Objective: Optimal training methods remain controversial for rarely performed emergency procedures. Previous research has failed to demonstrate the superiority or inferiority of live anesthetized animal models (LAA) as compared to other modalities. Most of the data on LAA use comes from military contexts; less information is available for civilian emergency medicine (EM) training. We sought to characterize the prevalence of LAA use among civilian EM residency programs and reasons for its use or discontinuation. Methods: Survey study of program directors of EM residency programs accredited by the Accreditation Council for Graduate Medical Education. A 16-item questionnaire was electronically delivered to program directors, including program region, current and historical use of LAA, and attitudes regarding the optimal procedural training modalities. Results: Of 179 survey recipients, 83 completed the survey (46.4%). Twelve programs (14.3%) currently use LAA, and 17 programs (20.5%) report previous LAA use. Reasons for discontinuing LAA use included ethical concerns, financial and logistical limitations, political pressures, and feeling that there were superior or equivalent alternative models available. Programs that currently use LAA were more likely to rank LAA as being the most preferable training modality while programs that do not currently use LAA were more likely to rank human cadavers as the most preferable modality. Conclusion Despite a lack of data showing educational outcomes-driven differences between LAA and alternative training models, LAA use is declining among civilian EM residencies. Despite this, disagreement exists among programs that do and do not use LAA regarding the most optimal procedural training.

Objective: Optimal training methods remain controversial for rarely performed emergency procedures. Previous research has failed to demonstrate the superiority or inferiority of live anesthetized animal models (LAA) as compared to other modalities. Most of the data on LAA use comes from military contexts; less information is available for civilian emergency medicine (EM) training. We sought to characterize the prevalence of LAA use among civilian EM residency programs and reasons for its use or discontinuation. Methods: Survey study of program directors of EM residency programs accredited by the Accreditation Council for Graduate Medical Education. A 16-item questionnaire was electronically delivered to program directors, including program region, current and historical use of LAA, and attitudes regarding the optimal procedural training modalities. Results: Of 179 survey recipients, 83 completed the survey (46.4%). Twelve programs (14.3%) currently use LAA, and 17 programs (20.5%) report previous LAA use. Reasons for discontinuing LAA use included ethical concerns, financial and logistical limitations, political pressures, and feeling that there were superior or equivalent alternative models available. Programs that currently use LAA were more likely to rank LAA as being the most preferable training modality while programs that do not currently use LAA were more likely to rank human cadavers as the most preferable modality. Conclusion Despite a lack of data showing educational outcomes-driven differences between LAA and alternative training models, LAA use is declining among civilian EM residencies. Despite this, disagreement exists among programs that do and do not use LAA regarding the most optimal procedural training.

Objective: Electrocardiogram (ECG) interpretation skills are of critical importance for diagnostic accuracy and patient safety. In our emergency department (ED), senior third-year emergency medicine residents (EM3s) are the initial interpreters of all ED ECGs. While this is an integral part of emergency medicine education, the accuracy of ECG interpretation is unknown. We aimed to review the adverse quality assurance (QA) events associated with ECG interpretation by EM3s. Methods: We conducted a retrospective study of all ED ECGs performed between October 2015 and October 2018, which were read primarily by EM3s, at an urban tertiary care medical center treating 56,000 patients per year. All cases referred to the ED QA committee during this time were reviewed. Cases involving a perceived error were referred to a 20-member committee of ED leadership staff, attendings, residents, and nurses for further consensus review. Ninety-five percent confidence intervals (CIs) were calculated. Results: EM3s read 92,928 ECGs during the study period. Of the 3,983 total ED QA cases reviewed, errors were identified in 268 (6.7%; 95% CI, 6.0%–7.6%). Four of the 268 errors involved ECG misinterpretation or failure to act on an ECG abnormality by a resident (1.5%; 95% CI, 0.0%–2.9%). Conclusion A small percentage of the cases referred to the QA committee were a result of EM3 misinterpretation of ECGs. The majority of emergency medicine residencies do not include the senior resident as a primary interpreter of ECGs. These findings support the use of EM3s as initial ED ECG interpreters to increase their clinical exposure.

BACKGROUND AND PURPOSE: The purpose of this study was to estimate the incidence and prevalence of epilepsy among an elderly and poor population in the United States. METHODS: Arizona Medicaid claims data from January 1, 2008 to December 31, 2010 were used for this analysis. Subjects who were aged > or =65 years and were continuously enrolled in any Arizona Medicaid health plans (eligible to patients with low income) for > or =12 months between January 1, 2008 and December 31, 2009 were considered eligible for inclusion in the study cohort. In addition to meeting the aforementioned criteria, incident and prevalent cases must have had epilepsy-related healthcare claims. Furthermore, incident cases were required to have a 1-year "clean" period immediately preceding the index date. Negative binomial and logistic regression models were used to assess the factors associated with epilepsy incidence and prevalence. RESULTS: The estimated epilepsy incidence and prevalence for this population in 2009 were 7.9 and 19.3 per 1,000 person-years, respectively. The incidence and prevalence rates were significantly higher for patients with comorbid conditions that were potential risk factors for epilepsy and were of younger age than for their non-comorbid and older counterparts (p<0.05). The prevalence rates were significantly higher for non-Hispanic Blacks and male beneficiaries than for non-Hispanic Whites and female beneficiaries, respectively (p<0.05). CONCLUSIONS: This patient population had higher epilepsy incidence and prevalence compared with the general US population. These differences may be at least in part attributable to their low socioeconomic status.
African Continental Ancestry Group ; Aged* ; Arizona ; Cohort Studies ; Delivery of Health Care ; Epilepsy* ; Female ; Humans ; Incidence* ; Logistic Models ; Male ; Medicaid ; Poverty* ; Prevalence* ; Risk Factors ; Social Class ; United States*

Objective: Patients with severe symptomatic aortic stenosis are assessed for coronary artery disease (CAD) prior to transcatheter aortic valve implantation (TAVI) with treatment implications. Invasive coronary angiography (ICA) is the recommended modality but is associated with peri-procedural complications. Integrating machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) into existing TAVI-planning CT protocol may aid exclusion of significant CAD and thus avoiding ICA in selected patients. Materials and Methods: A single-center, retrospective study was conducted, 41 TAVI candidates with both TAVI-planning CT and ICA performed were analyzed. CT datasets were evaluated by a ML-based CT-FFR software. Beta-blocker and nitroglycerin were not administered in these patients. The primary outcome was to identify significant CAD. The diagnostic performance of CT-FFR was compared against ICA. Results: On per-patient level, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy were 89%, 94%, 80%, 97% and 93%, respectively. On per-vessel level, the sensitivity, specificity, PPV, NPV and diagnostic accuracy were 75%, 94%, 67%, 96% and 92%, respectively. The area under the receiver operative characteristics curve per individual coronary vessels yielded overall 0.90 (95% confidence interval 85%–95%). ICA may be avoided in up to 80% of patients if CT-FFR results were negative. Conclusion ML-based CT-FFR can provide accurate screening capabilities for significant CAD thus avoiding ICA. Its integration to existing TAVI-planning CT is feasible with the potential of improving the safety and efficiency of pre-TAVI CAD assessment.