The prehospital management of traumatic brain injury

Assessing the prediction of arterial CO2 from end tidal CO2 in adult blunt trauma patients

BACKGROUND

The control of PaCO2 in ventilated patients is known to be of particular importance in the management and prognosis of trauma patients. Although EtCO2 is often used as a continuous, non-invasive, surrogate marker for PaCO2 in ventilated trauma patients in the emergency department (ED), previous studies suggest a poor correlation in this cohort. However, previous data has predominantly been collected retrospectively, raising the possibility that the elapsed time between PaCO2 sampling and EtCO2 recording may contribute to the poor correlation. As such this study aimed to analyse the correlation of PaCO2 to EtCO2 in the ventilated blunt trauma patient presenting to the ED through contemporaneous sampling.

METHODS

This study was conducted as a prospective observational study analysing the near simultaneous recording of EtCO2 and Arterial Blood Gas sampling of ventilated adult trauma patients in the ED of a Level 1 trauma centre over a 12-month period. Data was analysed using linear regression and subgroup analysis by Injury Severity Score (ISS) and Abbreviated Injury Score (AIS) of the Chest.

RESULTS

Linear regression of EtCO2 vs PaCO2 demonstrated a moderate correlation with r = 0.54 (p < 0.01, n = 51, 95 % CI 0.31-0.71). Subgroup analysis by ISS, revealed a stronger correlation in those with minor ISS (0-11) (r = 0.76, p < 0.01, n = 13, 95 % CI 0.36-0.92) compared to those more severely injured patients (ISS > 15) (r = 0.44, P < 0.01, n = 38, 95 % CI 0.14-0.67). Analysis by AIS Chest demonstrated similar correlation between patients without chest injuries (AIS 0) (r = 0.55, n = 29, p < 0.01, 95 % CI 0.23-0.76) and those with an AIS >1 (r = 0.51, n = 22, p = 0.02, 95 % CI 0.11-0.77). In patients with traumatic head injuries who had an EtCO2 between 30 and 39 mmHg, only 57 % had a measured PaCO2 within 5 mmHg.

CONCLUSIONS

As patients transition from minor to seriously injured, a decreasing strength of PaCO2 to EtCO2 correlation is observed, decreasing the reliability of EtCO2 as a surrogate marker of PaCO2 in this patient group. This inconsistency cannot be accounted for by the presence of chest injuries and worryingly is frequently seen in those with traumatic brain injuries.

Severe Pediatric Open Skull Fracture With Exposed Brain Matter: A Case Report

Head trauma in the pediatric population carries a high rate of morbidity and mortality. The major causes of head trauma are related to falls, recreational activities, motor vehicle accidents, and gunshot wounds. Traumatic brain injury (TBI) can occur after severe head trauma and is defined as an alteration in brain function, or other evidence of brain pathology, caused by an external force. Intracranial edema and herniation are common consequences of a TBI in pediatric patients and are commonly relieved via decompressive craniectomy.  This case study describes a 13-year-old male presenting to the trauma center after an unhelmeted all-terrain vehicle (ATV) accident with a positive head strike and loss of consciousness. The evaluation revealed extensive skull fractures extending from the frontal to the occipital lobe with brain exposure. Computed tomography (CT) scan of the head demonstrated extensive, open skull fractures with significant displacement of the exposed brain, extensive bilateral parietal and frontal bone fractures, and bilateral temporal bone displaced fractures more extensive on the left. A bilateral hemicraniectomy was performed due to diffuse cerebral edema and a left frontal ventriculostomy was placed to monitor and manage intracranial pressure (ICP). It is believed that the unique presentation of an open skull fracture with an exposed brain acted as a decompressive method allowing for extreme lifesaving measures to be performed to save the patient. Further exploration is needed to truly understand the effects of the unique injury presentation and the role of an open fracture in the delay of increased ICP.

Quantitative Electroencephalography Analysis for Improved Assessment of Consciousness Levels in Deep Coma Patients Using a Proposed Stimulus Stage

"Coma" is defined as an inability to obey commands, to speak, or to open the eyes. So, a coma is a state of unarousable unconsciousness. In a clinical setting, the ability to respond to a command is often used to infer consciousness. Evaluation of the patient's level of consciousness (LeOC) is important for neurological evaluation. The Glasgow Coma Scale (GCS) is the most widely used and popular scoring system for neurological evaluation and is used to assess a patient's level of consciousness. The aim of this study is the evaluation of GCSs with an objective approach based on numerical results. So, EEG signals were recorded from 39 patients in a coma state with a new procedure proposed by us in a deep coma state (GCS: between 3 and 8). The EEG signals were divided into four sub-bands as alpha, beta, delta, and theta, and their power spectral density was calculated. As a result of power spectral analysis, 10 different features were extracted from EEG signals in the time and frequency domains. The features were statistically analyzed to differentiate the different LeOC and to relate with the GCS. Additionally, some machine learning algorithms have been used to measure the performance of the features for distinguishing patients with different GCSs in a deep coma. This study demonstrated that GCS 3 and GCS 8 patients were classified from other levels of consciousness in terms of decreased theta activity. To the best of our knowledge, this is the first study to classify patients in a deep coma (GCS between 3 and 8) with 96.44% classification performance.

Prediction of acute organophosphate poisoning severity using machine learning techniques

Poisoning with organophosphate compounds is a significant public health risk, especially in developing countries. Considering the importance of early and accurate prediction of organophosphate poisoning prognosis, the aim of this study was to develop a machine learning-based prediction model to predict the severity of organophosphate poisoning. The data of patients with organophosphate poisoning were retrospectively extracted and split into training and test sets in a ratio of 70:30. The feature selection was done by least absolute shrinkage and selection operator method. Selected features were fed into five machine learning techniques, including Histogram Boosting Gradient, eXtreme Gradient Boosting, K-Nearest Neighborhood, Support Vector Machine (SVM) (kernel = linear), and Random Forest. The Scikit-learn library in Python programming language was used to implement the models. Finally, the performance of developed models was measured using ten-fold cross-validation methods and some evaluation criteria with 95 % confidence intervals. A total of 1237 patients were used to train and test the machine learning models. According to the criteria determining severe organophosphate poisoning, 732 patients were assigned to group 1 (patients with mild to moderate poisoning) and 505 patients were assigned to group 2 (patients with severe poisoning). With an AUC value of 0.907 (95 % CI 0.89-0.92), the model developed using XGBoost outperformed other models. Feature importance evaluation found that venous blood gas-pH, white blood cells, and plasma cholinesterase activity were the top three variables that contribute the most to the prediction performance of the prognosis in patients with organophosphate poisoning. XGBoost model yield an accuracy of 90.1 % (95 % CI 0.891-0.918), specificity of 91.4 % (95 % CI 0.90-0.92), a sensitivity of 89.5 % (95 % CI 0.87-0.91), F-measure of 91.2 % (95 % CI 0.90-0.921), and Kappa statistic of 91.2 % (95 % CI 0.90-0.92). The machine learning-based prediction models can accurately predict the severity of organophosphate poisoning. Based on feature selection techniques, the most important predictors of organophosphate poisoning were VBG-pH, white blood cell count, plasma cholinesterase activity, VBG-BE, and age. The best algorithm with the highest predictive performance was the XGBoost classifier.

Evacuation Strategies for U.S. Casualties with Traumatic Brain Injury (TBI) with and without Polytrauma

INTRODUCTION

According to the Military Health System Traumatic Brain Injury (TBI) Center of Excellence, 51,261 service members suffered moderate to severe TBI in the last 21 years. Moderate to severe TBI in service members is usually related to blast injury in combat operations, which necessitates medical evacuation to higher levels of care. Prevention of secondary insult, and mitigation of the unique challenges associated with the transport of TBI patients in a combat setting are important in reducing the morbidity and mortality associated with this injury. The primary goal of this study was a secondary analysis comparing the impact of time to transport on clinical outcomes for TBI patients without polytrauma versus TBI patients with polytrauma transported out of the combat theater via Critical Care Air Transport Teams (CCATT). Our secondary objective was to describe the occurrence of in-flight events and interventions for TBI patients without polytrauma versus TBI with polytrauma to assist with mission planning for future transports.

MATERIALS AND METHODS

We performed a secondary analysis of a retrospective cohort of 438 patients with TBI who were evacuated out of theater by CCATT from January 2007 to May 2014. Polytrauma was defined as abbreviated injury scale (AIS) of at least three to another region in addition to head/neck. Time to transport was defined as the time (in days) from injury to CCATT evacuation out of combat theater. We calculated descriptive statistics and examined the associations between time to transport and preflight characteristics, in-flight interventions and events, and clinical outcomes for TBI patients with and without polytrauma.

RESULTS

We categorized patients into two groups, those who had a TBI without polytrauma (n = 179) and those with polytrauma (n = 259). Within each group, we further divided those that were transported within 1 day of injury, in 2 days, and 3 or more days. Patients with TBI without polytrauma transported in 1 or 2 days were more likely to have a penetrating injury, an open head injury, a preflight Glascow Coma Score (GCS) of 8 or lower, and be mechanically ventilated compared to those transported later. Patients without polytrauma who were evacuated in 1 or 2 days required more in-flight interventions compared to patients without polytrauma evacuated later. Patients with polytrauma who were transported in 2 days were more likely to receive blood products, and patients with polytrauma who were evacuated within 1 day were more likely to have had at least one episode of hypotension en route. Polytrauma patients who were evacuated in 2-3 days had higher hospital days compared to polytrauma with earlier evacuations. There was no significant difference in mortality between any of the groups.

CONCLUSIONS

In patients with moderate to severe TBI transported via CCATT, early evacuation was associated with a higher rate of in-flight hypotension in polytrauma patients. Furthermore, those who had TBI without polytrauma that were evacuated in 1-2 days received more in-flight supplementary oxygen, blood products, sedatives, and paralytics. Given the importance of minimizing secondary insults in patients with TBI, recognizing this in this subset of the population may help systematize ways to minimize such events. Traumatic Brain Injury patients with polytrauma may benefit from further treatment and stabilization in theater prior to CCATT evacuation.

Association of Flow Rate of Prehospital Oxygen Administration and Clinical Outcomes in Severe Traumatic Brain Injury

The goal of this study was to investigate the association of prehospital oxygen administration flow with clinical outcome in severe traumatic brain injury (TBI) patients. This was a cross-sectional observational study using an emergency medical services-assessed severe trauma database in South Korea. The sample included adult patients with severe blunt TBI without hypoxia who were treated by EMS providers in 2013 and 2015. Main exposure was prehospital oxygen administration flow rate (no oxygen, low-flow 1~5, mid-flow 6~14, high-flow 15 L/min). Primary outcome was in-hospital mortality. A total of 1842 patients with severe TBI were included. The number of patients with no oxygen, low-flow oxygen, mid-flow oxygen, high-flow oxygen was 244, 573, 607, and 418, respectively. Mortality of each group was 34.8%, 32.3%, 39.9%, and 41.1%, respectively. Compared with the no-oxygen group, adjusted odds (95% CI) for mortality in the low-, mid-, and high-flow oxygen groups were 0.86 (0.62–1.20), 1.15 (0.83–1.60), and 1.21 (0.83–1.73), respectively. In the interaction analysis, low-flow oxygen showed lower mortality when prehospital saturation was 94–98% (adjusted odds ratio (AOR): 0.80 (0.67–0.95)) and ≥99% (AOR: 0.69 (0.53–0.91)). High-flow oxygen showed higher mortality when prehospital oxygen saturation was ≥99% (AOR: 1.33 (1.01~1.74)). Prehospital low-flow oxygen administration was associated with lower in-hospital mortality compared with the no-oxygen group. High-flow administration showed higher mortality.

Hamid AI, Abdullah MZ, Azman A, Abdullah JM. Detection of Moderate Traumatic Brain Injury from Resting-State Eye-Closed Electroencephalography

Traumatic brain injury (TBI) is one of the injuries that can bring serious consequences if medical attention has been delayed. Commonly, analysis of computed tomography (CT) or magnetic resonance imaging (MRI) is required to determine the severity of a moderate TBI patient. However, due to the rising number of TBI patients these days, employing the CT scan or MRI scan to every potential patient is not only expensive, but also time consuming. Therefore, in this paper, we investigate the possibility of using electroencephalography (EEG) with computational intelligence as an alternative approach to detect the severity of moderate TBI patients. EEG procedure is much cheaper than CT or MRI. Although EEG does not have high spatial resolutions as compared with CT and MRI, it has high temporal resolutions. The analysis and prediction of moderate TBI from EEG using conventional computational intelligence approaches are tedious as they normally involve complex preprocessing, feature extraction, or feature selection of the signal. Thus, we propose an approach that uses convolutional neural network (CNN) to automatically classify healthy subjects and moderate TBI patients. The input to this computational intelligence system is the resting-state eye-closed EEG, without undergoing preprocessing and feature selection. The EEG dataset used includes 15 healthy volunteers and 15 moderate TBI patients, which is acquired at the Hospital Universiti Sains Malaysia, Kelantan, Malaysia. The performance of the proposed method has been compared with four other existing methods. With the average classification accuracy of 72.46%, the proposed method outperforms the other four methods. This result indicates that the proposed method has the potential to be used as a preliminary screening for moderate TBI, for selection of the patients for further diagnosis and treatment planning.

Quality And Feasibility of Sonographic Measurement of the Optic Nerve Sheath Diameter to Estimate the Risk of Raised Intracranial Pressure After Traumatic Brain Injury in Prehospital Setting

OBJECTIVE

In patients with traumatic brain injury (TBI), early detection and subsequent prompt treatment of elevated intracranial pressure (ICP) is a challenge in the prehospital setting, because physical examination is limited in comatose patients and invasive device placement is not possible. The aim of this study was to evaluate the quality and feasibility of optic nerve sheath diameter (ONSD) measurements obtained during the prehospital management of patients with TBI.

METHODS

This study was a prospective, observational study of 23 patients with moderate and severe TBI during prehospital medical care. The primary endpoint was the quality of ONSD measurements expressed as the percentage of ONSD validated by the experts. Secondary endpoints included the feasibility of ONSD measurements as the percentage of ONSD performed and assessment by operators of ease and duration to perform.

RESULTS

Ultrasound ONSD was performed in 19 (82%) patients and 80% of ONSD measurements were validated by the experts. The ONSD measurements were possible in 15 (79%) cases. The physicians have assessed the ease of use at 8 (interquartile range [IQR] = 2.5-8) on 10 for and the median time to obtain ONSD measurement was 4 min (IQR = 3-5). ONSD measurement was performed in 12 (63%) cases during the transport and in 7 (37%) cases on scene, with 58% (n = 7) and 71% (n = 5) validated ONSD, respectively. The success rate in the helicopter was 43% compared to 80% in the ambulance.

CONCLUSION

This study shows that it is feasible to obtain high-quality ONSD measurements in the management of patients with TBI in a prehospital setting. A randomized study evaluating the usefulness of ONSD to guide management of TBI in the prehospital phase may be of great interest.

Efficacy of decompressive craniectomy in the management of intracranial pressure in severe traumatic brain injury

Traumatic brain injury (TBI) is a common cause of permanent disability for which clinical management remains suboptimal. Elevated intracranial pressure (ICP) is a common sequela following TBI leading to death and permanent disability if not properly managed. While clinicians often employ stepwise acute care algorithms to reduce ICP, a number of patients will fail medical management and may be considered for surgical decompression. Decompressive craniectomy (DC) involves removing a component of the bony skull to allow cerebral tissue expansion in order to reduce ICP. However, the impact of DC, which is performed in the setting of neurological instability, ongoing secondary injury, and patient resuscitation, has been challenging to study and outcomes are not well understood. This review summarizes historical and recent studies to elucidate indications for DC and the nuances, risks and complications in its application. The pathophysiology driving ICP elevation, and the corresponding medical interventions for their temporization and treatment, are thoroughly described. The current state of DC - including appropriate injury classification, surgical techniques, concurrent medical therapies, mortality and functional outcomes - is presented. We also report on the recent updates from large randomized controlled trials in severe TBI (Decompressive Craniectomy [DECRA] and Randomized Evaluation of Surgery with Craniectomy for Uncontrollable Elevation of ICP [RESCUEicp]), and recommendations for early DC to treat refractory ICP elevations in malignant middle cerebral artery syndrome. Limitations for DC, such as the equipoise between immediate reduction in ICP and clinically meaningful functional outcomes, are discussed in support of future investigations.