Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics

Long-term survival of traumatic brain injury and intra-cerebral haemorrhage patients: A multicentric observational cohort

PURPOSE

Mortality is often assessed during ICU stay and early after, but rarely at later stage. We aimed to compare the long-term mortality between TBI and ICH patients.

MATERIALS AND METHODS

From an observational cohort, we studied 580 TBI patients and 435 ICH patients, admitted from January 2013 to February 2021 in 3 ICUs and alive at 7-days post-ICU discharge. We performed a Lasso-penalized Cox survival analysis.

RESULTS

We estimated 7-year survival rates at 72.8% (95%CI from 67.3% to 78.7%) for ICH patients and at 84.9% (95%CI from 80.9% to 89.1%) for TBI patients: ICH patients presenting a higher mortality risk than TBI patients. Additionally, we identified variables associated with higher mortality risk (age, ICU length of stay, tracheostomy, low GCS, absence of intracranial pressure monitoring). We also observed anisocoria related with the mortality risk in the early stage after ICU stay.

CONCLUSIONS

In this ICU survivor population with a prolonged follow-up, we highlight an acute risk of death after ICU stay, which seems to last longer in ICH patients. Several variables characteristic of disease severity appeared associated with long-term mortality, raising the hypothesis that the most severe patients deserve closer follow-up after ICU stay.

Post-traumatic hyperoxia after pediatric TBI

OBJECTIVE

Hyperoxia has been suggested as a mechanism for secondary injury following adult traumatic brain injury (TBI), but its effects have not been well described in pediatric patients.

METHODS

Pediatric (≤18yo) TBI patients were identified in a prospective institutional registry from October 2008 to April 2022. The first, highest, and the Area Under the Curve (AUC) PaO2 in the first 24 hours were collected and calculated for each patient from arterial blood gas reports after admission to the ICU. Neurological outcome after 6 months was measured using dichotomized modified Rankin Scale (mRS) and Glasgow Outcome Scale - Extended (GOS-E). Multivariable logistic regression models were used to determine if the three measurements for hyperoxia predicted an unfavorable outcome after controlling for well-established clinical and imaging predictors of outcome.

RESULTS

We identified 98 pediatric patients with severe accidental TBI during the study period. Hyperoxia (PaO2 > 300 mmHg) occurred in 33% of the patients. The presence of elevated PaO2 values, determined by all three evaluations of hyperoxia, was not associated with unfavorable outcome after 6 months.

CONCLUSION

Utilizing multiple methods to assess exposure, hyperoxia was present in a substantial number of patients with severe TBI but was not associated with an unfavorable outcome.

Improved mortality analysis in early-phase dose-ranging clinical trials for emergency medical diseases using Bayesian time-to-event models with active comparators

Emergency medical diseases (EMDs) are the leading cause of death worldwide. A time-to-death analysis is needed to accurately identify the risks and describe the pattern of an EMD because the mortality rate can peak early and then decline. Dose-ranging Phase II clinical trials are essential for developing new therapies for EMDs. However, most dose-finding trials do not analyze mortality as a time-to-event endpoint. We propose three Bayesian dose-response time-to-event models for a secondary mortality analysis of a clinical trial: a two-group (active treatment vs control) model, a three-parameter sigmoid EMAX model, and a hierarchical EMAX model. The study also incorporates one specific active treatment as an active comparator in constructing three new models. We evaluated the performance of these six models and a very popular independent model using simulated data motivated by a randomized Phase II clinical trial focused on identifying the most effective hyperbaric oxygen dose to achieve favorable functional outcomes in patients with severe traumatic brain injury. The results show that the three-group, EMAX, and EMAX model with an active comparator produce the smallest averaged mean squared errors and smallest mean absolute biases. We provide a new approach for time-to-event analysis in early-phase dose-ranging clinical trials for EMDs. The EMAX model with an active comparator can provide valuable insights into the mortality analysis of new EMDs or other conditions that have changing risks over time. The restricted mean survival time, a function of the model's hazards, is recommended for displaying treatment effects for EMD research.

Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction

BACKGROUND

The prognostication of long-term functional outcomes remains challenging in patients with traumatic brain injury (TBI). Our aim was to demonstrate that intensive care unit (ICU) variables are not efficient to predict 6-month functional outcome in survivors with moderate to severe TBI (msTBI) but are mostly associated with mortality, which leads to a mortality bias for models predicting a composite outcome of mortality and severe disability.

METHODS

We analyzed the data from the multicenter randomized controlled Continuous Hyperosmolar Therapy in Traumatic Brain-Injured Patients trial and developed predictive models using machine learning methods and baseline characteristics and predictors collected during ICU stay. We compared our models' predictions of 6-month binary Glasgow Outcome Scale extended (GOS-E) score in all patients with msTBI (unfavorable GOS-E 1-4 vs. favorable GOS-E 5-8) with mortality (GOS-E 1 vs. GOS-E 2-8) and binary functional outcome in survivors with msTBI (severe disability GOS-E 2-4 vs. moderate to no disability GOS-E 5-8). We investigated the link between ICU variables and long-term functional outcomes in survivors with msTBI using predictive modeling and factor analysis of mixed data and validated our hypotheses on the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model.

RESULTS

Based on data from 370 patients with msTBI and classically used ICU variables, the prediction of the 6-month outcome in survivors was inefficient (mean area under the receiver operating characteristic 0.52). Using factor analysis of mixed data graph, we demonstrated that high-variance ICU variables were not associated with outcome in survivors with msTBI (p = 0.15 for dimension 1, p = 0.53 for dimension 2) but mostly with mortality (p < 0.001 for dimension 1), leading to a mortality bias for models predicting a composite outcome of mortality and severe disability. We finally identified this mortality bias in the IMPACT model.

CONCLUSIONS

We demonstrated using machine learning-based predictive models that classically used ICU variables are strongly associated with mortality but not with 6-month outcome in survivors with msTBI, leading to a mortality bias when predicting a composite outcome of mortality and severe disability.

Discovery of generalizable TBI phenotypes using multivariate time-series clustering

Traumatic Brain Injury (TBI) presents a broad spectrum of clinical presentations and outcomes due to its inherent heterogeneity, leading to diverse recovery trajectories and varied therapeutic responses. While many studies have delved into TBI phenotyping for distinct patient populations, identifying TBI phenotypes that consistently generalize across various settings and populations remains a critical research gap. Our research addresses this by employing multivariate time-series clustering to unveil TBI's dynamic intricates. Utilizing a self-supervised learning-based approach to clustering multivariate time-Series data with missing values (SLAC-Time), we analyzed both the research-centric TRACK-TBI and the real-world MIMIC-IV datasets. Remarkably, the optimal hyperparameters of SLAC-Time and the ideal number of clusters remained consistent across these datasets, underscoring SLAC-Time's stability across heterogeneous datasets. Our analysis revealed three generalizable TBI phenotypes (α, β, and γ), each exhibiting distinct non-temporal features during emergency department visits, and temporal feature profiles throughout ICU stays. Specifically, phenotype α represents mild TBI with a remarkably consistent clinical presentation. In contrast, phenotype β signifies severe TBI with diverse clinical manifestations, and phenotype γ represents a moderate TBI profile in terms of severity and clinical diversity. Age is a significant determinant of TBI outcomes, with older cohorts recording higher mortality rates. Importantly, while certain features varied by age, the core characteristics of TBI manifestations tied to each phenotype remain consistent across diverse populations.

Effect of Early Versus Delayed Tracheostomy Strategy on Functional Outcome of Patients With Severe Traumatic Brain Injury: A Target Trial Emulation

OBJECTIVES

Optimal timing of tracheostomy in severe traumatic brain injury (TBI) is unknown due to lack of clinical trials. We emulated a target trial to estimate the effect of early vs. delayed tracheostomy strategy on functional outcome of patients with severe TBI.

DESIGN

Target trial emulation using 1:1 balanced risk-set matching.

SETTING

North American hospitals participating in the TBI Hypertonic Saline randomized controlled trial of the Resuscitation Outcomes Consortium.

PATIENTS

The prematching population consisted of patients with TBI and admission Glasgow Coma Scale less than or equal to 8, who were alive and on mechanical ventilation on the fourth day following trial enrollment, and stayed in the ICU for at least 5 days. Patients with absolute indication for tracheostomy and patients who died during the first 28 days with a decision to withdraw care were excluded.

INTERVENTIONS

We matched patients who received tracheostomy at a certain timepoint (early group) with patients who had not received tracheostomy at the same timepoint but were at-risk of tracheostomy in the future (delayed group). The primary outcome was a poor 6-month functional outcome, defined as Glasgow Outcome Scale-Extended less than or equal to 4.

MEASUREMENTS AND MAIN RESULTS

Out of 1282 patients available for analysis, 275 comprised the prematching population, with 75 pairs being created postmatching. Median time of tracheostomy differed significantly in the early vs. the delayed group (7.0 d [6.0-10.0 d] vs. 12.0 d [9.8-18.3 d]; p < 0.001). Only 40% of patients in the delayed group received tracheostomy. There was no statistically significant difference between groups regarding poor 6-month functional outcome (early: 68.0% vs. delayed: 72.0%; p = 0.593).

CONCLUSIONS

In a target trial emulation, early as opposed to delayed tracheostomy strategy was not associated with differences in 6-month functional outcome following severe TBI. Considering the limitations of target trial emulations, delaying tracheostomy through a "watchful waiting" approach may be appropriate.

Detecting awareness after acute brain injury

Advances over the past two decades in functional neuroimaging have provided new diagnostic and prognostic tools for patients with severe brain injury. Some of the most pertinent developments in this area involve the assessment of residual brain function in patients in the intensive care unit during the acute phase of severe injury, when they are at their most vulnerable and prognosis is uncertain. Advanced neuroimaging techniques, such as functional MRI and EEG, have now been used to identify preserved cognitive processing, including covert conscious awareness, and to relate them to outcome in patients who are behaviourally unresponsive. Yet, technical and logistical challenges to clinical integration of these advanced neuroimaging techniques remain, such as the need for specialised expertise to acquire, analyse, and interpret data and to determine the appropriate timing for such assessments. Once these barriers are overcome, advanced functional neuroimaging technologies could improve diagnosis and prognosis for millions of patients worldwide.

Traumatic brain injury in elderly population: A global systematic review and meta-analysis of in-hospital mortality and risk factors among 2.22 million individuals

BACKGROUND

Traumatic brain injury (TBI) among elderly individuals poses a significant global health concern due to the increasing ageing population.

METHODS

We searched PubMed, Cochrane Library, and Embase from database inception to Feb 1, 2024. Studies performed in inpatient settings reporting in-hospital mortality of elderly people (≥60 years) with TBI and/or identifying risk factors predictive of such outcomes, were included. Data were extracted from published reports, in-hospital mortality as our main outcome was synthesized in the form of rates, and risk factors predicting in-hospital mortality was synthesized in the form of odds ratios. Subgroup analyses, meta-regression and dose-response meta-analysis were used in our analyses.

FINDINGS

We included 105 studies covering 2217,964 patients from 30 countries/regions. The overall in-hospital mortality of elderly patients with TBI was 16 % (95 % CI 15 %-17 %) from 70 studies. In-hospital mortality was 5 % (95 % CI, 3 %-7 %), 18 % (95 % CI, 12 %-24 %), 65 % (95 % CI, 59 %-70 %) for mild, moderate and severe subgroups from 10, 7, and 23 studies, respectively. A decrease in in-hospital mortality over years was observed in overall (1981-2022) and in severe (1986-2022) elderly patients with TBI. Older age 1.69 (95 % CI, 1.58-1.82, P < 0.001), male gender 1.34 (95 % CI, 1.25-1.42, P < 0.001), clinical conditions including traffic-related cause of injury 1.22 (95 % CI, 1.02-1.45, P = 0.029), GCS moderate (GCS 9-12 compared to GCS 13-15) 4.33 (95 % CI, 3.13-5.99, P < 0.001), GCS severe (GCS 3-8 compared to GCS 13-15) 23.09 (95 % CI, 13.80-38.63, P < 0.001), abnormal pupillary light reflex 3.22 (95 % CI, 2.09-4.96, P < 0.001), hypotension after injury 2.88 (95 % CI, 1.06-7.81, P = 0.038), polytrauma 2.31 (95 % CI, 2.03-2.62, P < 0.001), surgical intervention 2.21 (95 % CI, 1.22-4.01, P = 0.009), pre-injury health conditions including pre-injury comorbidity 1.52 (95 % CI, 1.24-1.86, P = 0.0020), and pre-injury anti-thrombotic therapy 1.51 (95 % CI, 1.23-1.84, P < 0.001) were related to higher in-hospital mortality in elderly patients with TBI. Subgroup analyses according to multiple types of anti-thrombotic drugs with at least two included studies showed that anticoagulant therapy 1.70 (95 % CI, 1.04-2.76, P = 0.032), Warfarin 2.26 (95 % CI, 2.05-2.51, P < 0.001), DOACs 1.99 (95 % CI, 1.43-2.76, P < 0.001) were related to elevated mortality. Dose-response meta-analysis of age found an odds ratio of 1.029 (95 % CI, 1.024-1.034, P < 0.001) for every 1-year increase in age on in-hospital mortality.

CONCLUSIONS

In the field of elderly patients with TBI, the overall in-hospital mortality and its temporal-spatial feature, the subgroup in-hospital mortalities according to injury severity, and dose-response meta-analysis of age were firstly comprehensively summarized. Substantial key risk factors, including the ones previously not elucidated, were identified. Our study is thus of help in underlining the importance of treating elderly TBI, providing useful information for healthcare providers, and initiating future management guidelines. This work underscores the necessity of integrating elderly TBI treatment and management into broader health strategies to address the challenges posed by the aging global population.

REVIEW REGISTRATION

PROSPERO CRD42022323231.

Performance of the IMPACT and CRASH prognostic models for traumatic brain injury in a contemporary multicenter cohort: a TRACK-TBI study

OBJECTIVE

The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization After Significant Head Injury (CRASH) prognostic models for mortality and outcome after traumatic brain injury (TBI) were developed using data from 1984 to 2004. This study examined IMPACT and CRASH model performances in a contemporary cohort of US patients.

METHODS

The prospective 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study (enrollment years 2014-2018) enrolled subjects aged ≥ 17 years who presented to level I trauma centers and received head CT within 24 hours of TBI. Data were extracted from the subjects who met the model criteria (for IMPACT, Glasgow Coma Scale [GCS] score 3-12 with 6-month Glasgow Outcome Scale-Extended [GOSE] data [n = 441]; for CRASH, GCS score 3-14 with 2-week mortality data and 6-month GOSE data [n = 831]). Analyses were conducted in the overall cohort and stratified on the basis of TBI severity (severe/moderate/mild TBI defined as GCS score 3-8/9-12/13-14), age (17-64 years or ≥ 65 years), and the 5 top enrolling sites. Unfavorable outcome was defined as GOSE score 1-4. Original IMPACT and CRASH model coefficients were applied, and model performances were assessed by calibration (intercept [< 0 indicated overprediction; > 0 indicated underprediction] and slope) and discrimination (c-statistic).

RESULTS

Overall, the IMPACT models overpredicted mortality (intercept -0.79 [95% CI -1.05 to -0.53], slope 1.37 [1.05-1.69]) and acceptably predicted unfavorable outcome (intercept 0.07 [-0.14 to 0.29], slope 1.19 [0.96-1.42]), with good discrimination (c-statistics 0.84 and 0.83, respectively). The CRASH models overpredicted mortality (intercept -1.06 [-1.36 to -0.75], slope 0.96 [0.79-1.14]) and unfavorable outcome (intercept -0.60 [-0.78 to -0.41], slope 1.20 [1.03-1.37]), with good discrimination (c-statistics 0.92 and 0.88, respectively). IMPACT overpredicted mortality and acceptably predicted unfavorable outcome in the severe and moderate TBI subgroups, with good discrimination (c-statistic ≥ 0.81). CRASH overpredicted mortality in the severe and moderate TBI subgroups and acceptably predicted mortality in the mild TBI subgroup, with good discrimination (c-statistic ≥ 0.86); unfavorable outcome was overpredicted in the severe and mild TBI subgroups with adequate discrimination (c-statistic ≥ 0.78), whereas calibration was nonlinear in the moderate TBI subgroup. In subjects ≥ 65 years of age, the models performed variably (IMPACT-mortality, intercept 0.28, slope 0.68, and c-statistic 0.68; CRASH-unfavorable outcome, intercept -0.97, slope 1.32, and c-statistic 0.88; nonlinear calibration for IMPACT-unfavorable outcome and CRASH-mortality). Model performance differences were observed across the top enrolling sites for mortality and unfavorable outcome.

CONCLUSIONS

The IMPACT and CRASH models adequately discriminated mortality and unfavorable outcome. Observed overestimations of mortality and unfavorable outcome underscore the need to update prognostic models to incorporate contemporary changes in TBI management and case-mix. Investigations to elucidate the relationships between increased survival, outcome, treatment intensity, and site-specific practices will be relevant to improve models in specific TBI subpopulations (e.g., older adults), which may benefit from the inclusion of blood-based biomarkers, neuroimaging features, and treatment data.

MRI and Clinical Variables for Prediction of Outcomes After Pediatric Severe Traumatic Brain Injury

Importance

Traumatic brain injury (TBI) is a leading cause of death and disability in children, and predicting functional outcome after TBI is challenging. Magnetic resonance imaging (MRI) is frequently conducted after severe TBI; however, the predictive value of MRI remains uncertain.

Objectives

To identify early MRI measures that predict long-term outcome after severe TBI in children and to assess the added predictive value of MRI measures over well-validated clinical predictors.

Design, Setting, and Participants

This preplanned prognostic study used data from the Approaches and Decisions in Acute Pediatric TBI (ADAPT) prospective observational comparative effectiveness study. The ADAPT study enrolled 1000 consecutive children (aged <18 years) with severe TBI between February 1, 2014, and September 30, 2017. Participants had a Glasgow Coma Scale (GCS) score of 8 or less and received intracranial pressure monitoring. Magnetic resonance imaging scans performed as part of standard clinical care within 30 days of injury were collected at 24 participating sites in the US, UK, and Australia. Summary imaging measures were correlated with the Glasgow Outcome Scale-Extended for Pediatrics (GOSE-Peds), and the predictive value of MRI measures was compared with the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) core clinical predictors. Data collection, image analysis, and data analyses were completed in July 2023.

Exposures

Pediatric severe TBI with an MRI scan performed as part of clinical care.

Main Outcomes and Measures

All measures were selected a priori. Magnetic resonance imaging measures included contusion, ischemia, diffuse axonal injury, intracerebral hemorrhage, and brainstem injury. Clinical predictors included the IMPACT core measures (GCS motor score and pupil reactivity). All models adjusted for age and sex. Outcome measures included the GOSE-Peds score obtained at 3, 6, and 12 months after injury.

Results

This study included 233 children with severe TBI who were enrolled at participating sites and had an MRI scan and preselected clinical predictors available. Their median age was 6.9 (IQR, 3.0-13.3) years, and more than half of participants (134 [57.5%]) were male. In a multivariable model including MRI measures and IMPACT core clinical variables, contusion volume (odds ratio [OR], 1.13; 95% CI, 1.02-1.26), brain ischemia (OR, 2.11; 95% CI, 1.58-2.81), brainstem lesions (OR, 5.40; 95% CI, 1.90-15.35), and pupil reactivity were each independently associated with GOSE-Peds score. Adding MRI measures to the IMPACT clinical predictors significantly improved model fit and discrimination between favorable and unfavorable outcomes compared with IMPACT predictors alone (area under the receiver operating characteristic curve, 0.77; 95% CI, 0.72-0.85 vs 0.67; 95% CI, 0.61-0.76 for GOSE-Peds score >3 at 6 months after injury).

Conclusions and Relevance

In this prognostic study of children with severe TBI, the addition of MRI measures significantly improved outcome prediction over well-established and validated clinical predictors. Magnetic resonance imaging should be considered in children with severe TBI to inform prognosis and may also promote stratification of patients in future clinical trials.

Machine Learning for Predicting Stillbirth: A Systematic Review

Stillbirth is a major global issue, with over 5 million cases each year. The multifactorial nature of stillbirth makes it difficult to predict. Artificial intelligence (AI) and machine learning (ML) have the potential to enhance clinical decision-making and enable precise assessments. This study reviewed the literature on predictive ML models for stillbirth highlighting input characteristics, performance metrics, and validation. The PubMed, Cochrane, and Web of Science databases were searched for studies using AI to develop predictive models for stillbirth. Findings were analyzed qualitatively using narrative synthesis and graphics. Risk of bias and the applicability of the studies were assessed using PROBAST. Model design and performance were discussed. Eight studies involving 14,840,654 women with gestational ages ranging from 20 weeks to full term were included in the qualitative analysis. Most studies used neural networks, random forests, and logistic regression algorithms. The number of predictive features varied from 14 to 53. Only 50% of studies validated the models. Cross-validation was commonly employed, and only 25% of studies performed external validation. All studies reported area under the curve as a performance metric (range 0.54-0.9), and five studies reported sensitivity (range, 60- 90%) and specificity (range, 64 - 93.3%). A stacked ensemble model that analyzed 53 features performed better than other models (AUC = 0.9; sensitivity and specificity > 85%). Available ML models can attain a considerable degree of accuracy for prediction of stillbirth; however, these models require further development before they can be applied in a clinical setting.

Assessing outcomes in traumatic brain injury: Helsinki score versus Glasgow coma scale

BACKGROUND

The precision of assessment and prognosis in traumatic brain injury (TBI) is paramount for effective triage and informed therapeutic strategies. While the Glasgow Coma Scale (GCS) remains the cornerstone for TBI evaluation, it overlooks critical primary imaging findings. The Helsinki Score (HS), a novel tool designed to incorporate radiological data, offers a promising approach to predicting TBI outcomes. This study aims to evaluate the prognostic efficacy of HS in comparison to GCS across a substantial TBI patient cohort.

METHODS

This retrospective study encompassed TBI patients treated at our institution between 2008 and 2019, specifically those with an admission GCS of 14 or lower. We assessed both the initial GCS and the HS derived from primary CT scans. Key outcome metrics included the Glasgow Outcome Scale (GOS) and mortality rates at hospital discharge and at 6 and 12-month intervals post-discharge. Predictive performances of GCS and HS were analyzed through Receiver Operating Characteristic (ROC) curves and Kendall tau-b correlation coefficients against each outcome.

RESULTS

The study included 544 patients, with an average age of 62.2 ± 21.5 years, median initial GCS of 14, and a median HS of 3. The mortality rate at discharge stood at 8.6%, with a median GOS of 4. Both GCS and HS demonstrated significant correlations with mortality and GOS outcomes (p < 0.05). Notably, HS showed a markedly superior correlation with mortality (τb = 0.36) compared to GCS (τb = -0.11) and with GOS outcomes (τb = -0.40 for HS vs. τb = 0.33 for GCS). ROC analyses affirmed HS's enhanced predictive accuracy over GCS for both mortality (AUC of 0.79 for HS vs. 0.62 for GCS) and overall outcomes (AUC of 0.77 for HS vs. 0.71 for GCS).

CONCLUSION

The findings validate the HS in a large German cohort and suggest that radiological assessments alone, as exemplified by HS, can surpass the traditional GCS in predicting TBI outcomes. However, the HS, despite its efficacy, lacks the integration of clinical evaluation, a vital component in TBI management. This underscores the necessity for a holistic approach that amalgamates both radiological and clinical insights for a more comprehensive and accurate prognostication in TBI care.

Evaluating and Updating the IMPACT Model to Predict Outcomes in Two Contemporary North American Traumatic Brain Injury Cohorts

The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) model is a widely recognized prognostic model applied after traumatic brain injury (TBI). However, it was developed with patient cohorts that may not reflect modern practice patterns in North America. We analyzed data from two sources: the placebo arm of the phase II double-blinded, multicenter, randomized controlled trial Prehospital Tranexamic Acid for TBI (TXA) cohort and an observational cohort with similar inclusion/exclusion criteria (Predictors of Low-risk Phenotypes after Traumatic Brain Injury Incorporating Proteomic Biomarker Signatures [PROTIPS] cohort). All three versions of the IMPACT model-core, extended, and laboratory-were evaluated for 6-month mortality (Glasgow Outcome Scale Extended [GOSE] = 1) and unfavorable outcomes (GOSE = 1-4). Calibration (intercept and slope) and discrimination (area under the receiver operating characteristic curve [ROC-AUC]) were used to assess model performance. We then compared three model updating methods-recalibration in the large, logistic recalibration, and coefficient update-with the best update method determined by likelihood ratio tests. In our calibration analysis, recalibration improved both intercepts and slopes, indicating more accurate predicted probabilities when recalibration was done. Discriminative performance of the IMPACT models, measured by AUC, showed mortality prediction ROCs between 0.61 and 0.82 for the TXA cohort, with the coefficient updated Lab model achieving the highest at 0.84. Unfavorable outcomes had lower AUCs, ranging from 0.60 to 0.79. Similarly, in the PROTIPS cohort, AUCs for mortality ranged from 0.75 to 0.82, with the coefficient updated Lab model also showing superior performance (AUC 0.84). Unfavorable outcomes in this cohort presented AUCs from 0.67 to 0.73, consistently lower than mortality predictions. The closed testing procedure using likelihood ratio tests consistently identified the coefficient update model as superior, outperforming the original and recalibrated models across all cohorts. In our comprehensive evaluation of the IMPACT model, the coefficient updated models were the best performing across all cohorts through a structured closed testing procedure. Thus, standardization of model updating procedures is needed to reproducibly determine the best performing versions of IMPACT that reflect the specific characteristics of a dataset.

Intracranial Pressure Thresholds for Cerebral Autoregulation Impairment: Age-Stratified Analysis of Ultra-Low-Frequency Pressure Reactivity Index (UL-PRx) in Traumatic Brain Injury

BACKGROUND

The study investigated the effectiveness of low-frequency sampling in detecting alterations in cerebrovascular reactivity (CVR) associated with changes in intracranial pressure (ICP) in patients with traumatic brain injury (TBI) across different age groups. The primary objective was to investigate an ICP threshold that indicates a decrease in CVR as evidenced by a significant increase in the ultra-low-frequency pressure reactivity index (UL-PRx). Additionally, the study aimed to develop an age-based categorization method for patients with TBI to investigate the differences between these ICP thresholds in different age groups.

METHODS

In this retrospective analysis, data from 263 patients with TBI were prospectively collected. ICP and mean arterial pressure were extracted from the hospital database at 5-min intervals. Demographic details, clinical presentation, computed tomography scans, neurosurgical interventions, and 12-months outcome were recorded. ICP versus UL-PRx values were categorized into ICP bins and graphically represented with boxplots for each age group, illustrating how as ICP values rise, there is a bin (age-tailored ICP [AT-ICP]) beyond which UL-PRx shows a sudden increase, indicating CVR loss. Homogeneous age groups were established to obtain a consistent AT-ICP threshold. The discriminatory ability of the AT-ICP thresholds was compared with the guideline-recommended thresholds by calculating the area under the Receiver Operating Characteristic curve of the ICP-derived indices (dose above threshold, and the hourly dosage above threshold).

RESULTS

Age groups 0-5, 6-20, 21-60, 61-70, and 71-85 years were the best age subdivisions, corresponding to AT-ICP thresholds of 20, 30, 35, 25, and 30 mmHg, respectively. The AT-ICP thresholds exhibited better discriminative ability compared with the guideline-recommended thresholds.

CONCLUSIONS

The AT-ICP thresholds offer a novel approach for estimating CVR impairment and the developed method represents an alternative solution to address the age stratification issue in patients with TBI.

The Australian Traumatic Brain Injury Initiative: Systematic Review of Clinical Factors Associated with Outcomes in People with Moderate-Severe Traumatic Brain Injury

The aim of the Australian Traumatic Brain Injury Initiative (AUS-TBI) is to design a data dictionary to inform data collection and facilitate prediction of outcomes for moderate-severe traumatic brain injury (TBI) across Australia. The process has engaged diverse stakeholders across six areas: social, health, clinical, biological, acute interventions, and long-term outcomes. Here, we report the results of the clinical review. Standardized searches were implemented across databases to April 2022. English-language reports of studies evaluating an association between a clinical factor and any clinical outcome in at least 100 patients with moderate-severe TBI were included. Abstracts, and full-text records, were independently screened by at least two reviewers in Covidence. The findings were assessed through a consensus process to determine inclusion in the AUS-TBI data resource. The searches retrieved 22,441 records, of which 1137 were screened at full text and 313 papers were included. The clinical outcomes identified were predominantly measures of survival and disability. The clinical predictors most frequently associated with these outcomes were the Glasgow Coma Scale, pupil reactivity, and blood pressure measures. Following discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous studies evaluating associations between clinical factors and outcomes in patients with moderate-severe TBI. A small number of factors were reported consistently, however, how and when these factors were assessed varied. The findings of this review and the subsequent consensus process have informed the development of an evidence-informed data dictionary for moderate-severe TBI in Australia.

Traumatic Brain Injury as an Independent Predictor of Futility in the Early Resuscitation of Patients in Hemorrhagic Shock

This review explores the concept of futility timeouts and the use of traumatic brain injury (TBI) as an independent predictor of the futility of resuscitation efforts in severely bleeding trauma patients. The national blood supply shortage has been exacerbated by the lingering influence of the COVID-19 pandemic on the number of blood donors available, as well as by the adoption of balanced hemostatic resuscitation protocols (such as the increasing use of 1:1:1 packed red blood cells, plasma, and platelets) with and without early whole blood resuscitation. This has underscored the urgent need for reliable predictors of futile resuscitation (FR). As a result, clinical, radiologic, and laboratory bedside markers have emerged which can accurately predict FR in patients with severe trauma-induced hemorrhage, such as the Suspension of Transfusion and Other Procedures (STOP) criteria. However, the STOP criteria do not include markers for TBI severity or transfusion cut points despite these patients requiring large quantities of blood components in the STOP criteria validation cohort. Yet, guidelines for neuroprognosticating patients with TBI can require up to 72 h, which makes them less useful in the minutes and hours following initial presentation. We examine the impact of TBI on bleeding trauma patients, with a focus on those with coagulopathies associated with TBI. This review categorizes TBI into isolated TBI (iTBI), hemorrhagic isolated TBI (hiTBI), and polytraumatic TBI (ptTBI). Through an analysis of bedside parameters (such as the proposed STOP criteria), coagulation assays, markers for TBI severity, and transfusion cut points as markers of futilty, we suggest amendments to current guidelines and the development of more precise algorithms that incorporate prognostic indicators of severe TBI as an independent parameter for the early prediction of FR so as to optimize blood product allocation.

Autoregulatory Cerebral Perfusion Pressure Insults in Traumatic Brain Injury and Aneurysmal Subarachnoid Hemorrhage: The Role of Insult Intensity and Duration on Clinical Outcome

BACKGROUND

This single-center, retrospective study investigated the outcome effect of the combined intensity and duration of differences between actual cerebral perfusion pressure (CPP) and optimal cerebral perfusion pressure (CPPopt), and also for absolute CPP, in patients with traumatic brain injury (TBI) and aneurysmal subarachnoid hemorrhage (aSAH).

METHODS

A total of 378 TBI and 432 aSAH patients treated in a neurointensive care unit between 2008 and 2018 with at least 24 hours of CPPopt data during the first 10 days following injury, and with 6-month (TBI) or 12-month (aSAH) extended Glasgow Outcome Scale (GOS-E) scores, were included in the study. ∆CPPopt-insults (∆CPPopt=actual CPP-CPPopt) and CPP-insults were visualized as 2-dimensional plots to highlight the combined effect of insult intensity (mm Hg) and duration (min) on patient outcome.

RESULTS

In TBI patients, a zone of ∆CPPopt ± 10 mm Hg was associated with more favorable outcome, with transitions towards unfavorable outcome above and below this zone. CPP in the range of 60 to 80 mm Hg was associated with higher GOS-E, whereas CPP outside this range was associated with lower GOS-E. In aSAH patients, there was no clear transition from higher to lower GOS-E for ∆CPPopt-insults; however, there was a transition from favorable to unfavorable outcome when CPP was <80 mm Hg.

CONCLUSIONS

TBI patients with CPP close to CPPopt exhibited better clinical outcomes, and absolute CPP within the 60 to 80 mm Hg range was also associated with favorable outcome. In aSAH patients, there was no clear transition for ∆CPPopt-insults in relation to outcome, whereas generally high absolute CPP values were associated overall with favorable recovery.

A systematic review and meta-analysis of major blood protein biomarkers that predict unfavorable outcomes in severe traumatic brain injury

INTRODUCTION

Severe traumatic brain injury (TBI) presentation and late clinical outcomes are usually evaluated by the Glasgow Outcome Scale-Extended (GOS-E), which lacks strong prognostic predictability. Several blood biomarkers have been linked to TBI, such as Tau, GFAP, UCH-L1, S-100B, and NSE. Clinical values of TBI biomarkers have yet to be evaluated in a focused multi-study meta-analysis. We reviewed relevant articles evaluating potential relationships between TBI biomarkers and both early and 6-month outcomes.

METHODS

All PubMed article publications from January 2000 to November 2023 with the search criteria "Protein Biomarker" AND "Traumatic Brain Injury" were included. Amongst all comparative studies, the sensitivity means and range values of biomarkers in predicting CT Rotterdam scores, ICU admission in the early period, or predicting GOS-E < 4 at the 6-month period were calculated from confusion matrices. Sensitivity values were modeled for each biomarker across studies and compared statistically for heterogeneity and differences.

RESULTS

From the 65 articles that met the criteria, 13 were included in this study. Six articles involved early-period TBI outcomes and seven involved 6-month outcomes. In the early period TBI outcomes, GFAP had a superior sensitivity to UCH-L1 and S-100B, and similar sensitivity to the CT Rotterdam score. In the 6-month period TBI outcomes, total Tau and NSE both had significant interstudy heterogeneity, making them inferior to GFAP, phosphorylated Tau, UCH-L1, and S-100B, all four of which had similar sensitivities at 75 %. This sensitivity range at 6-month outcomes was still relatively inferior to the CT Rotterdam score. Total Tau did not show any prognostic advantage at six months with GOS-E < 4, and phosphorylated Tau was similar in its sensitivity to other biomarkers such as GFAP and UCH-L1 and still inferior to the CT Rotterdam score.

CONCLUSION

This data suggests that TBI protein biomarkers do not possess better prognostic value with regards to outcomes.

Post-discharge 6-Month Functional Recovery of Traumatic Brain Injury Survivors with Unfavorable Functional Status at Discharge: A Registry-Based Cohort Study

BACKGROUND

Traumatic brain injury (TBI) is a major cause of physical disabilities worldwide. Herein, we aimed to investigate the factors contributing to post-discharge recovery in patients who were discharged with an unfavorable outcome.

METHODS

We collected data on the characteristics of patients, with a focus on those who survived TBI but had an unfavorable outcome at discharge as measured by Glasgow Outcome Scale Extended (GOSE) categories 2, 3, and 4. Post-discharge recovery was defined as achieving a favorable functional status at 6 months (GOSE of 5 or more) with a minimum 2-point increase in GOSE.

RESULTS

Of 4011 TBI patients in our registry, 797 had an unfavorable discharge functional status. In severe TBI, 51% achieved recovery, while in mild to moderate TBI, 57% achieved recovery after 6 months. Older patients and those with shorter intensive care unit length of stay were more likely to experience post-discharge recovery in both mild to moderate and severe TBI groups. The presence of skull base fracture was also associated with post-discharge recovery in severe TBI patients. Lastly, we show that, after adjustment for potential confounders, GOSE at discharge is associated with post-discharge recovery in both mild to moderate and severe TBI patients.

CONCLUSIONS

This study found that the majority of patients discharged with an unfavorable functional status were able to achieve a favorable outcome within 6 months. The novel post-discharge recovery in TBI patients might be a useful tool for illuminating the factors associated with a significant improvement after discharge.

Admission levels of serum biomarkers have additive and cumulative prognostic value in traumatic brain injury

Elevated levels of CNS-derived serum proteins are associated with poor outcome in traumatic brain injury (TBI), but the value of adding acute serum biomarker levels to common clinical outcome predictors lacks evaluation. We analyzed admission serum samples for Total-Tau (T-Tau), Neurofilament light chain (Nfl), Glial fibrillary acidic protein (GFAP), and Ubiquitin C-terminal hydrolase L1 (UCHL1) in a cohort of 396 trauma patients including 240 patients with TBI. We assessed the independent association of biomarkers with 1-year mortality and 6-12 months Glasgow Outcome Scale Extended (GOSE) score, as well as the additive and cumulative value of biomarkers on Glasgow Coma Scale (GCS) and Marshall Score for outcome prediction. Nfl and T-Tau levels were independently associated with outcome (OR: Nfl = 1.65, p = 0.01; T-Tau = 1.99, p < 0.01). Nfl or T-Tau improved outcome prediction by GCS (Wald Chi, Nfl = 6.8-8.8, p < 0.01; T-Tau 7.2-11.3, p < 0.01) and the Marshall score (Wald Chi, Nfl = 16.2-17.5, p < 0.01; T-Tau 8.7-12.4, p < 0.01). Adding T-Tau atop Nfl further improved outcome prediction in majority of tested models (Wald Chi range 3.8-9.4, p ≤ 0.05). Our data suggest that acute levels of serum biomarkers are independently associated with outcome after TBI and add outcome predictive value to commonly used clinical scores.

The Stress Index as a Predictor of Mortality in Patients with Isolated Moderate to Severe Traumatic Brain Injury

BACKGROUND

The Stress Index (SI), calculated as the ratio of blood glucose to serum potassium levels, is a promising prognostic marker in various acute care settings. This study aimed to evaluate the utility of the SI for predicting mortality in patients with isolated moderate-to-severe traumatic brain injury (TBI).

METHODS

This retrospective cohort study included adult trauma patients (aged ≥ 20 years) with isolated moderate to severe TBI (Abbreviated Injury Scale ≥ 3 for only head region) treated from 2009-2022. The SI was computed from the initial glucose and potassium levels upon arrival at the emergency department. Logistic regression models were used to assess the association between the SI and mortality after adjusting for relevant covariates. The most effective threshold value of the SI for predicting mortality was identified using receiver operating characteristic (ROC) analysis.

RESULTS

Among the 4357 patients with isolated moderate and severe TBI, 463 (10.6%) died. Deceased patients had a significantly higher SI (61.7 vs. 44.1, p < 0.001). In multivariate analysis, higher SI independently predicted greater mortality risk (odds ratio (OR) 6.70, 95% confidence interval (CI) 1.66-26.99, p = 0.007). The optimal SI cutoff for predicting mortality was 48.50 (sensitivity 62.0%, specificity 71.4%, area under the curve 0.724). Patients with SI ≥ 48.5 had nearly two-fold higher adjusted mortality odds compared to those below the threshold (adjusted OR 1.94, 95% CI 1.51-2.50, p < 0.001).

CONCLUSIONS

SI is a useful predictor of mortality in patients with isolated moderate-to-severe TBI. Incorporating SI with standard clinical assessments could enhance risk stratification and management approaches for this patient population.

Liberal or Restrictive Transfusion Strategy in Patients with Traumatic Brain Injury

BACKGROUND

The effect of a liberal transfusion strategy as compared with a restrictive strategy on outcomes in critically ill patients with traumatic brain injury is unclear.

METHODS

We randomly assigned adults with moderate or severe traumatic brain injury and anemia to receive transfusion of red cells according to a liberal strategy (transfusions initiated at a hemoglobin level of ≤10 g per deciliter) or a restrictive strategy (transfusions initiated at ≤7 g per deciliter). The primary outcome was an unfavorable outcome as assessed by the score on the Glasgow Outcome Scale-Extended at 6 months, which we categorized with the use of a sliding dichotomy that was based on the prognosis of each patient at baseline. Secondary outcomes included mortality, functional independence, quality of life, and depression at 6 months.

RESULTS

A total of 742 patients underwent randomization, with 371 assigned to each group. The analysis of the primary outcome included 722 patients. The median hemoglobin level in the intensive care unit was 10.8 g per deciliter in the group assigned to the liberal strategy and 8.8 g per deciliter in the group assigned to the restrictive strategy. An unfavorable outcome occurred in 249 of 364 patients (68.4%) in the liberal-strategy group and in 263 of 358 (73.5%) in the restrictive-strategy group (adjusted absolute difference, restrictive strategy vs. liberal strategy, 5.4 percentage points; 95% confidence interval, -2.9 to 13.7). Among survivors, a liberal strategy was associated with higher scores on some but not all the scales assessing functional independence and quality of life. No association was observed between the transfusion strategy and mortality or depression. Venous thromboembolic events occurred in 8.4% of the patients in each group, and acute respiratory distress syndrome occurred in 3.3% and 0.8% of patients in the liberal-strategy and restrictive-strategy groups, respectively.

CONCLUSIONS

In critically ill patients with traumatic brain injury and anemia, a liberal transfusion strategy did not reduce the risk of an unfavorable neurologic outcome at 6 months. (Funded by the Canadian Institutes of Health Research and others; HEMOTION ClinicalTrials.gov number, NCT03260478.).

Importance of AIM2 as a serum marker for reflecting severity and predicting a poor outcome of human severe traumatic brain injury: A prospective longitudinal cohort study

BACKGROUND

Absent in melanoma 2 (AIM2) participates in neuroinflammation. Here, the prognostic significance of serum AIM2 was explored in severe traumatic brain injury (sTBI).

METHODS

A total of 135 sTBI patients and 80 healthy controls were recruited in this prospective cohort study. Serum C-reactive protein (CRP) and AIM2 levels were measured. Glasgow Coma Scale (GCS) and Rotterdam computed tomography (CT) classification were recorded as the severity indicators. Prognostic parameters were posttraumatic six-month extended Glasgow outcome scale (GOSE) scores and poor outcome (GOSE scores of 1-4).

RESULTS

As opposed to controls, there were significantly elevated serum AIM2 levels after sTBI. Serum AIM2 levels were independently correlated with serum CRP levels, GCS scores, Rotterdam CT scores, GOSE scores and poor outcome. Also, serum AIM2 levels were efficiently predictive of poor outcome under the receiver operating characteristic (ROC) curve. Under the restricted cubic spline, serum AIM2 levels were linearly correlated with risk of poor outcome. Using subgroup analysis, serum AIM2 levels did not significantly interact with other indices, such as age, gender, alcohol drinking, cigarette smoking, etc. Also, combination model, in which serum AIM2, GCS scores and Rotterdam CT scores were merged, was outlined using nomogram and performed well under calibration curve, ROC curve and decision curve.

CONCLUSIONS

Raised serum AIM2 levels after sTBI, in intimate correlation with systemic inflammation and trauma severity, are independently discriminative of posttraumatic six-month neurological outcome, substantializing serum AIM2 as an inflammatory prognostic biomarker of sTBI.

Prognostication in Neurocritical Care

OBJECTIVE

This article synthesizes the current literature on prognostication in neurocritical care, identifies existing challenges, and proposes future research directions to reduce variability and enhance scientific and patient-centered approaches to neuroprognostication.

LATEST DEVELOPMENTS

Patients with severe acute brain injury often lack the capacity to make their own medical decisions, leaving surrogate decision makers responsible for life-or-death choices. These decisions heavily rely on clinicians' prognostication, which is still considered an art because of the previous lack of specific guidelines. Consequently, there is significant variability in neuroprognostication practices. This article examines various aspects of neuroprognostication. It explores the cognitive approach to prognostication, highlights the use of statistical modeling such as Bayesian models and machine learning, emphasizes the importance of clinician-family communication during prognostic disclosures, and proposes shared decision making for more patient-centered care.

ESSENTIAL POINTS

This article identifies ongoing challenges in the field and emphasizes the need for future research to ameliorate variability in neuroprognostication. By focusing on scientific methodologies and patient-centered approaches, this research aims to provide guidance and tools that may enhance neuroprognostication in neurocritical care.

Evaluation of ChatGPT in Predicting 6-Month Outcomes After Traumatic Brain Injury

OBJECTIVES

To evaluate the capacity of ChatGPT, a widely accessible and uniquely popular artificial intelligence-based chatbot, in predicting the 6-month outcome following moderate-to-severe traumatic brain injury (TBI).

DESIGN

Single-center observational retrospective study.

SETTING

Data are from a neuro-ICU from a level 1 trauma center.

PATIENTS

All TBI patients admitted to ICU between September 2021 and October 2022 were included in a prospective database.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Based on anonymized clinical, imaging, and biological information available at the patients' hospital admission and extracted from the database, clinical vignettes were retrospectively submitted to ChatGPT for prediction of patients' outcomes. The predictions of two intensivists (one neurointensivist and one non-neurointensivist) both from another level 1 trauma center (Beaujon Hospital), were also collected as was the International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) scoring. Each intensivist, as well as ChatGPT, made their prognostic evaluations independently, without knowledge of the others' predictions and of the patients' actual management and outcome. Both the intensivists and ChatGPT were given access to the exact same set of information. The main outcome was a 6-month-functional status dichotomized into favorable (Glasgow Outcome Scale Extended [GOSE] ≥ 5) versus poor (GOSE < 5). Prediction of intracranial hypertension management, pulmonary infectious risk, and removal of life-sustaining therapies was also investigated as secondary outcomes. Eighty consecutive moderate-to-severe TBI patients were included. For the 6-month outcome prognosis, area under the receiver operating characteristic curve (AUC-ROC) for ChatGPT, the neurointensivist, the non-neurointensivist, and IMPACT were, respectively, 0.62 (0.50-0.74), 0.70 (0.59-0.82), 0.71 (0.59-0.82), and 0.81 (0.72-0.91). ChatGPT had the highest sensitivity (100%), but the lowest specificity (26%). For secondary outcomes, ChatGPT's prognoses were generally less accurate than clinicians' prognoses, with lower AUC values for most outcomes.

CONCLUSIONS

This study does not support the use of ChatGPT for prediction of outcomes after TBI.

Traumatic Brain Injury and Traumatic Spinal Cord Injury

OBJECTIVE

This article reviews the mechanisms of primary traumatic injury to the brain and spinal cord, with an emphasis on grading severity, identifying surgical indications, anticipating complications, and managing secondary injury.

LATEST DEVELOPMENTS

Serum biomarkers have emerged for clinical decision making and prognosis after traumatic injury. Cortical spreading depolarization has been identified as a potentially modifiable mechanism of secondary injury after traumatic brain injury. Innovative methods to detect covert consciousness may inform prognosis and enrich future studies of coma recovery. The time-sensitive nature of spinal decompression is being elucidated.

ESSENTIAL POINTS

Proven management strategies for patients with severe neurotrauma in the intensive care unit include surgical decompression when appropriate, the optimization of perfusion, and the anticipation and treatment of complications. Despite validated models, predicting outcomes after traumatic brain injury remains challenging, requiring prognostic humility and a model of shared decision making with surrogate decision makers to establish care goals. Penetrating injuries, especially gunshot wounds, are often devastating and require public health and policy approaches that target prevention.

Resting-State EEG Signature of Early Consciousness Recovery in Comatose Patients with Traumatic Brain Injury

BACKGROUND

Resting-state electroencephalography (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI). We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in patients with TBI.

METHODS

This is a retrospective study of comatose patients with TBI who were admitted to a trauma center (October 2013 to January 2022). Demographics, basic clinical data, imaging characteristics, and EEGs were collected. We calculated the following using 10-min rsEEGs: power spectral density, permutation entropy (complexity measure), weighted symbolic mutual information (wSMI, global information sharing measure), Kolmogorov complexity (Kolcom, complexity measure), and heart-evoked potentials (the averaged EEG signal relative to the corresponding QRS complex on electrocardiography). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, and rsEEG data via a support vector machine.

RESULTS

We studied 113 of 134 (84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50 years, p = 0.01). Patients who recovered also had higher Kolcom (U = 1688, p = 0.01), increased beta power (U = 1,652 p = 0.003) with higher variability across channels (U = 1534, p = 0.034) and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04), and higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = 0.026; U = 1639, p = 0.024) than those who did not recover. The area under the receiver operating characteristic curve for rsEEG was higher than that for clinical data (using age, motor response, pupil reactivity) and higher than that for the Marshall computed tomography classification (0.69 vs. 0.66 vs. 0.56, respectively; p < 0.001).

CONCLUSIONS

We describe the rsEEG signature in recovery of consciousness prior to discharge in comatose patients with TBI. rsEEG measures performed modestly better than the clinical and imaging data in predicting recovery.

Acute-Phase Neurofilament Light and Glial Fibrillary Acidic Proteins in Cerebrospinal Fluid Predict Long-Term Outcome After Severe Traumatic Brain Injury

BACKGROUND

This study investigated trajectory profiles and the association of concentrations of the biomarkers neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) in ventricular cerebrospinal fluid (CSF) with clinical outcome at 1 year and 10-15 years after a severe traumatic brain injury (sTBI).

METHODS

This study included patients with sTBI at the Neurointensive Care Unit at Sahlgrenska University Hospital, Gothenburg, Sweden. The injury was regarded as severe if patients had a Glasgow Coma Scale ≤ 8 corresponding to Reaction Level Scale ≥ 4. CSF was collected from a ventricular catheter during a 2-week period. Concentrations of NfL and GFAP in CSF were analyzed with enzyme-linked immunosorbent assay. The Glasgow Outcome Scale (GOS) was used to assess the 1-year and 10-15-year outcomes. After adjustment for age and previous neurological diseases, logistic regression was performed for the outcomes GOS 1 (dead) or GOS 2-5 (alive) and GOS 1-3 (poor) or GOS 4-5 (good) versus the independent continuous variables (NfL and GFAP).

RESULTS

Fifty-three patients with sTBI were investigated; forty-seven adults are presented in the article, and six children (aged 7-18 years) are described in Supplement 1. The CSF concentrations of NfL gradually increased over 2 weeks post trauma, whereas GFAP concentrations peaked on days 3-4. Increasing NfL and GFAP CSF concentrations increased the odds of GOS 1-3 outcome 1 year after trauma (odds ratio [OR] 1.73, 95% confidence interval [CI] 1.07-2.80, p = 0.025; and OR 1.61, 95% CI 1.09-2.37, p = 0.016, respectively). Similarly, increasing CSF concentrations of NfL and GFAP increased the odds for GOS 1-3 outcome 10-15 years after trauma (OR 2.04, 95% CI 1.05-3.96, p = 0.035; and OR 1.60, 95% CI 1.02-2.00, p = 0.040).

CONCLUSIONS

This study shows that initial high concentrations of NfL and GFAP in CSF are both associated with higher odds for GOS 1-3 outcome 1 year and 10-15 years after an sTBI, implicating its potential usage as a prognostic marker in the future.

Recovery Potential in Patients Who Died After Withdrawal of Life-Sustaining Treatment: A TRACK-TBI Propensity Score Analysis

Among patients with severe traumatic brain injury (TBI), there is high prognostic uncertainty but growing evidence that recovery of independence is possible. Nevertheless, families are often asked to make decisions about withdrawal of life-sustaining treatment (WLST) within days of injury. The range of potential outcomes for patients who died after WLST (WLST+) is unknown, posing a challenge for prognostic modeling and clinical counseling. We investigated the potential for survival and recovery of independence after acute TBI in patients who died after WLST. We used Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) data and propensity score matching to pair participants with WLST+ to those with a similar probability of WLST (based on demographic and clinical characteristics), but for whom life-sustaining treatment was not withdrawn (WLST-). To optimize matching, we divided the WLST- cohort into tiers (Tier 1 = 0-11%, Tier 2 = 11-27%, Tier 3 = 27-70% WLST propensity). We estimated the level of recovery that could be expected in WLST+ participants by evaluating 3-, 6-, and 12-month Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale outcomes in matched WLST- participants. Of 90 WLST+ participants (80% male, mean [standard deviation; SD] age = 59.2 [17.9] years, median [IQR] days to WLST = 5.4 [2.2, 11.7]), 80 could be matched to WLST- participants. Of 56 WLST- participants who were followed at 6 months, 31 (55%) died. Among survivors in the overall sample and survivors in Tiers 1 and 2, more than 30% recovered at least partial independence (GOSE ≥4). In Tier 3, recovery to GOSE ≥4 occurred at 12 months, but not 6 months, post-injury. These results suggest a substantial proportion of patients with TBI and WLST may have survived and achieved at least partial independence. However, death or severe disability is a common outcome when the probability of WLST is high. While further validation is needed, our findings support a more cautious clinical approach to WLST and more complete reporting on WLST in TBI studies.

PaCO2 Association with Outcomes of Patients with Traumatic Brain Injury at High Altitude: A Prospective Single-Center Cohort Study

BACKGROUND

Partial pressure of carbon dioxide (PaCO2) is generally known to influence outcome in patients with traumatic brain injury (TBI) at normal altitudes. Less is known about specific relationships of PaCO2 levels and clinical outcomes at high altitudes.

METHODS

This is a prospective single-center cohort of consecutive patients with TBI admitted to a trauma center located at 2600 m above sea level. An unfavorable outcome was defined as a Glasgow Outcome Scale-Extended (GOSE) score < 4 at the 6-month follow-up.

RESULTS

We had a total of 81 patients with complete data, 80% (65/81) were men, and the median (interquartile range) age was 36 (25-50) years. Median Glasgow Coma Scale (GCS) score on admission was 9 (6-14); 49% (40/81) of patients had severe TBI (GCS 3-8), 32% (26/81) had moderate TBI (GCS 12-9), and 18% (15/81) had mild TBI (GCS 13-15). The median (interquartile range) Abbreviated Injury Score of the head (AISh) was 3 (2-4). The frequency of an unfavorable outcome (GOSE < 4) was 30% (25/81), the median GOSE was 4 (2-5), and the median 6-month mortality rate was 24% (20/81). Comparison between patients with favorable and unfavorable outcomes revealed that those with unfavorable outcome were older, (median age 49 [30-72] vs. 29 [22-41] years, P < 0.01), had lower admission GCS scores (6 [4-8] vs. 13 [8-15], P < 0.01), had higher AISh scores (4 [4-4] vs. 3 [2-4], P < 0.01), had higher Acute Physiology and Chronic Health disease Classification System II scores (17 [15-23] vs. 10 [6-14], P < 0.01), had higher Charlson scores (0 [0-2] vs. 0 [0-0], P < 0.01), and had higher PaCO2 levels (mean 35 ± 8 vs. 32 ± 6 mm Hg, P < 0.01). In a multivariate analysis, age (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.1-1.30, P < 0.01), AISh (OR 4.7, 95% CI 1.55-21.0, P < 0.05), and PaCO2 levels (OR 1.23, 95% CI 1.10-1.53, P < 0.05) were significantly associated with the unfavorable outcomes. When applying the same analysis to the subgroup on mechanical ventilation, AISh (OR 5.4, 95% CI 1.61-28.5, P = 0.017) and PaCO2 levels (OR 1.36, 95% CI 1.13-1.78, P = 0.015) remained significantly associated with the unfavorable outcome.

CONCLUSIONS

Higher PaCO2 levels are associated with an unfavorable outcome in ventilated patients with TBI. These results underscore the importance of PaCO2 levels in patients with TBI and whether it should be adjusted for populations living at higher altitudes.

Evaluating prognosis in unexplained infertility

IMPORTANCE

The diagnosis of unexplained infertility presents a dilemma as it signifies both uncertainty about the cause of infertility and the potential for natural conception. Immediate treatment of all would result in overtreatment. Prediction models estimating the likelihood of natural conception and subsequent live birth can guide treatment decisions.

OBJECTIVE

To evaluate if in couples with unexplained infertility, prediction models are effective in guiding treatment decisions.

EVIDENCE REVIEW

This review examines 25 studies that assess prediction models for natural conception in couples with unexplained infertility in terms of derivation, validation, and impact analysis.

FINDINGS

The largest prediction models have been integrated in the synthesis models of Hunault, which includes female age and infertility duration, having been pregnant before and motile sperm percentage. Despite its limited discriminative capacity, this model demonstrates excellent calibration. Importantly, the impact of the Hunault model has been evaluated in randomized clinical trials, and shows that in couples with unexplained infertility and 12-month natural conception chances exceeding 30%, immediate treatment with intrauterine insemination (IUI) and controlled ovarian hyperstimulation is not better than expectant management for 6 months. Below the threshold of 30%, treatment with IUI is superior over expectant management, but immediate in vitro fertilization was not better than IUI.

CONCLUSION

In couples with unexplained infertility and a good prognosis for natural conception, treatment can be delayed, whereas in couples with a poor prognosis, immediate treatment (with IUI-controlled ovarian hyperstimulation) is warranted.

RELEVANCE

These data indicate that in couples with unexplained infertility, integration of prediction models into clinical decision making can optimize treatment selection and maximize fertility outcomes while limiting unnecessary treatment.

Insights into epileptogenesis from post-traumatic epilepsy

Post-traumatic epilepsy (PTE) accounts for 5% of all epilepsies. The incidence of PTE after traumatic brain injury (TBI) depends on the severity of injury, approaching one in three in groups with the most severe injuries. The repeated seizures that characterize PTE impair neurological recovery and increase the risk of poor outcomes after TBI. Given this high risk of recurrent seizures and the relatively short latency period for their development after injury, PTE serves as a model disease to understand human epileptogenesis and trial novel anti-epileptogenic therapies. Epileptogenesis is the process whereby previously normal brain tissue becomes prone to recurrent abnormal electrical activity, ultimately resulting in seizures. In this Review, we describe the clinical course of PTE and highlight promising research into epileptogenesis and treatment using animal models of PTE. Clinical, imaging, EEG and fluid biomarkers are being developed to aid the identification of patients at high risk of PTE who might benefit from anti-epileptogenic therapies. Studies in preclinical models of PTE have identified tractable pathways and novel therapeutic strategies that can potentially prevent epilepsy, which remain to be validated in humans. In addition to improving outcomes after TBI, advances in PTE research are likely to provide therapeutic insights that are relevant to all epilepsies.

Anemia and Optimal Transfusion Thresholds in Brain-Injured Patients: A Narrative Review of the Literature

Anemia is a highly prevalent condition that may compromise oxygen delivery to vital organs, especially among the critically ill. Although current evidence supports the adoption of a restrictive transfusion strategy and threshold among the nonbleeding critically ill patient, it remains unclear whether this practice should apply to the brain-injured patient, given the predisposition to cerebral ischemia in this patient population, in which even nonprofound anemia may exert a detrimental effect on clinical outcomes. The purpose of this review is to provide an overview of the pathophysiological changes related to impaired cerebral oxygenation in the brain-injured patient and to present the available evidence on the effect of anemia and varying transfusion thresholds on the clinical outcomes of patients with acute brain injury.

Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels

BACKGROUND

Tools to increase the turnaround speed and accuracy of imaging reports could positively influence ED logistics. The Caire ICH is an artificial intelligence (AI) software developed for ED physicians to recognise intracranial haemorrhages (ICHs) on non-contrast enhanced cranial CT scans to manage the clinical care of these patients in a timelier fashion.

METHODS

A dataset of 532 non-contrast cranial CT scans was reviewed by five board-certified emergency physicians (EPs) with an average of 14.8 years of practice experience. The scans were labelled in random order for the presence or absence of an ICH. If an ICH was detected, the reader further labelled all subtypes present (ie, epidural, subdural, subarachnoid, intraparenchymal and/or intraventricular haemorrhage). After a washout period, the five EPs reviewed again the scans individually with the assistance of Caire ICH. The mean accuracy of the EP readings with AI assistance was compared with the mean accuracy of three general radiologists reading the films individually. The final diagnosis (ie, ground truth) was adjudicated by a consensus of the radiologists after their individual readings.

RESULTS

Mean EP reader accuracy significantly increased by 6.20% (95% CI for the difference 5.10%-7.29%; p=0.0092) when using Caire ICH to detect an ICH. Mean accuracy of the EP cohort in detecting an ICH using Caire ICH was found to be more accurate than the radiologist cohort prior to discussion; this difference, however, was not statistically significant.

CONCLUSION

The Caire ICH software significantly improved the accuracy and sensitivity of detecting an ICH by the EP to a level comparable to general radiologists. Further prospective research with larger numbers will be needed to understand the impact of Caire ICH on ED logistics and patient outcomes.

The Australian Traumatic Brain Injury Initiative: Statement of Working Principles and Rapid Review of Methods to Define Data Dictionaries for Neurological Conditions

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to develop a health informatics approach to collect data predictive of outcomes for persons with moderate-severe TBI across Australia. Central to this approach is a data dictionary; however, no systematic reviews of methods to define and develop data dictionaries exist to-date. This rapid systematic review aimed to identify and characterize methods for designing data dictionaries to collect outcomes or variables in persons with neurological conditions. Database searches were conducted from inception through October 2021. Records were screened in two stages against set criteria to identify methods to define data dictionaries for neurological conditions (International Classification of Diseases, 11th Revision: 08, 22, and 23). Standardized data were extracted. Processes were checked at each stage by independent review of a random 25% of records. Consensus was reached through discussion where necessary. Thirty-nine initiatives were identified across 29 neurological conditions. No single established or recommended method for defining a data dictionary was identified. Nine initiatives conducted systematic reviews to collate information before implementing a consensus process. Thirty-seven initiatives consulted with end-users. Methods of consultation were "roundtable" discussion (n = 30); with facilitation (n = 16); that was iterative (n = 27); and frequently conducted in-person (n = 27). Researcher stakeholders were involved in all initiatives and clinicians in 25. Importantly, only six initiatives involved persons with lived experience of TBI and four involved carers. Methods for defining data dictionaries were variable and reporting is sparse. Our findings are instructive for AUS-TBI and can be used to further development of methods for defining data dictionaries.

A Model Predicting the 6-Month Disability of Patients With Traumatic Brain Injury to Assess the Quality of Care in Intensive Care Units: Results from the CREACTIVE Study

Assessing quality of care is essential for improving the management of patients experiencing traumatic brain injury (TBI). This study aimed at devising a rigorous framework to evaluate the quality of TBI care provided by intensive care units (ICUs) and applying it to the Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe (CREACTIVE) consortium, which involved 83 ICUs from seven countries. The performance of the centers was assessed in terms of patients' outcomes, as measured by the 6-month Glasgow Outcome Scale-Extended (GOS-E). To account for the between-center differences in the characteristics of the admitted patients, we developed a multinomial logistic regression model estimating the probability of a four-level categorization of the GOS-E: good recovery (GR), moderate disability (MD), severe disability (SD), and death or vegetative state (D/VS). A total of 5928 patients admitted to the participating ICUs between March 2014 and March 2019 were analyzed. The model included 11 predictors and demonstrated good discrimination (area under the receiver operating characteristic [ROC] curve in the validation set for GR: 0.836, MD: 0.802, SD: 0.706, D/VS: 0.890) and calibration, both overall (Hosmer-Lemeshow test p value: 0.87) and in several subgroups, defined by prognostically relevant variables. The model was used as a benchmark for assessing quality of care by comparing the observed number of patients experiencing GR, MD, SD, and D/VS to the corresponding numbers expected in each category by the model, computing observed/expected (O/E) ratios. The four center-specific ratios were assembled with polar representations and used to provide a multidimensional assessment of the ICUs, overcoming the loss of information consequent to the traditional dichotomizations of the outcome in TBI research. The proposed framework can help in identifying strengths and weaknesses of current TBI care, triggering the changes that are necessary to improve patient outcomes.

Refining outcome prediction after traumatic brain injury with machine learning algorithms

Outcome after traumatic brain injury (TBI) is typically assessed using the Glasgow outcome scale extended (GOSE) with levels from 1 (death) to 8 (upper good recovery). Outcome prediction has classically been dichotomized into either dead/alive or favorable/unfavorable outcome. Binary outcome prediction models limit the possibility of detecting subtle yet significant improvements. We set out to explore different machine learning methods with the purpose of mapping their predictions to the full 8 grade scale GOSE following TBI. The models were set up using the variables: age, GCS-motor score, pupillary reaction, and Marshall CT score. For model setup and internal validation, a total of 866 patients could be included. For external validation, a cohort of 369 patients were included from Leuven, Belgium, and a cohort of 573 patients from the US multi-center ProTECT III study. Our findings indicate that proportional odds logistic regression (POLR), random forest regression, and a neural network model achieved accuracy values of 0.3-0.35 when applied to internal data, compared to the random baseline which is 0.125 for eight categories. The models demonstrated satisfactory performance during external validation in the data from Leuven, however, their performance were not satisfactory when applied to the ProTECT III dataset.

Comparative Analysis of Clinical Severity and Outcomes in Penetrating Versus Blunt Traumatic Brain Injury Propensity Matched Cohorts

Traumatic brain injury (TBI) is a global health challenge; however, penetrating brain injury (PBI) remains under-represented in evidence-based knowledge and research efforts. This study utilized data from the Trauma Quality Improvement Program (TQIP) of the National Trauma Data Bank (NTDB) to investigate outcomes of PBI as compared with clinical-severity-matched non-penetrating or blunt TBI. A total of 1765 patients with PBI were 1:1 propensity score-matched for clinical severity with blunt TBI patients. The intent of PBI was self-inflicted in 34.1% of the cases, and the mechanism was firearm-inflicted in 89.1%. Mortality was found to be significantly more common in PBI than in the severity- matched TBI cohort (33.9% vs. 14.3 %, p < 0.001) as was unfavorable outcome. Mortality was mediated by withdrawal of life-sustaining therapies (WOLST) 30% of the time, and WOLST occurred earlier (median 3 days vs. 6 days, p < 0.001) in PBI. Increased rate of mortality was observed with a Glasgow Coma Scale (GCS) of <11 in PBI as compared with <7 in blunt TBI. In conclusion, PBI patients exhibited higher mortality rates and unfavorable outcomes; one third of excess mortality was mediated by WOLST. The study also brings into question the applicability of the conventional TBI classification, based on GCS, in PBI. We emphasize the need to address the observed disparities and better understand the distinctive characteristics and mechanisms underlying PBI outcomes to improve patient care and reduce mortality.

The Australian Traumatic Brain Injury Initiative: Single Data Dictionary to Predict Outcome for People With Moderate-Severe Traumatic Brain Injury

In this series of eight articles, the Australian Traumatic Brain Injury Initiative (AUS-TBI) consortium describes the Australian approach used to select the common data elements collected acutely that have been shown to predict outcome following moderate-severe traumatic brain injury (TBI) across the lifespan. This article presents the unified single data dictionary, together with additional measures chosen to facilitate comparative effectiveness research and data linkage. Consultations with the AUS-TBI Lived Experience Expert Group provided insights on the merits and considerations regarding data elements for some of the study areas, as well as more general principles to guide the collection of data and the selection of meaningful measures. These are presented as a series of guiding principles and themes. The AUS-TBI Aboriginal and Torres Strait Islander Advisory Group identified a number of key points and considerations for the project approach specific to Aboriginal and Torres Strait Islander peoples, including key issues of data sovereignty and community involvement. These are outlined in the form of principles to guide selection of appropriate methodologies, data management, and governance. Implementation of the AUS-TBI approach aims to maximize ongoing data collection and linkage, to facilitate personalization of care and improved outcomes for people who experience moderate-severe TBI.

Is age or cardiovascular comorbidity the main predictor of reduced cerebrovascular pressure reactivity in older patients with traumatic brain injury?

Introduction

The Pressure Reactivity index (PRx) has been proposed as a surrogate measure for cerebrovascular autoregulation (CA) and it has been described that older age is associated with worse PRx. The etiology for this reduced capacity remains unknown.

Research question

To investigate the relation between age and PRx in a cohort of patients with traumatic brain injury (TBI) while correcting for cardiovascular comorbidities.

Material and methods

This is a retrospective analysis on prospectively collected data in 151 consecutive TBI patients between 2013 and 2023. PRx was averaged over 5 monitoring days and correlated with demographic, patient and injury data. A multiple regression analysis was performed with PRx as dependent variable and cardiovascular comorbidities, age, Glasgow motor score and pupillary reaction as independent variables. A similar model was constructed without age and compared.

Results

Age, sex, thromboembolic history, arterial hypertension, Glasgow motor score and pupillary reaction significantly correlated with PRx in univariate analysis. In multivariate analysis, age had a significant worsening effect on PRx (p = 0.01), while the cardiovascular risk factors and injury severity had no impact. The comparison of the models with and without age yielded a significant difference (p = 0.01), underpinning the independent effect of age.

Discussion and conclusion

In the present cohort study in TBI patients it was found that older age independently impaired cerebrovascular pressure reactivity regardless of cardiovascular comorbidity. Pathophysiology of TBI and physiology of ageing seem to line up to synergistically produce a negative effect on brain perfusion.

Association of Central Nervous System-Affecting Medications With Occurrence and Short-Term Mortality of Traumatic Brain Injury

BACKGROUND AND OBJECTIVES

The use of medications commonly prescribed after traumatic brain injury (TBI) has been little studied before TBI. This study examined the association between the use of medications that affect the central nervous system (CNS) and the occurrence and short-term mortality of TBI.

METHODS

Mandatory Finnish registries were used to identify TBI admissions, fatal TBIs, and drug purchases during 2005-2018. Patients with TBI were 1:1 matched to nontrauma control patients to investigate the association between medications and the occurrence of TBI and 30-day mortality after TBI. Number needed to harm (NNH) was calculated for all medications.

RESULTS

The cohort included 59 606 patients with TBI and a similar number of control patients. CNS-affecting drugs were more common in patients with TBI than in controls [odds ratio = 2.07 (2.02-2.13), P < .001)]. Benzodiazepines were the most common type of medications in patients with TBI (17%) and in controls (11%). The lowest NNH for the occurrence of TBI was associated with benzodiazepines (15.4), selective serotonin uptake inhibitors (18.5), and second-generation antipsychotics (25.8). Eight percent of the patients with TBI died within 30 days. The highest hazard ratios (HR) and lowest NNHs associated with short-term mortality were observed with strong opioids [HR = 1.41 (1.26-1.59), NNH = 33.1], second-generation antipsychotics [HR = 1.36 (1.23-1.50), NNH = 37.1], and atypical antidepressants [HR = 1.17 (1.04-1.31), NNH = 77.7].

CONCLUSION

Thirty-seven percent of patients with TBI used at least 1 CNS-affecting drug. This proportion was significantly higher than in the control population (24%). The highest risk and lowest NNH for short-term mortality were observed with strong opioids, second-generation antipsychotics, and atypical antidepressants. The current risks underscore the importance of weighing the benefits and risks before prescribing CNS-affecting drugs in patients at risk of head injury.

Guidelines for Neuroprognostication in Critically Ill Adults with Moderate-Severe Traumatic Brain Injury

BACKGROUND

Moderate-severe traumatic brain injury (msTBI) carries high morbidity and mortality worldwide. Accurate neuroprognostication is essential in guiding clinical decisions, including patient triage and transition to comfort measures. Here we provide recommendations regarding the reliability of major clinical predictors and prediction models commonly used in msTBI neuroprognostication, guiding clinicians in counseling surrogate decision-makers.

METHODS

Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology, we conducted a systematic narrative review of the most clinically relevant predictors and prediction models cited in the literature. The review involved framing specific population/intervention/comparator/outcome/timing/setting (PICOTS) questions and employing stringent full-text screening criteria to examine the literature, focusing on four GRADE criteria: quality of evidence, desirability of outcomes, values and preferences, and resource use. Moreover, good practice recommendations addressing the key principles of neuroprognostication were drafted.

RESULTS

After screening 8125 articles, 41 met our eligibility criteria. Ten clinical variables and nine grading scales were selected. Many articles varied in defining "poor" functional outcomes. For consistency, we treated "poor" as "unfavorable". Although many clinical variables are associated with poor outcome in msTBI, only the presence of bilateral pupillary nonreactivity on admission, conditional on accurate assessment without confounding from medications or injuries, was deemed moderately reliable for counseling surrogates regarding 6-month functional outcomes or in-hospital mortality. In terms of prediction models, the Corticosteroid Randomization After Significant Head Injury (CRASH)-basic, CRASH-CT (CRASH-basic extended by computed tomography features), International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT)-core, IMPACT-extended, and IMPACT-lab models were recommended as moderately reliable in predicting 14-day to 6-month mortality and functional outcomes at 6 months and beyond. When using "moderately reliable" predictors or prediction models, the clinician must acknowledge "substantial" uncertainty in the prognosis.

CONCLUSIONS

These guidelines provide recommendations to clinicians on the formal reliability of individual predictors and prediction models of poor outcome when counseling surrogates of patients with msTBI and suggest broad principles of neuroprognostication.

Intracranial Pressure-Derived Cerebrovascular Reactivity Indices and Their Critical Thresholds: A Canadian High Resolution-Traumatic Brain Injury Validation Study

Current neurointensive care guidelines recommend intracranial pressure (ICP) and cerebral perfusion pressure (CPP) centered management for moderate-severe traumatic brain injury (TBI) because of their demonstrated associations with patient outcome. Cerebrovascular reactivity metrics, such as the pressure reactivity index (PRx), pulse amplitude index (PAx), and RAC index, have also demonstrated significant prognostic capabilities with regard to outcome. However, critical thresholds for cerebrovascular reactivity indices have only been identified in two studies conducted at the same center. In this study, we aim to determine the critical thresholds of these metrics by leveraging a unique multi-center database. The study included a total of 354 patients from the CAnadian High-Resolution TBI (CAHR-TBI) Research Collaborative. Based on 6-month Glasgow Outcome Scores, patients were dichotomized into alive versus dead and favorable versus unfavorable. Chi-square values were then computed for incrementally increasing values of each physiological parameter of interest against outcome. The values that generated the greatest chi-squares for each parameter were considered to be the thresholds with the greatest outcome discriminatory capacity. To confirm that the identified thresholds provide prognostic utility, univariate and multivariable logistical regression analyses were performed adjusting for the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) variables. Through the chi-square analysis, a lower limit CPP threshold of 60 mm Hg and ICP thresholds of 18 mm Hg and 22 mm Hg were identified for both survival and favorable outcome predictions. For the cerebrovascular reactivity metrics, different thresholds were identified for the two outcome dichotomizations. For survival prediction, thresholds of 0.35, 0.25, and 0 were identified for PRx, PAx, and RAC, respectively. For favorable outcome prediction, thresholds of 0.325, 0.20, and 0.05 were found. Univariate logistical regression analysis demonstrated that the time spent above/below thresholds were associated with outcome. Further, multivariable logistical regression analysis found that percent time above/below the identified thresholds added additional variance to the IMPACT core model for predicting both survival and favorable outcome. In this study, we were able to validate the results of the previous two works as well as to reaffirm the ICP and CPP guidelines from the Brain Trauma Foundation (BTF) and the Seattle International Severe Traumatic Brain Injury Consensus Conference (SIBICC).

Should Patients with Traumatic Brain Injury with Significant Contusions be Treated with Different Neurointensive Care Targets?

BACKGROUND

Patients with traumatic brain injury (TBI) with large contusions make up a specific TBI subtype. Because of the risk of brain edema worsening, elevated cerebral perfusion pressure (CPP) may be particularly dangerous. The pressure reactivity index (PRx) and optimal cerebral perfusion pressure (CPPopt) are new promising perfusion targets based on cerebral autoregulation, but they reflect the global brain state and may be less valid in patients with predominant focal lesions. In this study, we aimed to investigate if patients with TBI with significant contusions exhibited a different association between PRx, CPP, and CPPopt in relation to functional outcome compared to those with small/no contusions.

METHODS

This observational study included 385 patients with moderate to severe TBI treated at a neurointensive care unit in Uppsala, Sweden. The patients were classified into two groups: (1) significant contusions (> 10 mL) and (2) small/no contusions (but with extra-axial or diffuse injuries). The percentage of good monitoring time (%GMT) with intracranial pressure > 20 mm Hg; PRx > 0.30; CPP < 60 mm Hg, within 60-70 mm Hg, or > 70 mm Hg; and ΔCPPopt less than - 5 mm Hg, ± 5 mm Hg, or > 5 mm Hg was calculated. Outcome (Glasgow Outcome Scale-Extended) was assessed after 6 months.

RESULTS

Among the 120 (31%) patients with significant contusions, a lower %GMT with CPP between 60 and 70 mm Hg was independently associated with unfavorable outcome. The %GMTs with PRx and ΔCPPopt ± 5 mm Hg were not independently associated with outcome. Among the 265 (69%) patients with small/no contusions, a higher %GMT of PRx > 0.30 and a lower %GMT of ΔCPPopt ± 5 mm Hg were independently associated with unfavorable outcome.

CONCLUSIONS

In patients with TBI with significant contusions, CPP within 60-70 mm Hg may improve outcome. PRx and CPPopt, which reflect global cerebral pressure autoregulation, may be useful in patients with TBI without significant focal brain lesions but seem less valid for those with large contusions. However, this was an observational, hypothesis-generating study; our findings need to be validated in prospective studies before translating them into clinical practice.

Long-term outcome in new onset refractory status epilepticus: a retrospective study

BACKGROUND

New onset refractory status epilepticus (NORSE) is a neurologic emergency without an immediately identifiable cause. The complicated and long ICU stay of the patients can lead to perceiving a prolongation of therapies as futile. However, a recovery is possible even in severe cases. This retrospective study investigates ICU treatments, short- and long-term outcome and ethical decisions of a case series of patients with NORSE.

METHODS

Overall, 283 adults were admitted with status epilepticus (SE) to the Neurocritical Care Unit of the University Hospital Zurich, Switzerland, between 01.2010 and 12.2022. Of them, 25 had a NORSE. We collected demographic, clinical, therapeutic and outcome data. Descriptive statistics was performed.

RESULTS

Most patients were female (68%), previously healthy (Charlson comorbidity index 1 [0-4]) and relatively young (54 ± 17 years). 96% presented with super-refractory SE. Despite extensive workup, the majority (68%) of cases remained cryptogenic. Most patients had a long and complicated ICU stay. The in-hospital mortality was 36% (n = 9). The mortality at last available follow-up was 56% (n = 14) on average 30 months after ICU admission. The cause of in-hospital death for 89% (n = 8) of the patients was the withholding/withdrawing of therapies. Medical staff except for one patient triggered the decision. The end of life (EOL) decision was taken 29 [12-51] days after the ICU admission. Death occurred on day 6 [1-8.5] after the decision was taken. The functional outcome improved over time for 13/16 (81%) hospital survivors (median mRS at hospital discharge 4 [3.75-5] vs. median mRS at last available follow-up 2 [1.75-3], p < 0.001).

CONCLUSIONS

Our data suggest that the long-term outcome can still be favorable in NORSE survivors, despite a prolonged and complicated ICU stay. Clinicians should be careful in taking EOL decisions to avoid the risk of a self-fulfilling prophecy. Our results encourage clinicians to continue treatment even in initially refractory cases.

The Australian Traumatic Brain Injury Initiative: Systematic Review of Predictive Value of Biological Markers for People With Moderate-Severe Traumatic Brain Injury

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to co-design a data resource to predict outcomes for people with moderate-severe traumatic brain injury (TBI) across Australia. Fundamental to this resource is the data dictionary, which is an ontology of data items. Here, we report the systematic review and consensus process for inclusion of biological markers in the data dictionary. Standardized database searches were implemented from inception through April 2022. English-language studies evaluating association between a fluid, tissue, or imaging marker and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Records were screened using a prioritization algorithm and saturation threshold in Research Screener. Full-length records were then screened in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association, and high-value predictors were discussed in a consensus process. Searches retrieved 106,593 records; 1,417 full-length records were screened, resulting in 546 included records. Two hundred thirty-nine individual markers were extracted, evaluated against 101 outcomes. Forty-one markers were judged to be high-value predictors of 15 outcomes. Fluid markers retained following the consensus process included ubiquitin C-terminal hydrolase L1 (UCH-L1), S100, and glial fibrillary acidic protein (GFAP). Imaging markers included computed tomography (CT) scores (e.g., Marshall scores), pathological observations (e.g., hemorrhage, midline shift), and magnetic resonance imaging (MRI) classification (e.g., diffuse axonal injury). Clinical context and time of sampling of potential predictive indicators are important considerations for utility. This systematic review and consensus process has identified fluid and imaging biomarkers with high predictive value of clinical and long-term outcomes following moderate-severe TBI.

Impact of Automated Prognostication on Traumatic Brain Injury Care: A Focus Group Study

BACKGROUND

Prognosticating outcomes for traumatic brain injury (TBI) patients is challenging due to the required specialized skills and variability among clinicians. Recent attempts to standardize TBI prognosis have leveraged machine learning (ML) methodologies. This study evaluates the necessity and influence of ML-assisted TBI prognostication through healthcare professionals' perspectives via focus group discussions.

METHODS

Two virtual focus groups included ten key TBI care stakeholders (one neurosurgeon, two emergency clinicians, one internist, two radiologists, one registered nurse, two researchers in ML and healthcare and one patient representative). They answered six open-ended questions about their perceptions and potential ML use in TBI prognostication. Transcribed focus group discussions were thematically analyzed using qualitative data analysis software.

RESULTS

The study captured diverse perceptions and interests in TBI prognostication across clinical specialties. Notably, certain clinicians who currently do not prognosticate expressed an interest in doing so independently provided they had access to ML support. Concerns included ML's accuracy and the need for proficient ML researchers in clinical settings. The consensus suggested using ML as a secondary consultation tool and promoting collaboration with internal or external research resources. Participants believed ML prognostication could enhance disposition planning and standardize care regardless of clinician expertise or injury severity. There was no evidence of perceived bias or interference during the discussions.

CONCLUSION

Our findings revealed an overall positive attitude toward ML-based prognostication. Despite raising multiple concerns, the focus group discussions were particularly valuable in underscoring the potential of ML in democratizing and standardizing TBI prognosis practices.