Emergency physicians should be shown all triage ECGs, even those with a computer interpretation of “Normal”

Artificial neural networks for ECG interpretation in acute coronary syndrome: A scoping review

INTRODUCTION

The electrocardiogram (ECG) is a crucial diagnostic tool in the Emergency Department (ED) for assessing patients with Acute Coronary Syndrome (ACS). Despite its widespread use, the ECG has limitations, including low sensitivity of the STEMI criteria to detect Acute Coronary Occlusion (ACO) and poor inter-rater reliability. Emerging ECG features beyond the traditional STEMI criteria show promise in improving early ACO diagnosis, but complexity hinders widespread adoption. The potential integration of Artificial Neural Networks (ANN) holds promise for enhancing diagnostic accuracy and addressing reliability issues in ECG interpretation for ACO symptoms.

METHODS

Ovid MEDLINE, CINAHL, EMBASE, Cochrane, PubMed and Scopus were searched from inception through to 8th of December 2023. A thorough search of the grey literature and reference lists of relevant articles was also performed to identify additional studies. Articles were included if they reported the use of ANN for ECG interpretation of Acute Coronary Syndrome in the Emergency Department patients.

RESULTS

The search yielded a total of 244 articles. After removing duplicates and excluding non-relevant articles, 14 remained for analysis. There was significant heterogeneity in the types of ANN models used and the outcomes assessed, making direct comparisons challenging. Nevertheless, ANN appeared to demonstrate higher accuracy than physician interpreters for the evaluated outcomes and this proved independent of both specialty and years of experience.

CONCLUSIONS

The interpretation of ECGs in patients with suspected ACS using ANN appears to be accurate and potentially superior when compared to human interpreters and computerised algorithms. This appears consistent across various ANN models and outcome variables. Future investigations should emphasise ANN interpretation of ECGs in patients with ACO, where rapid and accurate diagnosis can significantly benefit patients through timely access to reperfusion therapies.

Compared with physician overread, computer is less accurate but helpful in interpretation of electrocardiography for ST-segment elevation myocardial infarction

INTRODUCTION

Previous studies have demonstrated varying sensitivity and specificity of computer-interpreted electrocardiography (CIE) in identifying ST-segment elevation myocardial infarction (STEMI). This study aims to evaluate the accuracy of contemporary computer software in recognizing electrocardiography (ECG) signs characteristic of STEMI compared to emergency physician overread in clinical practice.

MATERIAL AND METHODS

In this retrospective observational single-center study, we reviewed the records of patients in the emergency department (ED) who underwent ECGs and troponin tests. Both the Philips DXL 16-Lead ECG. Algorithm and on-duty emergency physicians interpreted each standard 12‑lead ECG. The sensitivity and specificity of computer interpretation and physician overread ECGs for the definite diagnosis of STEMI were calculated and compared.

RESULTS

Among the 9340 patients included in the final analysis, 133 were definitively diagnosed with STEMI. When "computer-reported infarct or injury" was used as the indicator, the sensitivity was 87.2% (95% CI 80.3% to 92.4%) and the specificity was 86.2% (95% CI 85.5% to 86.9%). When "physician-overread STEMI" was used as the indicator, the sensitivity was 88.0% (95% CI 81.2% to 93.0%) and the specificity was 99.9% (95% CI 99.8% to 99.9%). The area under the receiver operating characteristic curve for physician-overread STEMI and computer-reported infarct or injury were 0.939 (95% CI 0.907 to 0.972) and 0.867 (95% CI 0.834 to 0.900), respectively.

CONCLUSIONS

This study reveals that while the sensitivity of the computer in recognizing ECG signs of STEMI is similar to that of physicians, physician overread of ECGs is more specific and, therefore, more accurate than CIE.

Electrocardiogram interpretation during nurse triage improves the performance of the triage system in patients with cardiovascular symptoms - A prospective observational study

BACKGROUND

An immediate ECG on arrival of a patient with cardiovascular symptoms in the ED may anticipate the need for life-saving intervention. The aim was to evaluate whether ECG interpretation during nurse triage can improve triage system performance in patients with cardiovascular symptoms.

METHODS

All patients who required an assessment for cardiovascular symptoms were considered for this observational study. During triage assessment, the nurses assessed the patient's level of urgency applying the MTS, then again after this evaluation (confirming or modifying the level of urgency based on personal clinical experience) and after interpretation of the patient's ECG. The main study outcome was the diagnosis of an acute cardiovascular event.

RESULTS

Of the 1211 patients in the study, 10.5% presented the main study outcome. ECG interpretation in triage exhibited a nurse-physician agreement of 92.9% (p<0.001). increased patient priority in 7.5% of cases and reduced it in 39.6%. The discriminatory ability of the triage system had an area under the ROC of 0.712and 0.845 after ECG interpretation. ECG interpretation improved the baseline assessment of priority, with an NRI of 60.1% (p<0.001).

CONCLUSIONS

ECG interpretation in triage can be a simple and safe tool that improves the assessment of patient priority.

Can an ECG performed during emergency department triage and interpreted as normal by computer analysis safely wait for clinician review until the time of patient assessment? A pilot study

INTRODUCTION

Electrocardiograms (ECGs) are frequently performed during patient triage in Emergency Departments (EDs). Emergency Physicians (EPs) are interrupted during other tasks to review ECGs. Critics believe this practice could lead to distraction with consequent medical error and decision fatigue. ECGs can be interpreted by computer software at the time of capture; some evidence exists to suggest that an ECG performed during ED triage with an immediate computer interpretation (ICI) of 'normal' will seldom contain information necessitating a change to triage management.

MATERIAL AND METHODS

All ED triage ECGs performed in the Royal Derby Hospital between 13th July 2017 and 12th July 2018 in patients without chest pain and with an ICI of 'normal' were identified through a database search. Forty were randomly selected and reviewed by two EPs (blinded to patient details, ICI and outcome) who were asked to identify those that required a change to triage management.

RESULTS

The study processes were feasible. At least one of the two EP reviewers felt that a change to triage management was required in 48% of cases (e.g. "review patient", "obtain blood gas", "review old ECGs"); they agreed on the need for change of management in 13% of cases. An ICI of normal had a NPV of 53% (95% CI 37-67%) for the need for a change to triage management based upon ECG findings. Inter-observer agreement was poor (kappa = 0.17).

CONCLUSIONS

Based on these results, ED triage ECGs should still be presented to EPs for immediate review regardless of the ICI. Inter-observer agreement between EPs was poor. Further research is required to link triage ECG interpretation, need for intervention and patient outcome.

Sharing and Teaching Electrocardiograms to Minimize Infarction (STEMI): reducing diagnostic time for acute coronary occlusion in the emergency department

BACKGROUND

Limits to ST-Elevation Myocardial Infarction (STEMI) criteria may lead to prolonged diagnostic time for acute coronary occlusion. We aimed to reduce ECG-to-Activation (ETA) time through audit and feedback on STEMI-equivalents and subtle occlusions, without increasing Code STEMIs without culprit lesions.

METHODS

This multi-centre, quality improvement initiative reviewed all Code STEMI patients from the emergency department (ED) over a one-year baseline and one-year intervention period. We measured ETA time, from the first ED ECG to the time a Code STEMI was activated. Our intervention strategy involved a grand rounds presentation and an internal website presenting weekly local challenging cases, along with literature on STEMI-equivalents and subtle occlusions. Our outcome measure was ETA time for culprit lesions, our process measure was website views/visits, and our balancing measure was the percentage of Code STEMIs without culprit lesions.

RESULTS

There were 51 culprit lesions in the baseline period, and 64 in the intervention period. Median ETA declined from 28.0 min (95% confidence interval [CI] 15.0-45.0) to 8.0 min (95%CI 6.0-15.0). The website garnered 70.4 views/week and 27.7 visitors/week in a group of 80 physicians. There was no change in percentage of Code STEMIs without culprit lesions: 28.2% (95%CI 17.8-38.6) to 20.0% (95%CI 11.2-28.8%). Conclusions Our novel weekly web-based feedback to all emergency physicians was associated with a reduction in ETA time by 20 min, without increasing Code STEMIs without culprit lesions. Local ECG audit and feedback, guided by ETA as a quality metric for acute coronary occlusion, could be replicated in other settings to improve care.

Comparison of PR, QRS, and QT interval measurements by seven ECG interpretation programs

BACKGROUND

Electrocardiograph-generated measurements of PR, QRS, and QT intervals are generally thought to be more precise than manual measurements on paper records. However, the performance of different programs has not been well compared.

METHODS

Routinely obtained digital electrocardiograms (ECGs), including over 500 pediatric ECGs, were used to create over 2000 10 s analog ECGs that were replayed through seven commercially available electrocardiographs. The measurements for PR interval, QRS duration, and QT interval made by each program were extracted and compared against each other (using the median of the programs after correction for program bias) and the population mean values.

RESULTS

Small but significant systematic biases were seen between programs. The smallest and largest variation from the population mean differed by 4.7 ms for PR intervals, 5.8 ms for QRS duration, and 12.4 ms for QT intervals. In pairwise comparison programs showed similar accuracy for most ECGs, with the average absolute errors at the 75th percentile for PR intervals being 4-6 ms from the median, QRS duration 4-8 ms, and QT interval 6-10 ms. However, substantial differences were present in the numbers and extent of large, clinically significant errors (e.g at the 98th percentile), for which programs differed by a factor of two for absolute errors, as well as differences in the mix of overestimations and underestimations.

CONCLUSIONS

When reading digital ECGs, users should be aware that small systematic differences exist between programs and that there may be large clinically important errors in difficult cases.

12-Lead Electrocardiograms Acquired and Transmitted by Emergency Medical Technicians are of Diagnostic Quality and Positively Impact Patient Care

INTRODUCTION

Existing peer-reviewed literature describing emergency medical technician (EMT) acquisition and transmission of 12-lead electrocardiograms (12L-ECGs), in the absence of a paramedic, is largely limited to feasibility studies.

STUDY OBJECTIVE

The objective of this retrospective observational study was to describe the impact of EMT-acquired 12L-ECGs in Suffolk County, New York (USA), both in terms of the diagnostic quality of the transmitted 12L-ECGs and the number of prehospital percutaneous coronary intervention (PCI)-center notifications made as a result of transmitted 12L-ECGs demonstrating a ST-elevation myocardial infarction (STEMI).

METHODS

A pre-existing database was queried for Emergency Medical Services (EMS) calls on which an EMT acquired a 12L-ECG from program initiation (January 2017) through December 31, 2019. Scanned copies of the 12L-ECGs were requested in order to be reviewed by a blinded emergency physician.

RESULTS

Of the 665 calls, 99 had no 12L-ECG available within the database. For 543 (96%) of the available 12L-ECGs, the quality was sufficient to diagnose the presence or absence of a STEMI. Eighteen notifications were made to PCI-centers about a concern for STEMI. The median time spent on scene and transporting to the hospital were 18 and 11 minutes, respectively. The median time from PCI-center notification to EMS arrival at the emergency department (ED) was seven minutes (IQR 5-14).

CONCLUSION

In the event a cardiac monitor is available, after a limited educational intervention, EMTs are capable of acquiring a diagnostically useful 12L-ECG and transmitting it to a remote medical control physician for interpretation. This allows for prehospital PCI-center activation for a concern of a 12L-ECG with a STEMI, in the event that a paramedic is not available to care for the patient.