Neurologic Emergencies Presenting as Trauma Activations to an Urban Level I Trauma Center.

BACKGROUND: It is speculated that there is overlap between neurologic emergencies and trauma, yet to date there has not been a study looking at the prevalence of neurologic emergencies amongst trauma activations. OBJECTIVES: We sought to determine the prevalence of neurologic emergencies in patients presenting to a level I trauma center as trauma team activations (TTAs). We explored a subset of acute ischemic stroke patients to determine delays in management. METHODS: This was a retrospective review of trauma registry data capturing all TTAs at a level I trauma and stroke center from 2011 to 2016. Neurologic emergencies were defined as ischemic stroke, intracerebral hemorrhage, subarachnoid hemorrhage, or status epilepticus. Among patients diagnosed with acute ischemic strokes, we compared stroke metrics with hospital stroke data during the same period. RESULTS: There were 18,859 trauma activations during the study period, of which 117 (0.6%) had a neurologic emergency. There were 52 patients with ischemic stroke (45%), 39 with intracerebral hemorrhage (34%), 15 with subarachnoid hemorrhage (13%), and 10 with status epilepticus (9%). Among the 52 patients with ischemic stroke, 20 (38%) received intravenous thrombolysis. The median time to computed tomography scan was 23 min and the median time to thrombolysis (tissue plasminogen activator) was 60 min. When compared with non-TTA patients during the same time period, both median time to computed tomography scan and time to tissue plasminogen activator were similar (p = 0.16 and p = 0.6, respectively). CONCLUSIONS: Neurologic emergencies, though relatively uncommon, do exist among TTAs. Despite the TTA, eligible patients met the benchmarks for acute stroke care delivery.

Automatic Hip Fracture Identification and Functional Subclassification with Deep Learning.

PURPOSE: To investigate the feasibility of automatic identification and classification of hip fractures using deep learning, which may improve outcomes by reducing diagnostic errors and decreasing time to operation. MATERIALS AND METHODS: Hip and pelvic radiographs from 1118 studies were reviewed, and 3026 hips were labeled via bounding boxes and classified as normal, displaced femoral neck fracture, nondisplaced femoral neck fracture, intertrochanteric fracture, previous open reduction and internal fixation, or previous arthroplasty. A deep learning-based object detection model was trained to automate the placement of the bounding boxes. A Densely Connected Convolutional Neural Network (or DenseNet) was trained on a subset of the bounding box images, and its performance was evaluated on a held-out test set and by comparison on a 100-image subset with two groups of human observers: fellowship-trained radiologists and orthopedists; senior residents in emergency medicine, radiology, and orthopedics. RESULTS: The binary accuracy for detecting a fracture of this model was 93.7% (95% confidence interval [CI]: 90.8%, 96.5%), with a sensitivity of 93.2% (95% CI: 88.9%, 97.1%) and a specificity of 94.2% (95% CI: 89.7%, 98.4%). Multiclass classification accuracy was 90.8% (95% CI: 87.5%, 94.2%). When compared with the accuracy of human observers, the accuracy of the model achieved an expert-level classification, at the very least, under all conditions. Additionally, when the model was used as an aid, human performance improved, with aided resident performance approximating unaided fellowship-trained expert performance in the multiclass classification. CONCLUSION: A deep learning model identified and classified hip fractures with expert-level performance, at the very least, and when used as an aid, improved human performance, with aided resident performance approximating that of unaided fellowship-trained attending physicians.Supplemental material is available for this article.© RSNA, 2020.

The Incidence and Outcome Differences in Severe Sepsis with and without Lactic Acidosis.

INTRODUCTION: To compare the incidence, characteristics, and outcomes of lactate expressors and nonexpressors in patients with severe sepsis and septic shock. METHODS: This is a retrospective cohort study of patients with severe sepsis and septic shock who presented over a 40-month period to an academic tertiary care center. Primary outcome of interest was in-hospital mortality. Secondary outcomes were hospital length of stay (LOS), Intensive Care Unit (ICU) LOS, and escalation of care. RESULTS: Three hundred and thirty-eight patients met inclusion criteria and were divided into a lactate expressor group (n = 197; initial lactate ≥2.5 mmol/L) and a nonexpressor group (n = 141; lactate <2.5 mmol/L). The mortality rate was 46.2% for lactate expressors and 24.8% for nonexpressors. There were no significant differences in hospital or ICU LOS. The escalation-of-care rate in the severe sepsis nonexpressor group was more than double that found in the expressor group: 16.5% versus 6.2% (P = 0.040). The two groups had baseline differences: expressor group had a higher median Acute Physiology and Chronic Health Evaluation II (APACHE II) illness severity score, and nonexpressors had an increased prevalence of comorbid conditions. APACHE II score (odds ratio [OR] 1.10 (1.07-1.14), P < 0.001) and being in the expressor group (OR 1.72 [1.03-2.89], P = 0.039) increased the odds of mortality. CONCLUSIONS: In patients with severe sepsis and septic shock, lactate nonexpressors are common. Although the mortality in this cohort is less than its counterparts who present with lactate elevation, it is still significant which warrants vigilance in their care.

Outcomes of severe sepsis and septic shock patients after stratification by initial lactate value.

BACKGROUND: In the setting of severe sepsis and septic shock, mortality increases when lactate levels are ≥ 4 mmol/L. However, the consequences of lower lactate levels in this population are not well understood. The study aimed to determine the in-hospital mortality associated with severe sepsis and septic shock when initial lactate levels are < 4 mmol/L. METHODS: This is a retrospective cohort study of septic patients admitted over a 40-month period. Totally 338 patients were divided into three groups based on initial lactate values. Group 1 had lactate levels < 2 mmol/L; group 2: 2-4 mmol/L; and group 3: ≥ 4 mmol/L. The primary outcome was in-hospital mortality. RESULTS: There were 111 patients in group 1, 96 patients in group 2, and 131 in group 3. The mortality rates were 21.6%, 35.4%, and 51.9% respectively. Univariate analysis revealed the mortality differences to be statistically significant. Multivariate logistic regression demonstrated higher odds of death with higher lactate tier group, however the findings did not reach statistical significance. CONCLUSION: This study found that only assignment to group 3, initial lactic acid level of ≥ 4 mmol/L, was independently associated with increased mortality after correcting for underlying severity of illness and organ dysfunction. However, rising lactate levels in the other two groups were associated with increased severity of illness and were inversely proportional to prognosis.

Prospective randomized trial of insulin glargine in acute management of diabetic ketoacidosis in the emergency department: a pilot study.

OBJECTIVES: The objective was to determine the efficacy of coadministration of subcutaneous (SQ) insulin glargine in combination with intravenous (IV) insulin for treating diabetic ketoacidosis (DKA). METHODS: This was a prospective, randomized, controlled trial comparing coadministration of insulin glargine and IV insulin (experimental) with IV insulin (standard care control). The setting was emergency departments (EDs) in two hospitals in Houston, Texas. Patients presenting with blood sugar ≥ 200 mg/dL, pH ≤ 7.3, bicarbonate (HCO3 ) ≤ 18 mg/dL, ketonemia or ketonuria, and anion gap ≥ 16 between November 2012 and April 2013 were enrolled. All patients received IV insulin. Additionally, the experimental group was given SQ insulin glargine within 2 hours of diagnosis. Upon closure of anion gap, patients in the control group were subsequently transitioned to long-acting insulin. In the study group, IV insulin was discontinued and long-acting SQ insulin was reinstituted 24 hours after initial introduction. The primary outcome of time to closure of anion gap (TCAG) was compared between groups using a general linear model (GLM), adjusting for initial anion gap, etiology, and presence of comorbidities. Similarly, the secondary outcome hospital length of stay (LOS) was adjusted for age, etiology, and hospital site in the GLM. Rate of hypoglycemia and intensive care unit (ICU) admission was compared using Fisher's exact test while ICU LOS was compared using Wilcoxon's two-sample test. RESULTS: A total of 40 patients were enrolled in this pilot trial. The estimated mean TCAG was 10.2 hours (SE ± 6.8 hours) in the experimental group and 11.6 hours (SE ± 6.4 hours) in the control group (p = 0.63). The estimated mean hospital LOS was 3.9 days (SE ± 3.4 days) in the experimental group and 4.8 days (SE ± 3.6 days) in the control group (p = 0.66). Incidents of hypoglycemia, rates of ICU admission, and ICU LOS were similar between the groups. CONCLUSIONS: Coadministration of glargine in combination with an insulin infusion in the acute management of DKA is feasible. Further study is needed to determine the true efficacy in terms of TCAG and hospital LOS.

Voluntary Medical Incident Reporting Tool to Improve Physician Reporting of Medical Errors in an Emergency Department.

INTRODUCTION: Medical errors are frequently under-reported, yet their appropriate analysis, coupled with remediation, is essential for continuous quality improvement. The emergency department (ED) is recognized as a complex and chaotic environment prone to errors. In this paper, we describe the design and implementation of a web-based ED-specific incident reporting system using an iterative process. METHODS: A web-based, password-protected tool was developed by members of a quality assurance committee for ED providers to report incidents that they believe could impact patient safety. RESULTS: The utilization of this system in one residency program with two academic sites resulted in an increase from 81 reported incidents in 2009, the first year of use, to 561 reported incidents in 2012. This is an increase in rate of reported events from 0.07% of all ED visits to 0.44% of all ED visits. In 2012, faculty reported 60% of all incidents, while residents and midlevel providers reported 24% and 16% respectively. The most commonly reported incidents were delays in care and management concerns. CONCLUSION: Error reporting frequency can be dramatically improved by using a web-based, user-friendly, voluntary, and non-punitive reporting system.