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

Anroedh, Sharda S.; Kardys, Isabella; Akkerhuis, K. Martijn; Biekart, Marileen; Hulst, B. van der; Deddens, G. J.; Smits, Pieter C.; Gardien, Martin; Dubois, Éric; Zijlstra, Felix; Boersma, Eric

doi:10.1007/s12471-018-1187-0

Cited by 11 publications

(8 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our reported incidence is similar to a prospective cohort study from Sweden, where a prehospital ECG detected STEMI in 20% of patients with suspected acute coronary syndrome [ 19 ]. Also, a Dutch investigation showed a comparable incidence of 24% STEMI diagnosis by prehospital ECG in patients with acute chest pain [ 2 ].…”

Section: Discussionmentioning

confidence: 99%

Prehospital management of patients with suspected acute coronary syndrome

Eckle

Lehmann

Drexler

2020

Med Klin Intensivmed Notfmed

View full text Add to dashboard Cite

Background In case of suspected acute coronary syndrome (ACS), international guidelines recommend to obtain a 12-lead ECG as soon as possible after first medical contact, to administrate platelet aggregation inhibitors and antithrombins, and to transfer the patient as quickly as possible to an emergency department. Methods A German emergency care service database was retrospectively analysed from 2014 to 2016. Data were tested for normal distribution and the Mann–Whitney test was used for statistical analysis. Results are presented as medians (IQR). Results A total of 1424 patients with suspected ACS were included in the present analysis. A 12-lead ECG was documented in 96% of patients (n = 1369). The prehospital incidence of ST-segment elevation myocardial infarction (STEMI) was 18% (n = 250). In 981 patients (69%), acetylsalicylic acid (ASA), unfractionated heparin (UFH), or ASA and UFH was given. Time in prehospital care differed significantly between non-STEMI (NSTEMI) ACS (37 [IQR 30, 44] min) and STEMI patients (33 [IQR 26, 40] min, n = 1395, p < 0.0001). Most of NSTEMI ACS and STEMI patients were brought to the emergency care unit, while 30% of STEMI patients were directly handed over to a cardiac catheterization laboratory. Conclusions Prehospital ECG helps to identify patients with STEMI, which occurs in 18% of suspected ACS. Patients without ST-elevations suffered from longer prehospital care times. Thus, it is tempting to speculate that ST-elevations in patients prompt prehospital medical teams to act more efficiently while the absence of ST-elevations even in patients with suspected ACS might cause unintended delays. Moreover, this analysis suggests the need for further efforts to make the cardiac catheterization laboratory the standard hand-over location for all STEMI patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Prehospital management of patients with suspected acute coronary syndrome

Eckle

Lehmann

Drexler

2020

Med Klin Intensivmed Notfmed

View full text Add to dashboard Cite

show abstract

“…When arriving at an emergency, paramedics are often first to record and interpret the ECG. Different studies [ 12 , 13 ] have been conducted to compare ECG interpretation accuracy between paramedics and physicians. Mencl et al [ 12 ] found no correlation between training, experience, or confidence in the ability of paramedics to recognize ST-elevation myocardial infarctions.…”

Section: Introductionmentioning

confidence: 99%

“…Identification of patients with acute myocardial infarction continues to be challenging, especially when automated ECG interpretation is inconclusive or misleading. However, a study [ 13 ] has shown that, when the ECG exhibits vagueness, clinician input (using the internet) can improve diagnostic performance and reduce time to treatment. It is well documented that misinterpretation of the ECG can lead to incorrect decision making regarding treatment, such as false activations (rates of up to 36% [ 14 ]) or patients being declined.…”

Section: Introductionmentioning

confidence: 99%

Human–Computer Agreement of Electrocardiogram Interpretation for Patients Referred to and Declined for Primary Percutaneous Coronary Intervention: Retrospective Data Analysis Study

Iftikhar¹,

Bond²,

McGilligan³

et al. 2021

JMIR Med Inform

View full text Add to dashboard Cite

Background When a patient is suspected of having an acute myocardial infarction, they are accepted or declined for primary percutaneous coronary intervention partly based on clinical assessment of their 12-lead electrocardiogram (ECG) and ST-elevation myocardial infarction criteria. Objective We retrospectively determined the agreement rate between human (specialists called activator nurses) and computer interpretations of ECGs of patients who were declined for primary percutaneous coronary intervention. Methods Various features of patients who were referred for primary percutaneous coronary intervention were analyzed. Both the human and computer ECG interpretations were simplified to either “suggesting” or “not suggesting” acute myocardial infarction to avoid analysis of complex heterogeneous and synonymous diagnostic terms. Analyses, to measure agreement, and logistic regression, to determine if these ECG interpretations (and other variables such as patient age, chest pain) could predict patient mortality, were carried out. Results Of a total of 1464 patients referred to and declined for primary percutaneous coronary intervention, 722 (49.3%) computer diagnoses suggested acute myocardial infarction, whereas 634 (43.3%) of the human interpretations suggested acute myocardial infarction (P<.001). The human and computer agreed that there was a possible acute myocardial infarction for 342 out of 1464 (23.3%) patients. However, there was a higher rate of human–computer agreement for patients not having acute myocardial infarctions (450/1464, 30.7%). The overall agreement rate was 54.1% (792/1464). Cohen κ showed poor agreement (κ=0.08, P=.001). Only the age (odds ratio [OR] 1.07, 95% CI 1.05-1.09) and chest pain (OR 0.59, 95% CI 0.39-0.89) independent variables were statistically significant (P=.008) in predicting mortality after 30 days and 1 year. The odds for mortality within 1 year of referral were lower in patients with chest pain compared to those patients without chest pain. A referral being out of hours was a trending variable (OR 1.41, 95% CI 0.95-2.11, P=.09) for predicting the odds of 1-year mortality. Conclusions Mortality in patients who were declined for primary percutaneous coronary intervention was higher than the reported mortality for ST-elevation myocardial infarction patients at 1 year. Agreement between computerized and human ECG interpretation is poor, perhaps leading to a high rate of inappropriate referrals. Work is needed to improve computer and human decision making when reading ECGs to ensure that patients are referred to the correct treatment facility for time-critical therapy.

show abstract

“…When arriving at an emergency, paramedics are often first to record and interpret the ECG. Different studies [12,13] have been conducted to compare ECG interpretation accuracy between paramedics and physicians. Mencl et al [12] found no correlation between training, experience, or confidence in the ability of paramedics to recognize ST-elevation myocardial infarctions.…”

Section: Introductionmentioning

confidence: 99%

“…Identification of patients with acute myocardial infarction continues to be challenging, especially when automated ECG interpretation is inconclusive or misleading. However, a study [13] has shown that, when the ECG exhibits vagueness, clinician input (using the internet) can improve diagnostic performance and reduce time to treatment. It is well documented that misinterpretation of the ECG can lead to incorrect decision making regarding treatment, such as false activations (rates of up to 36% [14]) or patients being declined.…”

Section: Introductionmentioning

confidence: 99%

Human–Computer Agreement of Electrocardiogram Interpretation for Patients Referred to and Declined for Primary Percutaneous Coronary Intervention: Retrospective Data Analysis Study (Preprint)

Iftikhar¹,

Bond²,

McGilligan³

et al. 2020

Preprint

View full text Add to dashboard Cite

BACKGROUND When a patient is suspected of having an acute myocardial infarction (AMI), patients are accepted or ‘turned-down’ for primary percutaneous coronary intervention (PPCI) partly based on clinical assessment of the 12-lead electrocardiogram (ECG) and STEMI criteria. OBJECTIVE This paper aims to retrospectively interrogate the agreement rate between the human (specialist nurse called PPCI ‘activator’) and computer interpretations of ECGs for cases where patients are turned-down for PPCI. METHODS Various features of patients who were referred for PPCI were analysed. Both the human and computer ECG interpretations were simplified to either being suggestive or not suggestive of AMI to avoid analysis of complex heterogeneous and synonymous diagnostic terms. Analysis to measure agreement was carried out along with logistic regression to measure the association between these interpretations (and other variables) in predicting mortality. RESULTS A total of 1464 patients referred for PPCI were turned-down. For these cases, 722 (49%) of the computerised diagnoses were suggestive of AMI whereas 634 (43%) of the human interpretations were suggestive of AMI (p<0.001). The human and computer agreed that there was a possible AMI in 342 cases (23.3%). However, both agreed more often that the patient was not having an AMI (n=450 [31%]). The overall agreement rate was 54%. Cohen's kappa coefficient (κ) showed a poor agreement (κ= 0.08 [p=0.001]). Other factors including age (odds ratio=1.06, 1.07) and chest pain (odds ratio=0.47, 0.59) were the only independent variables that were statistically significant (p<0.01) in predicting mortality after 30 days and 1 year. The odds for mortality within 1 year of referral were lower in patients with chest pain compared to those patients without chest pain. A referral being ‘out of hours’ is a ‘trending’ variable (odds ratio=1.93, 1.41, p=0.09) for predicting the odds of 1-year mortality. Other insights related to human and computer performance over hours of the day are also provided. CONCLUSIONS Mortality in patients turned down for PPCI is higher than the reported mortality for STEMI patients at one year. Agreement between computerised and human ECG interpretation is poor perhaps leading to a high rate of inappropriate referrals. Work is needed to improve machine and human decision making when reading ECGs to ensure that patients are signposted to the correct treatment facility for time-critical therapy.

show abstract

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

Cited by 11 publications

References 32 publications

Prehospital management of patients with suspected acute coronary syndrome

Prehospital management of patients with suspected acute coronary syndrome

Human–Computer Agreement of Electrocardiogram Interpretation for Patients Referred to and Declined for Primary Percutaneous Coronary Intervention: Retrospective Data Analysis Study

Human–Computer Agreement of Electrocardiogram Interpretation for Patients Referred to and Declined for Primary Percutaneous Coronary Intervention: Retrospective Data Analysis Study (Preprint)

Contact Info

Product

Resources

About