Sustained Performance of a "Physicianless" System of Automated Prehospital STEMI Diagnosis and Catheterization Laboratory Activation

Late Outcomes of Patients With Prehospital ST-Segment Elevation and Appropriate Cardiac Catheterization Laboratory Nonactivation

Background Patients with suspected ST-segment-elevation myocardial infarction (STEMI) and cardiac catheterization laboratory nonactivation (CCL-NA) or cancellation have reportedly similar crude and higher adjusted risks of death compared with those with CCL activation, though reasons for these poor outcomes are not clear. We determined late clinical outcomes among patients with prehospital ECG STEMI criteria who had CCL-NA compared with those who had CCL activation. Methods and Results We identified consecutive prehospital ECG transmissions between June 2, 2010 to October 6, 2016. Diagnoses according to the Fourth Universal Definition of myocardial infarction (MI), particularly rates of myocardial injury, were adjudicated. The primary outcome was all-cause death. Secondary outcomes included cardiovascular death/MI/stroke and noncardiovascular death. To explore competing risks, cause-specific hazard ratios (HRs) were obtained. Among 1033 included ECG transmissions, there were 569 (55%) CCL activations and 464 (45%) CCL-NAs (1.8% were inappropriate CCL-NAs). In the CCL activation group, adjudicated index diagnoses included MI (n=534, 94%, of which 99.6% were STEMI and 0.4% non-STEMI), acute myocardial injury (n=15, 2.6%), and chronic myocardial injury (n=6, 1.1%). In the CCL-NA group, diagnoses included MI (n=173, 37%, of which 61% were non-STEMI and 39% STEMI), chronic myocardial injury (n=107, 23%), and acute myocardial injury (n=47, 10%). At 2 years, the risk of all-cause death was higher in patients who had CCL-NA compared with CCL activation (23% versus 7.9%, adjusted risk ratio, 1.58, 95% CI, 1.24-2.00), primarily because of an excess in noncardiovascular deaths (adjusted HR, 3.56, 95% CI, 2.07-6.13). There was no significant difference in the adjusted risk for cardiovascular death/MI/stroke between the 2 groups (HR, 1.23, 95% CI, 0.87-1.73). Conclusions CCL-NA was not primarily attributable to missed STEMI, but attributable to "masquerading" with high rates of non-STEMI and myocardial injury. These patients had worse late outcomes than patients who had CCL activation, mainly because of higher rates of noncardiovascular deaths.

Artificial Intelligence: A Shifting Paradigm in Cardio-Cerebrovascular Medicine

The future of healthcare is an organic blend of technology, innovation, and human connection. As artificial intelligence (AI) is gradually becoming a go-to technology in healthcare to improve efficiency and outcomes, we must understand our limitations. We should realize that our goal is not only to provide faster and more efficient care, but also to deliver an integrated solution to ensure that the care is fair and not biased to a group of sub-population. In this context, the field of cardio-cerebrovascular diseases, which encompasses a wide range of conditions-from heart failure to stroke-has made some advances to provide assistive tools to care providers. This article aimed to provide an overall thematic review of recent development focusing on various AI applications in cardio-cerebrovascular diseases to identify gaps and potential areas of improvement. If well designed, technological engines have the potential to improve healthcare access and equitability while reducing overall costs, diagnostic errors, and disparity in a system that affects patients and providers and strives for efficiency.

Working Against the Clock: A Model for Rural STEMI Triage

Residents in rural communities have a higher incidence of cardiac death and risk factors associated with cardiac disease. Living in a rural region can add precious time that amplifies cardiac death during an ST-elevated myocardial infarction (STEMI) episode. The consensus is that improved efficiencies can increase myocardial salvage and decrease STEMI mortality rates. This article identifies issues that may impact pre-hospital STEMI triage of patients in a rural region of the United States (U.S.). A qualitative research design was chosen to gain insight into emergency personnel perceptions of pre-hospital STEMI triage. The participants (n = 18) were obtained from a convenience sample in rural Northeast Texas, U.S. Data were gathered by individual and group semi-structured interviews. Themes were identified, synthesized, and oriented to offer a basis for understanding opportunities to improve the delivery of rural STEMI care. This study demonstrated that quality improvement initiatives aimed at achieving pre-hospital STEMI triage efficiencies have dependencies on teamwork, technology, and training in the context of 3 stages (a) pre-transport, (b) door-to-door, and (c) post-transport. A pre-hospital STEMI triage model is offered based on the findings. By incorporating this model, emergency medical coordinators in rural communities have a better opportunity to facilitate timely reperfusion therapy for this high-risk population.

Impact of STEMI Diagnosis and Catheterization Laboratory Activation Systems on Sex- and Age-Based Differences in Treatment Delay

Background

Women and the elderly with ST-elevation myocardial infarction (STEMI) experience longer treatment delays despite prehospital STEMI diagnosis and catheterization laboratory activation systems. It is not known what role specific STEMI referral systems might play in mediating this gap in care. We therefore examined sex- and age-based differences in STEMI treatment delay (TD) in different STEMI activation systems.

Methods

This observational comparative effectiveness study comprised 3 retrospective STEMI cohorts: a traditional hospital-based activation cohort (Cohort 1), an automated “physician-blind” prehospital activation cohort (Cohort 2), and a prehospital activation with real-time physician oversight cohort (Cohort 3). Outcomes of interest included sex and age group (< or ≥ 75 years) differences in suboptimal (> 90 minutes) first medical contact-to-device time (FMC-to-device) within each cohort, as well as independent predictors of suboptimal FMC-to-device and in-hospital mortality across cohorts.

Results

Five hundred-sixty STEMI activations were analyzed. In Cohort 1 (n = 179), women and those ≥ 75 were more likely to experience suboptimal FMC-to-device times (78.7% vs 36.4%, P = 0.02 and 85.0% vs 58.3%, < 0.01, respectively). Similar findings were observed in Cohort 3 (n = 109) (53.5% vs 32.9%, 56.5% vs 33.3%, respectively; P = 0.05, for both). In Cohort 2 (n = 272), however, there was no significant age-based difference (30.4% vs 21.7%, P = 0.18), and the gap was numerically lower but still significant for women (32.1% vs 20.1%, P = 0.04). When examining prehospital activation cohorts only, female sex (P = 0.03), off-hours presentation (P < 0.01), and physician oversight (P < 0.01) were independent predictors of longer FMC-to-device times. Age ≥ 75 (P < 0.01), Killip class (P < 0.01), and female sex (P = 0.04) were independently associated with in-hospital mortality.

Conclusions

Automated “physician-blind” STEMI activation was associated with a reduced TD gap in women and the elderly, suggesting possible systemic bias. Appropriately powered confirmatory studies are required, but incorporating automated diagnosis and catheterization laboratory activation may be a solution to treatment gaps in STEMI care.

Effect of Real-Time Physician Oversight of Prehospital STEMI Diagnosis on ECG-Inappropriate and False Positive Catheterization Laboratory Activation

Background

ST-elevation myocardial infarction diagnosis at first medical contact (FMC) and prehospital cardiac catheterization laboratory (CCL) activation are associated with reduced total ischemic time and therefore have become the dominant ST-elevation myocardial infarction referral method in primary percutaneous coronary intervention systems. We sought to determine whether physician oversight was associated with improved diagnostic performance in a prehospital CCL activation system and what effect the additional interpretation has on treatment delay.

Methods

Between 2012 and 2015, all patients in 2 greater Montreal catchment areas with a chief symptom of chest paint or dyspnea had an in-the-field electrocardiogram (ECG). A machine diagnosis of "acute myocardial infarction" resulted either in automatic CCL (automated cohort without oversight) or transmission of the ECG to the receiving centre emergency physician for reinterpretation before CCL activation. System performance was assessed in terms of the proportion of false positive and inappropriate activations (IA), as well as the proportion of patients with FMC-to-device times ≤ 90 minutes.

Results

Four hundred twenty-eight (428) activations were analyzed (311 automated; 117 with physician oversight). Physician oversight tended to decrease IAs (7% vs 3%; P = 0.062), but was also associated with a smaller proportion of patients achieving target FMC-to-device (76% vs 60%; P < 0.001). There was no significant effect on the proportion of false positive activation.

Conclusions

Real-time physician oversight might be associated with fewer IAs, but also appears to have a deleterious effect on FMC-to-device performance. Identifying predictors of IA could improve overall performance by selecting ECGs that merit physician oversight and streamlining others. Larger clinical studies are warranted.

The Effect of Implementation of the American Heart Association Mission Lifeline PreAct Algorithm for Prehospital Cardiac Catheterization Laboratory Activation on the Rate of "False Positive" Activations

HYPOTHESIS

Emergency Medical Services (EMS) systems have developed protocols for prehospital activation of the cardiac catheterization laboratory for patients with suspected ST-elevation myocardial infarction (STEMI) to decrease first-medical-contact-to-balloon time (FMC2B). The rate of "false positive" prehospital activations is high. In order to decrease this rate and expedite care for patients with true STEMI, the American Heart Association (AHA; Dallas, Texas USA) developed the Mission Lifeline PreAct STEMI algorithm, which was implemented in Los Angeles County (LAC; California USA) in 2015. The hypothesis of this study was that implementation of the PreAct algorithm would increase the positive predictive value (PPV) of prehospital activation.

METHODS

This is an observational pre-/post-study of the effect of the implementation of the PreAct algorithm for patients with suspected STEMI transported to one of five STEMI Receiving Centers (SRCs) within the LAC Regional System. The primary outcome was the PPV of cardiac catheterization laboratory activation for percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). The secondary outcome was FMC2B.

RESULTS

A total of 1,877 patients were analyzed for the primary outcome in the pre-intervention period and 405 patients in the post-intervention period. There was an overall decrease in cardiac catheterization laboratory activations, from 67% in the pre-intervention period to 49% in the post-intervention period (95% CI for the difference, -14% to -22%). The overall rate of cardiac catheterization declined in post-intervention period as compared the pre-intervention period, from 34% to 30% (95% CI, for the difference -7.6% to 0.4%), but actually increased for subjects who had activation (48% versus 58%; 95% CI, 4.6%-15.0%). Implementation of the PreAct algorithm was associated with an increase in the PPV of activation for PCI or CABG from 37.9% to 48.6%. The overall odds ratio (OR) associated with the intervention was 1.4 (95% CI, 1.1-1.8). The effect of the intervention was to decrease variability between medical centers. There was no associated change in average FMC2B.

CONCLUSIONS

The implementation of the PreAct algorithm in the LAC EMS system was associated with an overall increase in the PPV of cardiac catheterization laboratory activation.

Reducing Delay to Treatment of ST-Elevation Myocardial Infarction With Software Electrocardiographic Interpretation and Transmission (SCINET)

BACKGROUND

Prehospital diagnosis of ST-elevation myocardial infarction (STEMI) has resulted in improved outcomes. However, many patients still walk in to the emergency department (ED) with STEMI, experiencing delays and worse outcomes. Software electrocardiogram (ECG) diagnosis of STEMI and electronic transmission to a cardiologist may result in improved door-to-device (D2D) times.

METHODS

We retrospectively identified all patients presenting with STEMI from January 2015 to September 2016. Components of delay in D2D, ED variables, and the patients' ECGs were extracted from our regional database. All ECGs performed for suspected myocardial infarction in the region were extracted over the study period. We assessed the accuracy of the software 12SL in diagnosing STEMI, ED contributors to delays in D2D, and the potential reduction in D2D if software diagnosis of STEMI resulted in activation of the cardiac catheterization laboratory.

RESULTS

A total of 379 patients presented to an ED in our region and received primary percutaneous coronary intervention over the study period. In the 143,574 ECGs performed over the study period for suspected STEMI, the overall sensitivity and specificity of 12SL were 90.5% and 99.98%, respectively. We estimated a potential 17-minute reduction in D2D in the 90.5% of patients correctly identified as having STEMI, with a false activation rate of 4%. Female patients and older patients experienced an even larger potential benefit, with 24- and 25-minute reductions in D2D, respectively.

CONCLUSIONS

Patients who walk in to an ED with STEMI experience significant system-related delays in recognition and treatment. Automated software diagnosis of STEMI is accurate and could result in significant improvements in D2D times.

e-Transmission of ECGs for expert consultation results in improved triage and treatment of patients with acute ischaemic chest pain by ambulance paramedics

AIMS

In pre-hospital settings handled by paramedics, identification of patients with myocardial infarction (MI) remains challenging when automated electrocardiogram (ECG) interpretation is inconclusive. We aimed to identify those patients and to get them on the right track to primary percutaneous coronary intervention (PCI).

METHODS AND RESULTS

In the Rotterdam-Rijnmond region, automated ECG devices on all ambulances were supplemented with a modem, enabling transmission of ECGs for online expert interpretation. The diagnostic protocol for acute chest pain was modified and monitored for 1 year. Patients with an ECG that met the criteria for ST-elevation myocardial infarction (STEMI) were immediately transported to a PCI hospital. ECGs that did not meet the STEMI criteria, but showed total ST deviation ≥800 µv were transmitted for online interpretation by the ECG expert. Online supervision was offered as a service if ECGs showed conduction disorders, or had an otherwise 'suspicious' pattern according to the ambulance paramedics. We enrolled 1,076 patients with acute ischaemic chest pain who did not meet the automated STEMI criteria. Their mean age was 63 years; 64% were men. After online consultation, 735 (68%) patients were directly transported to a PCI hospital for further treatment. PCI within 90 min was performed in 115 patients.

CONCLUSION

During a 1-year evaluation of the modified pre-hospital triage protocol for patients with acute ischaemic chest pain, over 100 acute MI patients with an initially inconclusive ECG received primary PCI within 90 min. Because of these results, we decided to continue the operation of the modified protocol.

A window-based time series feature extraction method

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets.