Early Imaging Associated With Improved Survival in Older Patients With Mild Traumatic Brain Injuries

London Major Trauma System: a review of an organised trauma system and the challenges it faces

London Major Trauma System (LMTS) was the first organised trauma system in the United Kingdom. It was created in 2010 in response to multiple reviews that suggested a large number of deaths from trauma may have been preventable. LMTS has all the features of a modern organised trauma system, including regionalisation, integration of care, transfer services, trauma teams, and a world leading research service. Since its introduction the benefits on mortality, morbidity, and other key metrics have been widely demonstrated. Despite its success, LMTS still faces a number of challenges; most notably from the ageing population, but also in ensuring equity of improvements across the entirety of the trauma network and throughout the whole patient journey. The very nature of LMTS being an inclusive and organised trauma system will help it in facing these challenges.

Concussion Management in Older People: A Scoping Review

OBJECTIVE

To map existing literature about concussion management in older people, identifying and analyzing gaps in our understanding.

CONTEXT

Concussion injuries affect older people, yet little guidance is available about how to approach concussion management with older people. Research does not always include older populations, and it is unclear to what extent standard concussion management is appropriate for older people.

DESIGN

Scoping review.

METHOD

A structured literature search was conducted using 4 databases to identify existing literature relating to concussion management in older people. Studies that assessed outcomes relating to the management of concussion/mild traumatic brain injury in those 65 years or older were included and mapped according to the main themes addressed.

RESULTS

The search yielded a total of 18 articles. Three themes related to early management (use of anticoagulants n = 6, intracranial lesions n = 3, and service delivery for older people n = 5), and 1 theme related to general management (cognitive issues n = 4). A lack of articles exploring general management in older people was observed.

CONCLUSION

Existing literature indicates that specific management strategies are needed for older people with concussion, especially in early management. This review highlights that good evidence is available about early management and this is reflected in some guidelines, yet little evidence about general management is available and this gap is not acknowledged in guidelines. Distinct approaches to early management in older people are clearly recommended to mitigate the risk of poor outcomes. In contrast, general concussion management for older people is poorly understood, with older people poorly represented in research. A better understanding is needed because-as observed in early management-older people have distinct characteristics that may render standard management approaches unsuitable.

Timing of computed tomography imaging in adult patients with severe trauma: A nationwide cohort study in Japan

PURPOSE

Computed tomography (CT) has become essential for the management of trauma patients. However, appropriate timing of CT acquisition remains undetermined. The purpose of this study was to assess the relationship between time to CT acquisition and mortality among adult patients with severe trauma.

METHODS

We conducted a retrospective cohort study using data from the Japan Trauma Data Bank, which had 256 participating institutions from all over Japan between 2004 and 2018. Patients were categorized upon arrival as either severe trunk trauma with signs of shock or severe head trauma with coma and separately analyzed. Cases were further divided into three groups based on time elapsed between arrival at hospital and CT acquisition as immediate (0-29 min), intermediate (30-59 min), or late (≥60 min). Primary outcome was mortality on discharge, and multivariate logistic regression with adjusting for confounders was used for evaluation.

RESULTS

A total of 8467 (3640 in immediate group, 3441 in intermediate group, 1386 in late group) with trunk trauma patients and 6762 (4367 in immediate group, 2031 in intermediate group, 364 in late group) with head trauma patients were eligible for analysis included in the trunk and head trauma groups, respectively. The trunk trauma patients with shock on hospital arrival was 56.4% (4773/8467), and the head trauma patients with deep coma upon EMS arrival was 44.2% (2988/6762). Mortality rate gradually increased from 5.7% to 15.8% with prolonged time to CT imaging among trunk trauma patients. Multivariate logistic regression for death on discharge among trunk trauma patients yielded an adjusted odds ratio of 1.79 (95% confidence interval: 1.42-2.27) for the late group compared to the immediate group. In contrast, among head trauma patients, an adjusted odds ratio was 0.93 (95% confidence interval: 0.71-1.20) for the late group compared to the immediate group.

CONCLUSION

CT scan at or after 60 min was associated with increased death on discharge among patients with severe trunk trauma but not in those with severe head trauma.

The impact on clinical outcomes after 1 year of implementation of an artificial intelligence solution for the detection of intracranial hemorrhage

BACKGROUND

To assess the effect of a commercial artificial intelligence (AI) solution implementation in the emergency department on clinical outcomes in a single level 1 trauma center.

METHODS

A retrospective cohort study for two time periods-pre-AI (1.1.2017-1.1.2018) and post-AI (1.1.2019-1.1.2020)-in a level 1 trauma center was performed. The ICH algorithm was applied to 587 consecutive patients with a confirmed diagnosis of ICH on head CT upon admission to the emergency department. Study variables included demographics, patient outcomes, and imaging data. Participants admitted to the emergency department during the same time periods for other acute diagnoses (ischemic stroke (IS) and myocardial infarction (MI)) served as control groups. Primary outcomes were 30- and 120-day all-cause mortality. The secondary outcome was morbidity based on Modified Rankin Scale for Neurologic Disability (mRS) at discharge.

RESULTS

Five hundred eighty-seven participants (289 pre-AI-age 71 ± 1, 169 men; 298 post-AI-age 69 ± 1, 187 men) with ICH were eligible for the analyzed period. Demographics, comorbidities, Emergency Severity Score, type of ICH, and length of stay were not significantly different between the two time periods. The 30- and 120-day all-cause mortality were significantly reduced in the post-AI group when compared to the pre-AI group (27.7% vs 17.5%; p = 0.004 and 31.8% vs 21.7%; p = 0.017, respectively). Modified Rankin Scale (mRS) at discharge was significantly reduced post-AI implementation (3.2 vs 2.8; p = 0.044).

CONCLUSION

The added value of this study emphasizes the introduction of artificial intelligence (AI) computer-aided triage and prioritization software in an emergent care setting that demonstrated a significant reduction in a 30- and 120-day all-cause mortality and morbidity for patients diagnosed with intracranial hemorrhage (ICH). Along with mortality rates, the AI software was associated with a significant reduction in the Modified Ranking Scale (mRs).

Changes in patterns of traumatic brain injury in the Michigan Trauma Quality Improvement Program database early in the COVID-19 pandemic

OBJECTIVE

The authors' objective was to investigate the impact of the global COVID-19 pandemic on hospital presentation and process of care for the treatment of traumatic brain injuries (TBIs). Improved understanding of these effects will inform sociopolitical and hospital policies in response to future pandemics.

METHODS

The Michigan Trauma Quality Improvement Program (MTQIP) database, which contains data from 36 level I and II trauma centers in Michigan and Minnesota, was queried to identify patients who sustained TBI on the basis of head/neck Abbreviated Injury Scale (AIS) codes during the periods of March 13 through July 2 of 2017-2019 (pre-COVID-19 period) and March 13, 2020, through July 2, 2020 (COVID-19 period). Analyses were performed to detect differences in incidence, patient characteristics, injury severity, and outcomes.

RESULTS

There was an 18% decrease in the rate of encounters with TBI in the first 8 weeks (March 13 through May 7), followed by a 16% increase during the last 8 weeks (May 8 through July 2), of our COVID-19 period compared with the pre-COVID-19 period. Cumulatively, there was no difference in the rates of encounters with TBI between the COVID-19 and pre-COVID-19 periods. Severity of TBI, as measured with maximum AIS score for the head/neck region and Glasgow Coma Scale score, was also similar between periods. During the COVID-19 period, a greater proportion of patients with TBI presented more than a day after sustaining their injuries (p = 0.046). COVID-19 was also associated with a doubling in the decubitus ulcer rate from 1.0% to 2.1% (p = 0.002) and change in the distribution of discharge status (p = 0.01). Multivariable analysis showed no differences in odds of death/hospice discharge, intensive care unit stay of at least a day, or need for a ventilator for at least a day between the COVID-19 and pre-COVID-19 periods.

CONCLUSIONS

During the early months of the COVID-19 pandemic, the number of patients who presented with TBI was initially lower than in the years 2017-2019 prior to the pandemic. However, there was a subsequent increase in the rate of encounters with TBI, resulting in overall similar rates of TBI between March 13 through July 2 during the COVID-19 period and during the pre-COVID-19 period. The COVID-19 cohort was also associated with negative impacts on time to presentation, rate of decubitus ulcers, and discharge with supervision. Policies in response to future pandemics must consider the resources necessary to care for patients with TBI.

What are the demographic and clinical differences between those older adults with traumatic brain injury who receive a neurosurgical intervention to those that do not? A systematic literature review with narrative synthesis

OBJECTIVES

This review aimed to identify the demographic and clinical differences between those older adults admitted directly under neurosurgical care and those that were not, and whether EMS clinicians could use these differences to improve patient triage.

METHODS

The authors searched for papers that included older adults who had suffered a TBI and were either admitted directly under neurosurgical care or were not. Titles and abstracts were screened, shortlisting potentially eligible papers before performing a full-text review. The Newcastle-Ottawa Scale was used to assess the risk of bias.

RESULTS

A total of nine studies were eligible for inclusion. A high abbreviated injury score head, Marshall score or subdural hematoma greater than 10 mm were associated with neurosurgical care. There were few differences between those patients who did and did not receive neurosurgical intervention.

CONCLUSIONS

Absence of guidelines and clinician bias means that differences between those treated aggressively and conservatively observed in the literature are fraught with bias. Further work is required to understand which patients would benefit from an escalation of care and whether EMS can identify these patients so they are transported directly to a hospital with the appropriate services on-site.

Intracerebral hemorrhage detection on computed tomography images using a residual neural network

Intracerebral hemorrhage (ICH) is a high mortality rate, critical medical injury, produced by the rupture of a blood vessel of the vascular system inside the skull. ICH can lead to paralysis and even death. Therefore, it is considered a clinically dangerous disease that needs to be treated quickly. Thanks to the advancement in machine learning and the computing power of today's microprocessors, deep learning has become an unbelievably valuable tool for detecting diseases, in particular from medical images. In this work, we are interested in differentiating computer tomography (CT) images of healthy brains and ICH using a ResNet-18, a deep residual convolutional neural network. In addition, the gradient-weighted class activation mapping (Grad-CAM) technique was employed to visually explore and understand the network's decisions. The generalizability of the detector was assessed through a 100-iteration Monte Carlo cross-validation (80% of the data for training and 20% for test). In a database with 200 CT images of brains (100 with ICH and 100 without ICH), the detector yielded, on average, 95.93%accuracy, 96.20% specificity, 95.65% sensitivity, 96.40% precision, and 95.91% F1-core, with an average computing time of 165.90 s to train the network (on 160 images) and 1.17 s to test it with 40 CT images. These results are comparable with the state of the art with a simpler and lower computational load approach. Our detector could assist physicians in their medical decision, in resource optimization and in reducing the time and error in the diagnosis of ICH.

A cost-effectiveness and value of information analysis to inform future research of tranexamic acid for older adults experiencing mild traumatic brain injury

BACKGROUND

Tranexamic acid reduces head injury deaths in patients with CT scan evidence of intracranial bleeding after mild traumatic brain injury (TBI). However, the cost-effectiveness of tranexamic acid for people with mild TBI in the pre-hospital setting, prior to CT scanning, is uncertain. A large randomised controlled trial (CRASH-4) is planned to address this issue, but the economic justification for it has not been established. The aim of the analysis was to estimate the likelihood of tranexamic acid being cost-effective given current evidence, the treatment effects required for cost-effectiveness, and the expected value of performing further research.

METHODS

An early economic decision model compared usual care for mild TBI with and without tranexamic acid, for adults aged 70 and above. The evaluation was performed from a UK healthcare perspective over a lifetime time horizon, with costs reported in 2020 pounds (GBP) and outcomes reported as quality-adjusted life years (QALYs). All analyses used a £20,000 per QALY cost-effectiveness threshold.

RESULTS

In the base case analysis, tranexamic acid was associated with an incremental cost-effectiveness ratio of £4885 per QALY gained, but the likelihood of it being cost-effective was highly dependent on the all-cause mortality treatment effect. The value of perfect information was £22.4 million, and the value of perfect information for parameters that could be collected in a trial was £21.9 million. The all-cause mortality risk ratio for tranexamic acid and the functional outcomes following TBI had the most impact on cost-effectiveness.

CONCLUSIONS

There is a high degree of uncertainty in the cost-effectiveness of tranexamic acid for older adults experiencing mild TBI, meaning there is a high value of performing future research in the UK. The value in a global context is likely to be far higher.

Traumatic brain injury in the elderly with high Glasgow coma scale and low injury severity scores: Factors influencing outcomes

BACKGROUND

Current trauma activation guidelines do not clearly address age as a risk factor when leveling trauma patients. Glasgow coma scale (GCS) and mode of injury play a major role in leveling trauma patients. We studied the above relationship in our elderly patients presenting with traumatic head injury.

METHODS

This study was a retrospective analysis of patients who presented to the emergency department with traumatic brain injuries. We classified the 270 patients into two groups. Group A was 64 years and younger, and group B was 65 years and older. Their GCS, ISS, age, sex, comorbidities, and anticoagulant use were abstracted. The primary outcome was mortality and length of stay. The groups were compared using an independent student's t-test and Chi-square analysis. The Cox regression analysis was used to analyze differences in the outcome while adjusting for the above factors.

RESULTS

There were 140 patients in group A, and 130 patients in group B who presented to the ED with a GCS of 14-15 and an ISS of below 15. The mean ISS significantly differed between group A (6.2 ± 6.8) vs (7.9 ± 3.2) in group B (p < 0.0001). The most common diagnosis in group A was concussion (57.3%), while in group B was subdural and subarachnoid hemorrhage (55%). In group B, 13.8% presented as a level one or level two trauma activation. The mean hospital and intensive care stay for group A was 2.1 (±1.9) days and 0.9 (±1.32) days, respectively, versus 4.2 (±3.04) days and 2.4 (±2.02 days) for the elderly group B. Mortality in group A was zero and in group B was 3.8%. Cox regression analysis showed age as an independent predictor of death as well as length of stay.

CONCLUSION

Elderly traumatic brain injury patients presenting to the ED with minor trauma and high GCS should be triaged at a higher level in most cases.

Isolated Intracranial Hemorrhage in Elderly Patients With Pre-Injury Anticoagulation: Is Full Trauma Team Activation Necessary?

BACKGROUND

Traumatic intracranial hemorrhage (ICH) is a highly morbid injury, particularly among elderly patients on preinjury anticoagulants (AC). Many trauma centers initiate full trauma team activation (FTTA) for these high-risk patients. We sought to determine if FTTA was superior compared with those who were evaluated as a trauma consultation (CON).

METHODS

Patients aged ≥55 on preinjury AC who presented from January 2015 to December 2019 with blunt isolated head injury (non-head AIS ≤2) and confirmed ICH were identified. CON patients and FTTA patients were matched by age and head AIS. Cox proportional hazard model was used to assess patient and injury characteristics with mortality and survivor discharge disposition.

REASULTS

There were 45 CON patients and 45 FTTA patients. Mean age was 80 years in both groups. Fall was the most common mechanism (98% CON vs. 92% FTTA). Glasgow Coma Score (GCS) was lower in FTTA (14 vs. 15, p<0.01). CON had a significantly longer time from arrival to CT scan (1.3 vs. 0.4 hrs, p<0.01). Hospital days were similar (CON: 3.9 vs. FTTA: 3.7 days). However, CON had increased ventilator use (p=0.03). Lower admission GCS was the only factor associated with increased risk of death. Among survivors, only head AIS increased the risk of discharge to a level of care higher than that of preinjury (p=0.01).

CONCLUSION

There was no difference in mortality or adverse discharge disposition between FTTA and CON, although FTTA was associated with a more rapid evaluation and diagnosis. Any alteration in GCS was strongly associated with mortality and should prompt evaluation by FTTA.

Field-Triage, Hospital-Triage and Triage-Assessment: A Literature Review of the Current Phases of Adult Trauma Triage

ABSTRACT

Despite major improvements in the United States trauma system over the past two decades, prehospital trauma triage is a significant challenge. Undertriage is associated with increased mortality, and overtriage results in significant resource overuse. The American College of Surgeons Committee on Trauma benchmarks for undertriage and overtriage are not being met. Many barriers to appropriate field triage exist, including lack of a formal definition for major trauma, absence of a simple and widely applicable triage mode, and emergency medical service adherence to triage protocols. Modern trauma triage systems should ideally be based on the need for intervention rather than injury severity. Future studies should focus on identifying the ideal definition for major trauma and creating triage models that can be easily deployed. This narrative review article presents challenges and potential solutions for prehospital trauma triage.

Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography

OBJECTIVE

The timely reporting of critical results in radiology is paramount to improved patient outcomes. Artificial intelligence has the ability to improve quality by optimizing clinical radiology workflows. We sought to determine the impact of a United States Food and Drug Administration-approved machine learning (ML) algorithm, meant to mark computed tomography (CT) head examinations pending interpretation as higher probability for intracranial hemorrhage (ICH), on metrics across our healthcare system. We hypothesized that ML is associated with a reduction in report turnaround time (RTAT) and length of stay (LOS) in emergency department (ED) and inpatient populations.

MATERIALS AND METHODS

An ML algorithm was incorporated across CT scanners at imaging sites in January 2018. RTAT and LOS were derived for reports and patients between July 2017 and December 2017 prior to implementation of ML and compared to those between January 2018 and June 2018 after implementation of ML. A total of 25,658 and 24,996 ED and inpatient cases were evaluated across the entire healthcare system before and after ML, respectively.

RESULTS

RTAT decreased from 75 to 69 minutes (P <0.001) at all facilities in the healthcare system. At the level 1 trauma center specifically, RTAT decreased from 67 to 59 minutes (P <0.001). ED LOS decreased from 471 to 425 minutes (P <0.001) for patients without ICH, and from 527 to 491 minutes for those with ICH (P = 0.456). Inpatient LOS decreased from 18.4 to 15.8 days for those without ICH (P = 0.001) and 18.1 to 15.8 days for those with ICH (P = 0.02).

CONCLUSION

We demonstrated that utilization of ML was associated with a statistically significant decrease in RTAT. There was also a significant decrease in LOS for ED patients without ICH, but not for ED patients with ICH. Further evaluation of the impact of such tools on patient care and outcomes is needed.

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

The most commonly used techniques for addressing each Emergency Department (ED) problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient flow time, and high left-without-being-seen (LWBS) rates) were specified to provide healthcare managers and researchers with a useful framework for effectively solving these operational deficiencies. Finally, we identified the existing research tendencies and highlighted opportunities for future work. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to undertake a review including scholarly articles published between April 1993 and October 2019. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. Furthermore, computer simulation and lean manufacturing were concluded to be the most prominent approaches for addressing the leading operational problems in EDs. In future interventions, ED administrators and researchers are widely advised to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for upgrading the performance of EDs. On a different tack, more interventions are required for tackling overcrowding and high left-without-being-seen rates.