Deploying a novel custom mobile application for STEMI activation and transfer in a large healthcare system to improve cross-team workflow. STEMIcathAID implementation project.

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) is a high-risk patient medical emergency. We developed a secure mobile application, STEMIcathAID, to optimize care for STEMI patients by providing a digital platform for communication between the STEMI care team members, EKG transmission, cardiac catherization laboratory (cath lab) activation and ambulance tracking. The aim of this report is to describe the implementation of the app into the current STEMI workflow in preparation for a pilot project employing the app for inter-hospital STEMI transfer. APPROACH: App deployment involved key leadership stakeholders from all multidisciplinary teams taking care of STEMI patients. The team developed a transition plan addressing all aspects of the health system improvement process including the workflow analysis and redesign, app installation, personnel training including user account access to the app, and development of a quality assurance program for progress evaluation. The pilot will go live in the Emergency Department (ED) of one of the hospitals within the Mount Sinai Hospital System (MSHS) during the daytime weekday hours at the beginning and extending to 24/7 schedule over 4-6 weeks. For the duration of the pilot, ED personnel will combine the STEMIcathAID app activation with previous established STEMI activation processes through the MSHS Clinical Command Center (CCC) to ensure efficient and reliable response to a STEMI alert. More than 250 people were provisioned app accounts including ED Physicians and frontline nurses, and trained on their user-specific roles and responsibilities and scheduled in the app. The team will be provided with a feedback form that is discipline specific to complete after every STEMI case in order to collect information on user experience with the STEMIcathAID app functionality. The form will also provide quantitative metrics for the key time sensitive steps in STEMI care. CONCLUSIONS: We developed a uniform approach for deployment of a mobile application for STEMI activation and transfer in a large urban healthcare system to optimize the clinical workflow in STEMI care. The results of the pilot will demonstrate whether the app has a significant impact on the quality of care for transfer of STEMI patients.

ST-segment elevation myocardial infarction in a 37-year-old man with normal coronaries--it is not always cocaine!

Heart disease is one of the leading causes of death in the United States. With the increase in substance abuse, the incidence of acute myocardial infarction (MI) in younger population has been on the rise. Traditionally, cocaine has been blamed for acute MI; however, recently, there have been more incidences of marijuana as an inciting factor. We present a case of marijuana-induced acute MI and discuss the proposed mechanism.

Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram.

OBJECTIVES: This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population. BACKGROUND: Rapid evaluation of left and right ventricular function using deep learning (DL) on electrocardiograms (ECGs) can assist diagnostic workflow. However, DL tools to estimate right ventricular (RV) function do not exist, whereas those to estimate left ventricular (LV) function are restricted to quantification of very low LV function only. METHODS: A multicenter study was conducted with data from 5 New York City hospitals: 4 for internal testing and 1 serving as external validation. We created novel DL models to classify left ventricular ejection fraction (LVEF) into categories derived from the latest universal definition of heart failure, estimate LVEF through regression, and predict a composite outcome of either RV systolic dysfunction or RV dilation. RESULTS: We obtained echocardiogram LVEF estimates for 147,636 patients paired to 715,890 ECGs. We used natural language processing (NLP) to extract RV size and systolic function information from 404,502 echocardiogram reports paired to 761,510 ECGs for 148,227 patients. For LVEF classification in internal testing, area under curve (AUC) at detection of LVEF ≤40%, 40% < LVEF ≤50%, and LVEF >50% was 0.94 (95% CI: 0.94-0.94), 0.82 (95% CI: 0.81-0.83), and 0.89 (95% CI: 0.89-0.89), respectively. For external validation, these results were 0.94 (95% CI: 0.94-0.95), 0.73 (95% CI: 0.72-0.74), and 0.87 (95% CI: 0.87-0.88). For regression, the mean absolute error was 5.84% (95% CI: 5.82%-5.85%) for internal testing and 6.14% (95% CI: 6.13%-6.16%) in external validation. For prediction of the composite RV outcome, AUC was 0.84 (95% CI: 0.84-0.84) in both internal testing and external validation. CONCLUSIONS: DL on ECG data can be used to create inexpensive screening, diagnostic, and predictive tools for both LV and RV dysfunction. Such tools may bridge the applicability of ECGs and echocardiography and enable prioritization of patients for further interventions for either sided failure progressing to biventricular disease.

Mobile application to optimize care for ST-segment elevation myocardial infarction patients in a large healthcare system, STEMIcathAID: rationale and design.

Aims: Technological advancements have transformed healthcare. System delays in transferring patients with ST-segment elevation myocardial infarction (STEMI) to a primary percutaneous coronary intervention (PCI) centre are associated with worse clinical outcomes. Our aim was to design and develop a secure mobile application, STEMIcathAID, streamlining communication, and coordination between the STEMI care teams to reduce ischaemia time and improve patient outcomes. Methods and results: The app was designed for transfer of patients with STEMI to a cardiac catheterization laboratory (CCL) from an emergency department (ED) of either a PCI capable or a non-PCI capable hospital. When a suspected STEMI arrives to a non-PCI hospital ED, the ED physician uploads the electrocardiogram and relevant patient information. An instant notification is simultaneously sent to the on-call CCL attending and transfer centre. The attending reviews the information, makes a video call and decides to either accept or reject the transfer. If accepted, on-call CCL team members receive an immediate push notification and begin communicating with the ED team via a HIPAA compliant chat. The app provides live GPS tracking of the ambulance and frequent clinical status updates of the patient. In addition, it allows for screening of STEMI patients in cardiogenic shock. Prior to discharge, important data elements have to be entered to close the case. Conclusion: We developed a novel mobile app to optimize care for STEMI patients and facilitate electronic extraction of relevant performance metrics to improve allocation of resources and reduction of costs.

Pacing in obstructive hypertrophic cardiomyopathy: a therapeutic option?

Hypertrophic cardiomyopathy (HCM) is a heterogeneous disease of cardiac muscle which can present with myriad functional and clinical manifestations. When symptoms and left ventricular outflow gradients are present, it is primarily treated with pharmacologic agents. For refractory patients, dual chamber pacing has been proposed; by altering timing and site of cardiac electrical activation, the hemodynamic abnormalities in HCM may be modified. Results of non-randomized and randomized trials have shown an average gradient reduction of 50%. However, pressure gradient reduction within the left ventricular outflow tract (LVOT) has not translated into improved objective functional measurements, even though subjective parameters may improve. Dual chamber pacing cannot be recommended as primary treatment for obstruction except in a subset of patients who are elderly or have significant comorbidities that preclude surgery. However, many patients will now receive implantable cardioverter-defibrillators (ICD) which will include both right atrial and right ventricular leads. This will allow DDD pacing which may be utilized for symptom palliation. Future investigations will determine if alternate forms of pacing, including left atrial or left ventricular pacing, may improve objective measures in these patients.

Increased incidence of life-threatening ventricular arrhythmias in implantable defibrillator patients after the World Trade Center attack.

OBJECTIVES: This study was designed to evaluate whether the destruction of the World Trade Center (WTC) on September 11, 2001 (9/11), led to an increased frequency of ventricular arrhythmias among patients fitted with an implantable cardioverter-defibrillator (ICD). BACKGROUND: The WTC attack induced psychological distress. Because ICDs store all serious arrhythmias for months, the attack provided a unique opportunity to compare pre- and post-9/11 frequencies of potentially lethal arrhythmias among ICD patients. METHODS: Two hundred consecutive ICD patients who presented for regularly scheduled follow-up to six affiliated clinics were recruited into this observational study. The electrograms stored in the ICDs for the three months before 9/11 and 13 months thereafter were scrutinized in a blinded manner (relative to date) for all ventricular tachyarrhythmias (tachycardia or fibrillation) triggering ICD therapy. RESULTS: The frequency of tachyarrhythmias increased significantly for the 30 days post-9/11 (p = 0.004) relative to all other months between May 2001 and October 2002. In the 30 days post-9/11, 16 patients (8%) demonstrated tachyarrhythmias, compared with only seven (3.5%) in the preceding 30 days, representing a 2.3-fold increase in risk (95% confidence interval 1.1 to 4.9; p = 0.03). The first arrhythmic event did not occur for three days following 9/11, with events accumulating in a progressive non-clustered pattern. CONCLUSIONS: Ventricular arrhythmias increased by more than twofold among ICD patients following the WTC attack. The delay in onset and the non-clustered pattern of these events differ sharply from effects following other disasters, suggesting that subacute stress may have served to promote this arrhythmogenesis.

Unusual anomalous single papillary muscle causing symptomatic mid-left ventricular cavity obstruction: octopus papillary muscle.

This report describes a patient with an unusual large anomalous papillary muscle within the left ventricular cavity causing symptomatic midventricular outflow obstruction. The obstructing papillary muscle comprised a large central core that extended multiple circumferential muscular arms to all the walls of the left ventricle, including the septum. The papillary muscle and the arms divided the left ventricle into apical and subaortic chambers. Flow communicated between the two chambers through multiple openings between the arms with a systolic peak Doppler gradient of 50 mm Hg.