Retrospective Comparison of Upper and Lower Extremity Intraosseous Access During Out-of-Hospital Cardiac Arrest Resuscitation.

OBJECTIVE: Intraosseous (IO) access is frequently utilized during the resuscitation of out-of-hospital cardiac arrest (OHCA) patients. Due to proximity to the heart and differential flow rates, the anatomical site of IO access may impact patient outcomes. Using a large dataset, we aimed to compare the outcomes of OHCA patients who received upper or lower extremity IO access during resuscitation. METHODS: The ESO Data Collaborative public use research datasets were used for this retrospective study. All adult (≥18 years of age) OHCA patients with successful IO access in an upper or lower extremity were evaluated for inclusion. Patients were excluded if they had intravenous (IV) access prior to IO access, or if they had a Do Not Resuscitate order documented. Our primary outcome was return of spontaneous circulation (ROSC). Secondary outcomes included survival to discharge and survival to discharge to home. Mixed-effects multivariable logistic regression models adjusted for age, sex, etiology, witnessed status, pre-first responder cardiopulmonary resuscitation (CPR), initial electrocardiogram (ECG) rhythm, location [private/residential, public, or assisted living/institutional], and response time in addition to the primary airway management strategy (endotracheal intubation, supraglottic device, surgical airway, no advanced airway) were used to compare the outcomes of patients with upper extremity IO access to the outcomes of patients with lower extremity IO access. RESULTS: After application of exclusion criteria, 155,884 patients who received IO access during resuscitation remained (76% lower extremity, 24% upper extremity). Upper extremity IO access was associated with greater adjusted odds of ROSC (1.11 [1.08, 1.15]), and this finding was consistent across multiple patient subgroups. Secondary analyses suggested that upper extremity access was associated with increased survival to discharge (1.18 [1.00, 1.39]) and survival to discharge to home (1.23 [1.02, 1.48]) in comparison to lower extremity IO access. CONCLUSION: In this large prehospital dataset, upper extremity IO access was associated with a small increase in the odds of ROSC in comparison to lower extremity IO access. These data support the need for prospective investigation of the ideal IO access site during OHCA resuscitation.

A Novel Algorithm for Improving the Prehospital Diagnostic Accuracy of ST-Segment Elevation Myocardial Infarction.

INTRODUCTION: Early detection of ST-segment elevation myocardial infarction (STEMI) on the prehospital electrocardiogram (ECG) improves patient outcomes. Current software algorithms optimize sensitivity but have a high false-positive rate. The authors propose an algorithm to improve the specificity of STEMI diagnosis in the prehospital setting. METHODS: A dataset of prehospital ECGs with verified outcomes was used to validate an algorithm to identify true and false-positive software interpretations of STEMI. Four criteria implicated in prior research to differentiate STEMI true positives were applied: heart rate <130, QRS <100, verification of ST-segment elevation, and absence of artifact. The test characteristics were calculated and regression analysis was used to examine the association between the number of criteria included and test characteristics. RESULTS: There were 44,611 cases available. Of these, 1,193 were identified as STEMI by the software interpretation. Applying all four criteria had the highest positive likelihood ratio of 353 (95% CI, 201-595) and specificity of 99.96% (95% CI, 99.93-99.98), but the lowest sensitivity (14%; 95% CI, 11-17) and worst negative likelihood ratio (0.86; 95% CI, 0.84-0.89). There was a strong correlation between increased positive likelihood ratio (r2 = 0.90) and specificity (r2 = 0.85) with increasing number of criteria. CONCLUSIONS: Prehospital ECGs with a high probability of true STEMI can be accurately identified using these four criteria: heart rate <130, QRS <100, verification of ST-segment elevation, and absence of artifact. Applying these criteria to prehospital ECGs with software interpretations of STEMI could decrease false-positive field activations, while also reducing the need to rely on transmission for physician over-read. This can have significant clinical and quality implications for Emergency Medical Services (EMS) systems.

A Novel Algorithm for Improving the Diagnostic Accuracy of Prehospital ST-Elevation Myocardial Infarction.

INTRODUCTION: ST-segment elevation myocardial infarction (STEMI) is a time-sensitive entity that has been shown to benefit from prehospital diagnosis by electrocardiogram (ECG). Current computer algorithms with binary decision making are not accurate enough to be relied on for cardiac catheterization lab (CCL) activation. HYPOTHESIS: An algorithmic approach is proposed to stratify binary STEMI computerized ECG interpretations into low, intermediate, and high STEMI probability tiers. METHODS: Based on previous literature, a four-criteria algorithm was developed to rule out/in common causes of prehospital STEMI false-positive computer interpretations: heart rate, QRS width, ST elevation criteria, and artifact. Prehospital STEMI cases were prospectively collected at a single academic center in Salt Lake City, Utah (USA) from May 2012 through October 2013. The prehospital ECGs were applied to the algorithm and compared against activation of the CCL by an emergency department (ED) physician as the outcome of interest. In addition to calculating test characteristics, linear regression was used to look for an association between number of criteria used and accuracy, and logistic regression was used to test if any single criterion performed better than another. RESULTS: There were 63 ECGs available for review, 39 high probability and 24 intermediate probability. The high probability STEMI tier had excellent test characteristics for ruling in STEMI when all four criteria were used, specificity 1.00 (95% CI, 0.59-1.00), positive predictive value 1.00 (0.91-1.00). Linear regression showed a strong correlation demonstrating that false-positives increased as fewer criteria were used (adjusted r-square 0.51; P <.01). Logistic regression showed no significant predictive value for any one criterion over another (P = .80). Limiting physician overread to the intermediate tier only would reduce the number of ECGs requiring physician overread by a factor of 0.62 (95% CI, 0.48-0.75; P <.01). CONCLUSION: Prehospital STEMI ECGs can be accurately stratified to high, intermediate, and low probabilities for STEMI using the four criteria. While additional study is required, using this tiered algorithmic approach in prehospital ECGs could lead to changes in CCL activation and decreased requirements for physician overread. This may have significant clinical and quality implications.

Hacking 9-1-1: Infrastructure Vulnerabilities and Attack Vectors.

9-1-1 call centers are a critical component of prehospital care: they accept emergency calls, dispatch field responders such as emergency medical services, and provide callers with emergency medical instructions before their arrival. The aim of this study was to describe the technical structure of the 9-1-1 call-taking system and to describe its vulnerabilities that could lead to compromised patient care. 9-1-1 calls answered from mobile phones and landlines use a variety of technologies to provide information about caller location and other information. These interconnected technologies create potential cyber vulnerabilities. A variety of attacks could be carried out on 9-1-1 infrastructure to various ends. Attackers could target individuals, groups, or entire municipalities. These attacks could result in anything from a nuisance to increased loss of life in a physical attack to worse overall outcomes owing to delays in care for time-sensitive conditions. Evolving 9-1-1 systems are increasingly connected and dependent on network technology. As implications of cybersecurity vulnerabilities loom large, future research should examine methods of hardening the 9-1-1 system against attack.

An Urban 9-1-1 System's Experience with Left Ventricular Assist Device Patients.

Background: Left ventricular assist devices (LVADs) are used with increasing frequency and left in place for longer periods of time. Prior publications have focused on the mechanics of troubleshooting the device itself. We aim to describe the epidemiology of LVAD patient presentations to emergency medical services (EMS), prehospital assessments and interventions, and hospital outcomes. Methods: This is a retrospective chart review of known LVAD patients that belong to a single academic center's heart failure program who activated the 9-1-1 system and were transported by an urban EMS system to one of the center's 2 emergency departments between January 2012 and December 2015. Identifying demographics were used to query the electronic medical record of the responding city fire agency and contracted transporting ambulance service. Two reviewers abstracted prehospital chief complaint, vital signs, assessments, and interventions. Emergency department and hospital outcomes were retrieved separately. Results: From January 2012 to December 2015, 15 LVAD patients were transported 16 times. The most common prehospital chief complaint was weakness (7/16), followed by chest pain (3/16). Of the 7 patients presenting with weakness, one was diagnosed with a stroke in the emergency department. Another patient was diagnosed with subarachnoid hemorrhage and expired during hospital admission. This was the only death in the cohort. The most common hospital diagnosis was GI bleed (3/16). The overall admission rate was 87.5% (14/16). Conclusions: EMS interactions with LVAD patients are infrequent but have high rates of admission and incidence of life-threatening diagnoses. The most common prehospital presenting symptoms were weakness and chest pain, and most prehospital interactions did not require LVAD-specific interventions. In addition to acquiring technical knowledge regarding LVADs, EMS providers should be aware of non-device-related complications including intracranial and GI bleeding and take this into account during their assessment.

A model for predicting emergency physician opinion of electrocardiogram tracing data quality.

BACKGROUND: Limited work has established an objective measure of ECG quality that correlates with physician opinion of the study. We seek to establish a threshold of acceptable ECG data quality for the purpose of ruling out STEMI derived from emergency physician opinion. METHODS: A panel of three emergency physicians rated 240 12-Lead ECGs as being acceptable or unacceptable data quality. Each lead of the ECG had the following measurements recorded: baseline wander, QRS signal amplitude, and artifact amplitude. A lasso regression technique was used to create the model. RESULTS: The area under the curve for the model using all 36 elements is 1.0, indicating a perfect fit. A simplified model using 22 terms has an area under the curve of 0.994. CONCLUSIONS: This study demonstrated that emergency physician opinion of ECG quality for the purpose of ruling out STEMI can be predicted through a regression model.

Prehospital Acute ST-Elevation Myocardial Infarction Identification in San Diego: A Retrospective Analysis of the Effect of a New Software Algorithm.

BACKGROUND: A significant increase in false positive ST-elevation myocardial infarction (STEMI) electrocardiogram interpretations was noted after replacement of all of the City of San Diego's 110 monitor-defibrillator units with a new brand. These concerns were brought to the manufacturer and a revised interpretive algorithm was implemented. OBJECTIVES: This study evaluated the effects of a revised interpretation algorithm to identify STEMI when used by San Diego paramedics. METHODS: Data were reviewed 6 months before and 6 months after the introduction of a revised interpretation algorithm. True-positive and false-positive interpretations were identified. Factors contributing to an incorrect interpretation were assessed and patient demographics were collected. RESULTS: A total of 372 (234 preimplementation, 138 postimplementation) cases met inclusion criteria. There was a significant reduction in false positive STEMI (150 preimplementation, 40 postimplementation; p < 0.001) after implementation. The most common factors resulting in false positive before implementation were right bundle branch block, left bundle branch block, and atrial fibrillation. The new algorithm corrected for these misinterpretations with most postimplementation false positives attributed to benign early repolarization and poor data quality. Subsequent follow-up at 10 months showed maintenance of the observed reduction in false positives. CONCLUSIONS: This study shows that introducing a revised 12-lead interpretive algorithm resulted in a significant reduction in the number of false positive STEMI electrocardiogram interpretations in a large urban emergency medical services system. Rigorous testing and standardization of new interpretative software is recommended before introduction into a clinical setting to prevent issues resulting from inappropriate cardiac catheterization laboratory activations.

Emergency department visits among patients with left ventricular assist devices.

Continuous-flow left ventricular assist devices (LVADs) are increasingly implanted to support patients with end-stage heart failure. These patients are at high risk for complications, many of which necessitate emergency care. While rehospitalization rates have been described, there is little data regarding emergency department (ED) visits. We hypothesize that ED visits are frequent and often require admission after LVAD implantation. We performed a retrospective review of patients in our health-care system followed by the advanced heart failure service for LVAD management after implantation between January 2011 and July 2015. We accounted for all ED visits in our system through February 2016, 7 months after the last implantation included. Clinically relevant demographic variables and ED visit details were recorded and analyzed to describe this population. We identified 81 patients with complete data, among whom there were 283 visits (3.49 visits/patient), occurring at a rate of approximately 7.3 ED visits per patient per year alive with LVAD. The most common reason for an ED visit is a complication related to bleeding (18% of visits), followed by chest pain (14%) and dizziness or syncope (13%). Thirty-six percent of patients were discharged from the ED without hospital admission. A growing populace with implanted LVADs represents an important population within emergency medicine. They are at risk for significant complications and frequently present to the ED. While many of these visits may be managed without hospital admission, this specialized patient group represents a potential area for improvement in provider education.