scholarly journals Predictive Performance of Traumatic Brain Injury Biomarkers in High-Risk Elderly Patients

2019 ◽  
Vol 5 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Matthew D Ward ◽  
Art Weber ◽  
VeRonika D Merrill ◽  
Robert D Welch ◽  
Jeffrey J Bazarian ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
High Risk ◽  
Elderly Patients ◽  
Predictive Performance ◽  
Study Data ◽  
Intracranial Injury ◽  
Younger Patients ◽  
Significant Difference ◽  
Patient Variables

Abstract Background Serum glial fibrillary acidic protein (GFAP) and ubiquitin carboxyl-terminal esterase L1 (UCH-L1) have recently received US Food and Drug Administration approval for prediction of abnormal computed tomography (CT) in mild traumatic brain injury patients (mTBI). However, their performance in elderly patients has not been characterized. Methods We performed a posthoc analysis using the A Prospective Clinical Evaluation of Biomarkers of Traumatic Brain Injury (ALERT-TBI) study data. Previously recorded patient variables and serum values of GFAP and UCH-L1 from mTBI patients were partitioned at 65 years of age (herein referred to as ≥65, high-risk; <65, low-risk). We sought to assess the influence of age on predictive performance, sensitivity, and negative predictive value (NPV) of serum UCH-L1 and GFAP to predict intracranial injury by CT. Results Elderly mTBI patients constituted 25.7% of the patient cohort (n = 504/1959). Sensitivity and NPV of GFAP/UCH-L1 were 100%, with no significant difference from younger patients (P = 0.5525 and P > 0.9999, respectively). Specificity was significantly lower in elderly patients (0.131 vs 0.442; P < 0.0001) and decreased stepwise with older age. Compared to younger patients, elderly mTBI patients without abnormal (i.e., normal) CT findings also had a significantly higher GFAP (38.6 vs 16.2 pg/mL; P < 0.0001) and UCH-L1 (347.4 vs 232.1 pg/mL; P < 0.0001). Conclusions Sensitivity and NPV to predict intracranial injury by CT was nearly identical between younger and elderly mTBI patients. Decrements in specificity and increased serum values suggest that special deference may be warranted for elderly patients.

Predictive Performance of Traumatic Brain Injury Biomarkers in High-Risk Elderly Patients

2020 ◽  
Vol 5 (3) ◽  
pp. 608-608 ◽  
Author(s):  
Matthew D Ward ◽  
Art Weber ◽  
VeRonika D Merrill ◽  
Robert D Welch ◽  
Jeffrey J Bazarian ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
High Risk ◽  
Elderly Patients ◽  
Predictive Performance

Prognosticating Traumatic Brain Injury (TBI): Analysis of CRASH, IMPACT Models and Patient Age in a Cohort of TBI Patients

Neurosurgery ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. E271-E272 ◽  
Author(s):  
Conor Gillespie ◽  
Catherine McMahon
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Survival Rates ◽  
Predictive Performance ◽  
Good Survival ◽  
Post Injury ◽  
Patient Age ◽  
Patient Âgé ◽  
Significant Difference ◽  
Impact Models

Abstract INTRODUCTION Both CRASH and IMPACT models have been developed in recent years to predict the outcome of Traumatic Brain Injury (TBI). However, there is no clear evidence as to how these models perform in a modern cohort of UK-patients. There is also predictive uncertainty with regards to survival rates and functional outcome in elderly (>65 yr) patients. METHODS Patients referred to a tertiary neuroscience center from December 2014 to January 2016 with a suspected TBI were retrospectively examined. For each model, the predicted survival and overall outcome were compared to the actual outcome on admission and at 6 mo post injury, stratified by patient age (>65 yr vs ≤65 yr). RESULTS A total of 161 patients met the initial criteria; mean age 65 yr (SD = 21) and 110 male. Both CRASH and IMPACT correctly predicted 6-mo mortality rates and functional outcomes in most patients (range 61.7%-82.4%), with better predictive performance for patients not accepted to the center (range 84%-98%). There was no significant difference in the initial survival of elderly patients if accepted (78% [95% CI 50.6-104.0] vs 81% [95% CI 67.8-94.8] but were lower for those not accepted (24% [95% CI 4.2-43.7] vs 76% [95% CI 63.5-88.5], P = .027). CONCLUSION Patients >65 yr admitted to tertiary neuroscience center had good survival rates on admission and at 6 mo. The lesser ability of CRASH and IMPACT models to predict poorer outcomes when accepted suggests that acceptance to specialist centers may be able to improve outcome and suggests more optimistic treatment and acceptance of appropriate over 65 yr should be considered.

scholarly journals The risk of pulmonary tuberculosis after traumatic brain injury

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hsin-Yueh Liu ◽  
Kuang-Ming Liao ◽  
Fu-Wen Liang ◽  
Yi-Chieh Hung ◽  
Jhi-Joung Wang ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Pulmonary Infection ◽  
Intracranial Injury ◽  
Icu Patients ◽  
Increased Risk ◽  
Significant Difference ◽  
Comparison Cohort ◽  
Comorbidity Index ◽  
The Brain

AbstractAfter traumatic brain injury (TBI), an inflammatory response in the brain might affect the immune system. The risk of pulmonary infection reportedly increases in patients with TBI. We aimed to evaluate the risk of tuberculosis (TB) in patients with TBI in Taiwan. All participants were selected from the intensive care unit (ICU). Patients with TBI were defined as patients in ICU with intracranial injury, and comparison cohort were patients in ICU without TBI diagnosis. There was a significant difference in TB risk between the patients with TBI and the comparison cohort according to age and the Charlson’s comorbidity index (CCI) score. Thus, we divided patients based on CCI into three groups for further analysis: mild (CCI = 0), moderate (CCI = 1/2), severe (CCI > 2). Mild-CCI group had a lower TB incidence rate (0.74%) and longer time to TB development (median: 2.43) than the other two groups. Moderate-CCI group had 1.52-fold increased risk of TB infection (p < 0.0001) compared with mild-CCI group. In the severe-CCI group, patients aged ≥ 80 years had 1.91-fold risk of TB compared with mild-CCI group (p = 0.0481). Severe-CCI group had significantly higher mortality than the mild-CCI group (p = 0.0366). Patients with TBI and more comorbidities had higher risk of TB infection with higher mortality rate.

scholarly journals Comparison of intracranial injury predictability between machine learning algorithms and the nomogram in pediatric traumatic brain injury

2021 ◽  
Vol 51 (5) ◽  
pp. E7
Author(s):  
Thara Tunthanathip ◽  
Jarunee Duangsuwan ◽  
Niwan Wattanakitrungroj ◽  
Sasiporn Tongman ◽  
Nakornchai Phuenpathom
Keyword(s):  
Machine Learning ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Predictive Value ◽  
Predictive Performance ◽  
Training Data ◽  
Intracranial Injury ◽  
Data Set ◽  
Head Ct ◽  
Cranial Ct

OBJECTIVE The overuse of head CT examinations has been much discussed, especially those for minor traumatic brain injury (TBI). In the disruptive era, machine learning (ML) is one of the prediction tools that has been used and applied in various fields of neurosurgery. The objective of this study was to compare the predictive performance between ML and a nomogram, which is the other prediction tool for intracranial injury following cranial CT in children with TBI. METHODS Data from 964 pediatric patients with TBI were randomly divided into a training data set (75%) for hyperparameter tuning and supervised learning from 14 clinical parameters, while the remaining data (25%) were used for validation purposes. Moreover, a nomogram was developed from the training data set with similar parameters. Therefore, models from various ML algorithms and the nomogram were built and deployed via web-based application. RESULTS A random forest classifier (RFC) algorithm established the best performance for predicting intracranial injury following cranial CT of the brain. The area under the receiver operating characteristic curve for the performance of RFC algorithms was 0.80, with 0.34 sensitivity, 0.95 specificity, 0.73 positive predictive value, 0.80 negative predictive value, and 0.79 accuracy. CONCLUSIONS The ML algorithms, particularly the RFC, indicated relatively excellent predictive performance that would have the ability to support physicians in balancing the overuse of head CT scans and reducing the treatment costs of pediatric TBI in general practice.

scholarly journals What are the strongest indicators of intracerebral hemorrhage in mild traumatic brain injury?

2021 ◽  
Vol 6 (1) ◽  
pp. e000717
Author(s):  
Panu Teeratakulpisarn ◽  
Phati Angkasith ◽  
Thanakorn Wannakul ◽  
Parichat Tanmit ◽  
Supatcha Prasertcharoensuk ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
High Risk ◽  
Ct Scan ◽  
Mild Traumatic Brain Injury ◽  
Skull Fracture ◽  
Brain Ct ◽  
Baseline Characteristics ◽  
Gcs Score ◽  
The Brain

BackgroundAlthough there are eight factors known to indicate a high risk of intracranial hemorrhage (ICH) in mild traumatic brain injury (TBI), identification of the strongest of these factors may optimize the utility of brain CT in clinical practice. This study aimed to evaluate the predictors of ICH based on baseline characteristics/mode of injury, indications for brain CT, and a combination of both to determine the strongest indicator.MethodsThis was a descriptive, retrospective, analytical study. The inclusion criteria were diagnosis of mild TBI, high risk of ICH, and having undergone a CT scan of the brain. The outcome of the study was any type of ICH. Stepwise logistic regression analysis was used to find the strongest predictors according to three models: (1) injury pattern and baseline characteristics, (2) indications for CT scan of the brain, and (3) a combination of models 1 and 2.ResultsThere were 100 patients determined to be at risk of ICH based on indications for CT of the brain in patients with acute head injury. Of these, 24 (24.00%) had ICH. Model 1 found that injury due to motor vehicle crash was a significant predictor of ICH, with an adjusted OR (95% CI) of 11.53 (3.05 to 43.58). Models 2 and 3 showed Glasgow Coma Scale (GCS) score of 13 to 14 after 2 hours of observation and open skull or base of skull fracture to be independent predictors, with adjusted OR (95% CI) of 11.77 (1.32 to 104.96) and 5.88 (1.08 to 31.99) according to model 2.DiscussionOpen skull or base of skull fracture and GCS score of 13 to 14 after 2 hours of observation were the two strongest predictors of ICH in mild TBI.Level of evidenceIII.

scholarly journals Multisite medical record review of emergency department visits for traumatic brain injury

2021 ◽  
Vol 27 (S1) ◽  
pp. i42-i48
Author(s):  
Barbara A Gabella ◽  
Jeanne E Hathaway ◽  
Beth Hume ◽  
Jewell Johnson ◽  
Julia F Costich ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Emergency Department ◽  
Brain Injury ◽  
Skull Fracture ◽  
Signs And Symptoms ◽  
International Classification Of Diseases ◽  
Emergency Department Visits ◽  
Intracranial Injury ◽  
Imaging Results ◽  
Icd 10

BackgroundIn 2016, the CDC in the USA proposed codes from the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for identifying traumatic brain injury (TBI). This study estimated positive predictive value (PPV) of TBI for some of these codes.MethodsFour study sites used emergency department or trauma records from 2015 to 2018 to identify two random samples within each site selected by ICD-10-CM TBI codes for (1) intracranial injury (S06) or (2) skull fracture only (S02.0, S02.1-, S02.8-, S02.91) with no other TBI codes. Using common protocols, reviewers abstracted TBI signs and symptoms and head imaging results that were then used to assign certainty of TBI (none, low, medium, high) to each sampled record. PPVs were estimated as a percentage of records with medium-certainty or high-certainty for TBI and reported with 95% confidence interval (CI).ResultsPPVs for intracranial injury codes ranged from 82% to 92% across the four samples. PPVs for skull fracture codes were 57% and 61% in the two university/trauma hospitals in each of two states with clinical reviewers, and 82% and 85% in the two states with professional coders reviewing statewide or nearly statewide samples. Margins of error for the 95% CI for all PPVs were under 5%.DiscussionICD-10-CM codes for traumatic intracranial injury demonstrated high PPVs for capturing true TBI in different healthcare settings. The algorithm for TBI certainty may need refinement, because it yielded moderate-to-high PPVs for records with skull fracture codes that lacked intracranial injury codes.

scholarly journals Intracranial Pressure during External Ventricular Drainage Weaning Is an Outcome Predictor of Traumatic Brain Injury

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Jia-cheng Gu ◽  
Hong Wu ◽  
Xing-zhao Chen ◽  
Jun-feng Feng ◽  
Guo-yi Gao ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Intracranial Pressure ◽  
External Ventricular Drainage ◽  
Unfavorable Outcome ◽  
Ventricular Drainage ◽  
Outcome Group ◽  
Significant Difference ◽  
The Mean ◽  
The Relationship

External ventricular drainage (EVD) is widely used in patients with a traumatic brain injury (TBI). However, the EVD weaning trial protocol varies and insufficient studies focus on the intracranial pressure (ICP) during the weaning trial. We aimed to establish the relationship between ICP during an EVD weaning trial and the outcomes of TBI. We enrolled 37 patients with a TBI with an EVD from July 2018 to September 2019. Among them, 26 were allocated to the favorable outcome group and 11 to the unfavorable outcome group (death, post-traumatic hydrocephalus, persistent vegetative state, and severe disability). Groups were well matched for sex, pupil reactivity, admission Glasgow Coma Scale score, Marshall computed tomography score, modified Fisher score, intraventricular hemorrhage, EVD days, cerebrospinal fluid output before the weaning trial, and the complications. Before and during the weaning trial, we recorded the ICP at 1-hour intervals to calculate the mean ICP, delta ICP, and ICP burden, which was defined as the area under the ICP curve. There were significant between-group differences in the age, surgery types, and intensive care unit days (p=0.045, p=0.028, and p=0.004, respectively). During the weaning trial, 28 (75.7%) patients had an increased ICP. Although there was no significant difference in the mean ICP before and during the weaning trial, the delta ICP was higher in the unfavorable outcome group (p=0.001). Moreover, patients who experienced death and hydrocephalus had a higher ICP burden, which was above 20 mmHg (p=0.016). Receiver operating characteristic analyses demonstrated the predictive ability of these variables (area under the curve AUC=0.818 [p=0.002] for delta ICP and AUC=0.758 [p=0.038] for ICP burden>20 mmHg). ICP elevation is common during EVD weaning trials in patients with TBI. ICP-related parameters, including delta ICP and ICP burden, are significant outcome predictors. There is a need for larger prospective studies to further explore the relationship between ICP during EVD weaning trials and TBI outcomes.

scholarly journals Serum S100B Determination in the Management of Pediatric Mild Traumatic Brain Injury

2012 ◽  
Vol 58 (7) ◽  
pp. 1116-1122 ◽  
Author(s):  
Damien Bouvier ◽  
Mathilde Fournier ◽  
Jean-Benoît Dauphin ◽  
Flore Amat ◽  
Sylvie Ughetto ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Reference Interval ◽  
Pediatric Emergency ◽  
Cranial Computed Tomography ◽  
Serum S100b ◽  
Significant Difference ◽  
Hospitalization Costs ◽  
Group 2

Abstract BACKGROUND The place of serum S100B measurement in mild traumatic brain injury (mTBI) management is still controversial. Our prospective study aimed to evaluate its utility in the largest child cohort described to date. METHODS Children younger than 16 years presenting at a pediatric emergency department within 3 h after TBI were enrolled prospectively for blood sampling to determine serum S100B concentrations. The following information was collected: TBI severity determined by using the Masters classification [1: minimal or Glasgow Coma Scale (GCS) 15, 2: mild or GCS 13–15, and 3: severe or GCS &lt;13]; whether hospitalized or not; good or bad clinical evolution (CE); whether cranial computed tomography (CCT) was prescribed; and related presence (CCT+) or absence (CCT−) of lesions. RESULTS For the 446 children enrolled, the median concentrations of S100B were 0.21, 0.31, and 0.44 μg/L in Masters groups 1, 2, and 3, respectively, with a statistically significant difference between these groups (P &lt; 0.05). In Masters group 2, 65 CCT scans were carried out. Measurement of S100B identified patients as CCT+ with 100% (95% CI 85–100) sensitivity and 33% (95% CI 20–50) specificity. Of the 424 children scored Masters 1 or 2, 21 presented “bad CE.” S100B identified bad CE patients with 100% (95% CI 84–100) sensitivity and 36% (95% CI 31–41) specificity. Of the 242 children hospitalized, 81 presented an S100B concentration within the reference interval. CONCLUSIONS Serum S100B determination during the first 3 h of management of children with mTBI has the potential to reduce the number of CCT scans, thereby avoiding unnecessary irradiation, and to save hospitalization costs.

Regenerative medicine and traumatic brain injury: from stem cell to cell-free therapeutic strategies

2021 ◽  
Author(s):  
Lianxu Cui ◽  
Yasmeen Saeed ◽  
Haomin Li ◽  
Jingli Yang
Keyword(s):  
Traumatic Brain Injury ◽  
Stem Cells ◽  
Stem Cell ◽  
Brain Injury ◽  
Regenerative Medicine ◽  
Cell Therapy ◽  
Therapeutic Strategies ◽  
Study Data ◽  
Health Concern ◽  
Standardized Treatment

Traumatic brain injury (TBI) is a serious health concern, yet there is a lack of standardized treatment to combat its long-lasting effects. The objective of the present study was to provide an overview of the limitation of conventional stem cell therapy in the treatment of TBI and to discuss the application of novel acellular therapies and their advanced strategies to enhance the efficacy of stem cells derived therapies in the light of published study data. Moreover, we also discussed the factor to optimize the therapeutic efficiency of stem cell-derived acellular therapy by overcoming the challenges for its clinical translation. Hence, we concluded that acellular therapy possesses the potential to bring a breakthrough in the field of regenerative medicine to treat TBI.

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