 0.621 respectively. The AUC of death prediction for patients with sTBI was 0.860, and its sensitivity and specificity were 88.60% and 81.60%. The calibration and decision curve analysis (DCA) were conducted to validate the performance and clinical value of the novel model. CONCLUSIONS: The clinic-radiomic model incorporating both clinical factors and radiomic signature showed good performance for mortality risk prediction of sTBI. The predictive model can identify sTBI with high sensitivity and can be applied in patients with sTBI.

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Selection of children with ultra-severe traumatic brain injury for neurosurgical intervention

Journal of Neurosurgery Pediatrics ◽

10.3171/2019.1.peds18293 ◽

2019 ◽

Vol 23 (6) ◽

pp. 670-679

Author(s):

Krista Greenan ◽

Sandra L. Taylor ◽

Daniel Fulkerson ◽

Kiarash Shahlaie ◽

Clayton Gerndt ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Decision Tree ◽

Prediction Model ◽

Severe Traumatic Brain Injury ◽

Pupillary Response ◽

Data Set ◽

Robust Model ◽

Gcs Score ◽

Combined Data

OBJECTIVEA recent retrospective study of severe traumatic brain injury (TBI) in pediatric patients showed similar outcomes in those with a Glasgow Coma Scale (GCS) score of 3 and those with a score of 4 and reported a favorable long-term outcome in 11.9% of patients. Using decision tree analysis, authors of that study provided criteria to identify patients with a potentially favorable outcome. The authors of the present study sought to validate the previously described decision tree and further inform understanding of the outcomes of children with a GCS score 3 or 4 by using data from multiple institutions and machine learning methods to identify important predictors of outcome.METHODSClinical, radiographic, and outcome data on pediatric TBI patients (age < 18 years) were prospectively collected as part of an institutional TBI registry. Patients with a GCS score of 3 or 4 were selected, and the previously published prediction model was evaluated using this data set. Next, a combined data set that included data from two institutions was used to create a new, more statistically robust model using binomial recursive partitioning to create a decision tree.RESULTSForty-five patients from the institutional TBI registry were included in the present study, as were 67 patients from the previously published data set, for a total of 112 patients in the combined analysis. The previously published prediction model for survival was externally validated and performed only modestly (AUC 0.68, 95% CI 0.47, 0.89). In the combined data set, pupillary response and age were the only predictors retained in the decision tree. Ninety-six percent of patients with bilaterally nonreactive pupils had a poor outcome. If the pupillary response was normal in at least one eye, the outcome subsequently depended on age: 72% of children between 5 months and 6 years old had a favorable outcome, whereas 100% of children younger than 5 months old and 77% of those older than 6 years had poor outcomes. The overall accuracy of the combined prediction model was 90.2% with a sensitivity of 68.4% and specificity of 93.6%.CONCLUSIONSA previously published survival model for severe TBI in children with a low GCS score was externally validated. With a larger data set, however, a simplified and more robust model was developed, and the variables most predictive of outcome were age and pupillary response.

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Outcome prediction model for severe traumatic brain injury

Acute Medicine & Surgery ◽

10.1002/ams2.5 ◽

2013 ◽

Vol 1 (1) ◽

pp. 31-36 ◽

Cited By ~ 3

Author(s):

Jiro Iba ◽

Osamu Tasaki ◽

Tomohito Hirao ◽

Tomoyoshi Mohri ◽

Kazuhisa Yoshiya ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Prediction Model ◽

Severe Traumatic Brain Injury ◽

Outcome Prediction

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Increased levels of interleukin-6, -8 and -10 are associated with fatal outcome following severe traumatic brain injury

Brain Injury ◽

10.3109/02699052.2014.916818 ◽

2014 ◽

Vol 28 (10) ◽

pp. 1311-1316 ◽

Cited By ~ 53

Author(s):

Luiz Carlos Brasiliano Ferreira ◽

Andrea Regner ◽

Karen Dal Lago Miotto ◽

Silvana de Moura ◽

Nilo Ikuta ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Severe Traumatic Brain Injury ◽

Interleukin 6 ◽

Fatal Outcome

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Early modifiable factors associated with fatal outcome in patients with severe traumatic brain injury: A case control study*

Critical Care Medicine ◽

10.1097/01.ccm.0000259526.45894.08 ◽

2007 ◽

Vol 35 (4) ◽

pp. 1027-1031 ◽

Cited By ~ 21

Author(s):

Dietrich Henzler ◽

D James Cooper ◽

Ann B. Tremayne ◽

Rolf Rossaint ◽

Alisa Higgins

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Severe Traumatic Brain Injury ◽

Case Control Study ◽

Fatal Outcome ◽

Case Control ◽

Factors Associated ◽

Modifiable Factors ◽

Control Study

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Temporal profile of intracranial pressure and cerebrovascular reactivity in severe traumatic brain injury and association with fatal outcome: An observational study

PLoS Medicine ◽

10.1371/journal.pmed.1002353 ◽

2017 ◽

Vol 14 (7) ◽

pp. e1002353 ◽

Cited By ~ 27

Author(s):

Hadie Adams ◽

Joseph Donnelly ◽

Marek Czosnyka ◽

Angelos G. Kolias ◽

Adel Helmy ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Intracranial Pressure ◽

Observational Study ◽

Severe Traumatic Brain Injury ◽

Fatal Outcome ◽

Cerebrovascular Reactivity ◽

Temporal Profile

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IL-6 polymorphism associated with fatal outcome in patients with severe traumatic brain injury

Brain Injury ◽

10.3109/02699052.2011.556107 ◽

2011 ◽

Vol 25 (4) ◽

pp. 365-369 ◽

Cited By ~ 34

Author(s):

André Luiz Dalla Libera ◽

Andrea Regner ◽

Juliana de Paoli ◽

Leonara Centenaro ◽

Tatiane Tolazzi Martins ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Severe Traumatic Brain Injury ◽

Fatal Outcome

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Elevated PCT at ICU discharge predicts poor prognosis in patients with severe traumatic brain injury: a retrospective cohort study

Journal of International Medical Research ◽

10.1177/0300060520922456 ◽

2020 ◽

Vol 48 (5) ◽

pp. 030006052092245

Author(s):

Yu-rong Wang ◽

Qing-bin Zheng ◽

Guang-fa Wei ◽

Li-jun Meng ◽

Qing-ling Feng ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Cohort Study ◽

Brain Injury ◽

Severe Traumatic Brain Injury ◽

Poor Prognosis ◽

Clinical Decision Making ◽

Elevated Serum ◽

Adverse Outcomes ◽

Apache Ii Score ◽

Icu Discharge

Purpose Disease severity and inflammatory response status are closely related to a poor prognosis and must be assessed in patients with severe traumatic brain injury (STBI) before intensive care unit (ICU) discharge. Whether elevated serum procalcitonin (PCT) levels can predict a poor prognosis in STBI patients before ICU discharge is unclear. Methods This retrospective observational cohort study enrolled 199 STBI patients who were in the ICU for at least 48 hours and survived after discharge. Based on serum PCT levels at discharge, patients were divided into the high-PCT group (PCT ≥ 0.25 ng/mL) and the low-PCT group (PCT < 0.25 ng/mL). We assessed the relationship between serum PCT levels and a poor prognosis. Results The high-PCT group had a higher rate of adverse outcomes compared with the low-PCT group. Multivariate logistic regression analysis showed that the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, white blood cell (WBC) count, C-reactive protein (CRP) level, and PCT level at discharge were significantly associated with adverse outcomes. Conclusions Elevated PCT levels at ICU discharge were associated with a poor prognosis in STBI patients. The serum PCT level as a single indicator has limited value for clinical decision-making.

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