Guidelines for the emergency department management of traumatic brain injury : an impact assessment and development of a prognostic model to inform hospital admission decisions

Background1.4 million patients attend English and Welsh Emergency Departments (ED) annually following head injury. 95% attend with a high level of consciousness, of whom 1% have life-threatening traumatic brain injuries (TBI), whilst 7% have TBI on CT imaging.National guidelines were introduced in England and Scotland to improve TBI outcomes and reduce hospital admissions. The impact of these guidelines has not been rigorously assessed. They recommend patients with injuries on CT imaging be admitted to hospital in case they deteriorate. Accurate prediction of deterioration could identify patients safe for discharge from the ED.AimsAssess the impact of national guidelines on deaths and admissions.Develop a prediction model for deterioration in patients with injuries identified by CT imaging.MethodsInterrupted time series analyses using national data for England and Scotland were conducted to evaluate guideline impact.A systematic review was completed to identify candidate prognostic factors for deterioration. Multivariable logistic regression was used to develop prognostic models using these factors in an English multi-centre retrospective cohort of patients.ResultsGuideline impact varied by age group. Associated reductions in hospital admissions and mortality were found in those aged 16-64. In older patients, an increase in TBI mortality was observed, which was unaffected by guideline introduction.A prognostic model and decision rule was developed, using data from a cohort of 1699 patients. It achieved a sensitivity of 99.5% (95% CI: 98.1% to 99.9%) and specificity of 7.4% (95% CI: 6% to 9.1%) to a measure of deterioration encompassing need for admission.ConclusionThis first national evaluation of head injury guidelines to use quasi-experimental methods suggests guideline impact varied by age. This first empirically derived prediction model to inform admission decisions suggests a small proportion of patients could be safely discharged from the ED. External validation is required before clinical use

Delayed presentation to the Emergency Department following a head injury : current care and the risks of intra-cranial pathology

Background: Head injury is a common reason for Emergency Department attendance. The clinical dilemma is differentiating between patients who have mild/minor head injuries into those that can be discharged following clinical review and those that require a CT head scan to rule out neurosurgical pathology. Clinical decision rule research to aid this risk assessment has been conducted almost exclusively on patients presenting within twenty-four hours of injury. Delayed presentation head injury patients may be a distinct sub-population with a different risk profile. Methods: Three studies were undertaken. A systematic review was conducted to identify and assess existing evidence regarding the risk assessment in delayed presentation head injury patients. A survey of emergency physicians using clinical vignettes was used to assess variation in the investigation of this patient group. Lastly, six months of audit data were analysed to assess the size of the population of delayed presentation head injury patients, and the use and sensitivity of existing NICE guidelines in their risk assessment.Results: Few existing studies of poor methodological quality were found. A large degree of variation in clinical practice was identified in the investigation of this group. Head injury patients presenting after twenty-four hours of injury were found to account for 15.5% of CT head scans for the investigation of adult head trauma. In patients presenting after twenty-four hours of injury 30% of identified intra-cranial injuries were in patients without a NICE indication for a CT head scan compared to only 2.2% of intra-cranial injuries in patients presenting within twenty-four hours of their injury.Conclusions: Head injury patients presenting more than twenty-four hours after injury represent a significant clinical sub-population. A different approach to that recommended in the current NICE guidelines may be required in the risk assessment of this group

Electrocardiographic characteristics in patients with heart failure and normal ejection fraction: a systematic review and meta‐analysis

Background: Little is known about ECG abnormalities in patients with heart failure and normal ejection fraction (HeFNEF) and how they relate to different etiologies or outcomes. Methods and Results: We searched the literature for peer‐reviewed studies describing ECG abnormalities in HeFNEF other than heart rhythm alone. Thirty five studies were identified and 32,006 participants. ECG abnormalities reported in patients with HeFNEF include atrial fibrillation (prevalence 12%–46%), long PR interval (11%–20%), left ventricular hypertrophy (LVH, 10%–30%), pathological Q waves (11%–18%), RBBB (6%–16%), LBBB (0%–8%), and long JTc (3%–4%). Atrial fibrillation is more common in patients with HeFNEF compared to those with heart failure and reduced ejection fraction (HeFREF). In contrast, long PR interval, LVH, Q waves, LBBB, and long JTc are more common in patients with HeFREF. A pooled effect estimate analysis showed that QRS duration ≥120 ms, although uncommon (13%–19%), is associated with worse outcomes in patients with HeFNEF. Conclusions: There is high variability in the prevalence of ECG abnormalities in patients with HeFNEF. Atrial fibrillation is more common in patients with HeFNEF compared to those with HeFREF. QRS duration ≥120 ms is associated with worse outcomes in patients with HeFNEF. Further studies are needed to address whether ECG abnormalities correlate with different phenotypes in HeFNEF

Predicting need for hospital admission in patients with traumatic brain injury or skull fractures identified on CT imaging : a machine learning approach

Background: Patients with mild traumatic brain injury on CT scan are routinely admitted for inpatient observation. Only a small proportion of patients require clinical intervention. We recently developed a decision rule using traditional statistical techniques that found neurologically intact patients with isolated simple skull fractures or single bleeds <5 mm with no preinjury antiplatelet or anticoagulant use may be safely discharged from the emergency department. The decision rule achieved a sensitivity of 99.5% (95% CI 98.1% to 99.9%) and specificity of 7.4% (95% CI 6.0% to 9.1%) to clinical deterioration. We aimed to transparently report a machine learning approach to assess if predictive accuracy could be improved. Methods: We used data from the same retrospective cohort of 1699 initial Glasgow Coma Scale (GCS) 13–15 patients with injuries identified by CT who presented to three English Major Trauma Centres between 2010 and 2017 as in our original study. We assessed the ability of machine learning to predict the same composite outcome measure of deterioration (indicating need for hospital admission). Predictive models were built using gradient boosted decision trees which consisted of an ensemble of decision trees to optimise model performance. Results: The final algorithm reported a mean positive predictive value of 29%, mean negative predictive value of 94%, mean area under the curve (C-statistic) of 0.75, mean sensitivity of 99% and mean specificity of 7%. As with logistic regression, GCS, severity and number of brain injuries were found to be important predictors of deterioration. Conclusion: We found no clear advantages over the traditional prediction methods, although the models were, effectively, developed using a smaller data set, due to the need to divide it into training, calibration and validation sets. Future research should focus on developing models that provide clear advantages over existing classical techniques in predicting outcomes in this population

Evaluation of the impact of the NICE head injury guidelines on inpatient mortality from traumatic brain injury : an interrupted time series analysis

Objective To evaluate the impact of National Institute for Health and Care Excellence (NICE) head injury guidelines on deaths and hospital admissions caused by traumatic brain injury (TBI). Setting All hospitals in England between 1998 and 2017. Participants Patients admitted to hospital or who died up to 30 days following hospital admission with International Classification of Diseases (ICD) coding indicating the reason for admission or death was TBI. Intervention An interrupted time series analysis was conducted with intervention points when each of the three guidelines was introduced. Analysis was stratified by guideline recommendation specific age groups (0–15, 16–64 and 65+). Outcome measures The monthly population mortality and admission rates for TBI. Study design An interrupted time series analysis using complete Office of National Statistics cause of death data linked to hospital episode statistics for inpatient admissions in England. Results The monthly TBI mortality and admission rates in the 65+ age group increased from 0.5 to 1.5 and 10 to 30 per 100 000 population, respectively. The increasing mortality rate was unaffected by the introduction of any of the guidelines. The introduction of the second NICE head injury guideline was associated with a significant reduction in the monthly TBI mortality rate in the 16–64 age group (-0.005; 95% CI: −0.002 to −0.007). In the 0–15 age group the TBI mortality rate fell from around 0.05 to 0.01 per 100 000 population and this trend was unaffected by any guideline. Conclusion The introduction of NICE head injury guidelines was associated with a reduced admitted TBI mortality rate after specialist care was recommended for severe TBI. The improvement was solely observed in patients aged 16–64 years. The cause of the observed increased admission and mortality rates in those 65+ and potential treatments for TBI in this age group require further investigation

Accuracy of telephone triage for predicting adverse outcomes in suspected COVID-19 : an observational cohort study linking NHS 111 telephone triage, primary and secondary healthcare and mortality records.

Objectives Settings in identifying need for emergency care amongst those with suspected COVID-19 infection and identify factors which affect triage accuracy. Approach An observational cohort study of adults who contacted the NHS 111 telephone triage service provided by Yorkshire Ambulance Service between March and June 2020 with symptoms indicating possible COVID-19 infection. Patient-level data encompassing  triage call, primary care, hospital care and death registration records relating to 40,261 adults were linked. The accuracy of triage outcome (self-care/non-urgent assessment versus ambulance/urgent assessment) was assessed for death or organ support 30 days from first contact. Multivariable logistic regression was used to identify factors associated with risk of false negative or false positive triage. Results Callers had a 3% (1,200/40,261) risk of serious adverse outcomes. Telephone triage recommended self-care or non-urgent assessment for 60% (24,335/40,261), with a 1.3% (310/24,335) risk of adverse outcomes 30 days from first contact. Telephone triage had 74.2% sensitivity (95% CI: 71.6 to 76.6%) and 61.5% specificity (61% to 62%) for the primary outcome. Analysis suggested respiratory comorbidities may be over-appreciated and diabetes under-appreciated as predictors of deterioration. Repeat contact with triage service appears to be an important under-recognised predictor of deterioration. Conclusion Patients advised to self-care or receive non-urgent clinical assessment had a small but non-negligible risk of serious clinical deterioration. Repeat contact with telephone services needs recognition as an important predictor of subsequent adverse outcomes

Prognostic accuracy of triage tools for adults with suspected COVID-19 in a prehospital setting: an observational cohort study

BACKGROUND: Tools proposed to triage patient acuity in COVID-19 infection have only been validated in hospital populations. We estimated the accuracy of five risk-stratification tools recommended to predict severe illness and compared accuracy to existing clinical decision making in a prehospital setting. METHODS: An observational cohort study using linked ambulance service data for patients attended by Emergency Medical Service (EMS) crews in the Yorkshire and Humber region of England between 26 March 2020 and 25 June 2020 was conducted to assess performance of the Pandemic Respiratory Infection Emergency System Triage (PRIEST) tool, National Early Warning Score (NEWS2), WHO algorithm, CRB-65 and Pandemic Medical Early Warning Score (PMEWS) in patients with suspected COVID-19 infection. The primary outcome was death or need for organ support. RESULTS: Of the 7549 patients in our cohort, 17.6% (95% CI 16.8% to 18.5%) experienced the primary outcome. The NEWS2 (National Early Warning Score, version 2), PMEWS, PRIEST tool and WHO algorithm identified patients at risk of adverse outcomes with a high sensitivity (>0.95) and specificity ranging from 0.3 (NEWS2) to 0.41 (PRIEST tool). The high sensitivity of NEWS2 and PMEWS was achieved by using lower thresholds than previously recommended. On index assessment, 65% of patients were transported to hospital and EMS decision to transfer patients achieved a sensitivity of 0.84 (95% CI 0.83 to 0.85) and specificity of 0.39 (95% CI 0.39 to 0.40). CONCLUSION: Use of NEWS2, PMEWS, PRIEST tool and WHO algorithm could improve sensitivity of EMS triage of patients with suspected COVID-19 infection. Use of the PRIEST tool would improve sensitivity of triage without increasing the number of patients conveyed to hospital

The risk of deterioration in GCS13-15 patients with traumatic brain injury identified by CT imaging : a systematic review and meta-analysis

The optimal management of mild traumatic brain injury (TBI) patients with injuries identified by computed tomography (CT) brain scan is unclear. Some guidelines recommend hospital admission for an observation period of at least 24 h. Others argue that selected lower-risk patients can be discharged from the Emergency Department (ED). The objective of our review and meta-analysis was to estimate the risk of death, neurosurgical intervention, and clinical deterioration in mild TBI patients with injuries identified by CT brain scan, and assess which patient factors affect the risk of these outcomes. A systematic review and meta-analysis adhering to PRISMA standards of protocol and reporting were conducted. Study selection was performed by two independent reviewers. Meta-analysis using a random effects model was undertaken to estimate pooled risks for: clinical deterioration, neurosurgical intervention, and death. Meta-regression was used to explore between-study variation in outcome estimates using study population characteristics. Forty-nine primary studies and five reviews were identified that met the inclusion criteria. The estimated pooled risk for the outcomes of interest were: clinical deterioration 11.7% (95% confidence interval [CI]: 11.7%-15.8%), neurosurgical intervention 3.5% (95% CI: 2.2%-4.9%), and death 1.4% (95% CI: 0.8%-2.2%). Twenty-one studies presented within-study estimates of the effect of patient factors. Meta-regression of study characteristics and pooling of within-study estimates of risk factor effect found the following factors significantly affected the risk for adverse outcomes: age, initial Glasgow Coma Scale (GCS), type of injury, and anti-coagulation. The generalizability of many studies was limited due to population selection. Mild TBI patients with injuries identified by CT brain scan have a small but clinically important risk for serious adverse outcomes. This review has identified several prognostic factors; research is needed to derive and validate a usable clinical decision rule so that low-risk patients can be safely discharged from the ED

The burden of traumatic brain injury from low-energy falls among patients from 18 countries in the CENTER-TBI Registry: A comparative cohort study.

BACKGROUND: Traumatic brain injury (TBI) is an important global public health burden, where those injured by high-energy transfer (e.g., road traffic collisions) are assumed to have more severe injury and are prioritised by emergency medical service trauma triage tools. However recent studies suggest an increasing TBI disease burden in older people injured through low-energy falls. We aimed to assess the prevalence of low-energy falls among patients presenting to hospital with TBI, and to compare their characteristics, care pathways, and outcomes to TBI caused by high-energy trauma. METHODS AND FINDINGS: We conducted a comparative cohort study utilising the CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research in TBI) Registry, which recorded patient demographics, injury, care pathway, and acute care outcome data in 56 acute trauma receiving hospitals across 18 countries (17 countries in Europe and Israel). Patients presenting with TBI and indications for computed tomography (CT) brain scan between 2014 to 2018 were purposively sampled. The main study outcomes were (i) the prevalence of low-energy falls causing TBI within the overall cohort and (ii) comparisons of TBI patients injured by low-energy falls to TBI patients injured by high-energy transfer-in terms of demographic and injury characteristics, care pathways, and hospital mortality. In total, 22,782 eligible patients were enrolled, and study outcomes were analysed for 21,681 TBI patients with known injury mechanism; 40% (95% CI 39% to 41%) (8,622/21,681) of patients with TBI were injured by low-energy falls. Compared to 13,059 patients injured by high-energy transfer (HE cohort), the those injured through low-energy falls (LE cohort) were older (LE cohort, median 74 [IQR 56 to 84] years, versus HE cohort, median 42 [IQR 25 to 60] years; p < 0.001), more often female (LE cohort, 50% [95% CI 48% to 51%], versus HE cohort, 32% [95% CI 31% to 34%]; p < 0.001), more frequently taking pre-injury anticoagulants or/and platelet aggregation inhibitors (LE cohort, 44% [95% CI 42% to 45%], versus HE cohort, 13% [95% CI 11% to 14%]; p < 0.001), and less often presenting with moderately or severely impaired conscious level (LE cohort, 7.8% [95% CI 5.6% to 9.8%], versus HE cohort, 10% [95% CI 8.7% to 12%]; p < 0.001), but had similar in-hospital mortality (LE cohort, 6.3% [95% CI 4.2% to 8.3%], versus HE cohort, 7.0% [95% CI 5.3% to 8.6%]; p = 0.83). The CT brain scan traumatic abnormality rate was 3% lower in the LE cohort (LE cohort, 29% [95% CI 27% to 31%], versus HE cohort, 32% [95% CI 31% to 34%]; p < 0.001); individuals in the LE cohort were 50% less likely to receive critical care (LE cohort, 12% [95% CI 9.5% to 13%], versus HE cohort, 24% [95% CI 23% to 26%]; p < 0.001) or emergency interventions (LE cohort, 7.5% [95% CI 5.4% to 9.5%], versus HE cohort, 13% [95% CI 12% to 15%]; p < 0.001) than patients injured by high-energy transfer. The purposive sampling strategy and censorship of patient outcomes beyond hospital discharge are the main study limitations. CONCLUSIONS: We observed that patients sustaining TBI from low-energy falls are an important component of the TBI disease burden and a distinct demographic cohort; further, our findings suggest that energy transfer may not predict intracranial injury or acute care mortality in patients with TBI presenting to hospital. This suggests that factors beyond energy transfer level may be more relevant to prehospital and emergency department TBI triage in older people. A specific focus to improve prevention and care for patients sustaining TBI from low-energy falls is required.CENTER-TBI was supported by the European Union 7th Framework program (EC grant 602150), recipient A.I.R. Maas. Additional funding was obtained from the Hannelore Kohl Stiftung (Germany) - recipient A.I.R. Maas, from OneMind (USA) - recipient A.I.R. Maas and from Integra LifeSciences Corporation (USA) - recipient A.I.R. Maas. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

CT head imaging in patients with head injury who present after 24 h of injury : A retrospective cohort study

Background National Institute for Health and Care Excellence guidelines used to triage patients with head injury to CT imaging are based on research conducted in populations presenting within 24 h of injury. We aim to compare guideline use, and outcomes, in patients with head injury that undergo CT imaging presenting within, and after 24 h of injury. Methods ED trauma CT head scan requests over a period of 6 months were matched to ED records. Case note review of adult patients with head injury that had undergone CT imaging was completed. Logistic regression was used to assess whether presentation after 24 h affected the guideline's ability to predict significant injuries. Results 650 case records were available for analysis. 8.6% (56/650) showed a traumatic abnormality, 1.5% (10/650) required neurosurgery or died. 15.5% (101/ 650) of CT scans were for patients presenting after 24 h. 8.4% (46/549) of those presenting within, and 9.9% (10/101) of those presenting after 24 h had traumatic CT abnormalities. The sensitivity of the guidelines for intracranial injuries was 98% (95% CI 87.0% to 99.9%) in those presenting within 24 h and 70% (95% CI 35.4% to 91.9%) in those presenting after 24 h of injury. The presence of a guideline indication statistically predicted significant injury, and this was unaffected by time of presentation. Conclusions Patients with head injury presenting after 24 h of injury are a clinically significant population. Existing guidelines appear to predict traumatic CT abnormalities irrespective of timing of presentation. However, their sole use in patients presenting after 24 h may result in significant injuries not being identified