Risk score to predict false-positive ST-segment elevation myocardial infarction in the emergency department: a retrospective analysis

[STEMI mimics : ST elevations on ECG: alternative diagnoses to acute coronary occlusion]

BACKGROUND

The electrocardiogram (ECG) is an integral part of basic emergency medical diagnosis and preoperative evaluation. In cases of ST elevation myocardial infarction (STEMI) immediate treatment is mandatory after correlation of ischemic symptoms with the ECG pattern. However, there are also ECG patterns that can imitate STEMI, possibly resulting in the true underlying diagnosis being missed and inappropriate therapy being initiated.

OBJECTIVES

This paper provides an overview of the most important diagnoses that can imitate STEMI on ECG.

MATERIAL AND METHODS

A literature search was carried out to determine the most important differential diagnoses of ST elevation on ECG. These STEMI mimics are discussed in detail and their relevance for emergency medicine is explained.

RESULTS

This article provides an overview of differential diagnoses that should be known in emergency medicine when assessing an ECG with ST elevations.

CONCLUSION

Good knowledge of the ECG patterns presented here can support decision-making in emergency medicine.

Diagnostic performance of a new ECG algorithm for reducing false positive cases in patients suspected acute coronary syndrome

BACKGROUND

Early and correct diagnosis of ST-segment elevation myocardial infarction (STEMI) is crucial for providing timely reperfusion therapy. Patients with ischemic symptoms presenting with ST-segment elevation on the electrocardiogram (ECG) are preferably transported directly to a catheterization laboratory (Cath-lab) for primary percutaneous coronary intervention (PPCI). However, the ECG often contains confounding factors making the STEMI diagnosis challenging leading to false positive Cath-lab activation. The objective of this study was to test the performance of a standard automated algorithm against an additional high specificity setting developed for reducing the false positive STEMI calls.

METHODS

We included consecutive patients with an available digital prehospital ECG triaged directly to Cath-lab for acute coronary angiography between 2009 and 2012. An adjudicated discharge diagnosis of STEMI or no myocardial infarction (no-MI) was assigned for each patient. The new automatic algorithm contains a feature to reduce false positive STEMI interpretation. The STEMI performance with the standard setting (STD) and the high specificity setting (HiSpec) was tested against the adjudicated discharge diagnosis in a retrospective manner.

RESULTS

In total, 2256 patients with an available digital prehospital ECG (mean age 63 ± 13 years, male gender 71%) were included in the analysis. The discharge diagnosis of STEMI was assigned in 1885 (84%) patients. The STD identified 165 true negative and 1457 true positive (206 false positive and 428 false negative) cases (77.3%, 44.5%, 87.6% and 17.3% for sensitivity, specificity, PPV and NPV, respectively). The HiSpec identified 191 true negative and 1316 true positive (180 false positive and 569 false negative) cases (69.8%, 51.5%, 88.0% and 25.1% for sensitivity, specificity, PPV and NPV, respectively). From STD to HiSpec, false positive cases were reduced by 26 (12,6%), but false negative results were increased by 33%.

CONCLUSIONS

Implementing an automated ECG algorithm with a high specificity setting was able to reduce the number of false positive STEMI cases. However, the predictive values for both positive and negative STEMI identification were moderate in this highly selected STEMI population. Finally, due the reduced sensitivity/increased false negatives, a negative AMI statement should not be solely based on the automated ECG statement.

Likelihood of myocardial infarction, revascularization and death following catheterization laboratory activation in patients with vs. without both chest pain and ST elevation

BACKGROUND

Emergent cardiac catheterization laboratory activation (CCLA) for patients with suspected ST-elevation myocardial infarction (STEMI) is employed to expedite acute revascularization (AR). The incidence of false-positive CCLA, in which AR is not performed, remains high. The combination of chest pain (CP) and electrocardiographic ST elevation (STE) are the hallmarks of STEMI. However, CCLA is sometimes initiated for patients lacking this combination. The study objective was to quantify the difference in likelihood of AR and mortality in patients with vs. without both CP and STE.

METHODS

Retrospective analysis of 1621 consecutive patients for whom CCLA was initiated in a six-hospital network. We assessed the likelihood of acute myocardial infarction (AMI), presence of a culprit lesion (CL), performance of AR, and hospital mortality among patients with both CP and STE (+CP/+STE) compared with patients lacking one or both [non(CP/STE)].

RESULTS

87.0% of patients presented with CP, 82.4% with STE, and 73.7% with both. Among +CP/+STE patients, AMI was confirmed in 90.4%, a CL in 88.9%, and AR performed in 83.1%. The corresponding values among non(CP/STE) patients were 35.8, 31.9, and 28.1%, respectively (P < 0.0001 for each). Nevertheless, mortality among non(CP/STE) patients was three-fold higher than in +CP/+STE patients (13.3% vs. 4.5%; P < 0.0001), with non-coronary deaths 24-fold more likely.

CONCLUSION

Patients lacking the combination of CP and STE have a markedly lower likelihood of AMI and AR than +CP/+STE patients, but significantly higher mortality. Protocols aimed at rapid, focused evaluation of non(CP/STE) patients prior to CCLA are needed.

Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain

Background

Due to an aging population and the increasing proportion of patients with various comorbidities, the number of patients with acute ischemic heart disease (AIHD) who present to the emergency department (ED) with atypical chest pain is increasing. The aim of this study was to develop and validate a prediction model for AIHD in patients with atypical chest pain.

Methods and results

A chest pain workup registry, ED administrative database, and clinical data warehouse database were analyzed and integrated by using nonidentifiable key factors to create a comprehensive clinical dataset in a single academic ED from 2014 to 2018. Demographic findings, vital signs, and routine laboratory test results were assessed for their ability to predict AIHD. An extreme gradient boosting (XGB) model was developed and evaluated, and its performance was compared to that of a single-variable model and logistic regression model. The area under the receiver operating characteristic curve (AUROC) was calculated to assess discrimination. A calibration plot and partial dependence plots were also used in the analyses. Overall, 4,978 patients were analyzed. Of the 3,833 patients in the training cohort, 453 (11.8%) had AIHD; of the 1,145 patients in the validation cohort, 166 (14.5%) had AIHD. XGB, troponin (single-variable), and logistic regression models showed similar discrimination power (AUROC [95% confidence interval]: XGB model, 0.75 [0.71–0.79]; troponin model, 0.73 [0.69–0.77]; logistic regression model, 0.73 [0.70–0.79]). Most patients were classified as non-AIHD; calibration was good in patients with a low predicted probability of AIHD in all prediction models. Unlike in the logistic regression model, a nonlinear relationship-like threshold and U-shaped relationship between variables and the probability of AIHD were revealed in the XGB model.

Conclusion

We developed and validated an AIHD prediction model for patients with atypical chest pain by using an XGB model.

Incidence and predictors of acute coronary syndrome within a year following a negative stress test-a false sense of security: is routine screening any useful?

One of the major issues in management of the acute coronary syndrome (ACS) is classification of patients with atypical presentation who have low risk of having a coronary episode at presentation. There have been multiple studies on the stratification of high risk patients and medical management of such cases, however, there is a sub-class of patients who do not fit any category. In this paper, we have looked at the current literature on stratification of patients based on the study tools available and the risk of having a coronary episode during the following year. In our overview, we have found that the current methods in place namely, cardiac stress test and stress echocardiogram have a good prognostic factor in terms of mortality in the next one year and can safely stratify the patients at low risk when correlated with clinical presentation and laboratory studies. However, such data are limited for computerized tomography or magnetic resonant imaging and their application might be limited due to accessibility and cost of studies. Current guidelines for classification of high risk patient do an excellent job and we believe that proper application of stress tests together with other imaging modalities together with laboratory, clinical judgment, and proper use of medical management can help with safe discharge of patients from the emergency department (ED) and reduction of burden from healthcare.