Point-of-care ultrasound may expedite diagnosis and revascularization of occult occlusive myocardial infarction

Missing occlusions: Quality gaps for ED patients with occlusion MI

BACKGROUND

ST-elevation Myocardial Infarction (STEMI) guidelines encourage monitoring of false positives (Code STEMI without culprit) but ignore false negatives (non-STEMI with occlusion myocardial infarction [OMI]). We evaluated the hospital course of emergency department (ED) patients with acute coronary syndrome (ACS) using STEMI vs OMI paradigms.

METHODS

This retrospective chart review examined all ACS patients admitted through two academic EDs, from June 2021 to May 2022, categorized as 1) OMI (acute culprit lesion with TIMI 0-2 flow, or acute culprit lesion with TIMI 3 flow and peak troponin I >10,000 ng/L; or, if no angiogram, peak troponin >10,000 ng/L with new regional wall motion abnormality), 2) NOMI (Non-OMI, i.e. MI without OMI) or 3) MIRO (MI ruled out: no troponin elevation). Patients were stratified by admission for STEMI. Initial ECGs were reviewed for automated interpretation of "STEMI", and admission/discharge diagnoses were compared.

RESULTS

Among 382 patients, there were 141 OMIs, 181 NOMIs, and 60 MIROs. Only 40.4% of OMIs were admitted as STEMI: 60.0% had "STEMI" on ECG, and median door-to-cath time was 103 min (IQR 71-149). But 59.6% of OMIs were not admitted as STEMI: 1.3% had "STEMI" on ECG (p < 0.001) and median door-to-cath time was 1712 min (IQR 1043-3960; p < 0.001). While 13.9% of STEMIs were false positive and had a different discharge diagnosis, 32.0% of Non-STEMIs had OMI but were still discharged as "Non-STEMI."

CONCLUSIONS

STEMI criteria miss a majority of OMI, and discharge diagnoses highlight false positive STEMI but never false negative STEMI. The OMI paradigm reveals quality gaps and opportunities for improvement.

Minutes matter: Time it takes to perform point-of-care ultrasound

Background

While point-of-care ultrasound (PoCUS) is a safe, versatile tool that can improve patient care, the perceived time investment needed to incorporate PoCUS into clinical care is cited as a barrier to performance. We sought to determine the time it takes to perform a PoCUS examination and whether this time was influenced by training level and prior ultrasound experience.

Methods

This was a retrospective study looking at time stamps of all emergency medicine (EM) provider-performed PoCUS examinations during clinical shifts from August 10, 2019, to June 7, 2022, at a suburban academic emergency department that is the site for a 3-year EM residency. Our workflow is order-based; when PoCUS is ordered, that patient's information populates the ultrasound machine worklist. Selecting the patient's name from the worklist generates a time-stamped patient information page (PIP). We defined the PIP time stamp as the start of the PoCUS examination. The duration of one PoCUS examination was defined as the time of the last image acquired minus the time of the PIP. General estimating equations were used to estimate differences between training level and between prior scan status using an exchangeable correlation and Tukey adjusted pairwise comparisons. A two-tailed chi-square analysis was used for comparing accuracy according to training level.

Results

Of 4187 PoCUS examinations abstracted, 2144 met study criteria. The median (IQR) time spent per examination was 6.0 (3-9) min. First-year residents took the longest to perform PoCUS among all providers (p < 0.0001). Residents with fewer than 250 prior scans took longer than residents with 501-800 (p = 0.0002) and >800 (p = 0.0013). Resident accuracy was not significantly different according to training level.

Conclusions

Overall median time to perform PoCUS was 6.0 min. EM residents became more efficient in performing PoCUS as they advanced from first- to third-year, without compromising accuracy.

The 2023 Core Content of advanced emergency medicine ultrasonography

In February 2023, the American Board of Emergency Medicine (ABEM) approved modifications to the Advanced Emergency Medicine Ultrasonography (AEMUS) Core Content, which defines the areas of knowledge considered essential for the practice of AEMUS. This manuscript serves as a revision of the AEMUS Core Content originally published in 2014. The revision of the Core Content for AEMUS training aims to establish standardized education and qualifications necessary for AEMUS fellowship program leadership, clinical application, administration, quality improvement, and research. The Core Content provides the organizational framework and serves as the basis for the development of content for the Focused Practice Examination (FPE) administered by ABEM. AEMUS fellowship directors may reference the Core Content when designing AEMUS fellowship curricula to help prepare graduates for the autonomous practice of AEMUS and the FPE. In this article, an updated revision of the previously published AEMUS Core Content is detailed, and the entire development of the Core Content is presented.

FOCUS accurately detects wall motion abnormalities in patients with ACS, A retrospective study

BACKGROUND

Chest pain is a common presentation to the Emergency Department (ED) with roughly 6 million visits a year. The primary diagnostic modality for the identification of acute coronary syndrome (ACS) is the electrocardiogram (ECG), which is used to screen for electrocardiographic findings representing acute coronary occlusion. It is known that the ischemia generated by an acutely occluded coronary vessel generates a wall motion abnormality which can be visualized by echocardiogram; however, emergency physician-performed focused cardiac ultrasound (FOCUS) currently does not have a formal role in the diagnosis of OMI within the emergency department.

PURPOSE

We sought to define the characteristics of FOCUS performed by emergency physicians of variable training levels in the identification of RWMA in patients presenting to the emergency department with high suspicion for ACS before undergoing cardiac catheterization or formal echocardiography. We also explored whether RWMA was associated with OMI in these patients.

METHODS

We performed a structured, retrospective review of adult patients presenting to a large, academic, tertiary care center with suspected ACS from July 1st, 2019, and October 24th, 2020. Patients were included if they underwent FOCUS in the ED during the time-period above for suspected ACS looking for RWMA and FOCUS images were stored and reviewable in our middleware software. The primary outcome was the accuracy, sensitivity, and specificity of FOCUS compared to formal echocardiography for the detection of RWMA. Secondary outcomes were sensitivity of FOCUS compared to formal echocardiography for detection of RWMA in patients with and without cardiac catheterization proven OMI and sensitivity and specificity of FOCUS operators based on training.

RESULTS

FOCUS for RWMA performed by emergency physicians had a sensitivity of 94% (95% CI, 82-98), specificity 35% (95% CI, 15-61), and overall accuracy of 78% (95% CI, 66-87). Of all subjects, 82% underwent urgent or emergency coronary angiography, of which 71% had OMI at the time of coronary angiography of the procedure. FOCUS identified RWMA in 87% of patients with coronary angiography proven OMI. Residents (PGY-1 - PGY-3) (n = 31) were able to detect RWMA with a sensitivity of 86% (95% CI, 64-96), a specificity of 56% (95% CI, 23-85%), and an accuracy of 77 (95% CI, 58-90%). Emergency ultrasound fellows and attendings (n = 34) were able to detect RWMA with a sensitivity of 85% (95% CI, 64-95%), a specificity of 75% (95% CI, 36-96%), and an accuracy of 82% (95% CI, 65-93%).

CONCLUSIONS

Our retrospective study concludes FOCUS performed by emergency physicians may be used to detect RWMA in patients with high concern for acute coronary syndrome. This may have its greatest utility in patients presenting without STEMI where the ECG is felt to be equivocal, but the clinician has high concern for OMI, in which the presence of RWMA might result in emergent cath lab activation, though this requires further study. The presence of RWMA in such cases may help to rule in OMI as a cause; however, the absence of RWMA should exclude OMI. Further research is necessary to confirm these findings.

Kenichi Harumi Plenary Address at Annual Meeting of the International Society of Computers in Electrocardiology: "What Should ECG Deep Learning Focus on? The diagnosis of acute coronary occlusion!"

According to the STEMI paradigm, only patients whose ECGs meet STEMI criteria require immediate reperfusion. This leads to reperfusion delays and significantly increases the mortality for the quarter of "non-STEMI" patients with totally occluded arteries. The Occlusion MI (OMI) paradigm has developed advanced ECG interpretation to identify this high-risk group, including examining the ECG in totality and assessing ST/T changes in proportion to the QRS. If neural networks are only developed based on STEMI databases and to identify STEMI criteria, they will simply reinforce a failed paradigm. But if deep learning is trained to identify OMI it could revolutionize patient care. This article reviews the paradigm shift from STEMI and OMI, and examines the potential and pitfalls of deep learning. This is based on the Kenichi Harumi Plenary Address at the Annual Meeting of the International Society of Computers in Electrocardiology, given by OMI expert Dr. Stephen Smith.