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Research in severe traumatic brain injury (TBI) has historically been limited by studies with relatively small sample sizes that result in low power to detect small, yet clinically meaningful outcomes. Data sharing and integration from existing sources hold promise to yield larger more robust sample sizes that improve the potential signal and generalizability of important research questions. However, curation and harmonization of data of different types and of disparate provenance is challenging. We report our approach and experience integrating multiple TBI data sets containing collected physiological data, including both expected and unexpected challenges encountered in the integration process. Our harmonized data set included data on 1536 patients from the Citicoline Brain Injury Treatment Trial (COBRIT), Effect of erythropoietin and transfusion threshold on neurological recovery after traumatic brain injury: a randomized clinical trial (EPO Severe TBI), BEST-TRIP, Progesterone for the Treatment of Traumatic Brain Injury III Clinical Trial (ProTECT III), Transforming Research and Clinical Knowledge in Traumatic brain Injury (TRACK-TBI), Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase-II (BOOST-2), and Ben Taub General Hospital (BTGH) Research Database studies. We conclude with process recommendations for data acquisition for future prospective studies to aid integration of these data with existing studies. These recommendations include using common data elements whenever possible, a standardized recording system for labeling and timing of high-frequency physiological data, and secondary use of studies in systems such as Federal Interagency Traumatic Brain Injury Research Informatics System (FITBIR), to engage investigators who collected the original data.

Background: The incidence of adult respiratory distress syndrome (ARDS) in severe traumatic brain injury (TBI) is poorly reported. Recently, a new definition for ARDS was proposed, the Berlin definition. The percentage of patients represented by TBI in the Berlin criteria study is limited. This study describes the incidence and associated mortality of ARDS in TBI patients., Methods: The study was an analysis of the safety of erythropoietin administration and transfusion threshold on the incidence of ARDS in severe TBI patients. Three reviewers independently assessed all patients enrolled in the study for acute lung injury/ARDS using the Berlin and the American-European Consensus Conference (AECC) definitions. A Cox proportional hazards model was used to assess the relationship between ARDS and mortality and 6-month Glasgow Outcome Scale (GOS) score., Results: Two hundred patients were enrolled in the study. Of the patients, 21% (41 of 200) and 26% (52 of 200) developed ARDS using the AECC and Berlin definitions, respectively, with a median time of 3 days (interquartile range, 3) after injury. ARDS by either definition was associated with increased mortality (p = 0.04) but not with differences in functional outcome as measured by the GOS score at 6 months. Adjusted analysis using the Berlin criteria showed an increased mortality associated with ADS (p = 0.01)., Conclusion: Severe TBI is associated with an incidence of ARDS ranging from 20% to 25%. The incidence is comparable between the Berlin and AECC definitions. ARDS is associated with increased mortality in severe TBI patients, but further studies are needed to validate these findings., Level of Evidence: Epidemiologic study, level II.

Cerebral dysfunction caused by traumatic brain injury may adversely affect cerebral hemodynamics and oxygenation leading to worse outcomes if oxygen capacity is decreased due to anemia. In a randomized clinical trial of 200 patients comparing transfusion thresholds <7 g/dl versus 10 g/dl, where transfusion of leukoreduced packed red blood cells was used to maintain the assigned hemoglobin threshold, no long-term neurological difference was detected. The current study examines secondary outcome measures of intracranial pressure (ICP), cerebral perfusion pressure (CPP), and brain tissue oxygenation (PbtO2) in patients enrolled in this randomized clinical trial. We observed a lower hazard for death (hazard ratio [HR]=0.12, 95% confidence interval [CI]=0.02-0.99) during the first 3 days post-injury, and a higher hazard for death after three days (HR=2.55, 95% CI=1.00-6.53) in the 10 g/dl threshold group as compared to the 7 g/dL threshold group. No significant differences were observed for ICP and CPP but MAP was slightly lower in the 7 g/dL group, although the decreased MAP did not result in increased hypotension. Overall brain tissue hypoxia events were not significantly different in the two transfusion threshold groups. When the PbtO2 catheter was placed in normal brain, however, tissue hypoxia occurred in 25% of patients in the 7 g/dL threshold group, compared to 10.2% of patients in the 10 g/dL threshold group (p=0.04). Although we observed a few differences in hemodynamic outcomes between the transfusion threshold groups, none were of major clinical significance and did not affect long-term neurological outcome and mortality.

Objective: This study was undertaken to examine averted stroke in optimized stroke systems. Methods: This secondary analysis of a multicenter trial from 2014 to 2020 compared patients treated by mobile stroke unit (MSU) versus standard management. The analytical cohort consisted of participants with suspected stroke treated with intravenous thrombolysis. The main outcome was a tissue‐defined averted stroke, defined as a final diagnosis of stroke with resolution of presenting symptoms/signs by 24 hours attributed to thrombolysis and no acute infarction/hemorrhage on imaging. An additional outcome was stroke with early symptom resolution, defined as a final diagnosis of stroke with resolution of presenting symptoms/signs by 24 hours attributed to thrombolysis. Results: Among 1,009 patients with a median last known well to thrombolysis time of 87 minutes, 159 (16%) had tissue‐defined averted stroke and 276 (27%) had stroke with early symptom resolution. Compared with standard management, MSU care was associated with more tissue‐defined averted stroke (18% vs 11%, adjusted odds ratio [aOR] = 1.82, 95% confidence interval [CI] = 1.13–2.98) and stroke with early symptom resolution (31% vs 21%, aOR = 1.74, 95% CI = 1.12–2.61). The relationships between thrombolysis treatment time and averted/early recovered stroke appeared nonlinear. Most models indicated increased odds for stroke with early symptom resolution but not tissue‐defined averted stroke with earlier treatment. Additionally, younger age, female gender, hyperlipidemia, lower National Institutes of Health Stroke Scale, lower blood pressure, and no large vessel occlusion were associated with both tissue‐defined averted stroke and stroke with early symptom resolution. Interpretation: In optimized stroke systems, 1 in 4 patients treated with thrombolysis recovered within 24 hours and 1 in 6 had no demonstrable brain injury on imaging. ANN NEUROL 2024;95:347–361 [ABSTRACT FROM AUTHOR]

The original unstructured Glasgow Outcome Scale (uGOS) and the newer structured interviews GOS and the Extended GOS (GOS-E) have been used widely as outcomes in severe traumatic brain injury (TBI) trials. We compared outcome categories (ranging from dead [D] to good recovery [GR]) for each measure in a randomized trial of transfusion threshold and the implications of measure choice and analysis methods for the results of the trial. We planned to explore patient symptomology possibly driving any discrepancies between the patient's uGOS and GOS scores. Category correspondence between uGOS and GOS scores occurred in 160 (88.4%) of the 181 analyzed cases. The GOS-E and GOS instruments incorporated more behavioral/cognitive/social and other components, leading to a worse outcome in some cases than for the uGOS. Choice of outcome measure and analysis led to incongruous conclusions. Dichotomizing uGOS into favorable outcome (GR and moderate disability [MD] categories) versus unfavorable (severe disability [SD], vegetative state [VS], and D categories), we observed a significant effect of transfusion threshold (odds ratio [OR] = 0.51, p = 0.03; adjusted OR = 0.40, p = 0.02). For the same dichotomization of GOS and GOS-E, the effect was not statistically significant but the ORs were similar (ORs between 0.57 and 0.68, p > 0.15 for all). An effect was not detected using ordinal logistic regression or sliding dichotomy method for all three measures. Differences in categorizations of subjects between moderate and severe disability among the scales impacted conclusions of the trial. In future studies, particular attention should be given to implementing GOS measures and describing the methodology for how outcomes were ascertained. [ABSTRACT FROM AUTHOR]

Gold standard prognostic models for long-term outcome in patients with severe traumatic brain injury (TBI) use admission characteristics and are considered useful in some areas but not for clinical practice. In this study, we aimed to build prognostic models for 6-month Glasgow Outcome Score (GOS) in patients with severe TBI, combining baseline characteristics with physiological, treatment, and injury severity data collected during the first 24 h after injury. We used a training dataset of 472 TBI subjects and several data mining algorithms to predict the long-term neurological outcome. Performance of these algorithms was assessed in an independent (test) sample of 158 subjects. The least absolute shrinkage and selection operator (LASSO) led to the highest prediction accuracy (area under the receiving operating characteristic curve = 0.86) in the test set. The most important post-baseline predictor of GOS was the best motor Glasgow Coma Scale (GCS) recorded in the first day post-injury. The LASSO model containing the best motor GCS and baseline variables as predictors outperformed a model with baseline data only. TBI patient physiology of the first day-post-injury did not have a major contribution to patient prognosis six months after injury. In conclusion, 6-month GOS in patients with TBI can be predicted with good accuracy by the end of the first day post-injury, using hospital admission data and information on the best motor GCS achieved during those first 24 h post-injury. Passed the first day after injury, important physiological predictors could emerge from landmark analyses, leading to prediction models of higher accuracy than the one proposed in the current research. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is prevalent among active duty military service members, with studies reporting up to 23% experiencing at least one TBI, with 10–60% of service members reporting at least one subsequent repeat TBI. A TBI has been associated with an increased risk of cumulative effects and long-term neurobehavioral symptoms, impacting operational readiness in the short-term and overall health in the long term. The association between multiple TBI and post-concussive symptoms (PCS), however, defined as symptoms that follow a concussion or TBI, in the military has not been adequately examined. Previous studies in military populations are limited by methodological issues including small sample sizes, the use of non-probability sampling, or failure to include the total number of TBI. To overcome these limitations, we examined the association between the total lifetime number of TBI and total number of PCS among U.S. active duty military service members who participated in the Millennium Cohort Study. A secondary data analysis was conducted using the Millennium Cohort Study's 2014 survey (n = 28,263) responses on self-reported TBI and PCS (e.g., fatigue, restlessness, sleep disturbances, poor concentration, or memory loss). Zero-inflated negative binomial models calculated prevalence ratios (PRs) and 95% confidence intervals (CIs) for the unadjusted and adjusted associations between lifetime TBIs and PCS. A third of military participants reported experiencing one or more TBIs during their lifetime with 72% reporting at least one PCS. As the mean number of PCS increased, mean lifetime TBIs increased. The mean number of PCS by those with four or more TBI (4.63) was more than twice that of those with no lifetime TBI (2.28). One, two, three, and four or more TBI had 1.10 (95% CI: 1.06–1.15), 1.19 (95% CI: 1.14–1.25), 1.23 (95% CI: 1.17–1.30), and 1.30 times (95% CI: 1.24–1.37) higher prevalence of PCS, respectively. The prevalence of PCS was 2.4 (95% CI: 2.32–2.48) times higher in those with post-traumatic stress disorder than their counterparts. Active duty military service members with a history of TBI are more likely to have PCS than those with no history of TBI. These results suggest an elevated prevalence of PCS as the number of TBI increased. This highlights the need for robust, longitudinal studies that can establish a temporal relationship between repetitive TBI and incidence of PCS. These findings have practical relevance for designing both workplace safety prevention measures and treatment options regarding the effect on and from TBI among military personnel. [ABSTRACT FROM AUTHOR]

Introduction Traumatic brain injury (TBI) is an occupational health hazard of military service. Few studies have examined differences in military occupational categories (MOC) which take into consideration the physical demands and job requirements across occupational groups. Methods This study was approved by the University of Texas Health Science Center at Houston Institutional Review Board. Data for this cross-sectional study were obtained from the Naval Health Research Center's Millennium Cohort Study, an ongoing DoD study. Univariate analyses were employed to calculate frequencies and proportions for all variables. Bivariate analyses included unadjusted odds ratios (OR) and 95% CI for the association between all variables and TBI. Multivariable logistic regression was used to calculate adjusted ORs and 95% CIs to assess the association between MOC and TBI, adjusted for potential confounders: sex, race/ethnicity, rank, military status, branch of service, before-service TBI, and panel. Logistic regression models estimated odds of TBI for each MOC, and stratified models estimated odds separately for enlisted and officer MOCs. Results Approximately 27% of all participants reported experiencing a service-related TBI. All MOCs were statistically significantly associated with increased odds of service-related TBI, with a range of 16 to 45%, except for "Health Care" MOCs (OR: 1.01, 95% CI 0.91-1.13). Service members in "Infantry/Tactical Operations" had the highest odds (OR: 1.45, 95% CI 1.31-1.61) of service-related TBI as compared to "Administration & Executives." Among enlisted service members, approximately 28% reported experiencing a service-related TBI. Among enlisted-specific MOCs, the odds of TBI were elevated for those serving in "Infantry, Gun Crews, Seamanship (OR: 1.79, 95% CI 1.58-2.02)," followed by "Electrical/Mechanical Equipment Repairers (OR: 1.23, 95% CI 1.09-1.38)," "Service & Supply Handlers (OR 1.21, 95% CI 1.08-1.37)," "Other Technical & Allied Specialists (OR 1.21, 95% CI 1.02-1.43)," "Health Care Specialists (OR 1.19, 95% CI 1.04-1.36)," and "Communications & Intelligence (OR: 1.16, 95% CI 1.02-1.31)," compared to "Functional Support & Administration." Among officer service members, approximately 24% reported experiencing a service-related TBI. After adjustment the odds of TBI were found to be significant for those serving as "Health Care Officers" (OR: 0.65, 95% CI: 0.52-0.80) and "Intelligence Officers" (OR: 1.27, 95% CI: 1.01-1.61). Conclusions A strength of this analysis is the breakdown of MOC associations with TBI stratified by enlisted and officer ranks, which has been previously unreported. Given the significantly increased odds of service-related TBI reporting within enlisted ranks, further exploration into the location (deployed versus non-deployed) and mechanism (e.g. blast, training, sports, etc.) for these injuries is needed. Understanding injury patterns within these military occupations is necessary to increase TBI identification, treatment, and foremost, prevention. Results highlight the importance of examining specific occupational categories rather than relying on gross categorizations, which do not account for shared knowledge, skills, and abilities within occupations. The quantification of risk among enlisted MOCs suggests a need for further research into the causes of TBI. [ABSTRACT FROM AUTHOR]

Prognostic assessment in traumatic brain injury (TBI) is embedded deeply in clinical care. Considering the limitations of current prognostic indicators, there is increasing interest in understanding the role of new biomarkers, and in finding other prognostic indicators of long-term outcomes following TBI. New prognostic indicators may result in the development of more accurate prediction models that could be useful for both risk stratification and clinical decision making. We aimed to review methodological issues and provide tentative guidelines for prognostic research in TBI. Prognostic factor research focuses on the role of a specific patient or disease-related characteristic in relation to outcome. Typically, univariable relations of the prognostic factor are studied, followed by analyses adjusting for other variables related to the outcome. Following existing guidelines, we emphasize the importance of transparent reporting of patient and specimen characteristics, study design, clinical end-points, and statistical analysis. Prognostic model research considers combinations of predictors, with challenges for model specification, estimation, evaluation, validation, and presentation. We highlight modern approaches and opportunities related to missing values, exploration of non-linear effects, and assessing between-study heterogeneity. Prognostic research in TBI can be improved if key methodological principles are adhered to and when research is performed in collaboration among multiple centers to ensure generalizability. [ABSTRACT FROM AUTHOR]

Despite pre-clinical evidence for the role of inflammation in traumatic brain injury (TBI), there is limited data on inflammatory biomarkers in mild TBI (mTBI). In this study, we describe the profile of plasma inflammatory cytokines and explore associations between these cytokines and neuropsychological outcomes after mTBI. Patients with mTBI with negative computed tomography and orthopedic injury (OI) controls without mTBI were prospectively recruited from emergency rooms at three trauma centers. Plasma inflammatory cytokine levels were measured from venous whole–blood samples that were collected at enrollment (within 24 h of injury) and at 6 months after injury. Neuropsychological tests were performed at 1 week, 1 month, 3 months, and 6 months after the injury. Multivariate regression analysis was performed to identify associations between inflammatory cytokines and neuropsychological outcomes. A total of 53 mTBI and 24 OI controls were included in this study. The majority of patients were male (62.3%), and injured in motor vehicle accidents (37.7%). Plasma interleukin (IL)-2 (p = 0.01) and IL-6 (p = 0.01) within 24 h post-injury were significantly higher for mTBI patients compared with OI controls. Elevated plasma IL-2 at 24 h was associated with more severe 1-week post-concussive symptoms (p = 0.001). At 6 months, elevated plasma IL-10 was associated with greater depression scores (p = 0.004) and more severe post-traumatic stress disorder (PTSD) symptoms (p = 0.001). Plasma cytokine levels (within 24 h and at 6 months post-injury) were significantly associated with early and late post-concussive symptoms, PTSD, and depression scores after mTBI. These results highlight the potential role of inflammation in the pathophysiology of post-traumatic symptoms after mTBI. [ABSTRACT FROM AUTHOR]

Objective: To characterize admission characteristics associated with multiple organ dysfunction following traumatic brain injury - including head injury severity, polytrauma, and plasma cytokine levels. Design: Secondary analysis of a randomized trial. Setting: Two level 1 trauma centers in Houston, TX. Patients: 200 patients with closed head injury who were unable to follow commands and enrolled within 6 hours of injury. Measurements: Multiple organ dysfunction was measured by the Sequential Organ Failure Assessment (SOFA) score. Dichotomized International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) score and Injury Severity Score (ISS) were used to assess head injury severity and polytrauma at baseline, respectively. Levels of plasma and cerebral spinal fluid (CSF) inflammatory markers were determined using commercially available kits. In order to distinguish between primary and secondary brain injury, analyses were divided into early (within 3 days of injury) and late time points (after 3 days of injury). Results: Respiratory dysfunction occurred in a more delayed fashion (peak incidence at 5 days after injury) than dysfunction of cardiovascular, renal, or coagulation systems. High-risk head injury was associated with a higher total SOFA score than low-risk injury (7 vs 5, median; P < 0.001). However, polytrauma was not associated with higher total SOFA scores. Initial serum levels of IL-6, IL-8, and IL-10 showed significant positive correlation with total SOFA scores (r = 0.39, r = 0.27, and r = 0.29; P < 0.001). Conclusions: Severity of head injury but not polytrauma is associated with multiple organ dysfunction after traumatic brain injury. Plasma cytokine levels show significant correlation with the extent of multiple organ dysfunction. [ABSTRACT FROM AUTHOR]