IMPACT Score for Traumatic Brain Injury: Validation of the Prognostic Tool in a Spanish Cohort

Controlled lumbar cerebrospinal fluid drainage effectively decreases the need for second and third tier interventions for intracranial hypertension in severe traumatic brain injury patients

INTRODUCTION

Early treatment of elevated intracranial pressure (ICP) is a cornerstone of the therapy in severe traumatic brain injury (TBI) patients. Treatment of refractory high ICP however, remain challenging as only limited and risky third-tier therapeutic interventions are available. Controlled lumbar cerebrospinal fluid (CSF) drainage has been known as an efficient method of ICP reduction after TBI for decades, but it is not recommended in international guidelines because of low evidence background and safety issues. Our centre has a long-standing experience using this intervention for more than 15 years. Here we present our data about the safety and efficacy of controlled lumbar drainage to avoid further second- and third tier ICP lowering therapies and beneficially influence functional outcome.

METHODS

Observational (retrospective and prospective) analysis was performed using demographic, clinical and outcome data of severe TBI patients admitted to our centre. Analysis was retrospective between 2008 and 2013 and prospective from 2014 to 2019. Only severe TBI patients (GCS<9) with ICP monitoring were enrolled. Lumbar drainage (LD) was used as a second-tier therapy to control intracranial hypertension in salvageable patients with normal haemostasis and discernible basal cisterns on pre-interventional CT scan.

RESULTS

Data of 45 patients were analysed. Patients were young, comatose and with severe injuries (median age: 29, GMS: 4, ISS: 25). Lumbar drain was inserted mainly on the first week and maintained for further 5 days. Episodes of intracranial hypertension (ICP>20 Hgmm) within one day (10 vs 2) were reduced. The need of additional second- and third-line therapies (deep sedation, hyperventilation, barbiturate administration, decompressive craniectomy) also significantly decreased (60 vs 25 interventions, p<0.001). The in-hospital mortality and 6-month functional outcome were more favourable than the whole TBI population and as predicted by prognostic calculations (mortality: 16% vs. 48 %; GOSE 1-4: 49% vs. 65% vs CRASH: 87% vs. IMPACT: 51 %) in this period.

CONCLUSIONS

Our results support the view that controlled lumbar drainage is a highly efficient method to manage intracranial hypertension and significantly decreases the need of further harmful ICP lowering therapies without altering functional outcome of severe TBI patients.

A Precision Medicine Agenda in Traumatic Brain Injury

Traumatic brain injury remains a leading cause of death and disability across the globe. Substantial uncertainty in outcome prediction continues to be the rule notwithstanding the existing prediction models. Additionally, despite very promising preclinical data, randomized clinical trials (RCTs) of neuroprotective strategies in moderate and severe TBI have failed to demonstrate significant treatment effects. Better predictive models are needed, as the existing validated ones are more useful in prognosticating poor outcome and do not include biomarkers, genomics, proteonomics, metabolomics, etc. Invasive neuromonitoring long believed to be a "game changer" in the care of TBI patients have shown mixed results, and the level of evidence to support its widespread use remains insufficient. This is due in part to the extremely heterogenous nature of the disease regarding its etiology, pathology and severity. Currently, the diagnosis of traumatic brain injury (TBI) in the acute setting is centered on neurological examination and neuroimaging tools such as CT scanning and MRI, and its treatment has been largely confronted using a "one-size-fits-all" approach, that has left us with many unanswered questions. Precision medicine is an innovative approach for TBI treatment that considers individual variability in genes, environment, and lifestyle and has expanded across the medical fields. In this article, we briefly explore the field of precision medicine in TBI including biomarkers for therapeutic decision-making, multimodal neuromonitoring, and genomics.

Prognosis in moderate-severe traumatic brain injury in a Swedish cohort and external validation of the IMPACT models

Background

A major challenge in management of traumatic brain injury (TBI) is to assess the heterogeneity of TBI pathology and outcome prediction. A reliable outcome prediction would have both great value for the healthcare provider, but also for the patients and their relatives. A well-known prediction model is the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) prognostic calculator. The aim of this study was to externally validate all three modules of the IMPACT calculator on TBI patients admitted to Uppsala University hospital (UUH).

Method

TBI patients admitted to UUH are continuously enrolled into the Uppsala neurointensive care unit (NICU) TBI Uppsala Clinical Research (UCR) quality register. The register contains both clinical and demographic data, radiological evaluations, and outcome assessments based on the extended Glasgow outcome scale extended (GOSE) performed at 6 months to 1 year. In this study, we included 635 patients with severe TBI admitted during 2008–2020. We used IMPACT core parameters: age, motor score, and pupillary reaction.

Results

The patients had a median age of 56 (range 18–93), 142 female and 478 male. Using the IMPACT Core model to predict outcome resulted in an AUC of 0.85 for mortality and 0.79 for unfavorable outcome. The CT module did not increase AUC for mortality and slightly decreased AUC for unfavorable outcome to 0.78. However, the lab module increased AUC for mortality to 0.89 but slightly decreased for unfavorable outcome to 0.76. Comparing the predicted risk to actual outcomes, we found that all three models correctly predicted low risk of mortality in the surviving group of GOSE 2–8. However, it produced a greater variance of predicted risk in the GOSE 1 group, denoting general underprediction of risk. Regarding unfavorable outcome, all models once again underestimated the risk in the GOSE 3–4 groups, but correctly predicts low risk in GOSE 5–8.

Conclusions

The results of our study are in line with previous findings from centers with modern TBI care using the IMPACT model, in that the model provides adequate prediction for mortality and unfavorable outcome. However, it should be noted that the prediction is limited to 6 months outcome and not longer time interval.

Blood-based biomarkers for prediction of intracranial hemorrhage and outcome in patients with moderate or severe traumatic brain injury

BACKGROUND

Early identification of traumatic intracranial hemorrhage (ICH) has implications for triage and intervention. Blood-based biomarkers were recently approved by the Food and Drug Administration (FDA) for prediction of ICH in patients with mild traumatic brain injury (TBI). We sought to determine if biomarkers measured early after injury improve prediction of mortality and clinical/radiologic outcomes compared with Glasgow Coma Scale (GCS) alone in patients with moderate or severe TBI (MS-TBI).

METHODS

We measured glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCH-L1), and microtubule-associated protein-2 (MAP-2) on arrival to the emergency department (ED) in patients with blunt TBI enrolled in the placebo arm of the Prehospital TXA for TBI Trial (prehospital GCS score, 3-12; SPB, > 90). Biomarkers were modeled individually and together with prehospital predictor variables [PH] (GCS score, age, sex). Data were divided into a training data set and test data set for model derivation and evaluation. Models were evaluated for prediction of ICH, mass lesion, 48-hour and 28-day mortality, and 6-month Glasgow Outcome Scale-Extended (GOS-E) and Disability Rating Scale (DRS). Area under the curve (AUC) was evaluated in test data for PH alone, PH + individual biomarkers, and PH + three biomarkers.

RESULTS

Of 243 patients with baseline samples (obtained a median of 84 minutes after injury), prehospital GCS score was 8 (interquartile range, 5-10), 55% had ICH, and 48-hour and 28-day mortality were 7% and 13%, respectively. Poor neurologic outcome at 6 months was observed in 34% based on GOS-E of 4 or less, and 24% based on DRS greater than or equal to7. Addition of each biomarker to PH improved AUC in the majority of predictive models. GFAP+PH compared with PH alone significantly improved AUC in all models (ICH, 0.82 vs. 0.64; 48-hour mortality, 0.84 vs. 0.71; 28-day mortality, 0.84 vs. 0.66; GOS-E, 0.78 vs. 0.69; DRS, 0.84 vs. 0.81, all p < 0.001).

CONCLUSION

Circulating blood-based biomarkers may improve prediction of neurological outcomes and mortality in patients with MS-TBI over prehospital characteristics alone. Glial fibrillary acidic protein appears to be the most promising. Future evaluation in the prehospital setting is warranted.

LEVEL OF EVIDENCE

Prospective, Prognostic and Epidemiological, level II.

Sleep apnea and risk of traumatic brain injury and associated mortality and healthcare costs: a population-based cohort study

Background

The objective of this study was aimed to investigate whether sleep apnea patients had a higher risk of traumatic brain injury.

Methods

Data were collected from the Taiwan Longitudinal Health Insurance Database during the period of 2000-2012. The study cohort comprised 6,456 patients aged ≥20 years with a first diagnosis of sleep apnea. The primary outcome was the incidence of traumatic brain injury. Kaplan-Meier survival analysis and Cox proportional-hazards modeling were used.

Results

After adjustments for associated comorbidities and hypnotic medications, sleep apnea patients were associated with a 1.19-fold higher risk of traumatic brain injury (95% CI, 1.07-1.33) compared with patients without sleep apnea. Sleep apnea patients who took benzodiazepine (BZD) had a 1.30-fold increased risk of traumatic brain injury compared with patients without sleep apnea (95% CI, 1.14-1.49). However, this risk was not statistically significant, with a 1.03-fold risk of traumatic brain injury in sleep apnea patients without BZD use (95% CI, 0.84-1.25) compared with patients without sleep apnea. Compared with patients without sleep apnea, the risk of traumatic brain injury in sleep apnea patients aged 65-79 years old was higher (adjusted hazard ratio, 1.36; 95% CI, 1.06-1.74).

Conclusions

Sleep apnea patients, regardless of hypnotic use, had a higher risk of traumatic brain injury compared with patients without sleep apnea.

Prognosis in Moderate and Severe Traumatic Brain Injury: A Systematic Review of Contemporary Models and Validation Studies

Outcome prognostication in traumatic brain injury (TBI) is important but challenging due to heterogeneity of the disease. The aim of this systematic review is to present the current state-of-the-art on prognostic models for outcome after moderate and severe TBI and evidence on their validity. We searched for studies reporting on the development, validation or extension of prognostic models for functional outcome after TBI with Glasgow Coma Scale (GCS) ≤12 published between 2006-2018. Studies with patients age ≥14 years and evaluating a multi-variable prognostic model based on admission characteristics were included. Model discrimination was expressed with the area under the receiver operating characteristic curve (AUC), and model calibration with calibration slope and intercept. We included 58 studies describing 67 different prognostic models, comprising the development of 42 models, 149 external validations of 31 models, and 12 model extensions. The most common predictors were GCS (motor) score (n = 55), age (n = 54), and pupillary reactivity (n = 48). Model discrimination varied substantially between studies. The International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) models were developed on the largest cohorts (8509 and 10,008 patients, respectively) and were most often externally validated (n = 91), yielding AUCs ranging between 0.65-0.90 and 0.66-1.00, respectively. Model calibration was reported with a calibration intercept and slope for seven models in 53 validations, and was highly variable. In conclusion, the discriminatory validity of the IMPACT and CRASH prognostic models is supported across a range of settings. The variation in calibration, reflecting heterogeneity in reliability of predictions, motivates continuous validation and updating if clinical implementation is pursued.