Traumatic Brain Injury Patients Research Articles

Retrospective Outcome Analysis of Geriatric Traumatic Brain Injury Treated at a Tertiary Care Center in India

Abstract Background Trauma is a major cause of morbidity and mortality in elderly patients and its management is challenging. Outcome assessment in these patients is difficult because of preexisting chronic medical conditions as it may be impossible to isolate the effect of traumatic brain injury. This study aimed to examine the clinical outcomes and epidemiological and clinicoradiological characteristics of geriatric traumatic brain injury patients at a tertiary care center. Methods The clinical records of patients aged ≥60 years with head injuries treated at King George's Medical University between 2016 and 2020 were included in the study. Patients were followed up in the outpatient department or through telephone consultation. The follow-up period was updated using the Glasgow outcome score (GOS) of patients for current neurological status and relevant radiological investigations. Results The mean age of subjects was 66.16 ± 6.55 years. Road traffic accidents were the most frequent cause of brain injuries (448 [68.5%]). In total, 41% of the study patients had severe head injuries (Glasgow coma scale, GCS < 9) at admission. The in-hospital mortality was 25.2%. In total, 60.7% of discharged patients showed favorable outcomes (GOS: 4 or 5). GCS at admission, best motor response, and associated comorbidity (diabetes mellitus) significantly predicted the outcome at 6 months. The majority of the patients (82.6 %) were 60 to 70 years of age. Conclusion Road traffic accidents are the most frequent cause of brain injuries in geriatrics. Most of them were managed medically, and majority were discharged (74.8%). Out of those discharged, 39.3% had unfavorable outcomes.

Latent Trajectories of Cerebral Perfusion Pressure and Risk Prediction Models Among Patients with Traumatic Brain Injury: Based on an Interpretable Artificial Neural Network

This study aimed to characterize long-term cerebral perfusion pressure (CPP) trajectory in traumatic brain injury (TBI) patients and construct an interpretable prediction model to assess the risk of unfavorable CPP evolution patterns. TBI patients with CPP records were identified from the Medical Information Mart for the Intensive Care (MIMIC)-IV 2.1, eICU Collaborative Research Database (eICU-CRD) 2.0 and HiRID dataset 1.1.1. The research process consisted of two stages. First, group-based trajectory modeling (GBTM) was used to identify different CPP trajectories. Second, different ANN algorithms were employed to predict the trajectories of CPP. A total of 331 eligible patients' records from MIMIC-IV 2.1 and eICU-CRD 2.0 were used for trajectory analysis and model development. Additionally, 310 patients' data from HiRID were used for external validation. The GBTM identified 5 CPP trajectory groups, group 1 and group 5 were merged into class 1 based on unfavorable in-hospital mortality. The best 6 predictors were invasive systolic blood pressure coefficient of variation (ISBPCV), venous blood chloride ion concentration, PaCO2, PT (Prothrombin Time), CPP coefficient of variation (CPPCV), and mean CPP. Compared with other algorithms, Scaled Conjugate Gradient (SCG) performed relatively better in identifying class 1. This study identified 2 CPP trajectory groups associated with elevated risk and 3 with reduced risk. PaCO2 might be a strong predictor for the unfavorable CPP class. The ANN model achieved the primary goal of risk stratification, which is conducive to early intervention and individualized treatment.

Temporal profile of cerebrospinal fluid galactin-3 and associated cytokine responses after severe traumatic brain injury in patients: a retrospective study

Temporal profile of cerebrospinal fluid galactin-3 and associated cytokine responses after severe traumatic brain injury in patients: a retrospective study

Stress-induced hyperglycemia and mortality in patients with traumatic brain injury without preexisting diabetes: A meta-analysis.

Stress-induced hyperglycemia (SIH) is common in patients with traumatic brain injury (TBI) and has been suggested to influence mortality rates. This meta-analysis aims to evaluate the impact of SIH on the mortality of TBI patients without preexisting diabetes mellitus (DM). A comprehensive search was performed in Medline, Web of Science, Embase, Wanfang, and CNKI databases up to May 15, 2024, to retrieve relevant studies. Observational studies reporting the incidence of all-cause mortality among TBI patients without preexisting DM, comparing those with and without SIH, were included. The association between SIH and all-cause mortality was analyzed using risk ratios (RR) and 95% confidence intervals (CI) with a random-effects model. Twelve cohort studies comprising 15 datasets with 16,387 TBI patients were included. The pooled analysis showed that SIH was associated with a higher risk of all-cause mortality (RR: 2.00, 95% CI: 1.72-2.33, p < 0.001), with mild heterogeneity (I² = 25%). Sensitivity analysis confirmed the robustness of these findings. Subgroup analyses indicated no significant differences based on study design, patient age, gender proportion, SIH definition, or follow-up duration. However, the association was slightly weaker but still significant in studies using multivariate analyses (RR: 1.76) compared to univariate analyses (RR: 2.69). In conclusion, SIH was associated with a higher risk of all-cause mortality in TBI patients without preexisting DM. Further research should explore the underlying mechanisms and optimal management strategies for SIH in this population.

B - 50 Traumatic Brain Injury in Patients with Psychogenic Non-epileptic Seizures and Functioning

Abstract Objective Past studies reveal that many patients with psychogenic non-epileptic seizures (PNES) also have a traumatic brain injury (TBI) history, but the specific influence of prior TBI on patients is presently under examination. This study aims to investigate the relationship between patients with PNES with a TBI history and symptoms/functioning, compared to those without a TBI history. Method Data collected from patients seen for comprehensive neuropsychiatric evaluation was analyzed, including TBI history, TBI severity, and Global Assessment of Functioning (GAF) scores. The GAF scale allows assignment of a numerical rating to patients based on their psychological and social functioning. Results Patients with PNES without TBI (n = 120; mean age 51) had higher average GAF scores (52.4) compared to those with TBI (n = 164, mean age 54, mean GAF 50) (p = 0.0059). Across PNES patients with a history of TBI, those with mild TBI exhibited notably lower GAF scores (43.2) than those with moderate (48.87) or severe (50) history of TBI. Conclusion Patients with PNES and a history of TBI had lower (worse) GAF scores than those without TBI, and worse in cases of mild TBI. Further exploration of demographic variables, education, and employment status will address potential confounds. Understanding the complex interplay between PNES and TBI may improve diagnosis and management strategies, with further research in advancing clinical practice.

Development of Seizures Following Traumatic Brain Injury: A Retrospective Study.

Objectives: The multifaceted impact of Traumatic brain injury (TBI) encompasses complex healthcare costs and diverse health complications, including the emergence of Post-Traumatic Seizures (PTS). In this study, our goal was to discern and elucidate the incidence and risk factors implicated in the pathogenesis of PTS. We hypothesize that the development of PTS following TBI varies based on the type and severity of TBI. Methods: Our study leveraged the Nationwide Inpatient Sample (NIS) to review primary TBI cases spanning 2016-2020 in the United States. Admissions featuring the concurrent development of seizures during the admission were queried. The demographic variables, concomitant diagnoses, TBI subtypes, hospital charges, hospital length of stay (LOS), and mortality were analyzed. Results: The aggregate profile of TBI patients delineated a mean age of 61.75 (±23.8) years, a male preponderance (60%), and a predominantly White demographic (71%). Intriguingly, patients who encountered PTS showcased extended LOS (7.5 ± 9.99 vs. 6.87 ± 10.98 days, p < 0.001). Paradoxically, PTS exhibited a reduced overall in-hospital mortality (6% vs. 8.1%, p < 0.001). Notably, among various TBI subtypes, traumatic subdural hematoma (SDH) emerged as a predictive factor for heightened seizure development (OR 1.38 [1.32-1.43], p < 0.001). Conclusions: This rigorous investigation employing an extensive national database unveils a 4.95% incidence of PTS, with SDH accentuating odds of seizure risk by OR: 1.38 ([1.32-1.43], p < 0.001). The paradoxical correlation between lower mortality and PTS is expected to be multifactorial and necessitates further exploration. Early seizure prophylaxis, prompt monitoring, and equitable healthcare provision remain pivotal avenues for curbing seizure incidence and comprehending intricate mortality trends.

ASA-score is associated with 90-day mortality after complicated mild traumatic brain injury – a retrospective cohort study

PurposeThis study explores the association of the American Society of Anesthesiologists (ASA) score with 90-day mortality in complicated mild traumatic brain injury (mTBI) patients, and in trauma patients without a TBI.MethodsThis retrospective study was conducted using a cohort of trauma patients treated at a level III trauma center in Stockholm, Sweden from January to December 2019. The primary endpoint was 90-day mortality. The population was identified using the Swedish Trauma registry. The Trauma and Injury Severity Score (TRISS) was used to estimate the likelihood of survival. Trauma patients without TBI (NTBI) were used for comparison. Data analysis was conducted using R software, and statistical analysis included univariate and multivariate logistic regression.ResultsA total of 244 TBI patients and 579 NTBI patients were included, with a 90-day mortality of 8.2% (n = 20) and 5.4% (n = 21), respectively. Deceased patients in both cohorts were generally older, with greater comorbidities and higher injury severity. Complicated mTBI constituted 97.5% of the TBI group. Age and an ASA score of 3 or higher were independently associated with increased mortality risk in the TBI group, with odds ratios of 1.04 (95% 1.00–1.09) and 3.44 (95% CI 1.10–13.41), respectively. Among NTBI patients, only age remained a significant mortality predictor. TRISS demonstrated limited predictive utility across both cohorts, yet a significant discrepancy was observed between the outcome groups within the NTBI cohort.ConclusionThis retrospective cohort study highlights a significant association between ASA score and 90-day mortality in elderly patients with complicated mTBI, something that could not be observed in comparative NTBI cohort. These findings suggest the benefit of incorporating ASA score into prognostic models to enhance the accuracy of outcome prediction models in these populations, though further research is warranted.

A Bayesian Multi-Layered Record Linkage Procedure to Analyze Functional Status of Medicare Patients with Traumatic Brain Injury

Understanding associations between injury severity and post-acute care recovery for older adults with traumatic brain injury (TBI) is crucial to improving care. Estimating these associations requires information on patients’ injury, demographics, and long-term health outcomes. This data is despersed across two different datasets: Medicare claims data and the National Trauma Data Bank (NTDB). Because of privacy regulations, unique identifiers are not available to link records across these two data sets. Record linkage methods identify records that represent the same patient across data sets in the absence of unique identifiers. With a large number of records, these methods may result in many false links. Health providers are a natural grouping scheme for patients, because only records that receive care from the same provider can represent the same patient. In some cases, providers are defined within each data set, but they are not uniquely identified across data sets. We propose a Bayesian record linkage procedure that simultaneously links providers and patients. The procedure improves the accuracy of the estimated links compared to current methods. We implement the proposed method to examine the associations between functional status assessments and TBI patients' ability to be independent following their injury by linking records from Medicare enrollment records and the NTDB.

The Correlation Between CT Findings and Neurosurgical Intervention in Mild Traumatic Brain Injury Patients with Isolated Subdural Hematomas

Abstract Objective In patients with mild traumatic brain injuries (mTBIs), with Glasgow Coma Scale (GCS) scores of 13 to 15, isolated subdural hematomas (iSDHs) are identified as a prevalent category of intracranial hemorrhage. The primary objective of our research was to investigate the relationship between the characteristics of iSDHs, as revealed through computed tomography (CT) scans on patient admission, and the consequent necessity for neurosurgical intervention. Materials and Methods This was a 1-year study, employing a prospective observational design at our institution. We enrolled adult trauma patients diagnosed with mTBIs and concurrent iSDHs, intent on documenting the hemorrhages' quantitative parameters such as maximum length and thickness, among other related variables. The eventual execution of neurosurgical procedures constituted our primary outcome, aiming to establish a decisive correlation between CT scan metrics of iSDHs upon admission and the imperative for subsequent surgical intervention. Results A total of 50 patients were included in our study: 14 patients received a neurosurgical intervention and 36 patients did not. The neurosurgical intervention group had a mean maximum SDH length and thickness that were 38 mm longer and 9.6 mm thicker than those of the non-neurosurgical intervention group (p &lt; 0.001 for both). Conclusion In this study, we evaluated the odds of a neurosurgical intervention based on hemorrhage characteristics on CT, in patients with an iSDH and mTBI. Once validated in a second population, these data can be used to evaluate the necessity of interhospital transfers and to better inform patients and families of the risk of future neurosurgical intervention and prognosis.

Association Between Impulsivity, Self-Harm, Suicidal Ideation, and Suicide Attempts in Patients with Traumatic Brain Injury.

Traumatic brain injury (TBI) affects over 48 million people worldwide each year. Suicide is common in TBI, and there are several known contributing factors, including severe TBI, depression, alcohol use, and male sex. Impulsivity, or the tendency to act quickly with little thought, may be an early predictor of suicidality following TBI. The purpose of this study was to evaluate the risk of suicidality in patients with a prior history of impulsivity following a traumatic brain injury (TBI). Using de-identified electronic health records from the TriNetX United States Collaborative Network with Natural Language Processing, three cohorts were generated: the impulsivity TBI cohort (I+TBI+) included subjects with a diagnosis of impulsivity before a diagnosis of TBI; the no impulsivity TBI cohort (I-TBI+) included patients with TBI but no impulsivity; the impulsivity no TBI cohort (I+TBI-) included patients with impulsivity but TBI. Two analyses were conducted, including analysis 1 (impulsivity TBI vs. no impulsivity TBI) and analysis 2 (impulsivity TBI vs. impulsivity no TBI). Patients were 1:1 propensity score matched by age, sex, race, ethnicity, psychiatric diagnoses, and antidepressant use. Outcomes included a diagnosis of self-harm, suicidal ideation, or a suicide attempt within one year after the index event. The all-time incidence of each outcome was assessed across different age categories. The chi-square test (categorical variables) and t-test (numerical variables) were used to assess for differences between groups. A total of 1,292,776 TBI patients were identified in the study. After 1:1 propensity score-matching, there were 20,694 patients (mean [SD] age, 48.1 [21.8]; 8,424 females [40.7%]) with impulsivity and TBI (I+TBI+), 1,272,082 patients (mean [SD] age, 46.0 [23.1]; 562,705 females [44.2%]) with TBI alone (I-TBI+), and 90,669 patients (mean [SD] age, 43.7 [22.6]; 45,188 females [49.8%]) with impulsivity alone (I+TBI-). Within the first year after a TBI, patients with impulsivity were more likely to exhibit self-harm (P < 0.001), suicidal ideation (P < 0.001) or a suicide attempt (P < 0.001). Compared to TBI patients without impulsivity, those with impulsivity had a four-fold increase in the incidence of self-harm (2.81% vs. 0.63%), an eight-fold increase in suicidal ideation (52.42% vs. 6.41%), and a twenty-one-fold increase in suicide attempts (32.02% vs. 1.50%). This study suggests that impulsivity diagnosed before a TBI may increase the risk of post-traumatic suicidality, with a four-fold increased risk of self-harm, an eight-fold increased risk of suicidal ideation and a twenty-one-fold increased risk of suicide attempts. This characterizes a group of at-risk individuals who may benefit from early psychiatric support and targeted interventions following a TBI.

Neuroinflammatory Biomarkers and Their Associations With Cognitive, Affective, and Functional Outcomes 3 to 12 Months After a Traumatic Brain Injury: A Pilot Study.

Neuroinflammation is an important feature of traumatic brain injury (TBI) that remains poorly understood in the 3- to 12-month period post-TBI. The purpose of our pilot study was to examine the relationships between biomarkers of neuroinflammation and functional outcomes in TBI patients 3 to 12months postinjury. TBI patients (n =36) 3 to 12months post-TBI were recruited from a South Florida TBI clinic from May 2022 to June 2023. The Disability Rating Scale, Satisfaction with Life Scale, NIH Toolbox Sorting Working Memory, Neuro-Quality of Life Cognitive Function, Anxiety, Depression, and Sleep assessments were performed. Multiple plasma biomarkers were assayed. Analysis of variance was used to compare between-group results. Linear regression was performed to analyze relationships between biomarkers and outcomes. Brain-derived neurotrophic factor concentrations were higher as postinjury time interval increased and were associated with cognitive battery outcomes. S-100β and glial fibrillary acidic protein were associated with anxiety score and hospital length of stay; S-100β was also associated with depression. Interleukin 6 was associated with cognitive function score and time since injury. We found S-100β, glial fibrillary acidic protein, Interleukin 6, and brain-derived neurotrophic factor to play a larger role in the TBI recovery period than other biomarkers examined. Clinicians should continue to monitor for symptoms post-TBI, as the neuroinflammatory process continues to persist even into the later rehabilitation stage.

Group based trajectory modeling identifies distinct patterns of sympathetic hyperactivity following traumatic brain injury.

Background Paroxysmal Sympathetic Hyperactivity (PSH) occurs with high prevalence among critically ill Traumatic Brain Injury (TBI) patients and is associated with worse outcomes. The PSH-Assessment Measure (PSH-AM) consists of a Clinical Features Scale (CFS) and a Diagnosis Likelihood Tool (DLT), intended to quantify the severity of sympathetically-mediated symptoms and likelihood that they are due to PSH, respectively, on a daily basis. Here, we aim to identify and explore the value of dynamic trends in the evolution of sympathetic hyperactivity following acute TBI using elements of the PSH-AM. Methods We performed an observational cohort study of 221 acute critically ill TBI patients for whom daily PSH-AM scores were calculated over the first 14 days of hospitalization. A principled group-based trajectory modeling approach using unsupervised K-means clustering was used to identify distinct patterns of CFS evolution within the cohort. We also evaluated the relationships between trajectory group membership and PSH diagnosis, as well as PSH DLT score, hospital discharge GCS, ICU and hospital length of stay, duration of mechanical ventilation, and mortality. Baseline clinical and demographic features predictive of trajectory group membership were analyzed using univariate screening and multivariate multinomial logistic regression. Results We identified four distinct trajectory groups. Trajectory group membership was significantly associated with clinical outcomes including PSH diagnosis and DLT score, ICU length of stay, and duration of mechanical ventilation. Baseline features independently predictive of trajectory group membership included age and post-resuscitation motor GCS. Conclusions This study adds to the sparse research characterizing the heterogeneous temporal trends of sympathetic nervous system activation during the acute phase following TBI. This may open avenues for early identification of at-risk patients to receive tailored interventions to limit secondary brain injury associated with autonomic dysfunction and thereby improve TBI patient outcomes.

Frailty Predicts in-Hospital Death in Traumatic Brain Injury Patients: A Retrospective Cohort Study.

Traumatic brain injury (TBI) is a severe public health problem in elderly patients, and frailty is associated with higher mortality rates in older patients. This study aims to assess the prognostic value of frailty in patients with TBI. Clinical data from 348 TBI patients treated at Affiliated Kunshan Hospital of Jiangsu University and Kunshan Hospital of Traditional Chinese Medicine between December 2018 and December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to determine risk factors affecting in-hospital mortality, and receiver operating characteristic (ROC) curves were plotted to assess the discriminatory power of the frailty index. Frailty was assessed using the FRAIL scale, where FRAIL stands for Fatigue, Resistance, Ambulation, Illness, and Loss of weight, with each item scored as 0 or 1. Using the FRIAL questionnaire, 122 patients had low frailty and 226 had high frailty. Multivariate logistic regression analysis showed that high frailty was a risk factor for in-hospital mortality in TBI patients (P<0.001, OR=2.012 [1.788-2.412]). The proportion of infections occurring in the two groups was statistically different (P=0.015), with severely infected TBI patients being more likely to develop complications. The ROC curve showed an area under the curve for the FRAIL score of 0.845 [0.752-0.938]. Frailty is an important risk factor for in-hospital mortality in elderly TBI patients, and more attention should be paid to patients with high levels of frailty. Clinicians should consider the degree of frailty when assessing TBI and making treatment decisions.

A Machine Learning Model Based on CT Imaging Metrics and Clinical Features to Predict the Risk of Hospital-Acquired Pneumonia After Traumatic Brain Injury.

To develop a validated machine learning (ML) algorithm for predicting the risk of hospital-acquired pneumonia (HAP) in patients with traumatic brain injury (TBI). We employed the Least Absolute Shrinkage and Selection Operator (LASSO) to identify critical features related to pneumonia. Five ML models-Logistic Regression (LR), Extreme Gradient Boosting (XGB), Random Forest (RF), Naive Bayes Classifier (NB), and Support Vector Machine (SVC)-were developed and assessed using the training and validation datasets. The optimal model was selected based on its performance metrics and used to create a dynamic web-based nomogram. In a cohort of 858 TBI patients, the HAP incidence was 41.02%. LR was determined to be the optimal model with superior performance metrics including AUC, accuracy, and F1-score. Key predictive factors included Age, Glasgow Coma Score, Rotterdam Score, D-dimer, and the Systemic Immune Response to Inflammation Index (SIRI). The nomogram developed based on these predictors demonstrated high predictive accuracy, with AUCs of 0.818 and 0.819 for the training and validation datasets, respectively. Decision curve analysis (DCA) and calibration curves validated the model's clinical utility and accuracy. We successfully developed and validated a high-performance ML algorithm to assess the risk of HAP in TBI patients. The dynamic nomogram provides a practical tool for real-time risk assessment, potentially improving clinical outcomes by aiding in early intervention and personalized patient management.

Changes of NLRP3 in serum and cerebrospinal fluid of patients after moderate to severe traumatic brain injury and their predictive values for prognosis.

Traumatic brain injury (TBI) remains a major concern for global health. Recent studies have suggested the role of NOD-like receptor pyrin domain-containing protein 3 (NLRP3), an inflammatory marker, in the cerebrospinal fluid (CSF) and serum as potential indicators of TBI prognosis. The objective of the study was to characterize NLRP3 as a clinically applicable tool for predicting the outcomes of TBI patients. A total of 270 patients with moderate to severe TBI were included in this retrospective analysis. Serum and CSF samples were collected at 1-, 3-, 7-, and 21-day post-injury to measure NLRP3 levels. The prognosis of patients was evaluated after 3 months using the Glasgow Outcome Scale (GOS). Patients were categorized into good prognosis (GOS score >3) and poor prognosis (GOS score ≤3) groups. The relationship between NLRP3 levels and prognosis was analyzed. Patients with poor prognosis had significantly elevated NLRP3 levels in their serum on days 1 and 3 post-injury compared with those with a good prognosis. The difference was more pronounced during these early days compared with days 7 and 21. However, NLRP3 levels in CSF consistently showed a large difference between the two groups throughout the observation period. Receiver operating characteristic analysis revealed that the level of NLRP3 in the CSF on day 3 post-injury had the highest predictive value for prognosis, with an area under the curve of 0.83, followed by the level of NLRP3 in the serum on day 3 post-injury. The levels of NLRP3, especially in the CSF on day 3 post-injury, can serve as a potential biomarker for predicting prognosis in moderate to severe TBI patients. Early measurement of NLRP3 levels can provide valuable insights into patient outcomes and guide therapeutic strategies.

Association of glycemic variability and prognosis in patients with traumatic brain injury: A retrospective study from the MIMIC-IV database.

Elevated glycemic variability (GV) often occurs in intensive care unit (ICU) patients and is associated with patient prognosis. However, the association between GV and prognosis in ICU patients with traumatic brain injury (TBI) remains unclear. Clinical data of ICU patients with TBI were obtained from the Medical Information Mart for Intensive Care (MIMIC) -IV database. The coefficient of variation (CV) was utilized to quantify GV, while the Glasgow Coma Scale (GCS) was employed to evaluate the consciousness status of TBI patients. Pearson linear correlation analysis, linear regression, COX regression and restricted cubic spline (RCS) were used to investigate the relationship between CV and consciousness impairment, as well as the risk of in-hospital mortality. A total of 1641 ICU patients with TBI were included in the study from the MIMIC-IV database. Pearson linear correlation and restricted cubic spline (RCS) analysis results showed a negative linear relationship between CV and the last GCS (P = 0.002) with no evidence of nonlinearity (P for nonlinear = 0.733). Multivariable linear regression suggested a higher CV was associated with a lower discharge GCS [β (95 %CI) = -1.86 (-3.08 ∼ -0.65), P = 0.003]. Furthermore, multivariable COX regression indicated that CV ≥ 0.3 was a risk factor for in-hospital death in TBI patients [HR (95 %CI) = 1.74 (1.15-2.62), P = 0.003], and this result was also consistent across sensitivity and subgroup analyses. Higher GV is related to poorer consciousness outcomes and increased risk of in-hospital death in ICU patients with TBI. Additional research is needed to understand the logical relationship between GV and TBI progression.

Clinical Significance of the Control CT Rotterdam Score Compared With the Admission CT Rotterdam Score in Patients With Isolated Severe Traumatic Brain Injury in the Intensive Care Unit.

The Rotterdam scale is one of the most commonly used radiological scales for evaluating and predicting outcomes in traumatic brain injury (TBI) cases. Given the evolving nature of TBI, our study is designed to compare the Rotterdam score of computed tomography (CT) findings upon admission (Rotterdam score I) with the score after 72 hours (Rotterdam score II) of treatment in the trauma intensive care unit (ICU). A retrospective observational study was conducted on 54 patients who received intensive care treatment for isolated severe TBI over five years. We included severe TBI patients with no age restrictions who required admission to the ICU within 12 hours of the onset of trauma. An initial Rotterdam CT score was obtained via a CT head scan within four hours of the trauma, followed by a control CT head scan 72 hours after ICU admission. It was essential to have documentation on the clinical and laboratory treatment course and access to radiological CT diagnostics. Receiver operating characteristic (ROC) curves were employed in this study to evaluate the accuracy of diagnostic tests, such as the Rotterdam score. The ROC curves provided a graphical representation of the tests' diagnostic performance, which helped assess their effectiveness. There was a significant difference (p < 0.001) in the diagnostic scores of CT scans upon admission (Rotterdam score I) and control CT scans after 72 hours (Rotterdam score II) in the total sample. The Rotterdam score I was notably higher, 3.6 (±0.8), in patients requiring neurosurgical intervention compared to those who did not, 2.8 (±0.9), with significance (p = 0.003). The Rotterdam score I demonstrated a substantial predictive value for unfavorable outcomes (p = 0.048), as did the Rotterdam score II after the 72-hour mark (p = 0.006). The control Rotterdam score 72 hours after admission predicts mortality in isolated TBI patients more significantly than the Rotterdam score determined at the patient's admission to the intensive care unit.

Acutely blocking excessive mitochondrial fission prevents chronic neurodegeneration after traumatic brain injury

Progression of acute traumatic brain injury (TBI) into chronic neurodegeneration is a major health problem with no protective treatments. Here, we report that acutely elevated mitochondrial fission after TBI in mice triggers chronic neurodegeneration persisting 17months later, equivalent to many human decades. We show that increased mitochondrial fission after mouse TBI is related to increased brain levels of mitochondrial fission 1 protein (Fis1) and that brain Fis1 is also elevated in human TBI. Pharmacologically preventing Fis1 from binding its mitochondrial partner, dynamin-related protein 1 (Drp1), for 2weeks after TBI normalizes the balance of mitochondrial fission/fusion and prevents chronically impaired mitochondrial bioenergetics, oxidative damage, microglial activation and lipid droplet formation, blood-brain barrier deterioration, neurodegeneration, and cognitive impairment. Delaying treatment until 8months after TBI offers no protection. Thus, time-sensitive inhibition of acutely elevated mitochondrial fission may represent a strategy to protect human TBI patients from chronic neurodegeneration.

11: Effective use of veno-venous extracorporeal membrane oxygenation in traumatic brain injury patients complicated by intracranial hemorrhage

11: Effective use of veno-venous extracorporeal membrane oxygenation in traumatic brain injury patients complicated by intracranial hemorrhage

Impact of Intensive Insulin Therapy on Clinical Outcomes of Traumatic Brain Injury Patients with Pre-Existing Diabetes

Impact of Intensive Insulin Therapy on Clinical Outcomes of Traumatic Brain Injury Patients with Pre-Existing Diabetes