Prehospital Detection of Life-Threatening Intracranial Pathology: An Unmet Need for Severe TBI in Austere, Rural, and Remote Areas

Acute subdural haematoma exacerbates cerebral blood flow disorder and promotes the development of intraoperative brain bulge in patients with severe traumatic brain injury

BACKGROUND

Decompressive craniectomy (DC) is a routine procedure used for the treatment of severe traumatic brain injury (TBI) with concomitant acute subdural haematoma (SDH). However, certain patients are prone to developing malignant brain bulge during DC, which prolongs the operative time and worsens patient outcomes. Previous studies have shown that malignant intraoperative brain bulge (IOBB) may be associated with excessive arterial hyperaemia caused by cerebrovascular system disorders. Through a clinical retrospective analysis and prospective observations, we found that the cerebral blood flow of patients who possessed risk factors manifested high resistance and low flow velocity, which severely affected brain tissue perfusion and resulted in the occurrence of malignant IOBB. In the current literature, rat models of severe brain injury-associated brain bulge have rarely been reported.

METHODS

To gain an in-depth understanding of cerebrovascular changes and the cascade of responses related to brain bulge, we introduced acute SDH into the Marmarou model for the preparation of a rat model of high intracranial pressure (ICP) to simulate the pathological conditions experienced by patients with severe brain injury.

RESULTS

With the introduction of a 400-µL haematoma, significant dynamic changes occurred in ICP, mean arterial pressure, and relative blood perfusion rate of the cerebral cortical vessels. ICP increased to 56.9 ± 2.3 mmHg, mean arterial pressure showed reactive decrease, and the blood flow of cerebral cortical arteries and veins on the non-SDH-affected side decreased to < 10%. These changes could not fully recover even after DC. This resulted in generalised damage to the neurovascular unit and a lag effect to the venous blood reflux, which triggered malignant IOBB formation during DC.

CONCLUSION

An excessive increase in ICP causes cerebrovascular dysfunction and brings about a cascade of damage to brain tissue, which forms the basis for the development of diffuse brain swelling. The subsequent heterogeneous responses of the cerebral arteries and veins during craniotomy may be the main cause of primary IOBB. Clinicians should pay particular attention to the redistribution of CBF to various vessels when performing DC in patients with severe TBI.

Development and validation of a prehospital-stage prediction tool for traumatic brain injury: a multicentre retrospective cohort study in Korea

OBJECTIVES

Predicting diagnosis and prognosis of traumatic brain injury (TBI) at the prehospital stage is challenging; however, using comprehensive prehospital information and machine learning may improve the performance of the predictive model. We developed and tested predictive models for TBI that use machine learning algorithms using information that can be obtained in the prehospital stage.

DESIGN

This was a multicentre retrospective study.

SETTING AND PARTICIPANTS

This study was conducted at three tertiary academic emergency departments (EDs) located in an urban area of South Korea. The data from adult patients with severe trauma who were assessed by emergency medical service providers and transported to three participating hospitals between 2014 to 2018 were analysed.

RESULTS

We developed and tested five machine learning algorithms-logistic regression analyses, extreme gradient boosting, support vector machine, random forest and elastic net (EN)-to predict TBI, TBI with intracranial haemorrhage or injury (TBI-I), TBI with ED or admission result of admission or transferred (TBI with non-discharge (TBI-ND)) and TBI with ED or admission result of death (TBI-D). A total of 1169 patients were included in the final analysis, and the proportions of TBI, TBI-I, TBI-ND and TBI-D were 24.0%, 21.5%, 21.3% and 3.7%, respectively. The EN model yielded an area under receiver-operator curve of 0.799 for TBI, 0.844 for TBI-I, 0.811 for TBI-ND and 0.871 for TBI-D. The EN model also yielded the highest specificity and significant reclassification improvement. Variables related to loss of consciousness, Glasgow Coma Scale and light reflex were the three most important variables to predict all outcomes.

CONCLUSION

Our results inform the diagnosis and prognosis of TBI. Machine learning models resulted in significant performance improvement over that with logistic regression analyses, and the best performing model was EN.

Epidemiology, patterns of care and outcomes of traumatic brain injury in deployed military settings: implications for future military operations

BACKGROUND

Traumatic brain injury (TBI) is prevalent and highly morbid among Service Members. A better understanding of TBI epidemiology, outcomes, and care patterns in deployed settings could inform potential approaches to improve TBI diagnosis and management.

METHODS

A retrospective cohort analysis of Service Members who sustained a TBI in deployed settings between 2001 and 2018 was conducted. Among individuals hospitalized with TBI, we compared the demographic characteristics, mechanism of injury, injury type, and severity between combat and non-combat injuries. We compared diagnostic tests and procedures, evacuation patterns, return to duty rates and days in care between individuals with concussion and those with severe TBI.

RESULTS

There were 46,309 Service Members with TBI and 9,412 who were hospitalized; of those hospitalized, 55% (4,343) had isolated concussion and 9% (796) had severe TBI, of whom 17% (132/796) had polytrauma. Overall mortality was 2% and ranged from 0.1% for isolated concussion to 18% for severe TBI. The vast majority of TBI were evacuated by rotary wing to Role 3 or higher, including those with isolated concussion. As compared to severe TBI, individuals with isolated concussion had fewer diagnostic or surgical procedures performed. Only 6% of Service Members with severe TBI were able to return to duty as compared to 54% of those with isolated concussion. TBI resulted in 123,677 lost duty days; individuals with isolated concussion spent a median of 2 days in care and those with severe TBI spent a median of 17 days in care and a median of 6 days in the intensive care unit.

CONCLUSIONS

While most TBI in the deployed setting is mild, TBI is frequently associated with hospitalization and polytrauma. Over-triage of mild TBI is common. Improved TBI capabilities applicable to forward settings will be critical to the success of future multi-domain operations with limitations in air superiority.

LEVEL OF EVIDENCE

Prognostic, Level III.