State-of-the-Art Evaluation of Emergency Department Patients Presenting With Potential Acute Coronary Syndromes

Rapid Acute Coronary Syndrome Evaluation Over One Hour With High-Sensitivity Cardiac Troponin I: A United States-Based Stepped-Wedge, Randomized Trial

STUDY OBJECTIVE

The real-world effectiveness and safety of a 0/1-hour accelerated protocol using high-sensitivity cardiac troponin (hs-cTn) to exclude myocardial infarction (MI) compared to routine care in the United States is uncertain. The objective was to compare a 0/1-hour accelerated protocol for evaluation of MI to a 0/3-hour standard care protocol.

METHODS

The RACE-IT trial was a stepped-wedge, randomized trial across 9 emergency departments (EDs) that enrolled 32,609 patients evaluated for possible MI from July 2020 through April 2021. Patients undergoing high-sensitivity cardiac troponin I testing with concentrations less than or equal to 99th percentile were included. Patients who had MI excluded by the 0/1-hour protocol could be discharged from the ED. Patients in the standard care protocol had 0- and 3-hour troponin testing and application of a modified HEART score to be eligible for discharge. The primary endpoint was the proportion of patients discharged from the ED without 30-day death or MI.

RESULTS

There were 13,505 and 19,104 patients evaluated in the standard care and accelerated protocol groups, respectively, of whom 19,152 (58.7%) were discharged directly from the ED. There was no significant difference in safe discharges between standard care and the accelerated protocol (59.5% vs 57.8%; adjusted odds ratio (aOR)=1.05, 95% confidence interval [CI] 0.95 to 1.16). At 30 days, there were 90 deaths or MIs with 38 (0.4%) in the standard care group and 52 (0.4%) in the accelerated protocol group (aOR=0.84, 95% CI 0.43 to 1.68).

CONCLUSION

A 0/1-hour accelerated protocol using high-sensitivity cardiac troponin I did not lead to more safe ED discharges compared with standard care.

Sex differences in the management of patients with suspected acute coronary syndrome in China

Few studies have assessed sex differences in the management of suspected acute coronary syndrome (ACS). We aimed to compare the evaluation, treatment, and outcomes between males and females with suspected ACS in the emergency department. Data were obtained from a prospective registry of acute chest pain involving 21 emergency departments in Shandong Province, China. The primary endpoint was 30-day major adverse cardiac events (MACEs). Overlap propensity score weighting was used to address potential confounding. A total of 8046 patients were analysed (42.8% female). Overlap-weighted analysis showed no significant association of female sex with 30-day MACEs (odds ratio, 0.91; 95% CI 0.75 to 1.11; P = 0.363). Secondary analyses found that women were less likely to be identified as high risk at first presentation (odds ratio, 0.86; 95% CI 0.78 to 0.94; P < 0.001). In the emergency department, women were less likely to undergo antiplatelet therapy (odds ratio, 0.87; 95% CI 0.79 to 0.96; P = 0.004) or coronary angiography (odds ratio, 0.78; 95% CI, 0.69 to 0.88; P < 0.001). Women had a longer length of stay in the emergency department and were less likely to be admitted to a ward at disposition. These sex differences existed only in the non-ST-elevation subgroup and were independent of risk stratification. Women with non-ST-elevation chest pain in China received suboptimal treatment in the emergency department. However, their clinical outcomes were not significantly different from those of men. Further studies are needed to determine the causes and impacts of these sex differences.

Troponin in early presenters to rule out myocardial infarction

AIMS

Whether a single cardiac troponin measurement can safely rule out myocardial infarction in patients presenting within a few hours of symptom onset is uncertain. The study aim was to assess the performance of troponin in early presenters.

METHODS AND RESULTS

In patients with possible myocardial infarction, the diagnostic performance of a single measurement of high-sensitivity cardiac troponin I at presentation was evaluated and externally validated in those tested ≤3, 4-12, and >12 h from symptom onset. The limit-of-detection (2 ng/L), rule-out (5 ng/L), and sex-specific 99th centile (16 ng/L in women; 34 ng/L in men) thresholds were compared. In 41 103 consecutive patients [60 (17) years, 46% women], 12 595 (31%) presented within 3 h, and 3728 (9%) had myocardial infarction. In those presenting ≤3 h, a threshold of 2 ng/L had greater sensitivity and negative predictive value [99.4% (95% confidence interval 99.2%-99.5%) and 99.7% (99.6%-99.8%)] compared with 5 ng/L [96.5% (96.2%-96.8%) and 99.3% (99.1%-99.4%)]. In those presenting ≥3 h, the sensitivity and negative predictive value were similar for both thresholds. The sensitivity of the 99th centile was low in early and late presenters at 71.4% (70.6%-72.2%) and 92.5% (92.0%-93.0%), respectively. Findings were consistent in an external validation cohort of 7088 patients.

CONCLUSION

In early presenters, a single measurement of high-sensitivity cardiac troponin I below the limit of detection may facilitate the safe rule out of myocardial infarction. The 99th centile should not be used to rule out myocardial infarction at presentation even in those presenting later following symptom onset.

The effect of point-of-care ultrasound on length of stay and mortality in patients with chest pain/dyspnea

PURPOSE

This study aims to investigate the effects of point-of-care ultrasound (PoCUS) on length of stay (LOS) and mortality in hemodynamically stable patients with chest pain/dyspnea.

MATERIALS AND METHODS

The prospective study was conducted from June 2020 to May 2021. A convenience sample of adult non-traumatic patients with chest pain/dyspnea was included and evaluated by PoCUS. The primary outcome was the relationship between the door-to-PoCUS time and LOS/mortality categorized by the ST-segment elevation (STE) and non-STE on the initial electrocardiogram. The diagnostic accuracy of PoCUS was computed, compared to the final diagnosis.

RESULTS

A total of 465 patients were included. 3 of 18 patients with STE had unexpected cardiac tamponade and 1 had myocarditis with pulmonary edema. PoCUS had a minimal effect on LOS and mortality in patients with STE. In the non-STE group, the shorter door-to-PoCUS time was associated with a shorter LOS (coefficient, 1.26±0.47, p=0.008). After categorizing the timing of PoCUS as 30, 60, 90, and 120 minutes, PoCUS had a positive effect, especially when performed within 90 minutes of arrival, on LOS of less than 360 minutes (OR, 2.42, 95% CI, 1.61-3.64) and patient survival (OR, 3.32, 95% CI, 1.14-9.71). The overall diagnostic performance of PoCUS was 96.6% (95% CI, 94.9-98.2%), but lower efficacy occurred in pulmonary embolism and myocardial infarction.

CONCLUSION

The use of PoCUS was associated with a shorter LOS and less mortality in patients with non-STE, especially when performed within 90 minutes of arrival. Although the effect on patients with STE was minimal, PoCUS played a role in discovering unexpected diagnoses.

Single Troponin Measurement to Rule Out Myocardial Infarction: JACC Review Topic of the Week

The term "single-sample rule-out" refers to the ability of very low concentrations of high-sensitivity cardiac troponin (hs-cTn) on presentation to exclude acute myocardial infarction with high clinical sensitivity and negative predictive value. Observational and randomized studies have confirmed this ability. Some guidelines endorse use of a concentration of hs-cTn at the assay's limit of detection, while other studies have validated the use of higher concentrations, allowing this approach to identify a greater proportion of patients at low risk. In most studies, at least 30% of patients can be triaged with this approach. The concentration of hs-cTn varies according to the assay used and sometimes how regulations permit reporting. It is clear that patients need to be at least 2 hours from the onset of symptoms being evaluated. Caution is warranted, particularly with older patients, women, and patients with underlying cardiac comorbidities.

Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations

Although guidelines recommend fixed cardiac troponin thresholds for the diagnosis of myocardial infarction, troponin concentrations are influenced by age, sex, comorbidities and time from symptom onset. To improve diagnosis, we developed machine learning models that integrate cardiac troponin concentrations at presentation or on serial testing with clinical features and compute the Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS) score (0-100) that corresponds to an individual's probability of myocardial infarction. The models were trained on data from 10,038 patients (48% women), and their performance was externally validated using data from 10,286 patients (35% women) from seven cohorts. CoDE-ACS had excellent discrimination for myocardial infarction (area under curve, 0.953; 95% confidence interval, 0.947-0.958), performed well across subgroups and identified more patients at presentation as low probability of having myocardial infarction than fixed cardiac troponin thresholds (61 versus 27%) with a similar negative predictive value and fewer as high probability of having myocardial infarction (10 versus 16%) with a greater positive predictive value. Patients identified as having a low probability of myocardial infarction had a lower rate of cardiac death than those with intermediate or high probability 30 days (0.1 versus 0.5 and 1.8%) and 1 year (0.3 versus 2.8 and 4.2%; P < 0.001 for both) from patient presentation. CoDE-ACS used as a clinical decision support system has the potential to reduce hospital admissions and have major benefits for patients and health care providers.

Prediction of significant coronary artery disease in acute chest pain without infarction in emergency department: MAPAC Cardio-PreTest model

Acute nontraumatic chest pain is a frequent reaso n for consultation in emergency departments and represents a diagnostic challenge. The objective is to estimate the risk of significant coronary artery disease (CAD) in patients with cardiogenic acute chest pain for whom the diagnosis of infarction was ruled out in the emergency department with a nondiagnostic ECG and negative high-sensitivity troponins. We prospectively recruited 1625 patients from emergency departments of seven Spanish hospitals. The outcome was presence of significant CAD determined by presence of ischaemia in functional tests or more than 70% stenosis in imaging tests. In this study, we developed a predictive model and evaluated its performance and clinical utility. The prevalence of significant CAD was 14% [227/1625; 95% confidence interval (CI), 12-16]. MAPAC Cardio-PreTest model included seven predictors: age, sex, smoking, history of hypertension, family history of CAD, history of hyperuricaemia, and type of chest pain. The optimism-adjusted model discrimination was C-statistic 0.654 (95% CI, 0.618-0.693). Calibration plot showed good agreement between the predicted and observed risks, and calibration slope was 0.880 (95% CI, 0.731-1.108) and calibration-in-the-large -0.001 (95% CI, -0.141 to 0.132). The model increased net benefit and improved risk classification over the recommended approach by the European Society of Cardiology [Net Reclassification Index (NRI) of events = 5.3%, NRI of nonevents = 7.0%]. MAPAC Cardio-PreTest model is an online prediction tool to estimate the individualised probability of significant CAD in patients with acute chest pain without a diagnosis of infarction in emergency department. The model was more useful than the current alternatives in helping patients and clinicians make individually tailored choices about the intensity of monitoring or additional coronary tests.

Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning

OBJECTIVE

Early revascularization of the occluded coronary artery in patients with ST elevation myocardial infarction (STEMI) has been demonstrated to decrease mortality and morbidity. Currently, physicians rely on features of electrocardiograms (ECGs) to identify the most likely location of coronary arteries related to an infarct. We sought to predict these culprit arteries more accurately by using deep learning.

METHODS

A deep learning model with a convolutional neural network (CNN) that incorporated ECG signals was trained on 384 patients with STEMI who underwent primary percutaneous coronary intervention (PCI) at a medical center. The performances of various signal preprocessing methods (short-time Fourier transform [STFT] and continuous wavelet transform [CWT]) with different lengths of input ECG signals were compared. The sensitivity and specificity for predicting each infarct-related artery and the overall accuracy were evaluated.

RESULTS

ECG signal preprocessing with STFT achieved fair overall prediction accuracy (79.3%). The sensitivity and specificity for predicting the left anterior descending artery (LAD) as the culprit vessel were 85.7% and 88.4%, respectively. The sensitivity and specificity for predicting the left circumflex artery (LCX) were 37% and 99%, respectively, and the sensitivity and specificity for predicting the right coronary artery (RCA) were 88.4% and 82.4%, respectively. Using CWT (Morlet wavelet) for signal preprocessing resulted in better overall accuracy (83.7%) compared with STFT preprocessing. The sensitivity and specificity were 93.46% and 80.39% for LAD, 56% and 99.7% for LCX, and 85.9% and 92.9% for RCA, respectively.

CONCLUSION

Our study demonstrated that deep learning with a CNN could facilitate the identification of the culprit coronary artery in patients with STEMI. Preprocessing ECG signals with CWT was demonstrated to be superior to doing so with STFT.

SVEAT score outperforms HEART score in patients admitted to a chest pain observation unit

BACKGROUND

Timely and accurate identification of subgroup at risk for major adverse cardiovascular events among patients presenting with acute chest pain remains a challenge. Currently available risk stratification scores are suboptimal. Recently, a new scoring system called the Symptoms, history of Vascular disease, Electrocardiography, Age, and Troponin (SVEAT) score has been shown to outperform the History, Electrocardiography, Age, Risk factors and Troponin (HEART) score, one of the most used risk scores in the United States.

AIM

To assess the potential usefulness of the SVEAT score as a risk stratification tool by comparing its performance to HEART score in chest pain patients with low suspicion for acute coronary syndrome and admitted for overnight observation.

METHODS

We retrospectively reviewed medical records of 330 consecutive patients admitted to our clinical decision unit for acute chest pain between January 1^st to April 17^th, 2019. To avoid potential biases, investigators assigned to calculate the SVEAT, and HEART scores were blinded to the results of 30-d combined endpoint of death, acute myocardial infarction or confirmed coronary artery disease requiring revascularization or medical therapy [30-d major adverse cardiovascular event (MACE)]. An area under receiving-operator characteristic curve (AUC) for each score was then calculated. C-statistic and logistic model were used to compare predictive performance of the two scores.

RESULTS

A 30-d MACE was observed in 11 patients (3.33% of the subjects). The AUC of SVEAT score (0.8876, 95%CI: 0.82-0.96) was significantly higher than the AUC of HEART score (0.7962, 95%CI: 0.71-0.88), P = 0.03. Using logistic model, SVEAT score with cut-off of 4 or less significantly predicts 30-d MACE (odd ratio 1.52, 95%CI: 1.19-1.95, P = 0.001) but not the HEART score (odd ratio 1.29, 95%CI: 0.78-2.14, P = 0.32).

CONCLUSION

The SVEAT score is superior to the HEART score as a risk stratification tool for acute chest pain in low to intermediate risk patients.

A Case of Elevated Troponin I Level After Packed Red Blood Cell Transfusion With Normal Coronary Angiography

Other than acute coronary syndrome (ACS), many clinical conditions are associated with increased cardiac troponin I (cTnI) levels. Conditions such as pulmonary embolism, acute heart failure, myocarditis, sepsis, and renal failure are commonly reported as underlying causes. Analytical interference with the cTnI assay can also lead to falsely elevated troponin I levels. That can happen due to multiple causes such as fibrin clots, heterophile antibodies, microparticles contained in the sample, rheumatoid factor, interference by bilirubin, hemolysis, and elevated alkaline phosphatase activity. Herein, we present the case of a 66-year-old female who presented with pleuritic chest pain and had a cTnI of 35.5 ng/mL post-transfusion of three units of packed red blood cells. The patient had a complete ischemic workup for ACS, including coronary angiography, which was negative for coronary artery disease.

Soluble lectin-like oxidized low-density lipoprotein receptor-1 predicts premature death in acute coronary syndromes

AIMS

The lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) and its shedding product [soluble LOX-1 (sLOX-1)] are implicated in atherosclerotic cardiovascular disease (ASCVD) pathogenesis. Herein, we examined the relationship of sLOX-1 with both fatal events and plaque progression in patients with acute coronary syndromes (ACS).

METHODS AND RESULTS

Plasma sLOX-1 was assessed at baseline in ACS and chronic coronary syndrome (CCS) patients prospectively recruited in the multicentre SPUM-ACS study, with sex- and age-matched healthy subjects serving as additional controls (n = 2924). Compared with both CCS and controls, ACS patients showed markedly elevated sLOX-1 levels (median, 2.00 and 2.00 vs. 35.08 pg/mL; P < 0.0001) which were independently associated with increased mortality risk over 30-day [tertile (T)3: adjusted hazard ratio (HR), 3.11; 95% confidence interval (CI), 1.44-10.61; P = 0.0055] and 1-year intervals (T3: adjusted HR, 2.04; 95% CI, 1.19-3.92; P = 0.0098). Results remained consistent after adjustment for GRACE 2.0 (T3: adjusted HR, 1.86; 95% CI, 1.04-3.74; P = 0.0391) and were primarily driven by the pronounced relationship of sLOX-1 with cardiovascular mortality at 30 days (T3: adjusted HR, 3.81; 95% CI, 1.62-19.62; P = 0.0036) and at 1 year (T3: adjusted HR, 2.29; 95% CI, 1.19-5.34; P = 0.0148). In ACS patients undergoing serial intracoronary imaging and statin therapy, sLOX-1 dropped significantly in those with coronary plaque regression at 1 year (ΔsLOX-1: -4.64 ± 1.80; P = 0.0057), and showed a good discrimination for predicting plaque progression (area under the curve = 0.74; 95% CI, 0.59-0.86; P = 0.0031).

CONCLUSION

Plasma sLOX-1 levels are increased during ACS and predict fatal events beyond traditional and emerging risk factors. Persistently high sLOX-1 associates with coronary plaque progression in patients with established ASCVD.

CLINICAL TRIAL REGISTRATION

NCT01000701.

Analysis of the accuracy of automatic electrocardiogram interpretation in ST-segment elevation myocardial infarction

Objective

This study aimed to analyze the association between the culprit artery and the diagnostic accuracy of automatic electrocardiogram (ECG) interpretation in patients with ST-segment elevation myocardial infarction (STEMI).

Methods

This single-centered, retrospective cohort study included adult patients with STEMI who visited the emergency department between January 2017 and December 2020. The primary endpoint was the association between the culprit artery occlusion and the misinterpretation of ECG, evaluated by the chi-square test or Fisher exact test.

Results

The rate of misinterpretation of the automated ECG for patients with STEMI was 26.5% (31/117 patients). There was no significant correlation between the ST segment change in the four involved leads (anteroseptal, lateral, inferior, and aVR) and the misinterpretation of ECG (all P > 0.05). Single culprit artery occlusion significantly affected the misinterpretation of ECG compared with multiple culprit artery occlusion (single vs. multiple, 27/86 [31.3%] vs. 4/31 [12.9%], P = 0.045). There was no association between culprit artery and the misinterpretation of ECG (P = 0.132).

Conclusion

Single culprit artery occlusion might increase misinterpretation of ECG compared with multiple culprit artery occlusions in the automatic interpretation of STEMI.

Diagnostic Accuracy of the Deep Learning Model for the Detection of ST Elevation Myocardial Infarction on Electrocardiogram

We aimed to measure the diagnostic accuracy of the deep learning model (DLM) for ST-elevation myocardial infarction (STEMI) on a 12-lead electrocardiogram (ECG) according to culprit artery sorts. From January 2017 to December 2019, we recruited patients with STEMI who received more than one stent insertion for culprit artery occlusion. The DLM was trained with STEMI and normal sinus rhythm ECG for external validation. The primary outcome was the diagnostic accuracy of DLM for STEMI according to the three different culprit arteries. The outcomes were measured using the area under the receiver operating characteristic curve (AUROC), sensitivity (SEN), and specificity (SPE) using the Youden index. A total of 60,157 ECGs were obtained. These included 117 STEMI-ECGs and 60,040 normal sinus rhythm ECGs. When using DLM, the AUROC for overall STEMI was 0.998 (0.996–0.999) with SEN 97.4% (95.7–100) and SPE 99.2% (98.1–99.4). There were no significant differences in diagnostic accuracy within the three culprit arteries. The baseline wanders in false positive cases (83.7%, 345/412) significantly interfered with the accurate interpretation of ST elevation on an ECG. DLM showed high diagnostic accuracy for STEMI detection, regardless of the type of culprit artery. The baseline wanders of the ECGs could affect the misinterpretation of DLM.

The use of point-of-care ultrasound in new-onset dyspnea: an unexpected diagnosis

In this article, we report a patient with new-onset dyspnea and symptoms suggestive of heart failure, who had an unexpected diagnosis of a large left atrial myxoma with diastolic protrusion into the left ventricle. We further underline the role of cardiac Point-of-Care Ultrasound (POCUS) in the initial evaluation of patients with cardiac complaints in the emergency room setting. It can help to differentiate the patients' symptoms in order to achieve a more accurate diagnosis and thus increase the efficacy of the established therapy. In some cases, as with this patient, it can help to establish a diagnosis which needs prompt therapy.

The diagnostic accuracy of coronary computed tomography angiography in patients with and without previous coronary interventions

BACKGROUND

Invasive coronary angiography (ICA) is the gold standard for imaging coronary arteries and the severity of coronary artery disease (CAD). Coronary computed tomography angiography (CCTA) has undergone remarkable progress in the diagnosis of CAD.

OBJECTIVES

To evaluate the effect of prior vs no previous coronary interventions on the diagnostic accuracy of CCTA as an alternative to ICA to improve health outcomes for patients with suspected CAD.

METHODS

A prospective cohort study was carried out among patients suspected of CAD and for evaluation of grafts and stents to investigate recurrent ischemic symptoms. 120 patients imaged by CCTA were then referred to ICA, which is considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CCTA were assessed relative to ICA.

RESULTS

Based on a per-patient analysis, the comparison with ICA reveals variations in sensitivity, specificity, PPV, NPV and accuracy of CCTA. In patients without any previous coronary interventions, the sensitivity was 97.8%, and specificity was 95.6%. The PPV and NPV were 97.8% and 95.5%, respectively. Regarding patients with coronary artery bypass grafts (CABG), the sensitivity was 95% and specificity 100%. The PPV and NPV were 100% and 90.9%, respectively. Regarding patients with prior percutaneous coronary intervention (PCI), the results were a sensitivity of 84.6%, specificity of 77.8%, PPV of 84.6% and NPV of 77.8%.

CONCLUSION

CCTA is a powerful diagnostic tool, especially for the evaluation of the major coronary arteries and evaluation of patients with prior CABG. ICA is recommended for evaluation of patients with an intracoronary stent.

Threshold Effects of Total Copper Intake on Cognitive Function in US Older Adults and the Moderating Effect of Fat and Saturated Fatty Acid Intake

BACKGROUND

Evidence for a relationship between total copper intake and cognition is lacking, and few studies have assessed the moderating effect of dietary fat and saturated fatty acid (SFA) intake on this relationship.

OBJECTIVE

Our aim was to explore the curvilinear association between total copper intake and cognitive function in older adults, and to clarify the moderating effect of dietary fat and SFA intake on the association.

DESIGN

This was a cross-sectional analysis of data from National Health and Nutrition Examination Surveys 2011-2014.

PARTICIPANTS

The analysis included 2,483 participants aged 60 years and older.

MAIN OUTCOME MEASURES

Cognitive function was evaluated by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning subtest, the Animal Fluency Test, and the Digit Symbol Substitution Test (DSST).

STATISTICAL ANALYSES PERFORMED

Smooth curve fitting and two-piecewise linear regression models were performed to address the nonlinear association between total copper intake and cognitive function. Multivariable quadratic regression models and analyses stratified by total fat or SFA intake were used to assess the effects of the interaction between copper and fat intake and between copper and SFA intake on cognitive function.

RESULTS

There was a nonlinear association between total copper intake and cognitive test scores. The inflection point of copper was 0.8 mg/d for the Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest and 1.4 mg/d for both the Animal Fluency test and the DSST. When copper intake was below the inflection point, positive associations were apparent for copper intake and Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest scores (β = 3.9; 95% CI 1.2 to 6.5), Animal Fluency test scores (β = 1.7, 95% CI .9 to 2.6), and DSST scores (β = 6.0, 95% CI 3.8 to 8.3). When copper intake was above the inflection point, a nonsignificant downward trend was found. Interactive effects between total copper and total fat intake (P interaction = .000) and between total copper and SFA intake (P interaction = .011) on the DSST scores were observed. In the low fat intake and low SFA intake groups, DSST scores first increased and then decreased with increasing copper. However, in the high fat intake and high SFA intake groups, DSST scores first increased and then flattened with increasing copper.

CONCLUSIONS

The present study suggests a nonlinear association between copper intake and cognitive function and identifies threshold effects of copper intake on cognitive function. Copper intake below the inflection point was positively and independently associated with cognitive function. High fat and high SFA intake may protect older adults against a decline in DSST scores related to high copper intake.

Outpatient Management of Patients With Angina With No Obstructive Coronary Arteries: How to Come to a Proper Diagnosis and Therapy

Two-thirds of women and one-third of men who undergo a clinically indicated coronary angiography for stable angina, have no obstructive coronary artery disease (CAD). Coronary vascular dysfunction is a highly prevalent underlying cause of angina in these so called “Angina with No Obstructive Coronary Arteries (ANOCA)” patients, foremost in middle aged women. Coronary vascular dysfunction encompasses various endotypes, namely epicardial and microvascular coronary spasms, impaired vasodilatation, and increased microvascular resistance. ANOCA patients, especially those with underlying coronary vascular dysfunction, have an adverse cardiovascular prognosis, poor physical functioning, and a reduced quality of life. Since standard ischemia detection tests and coronary angiograms are not designed to diagnose coronary vascular dysfunction, this ischemic heart disease is often overlooked and hence undertreated. But adequate diagnosis is vital, so that treatment can be started to reduce symptoms, reduce healthcare costs and improve quality of life and cardiovascular prognosis. The purpose of this review is to give a contemporary overview of ANOCA with focus on coronary vascular dysfunction. We will provide a possible work-up of patients suspected of coronary vascular dysfunction in the outpatient clinical setting, based on the latest scientific insights and international consensus documents. We will discuss the value of ischemia detection testing, and non-invasive and invasive methods to diagnose coronary vascular dysfunction. Furthermore, we will go into pharmacological and non-pharmacological therapeutic options including anti-anginal regimens and lifestyle interventions.

Multiple Cardiac Biomarker Testing Among Patients With Acute Dyspnea From the ICON-RELOADED Study

BACKGROUND

Among patients with acute dyspnea, concentrations of N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T, and insulin-like growth factor binding protein-7 predict cardiovascular outcomes and death. Understanding the optimal means to interpret these elevated biomarkers in patients presenting with acute dyspnea remains unknown.

METHODS AND RESULTS

Concentrations of NT-proBNP, high-sensitivity cardiac troponin T, and insulin-like growth factor binding protein-7 were analyzed in 1448 patients presenting with acute dyspnea from the prospective, multicenter International Collaborative of NT-proBNP-Re-evaluation of Acute Diagnostic Cut-Offs in the Emergency Department (ICON-RELOADED) Study. Eight biogroups were derived based upon patterns in biomarker elevation at presentation and compared for differences in baseline characteristics. Of 441 patients with elevations in all 3 biomarkers, 218 (49.4%) were diagnosed with acute heart failure (HF). The frequency of acute HF diagnosis in this biogroup was higher than those with elevations in 2 biomarkers (18.8%, 44 of 234), 1 biomarker (3.8%, 10 of 260), or no elevated biomarkers (0.4%, 2 of 513). The absolute number of elevated biomarkers on admission was prognostic of the composite end point of mortality and HF rehospitalization. In adjusted models, patients with one, 2, and 3 elevated biomarkers had 3.74 (95% confidence interval [CI], 1.26-11.1, P = .017), 12.3 (95% CI, 4.60-32.9, P < .001), and 12.6 (95% CI, 4.54-35.0, P < .001) fold increased risk of 180-day mortality or HF rehospitalization.

CONCLUSIONS

A multimarker panel of NT-proBNP, hsTnT, and IGBFP7 provides unique clinical, diagnostic, and prognostic information in patients presenting with acute dyspnea. Differences in the number of elevated biomarkers at presentation may allow for more efficient clinical risk stratification of short-term mortality and HF rehospitalization.

High-Sensitivity Cardiac Troponin on Presentation to Rule Out Myocardial Infarction: A Stepped-Wedge Cluster Randomized Controlled Trial

BACKGROUND

High-sensitivity cardiac troponin assays enable myocardial infarction to be ruled out earlier, but the safety and efficacy of this approach is uncertain. We investigated whether an early rule-out pathway is safe and effective for patients with suspected acute coronary syndrome.

METHODS

We performed a stepped-wedge cluster randomized controlled trial in the emergency departments of 7 acute care hospitals in Scotland. Consecutive patients presenting with suspected acute coronary syndrome between December 2014 and December 2016 were included. Sites were randomized to implement an early rule-out pathway where myocardial infarction was excluded if high-sensitivity cardiac troponin I concentrations were <5 ng/L at presentation. During a previous validation phase, myocardial infarction was ruled out when troponin concentrations were <99th percentile at 6 to 12 hours after symptom onset. The coprimary outcome was length of stay (efficacy) and myocardial infarction or cardiac death after discharge at 30 days (safety). Patients were followed for 1 year to evaluate safety and other secondary outcomes.

RESULTS

We enrolled 31 492 patients (59±17 years of age [mean±SD]; 45% women) with troponin concentrations <99th percentile at presentation. Length of stay was reduced from 10.1±4.1 to 6.8±3.9 hours (adjusted geometric mean ratio, 0.78 [95% CI, 0.73-0.83]; P<0.001) after implementation and the proportion of patients discharged increased from 50% to 71% (adjusted odds ratio, 1.59 [95% CI, 1.45-1.75]). Noninferiority was not demonstrated for the 30-day safety outcome (upper limit of 1-sided 95% CI for adjusted risk difference, 0.70% [noninferiority margin 0.50%]; P=0.068), but the observed differences favored the early rule-out pathway (0.4% [57/14 700] versus 0.3% [56/16 792]). At 1 year, the safety outcome occurred in 2.7% (396/14 700) and 1.8% (307/16 792) of patients before and after implementation (adjusted odds ratio, 1.02 [95% CI, 0.74-1.40]; P=0.894), and there were no differences in hospital reattendance or all-cause mortality.

CONCLUSIONS

Implementation of an early rule-out pathway for myocardial infarction reduced length of stay and hospital admission. Although noninferiority for the safety outcome was not demonstrated at 30 days, there was no increase in cardiac events at 1 year. Adoption of this pathway would have major benefits for patients and health care providers. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03005158.

Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department

BACKGROUND

Chest pain is among the most common presenting complaints in the emergency department (ED). Swift and accurate risk stratification of chest pain patients in the ED may improve patient outcomes and reduce unnecessary costs. Traditional logistic regression with stepwise variable selection has been used to build risk prediction models for ED chest pain patients. In this study, we aimed to investigate if machine learning dimensionality reduction methods can improve performance in deriving risk stratification models.

METHODS

A retrospective analysis was conducted on the data of patients > 20 years old who presented to the ED of Singapore General Hospital with chest pain between September 2010 and July 2015. Variables used included demographics, medical history, laboratory findings, heart rate variability (HRV), and heart rate n-variability (HRnV) parameters calculated from five to six-minute electrocardiograms (ECGs). The primary outcome was 30-day major adverse cardiac events (MACE), which included death, acute myocardial infarction, and revascularization within 30 days of ED presentation. We used eight machine learning dimensionality reduction methods and logistic regression to create different prediction models. We further excluded cardiac troponin from candidate variables and derived a separate set of models to evaluate the performance of models without using laboratory tests. Receiver operating characteristic (ROC) and calibration analysis was used to compare model performance.

RESULTS

Seven hundred ninety-five patients were included in the analysis, of which 247 (31%) met the primary outcome of 30-day MACE. Patients with MACE were older and more likely to be male. All eight dimensionality reduction methods achieved comparable performance with the traditional stepwise variable selection; The multidimensional scaling algorithm performed the best with an area under the curve of 0.901. All prediction models generated in this study outperformed several existing clinical scores in ROC analysis.

CONCLUSIONS

Dimensionality reduction models showed marginal value in improving the prediction of 30-day MACE for ED chest pain patients. Moreover, they are black box models, making them difficult to explain and interpret in clinical practice.

Prospective Validation and Comparative Analysis of Coronary Risk Stratification Strategies Among Emergency Department Patients With Chest Pain

Background

Coronary risk stratification is recommended for emergency department patients with chest pain. Many protocols are designed as “rule‐out” binary classification strategies, while others use graded‐risk stratification. The comparative performance of competing approaches at varying levels of risk tolerance has not been widely reported.

Methods and Results

This is a prospective cohort study of adult patients with chest pain presenting between January 2018 and December 2019 to 13 medical center emergency departments within an integrated healthcare delivery system. Using an electronic clinical decision support interface, we externally validated and assessed the net benefit (at varying risk thresholds) of several coronary risk scores (History, ECG, Age, Risk Factors, and Troponin [HEART] score, HEART pathway, Emergency Department Assessment of Chest Pain Score Accelerated Diagnostic Protocol), troponin‐only strategies (fourth‐generation assay), unstructured physician gestalt, and a novel risk algorithm (RISTRA‐ACS). The primary outcome was 60‐day major adverse cardiac event defined as myocardial infarction, cardiac arrest, cardiogenic shock, coronary revascularization, or all‐cause mortality. There were 13 192 patient encounters included with a 60‐day major adverse cardiac event incidence of 3.7%. RISTRA‐ACS and HEART pathway had the lowest negative likelihood ratios (0.06, 95% CI, 0.03–0.10 and 0.07, 95% CI, 0.04–0.11, respectively) and the greatest net benefit across a range of low‐risk thresholds. RISTRA‐ACS demonstrated the highest discrimination for 60‐day major adverse cardiac event (area under the receiver operating characteristic curve 0.92, 95% CI, 0.91–0.94, P<0.0001).

Conclusions

RISTRA‐ACS and HEART pathway were the optimal rule‐out approaches, while RISTRA‐ACS was the best‐performing graded‐risk approach. RISTRA‐ACS offers promise as a versatile single approach to emergency department coronary risk stratification.

Registration

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03286179.

The Role of Using HEART Score to Risk Stratify Chest Pain Among Emergency Department High Utilizers

The HEART score is used to effectively risk stratify undifferentiated chest pain patients in the Emergency Department (ED). It is unclear whether such risk stratification can be applied among ED high utilizers. We aim to determine the efficacy and safety of using the HEART score to predict 30-day short-term major adverse cardiac events (MACE) in ED high utilizers. We conducted a retrospective, observational study in which ED high utilizers were defined as patients who had four or more ED visits within the past 12 months. ED high utilizers presenting at the study ED with chest pain were enrolled. Patients in which the HEART score was utilized were placed in the HEART group and patients with no HEART scores documented were placed to the usual care group. Hospital admissions and cardiac stress tests performed during the index hospitalizations, and 30-day MACE rates were analyzed and compared between the HEART and usual care groups. From January 1, 2017 to December 31, 2019, a total of 8,315 patient visits from ED high utilizers were enrolled. In the HEART group, 49% of ED visits were admitted with 20% receiving stress tests. A 30-day MACE outcome occurred among 1.4% of visits. In the usual care group, 44% of ED visits were admitted, with only 9% receiving index stress tests and a 1.5% of 30-day MACE occurrence (p=0.727). The study showed that similar short-term MACE outcomes occurred between patients using HEART scores and usual care to risk stratify chest pain among ED high utilizers.

Cardiac MRI in Patients with Acute Chest Pain

Acute chest pain is a common reason for visits to the emergency department. It is important to distinguish among the various causes of acute chest pain, because treatment and prognosis are substantially different among the various conditions. It is critical to exclude acute coronary syndrome (ACS), which is a major cause of hospitalization, death, and health care costs worldwide. Myocardial ischemia is defined as potential myocyte death secondary to an imbalance between oxygen supply and demand due to obstruction of an epicardial coronary artery. Unobstructed coronary artery disease can have cardiac causes (eg, myocarditis, myocardial infarction with nonobstructed coronary arteries, and Takotsubo cardiomyopathy), and noncardiac diseases can manifest with acute chest pain and increased serum cardiac biomarker levels. In the emergency department, cardiac MRI may aid in the identification of patients with non-ST-segment elevation myocardial infarction or unstable angina or ACS with unobstructed coronary artery disease, if the patient's clinical history is known to be atypical. Also, cardiac MRI is excellent for risk stratification of patients for adverse left ventricular remodeling or major adverse cardiac events. Cardiac MRI should be performed early in the course of the disease (<2 weeks after onset of symptoms). Steady-state free-precession T2-weighted MRI with late gadolinium enhancement is the mainstay of the cardiac MRI protocol. Further sequences can be used to analyze the different pathophysiologic subjacent mechanisms of the disease, such as microvascular obstruction or intramyocardial hemorrhage. Finally, cardiac MRI may provide several prognostic biomarkers that help in follow-up of these patients. Online supplemental material is available for this article. ^©RSNA, 2020.

ACR Appropriateness Criteria® Acute Nonspecific Chest Pain-Low Probability of Coronary Artery Disease

Patients with acute nonspecific chest pain and low probability for coronary disease remain an important clinical management dilemma. We focus on evidence for imaging, in an integrated decision-making setting. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

An extracellular vesicle epitope profile is associated with acute myocardial infarction

The current standard biomarker for myocardial infarction (MI) is high-sensitive troponin. Although powerful in clinical setting, search for new markers is warranted as early diagnosis of MI is associated with improved outcomes. Extracellular vesicles (EVs) attracted considerable interest as new blood biomarkers. A training cohort used for diagnostic modelling included 30 patients with STEMI, 38 with stable angina (SA) and 30 matched-controls. Extracellular vesicle concentration was assessed by nanoparticle tracking analysis. Extracellular vesicle surface-epitopes were measured by flow cytometry. Diagnostic models were developed using machine learning algorithms and validated on an independent cohort of 80 patients. Serum EV concentration from STEMI patients was increased as compared to controls and SA. EV levels of CD62P, CD42a, CD41b, CD31 and CD40 increased in STEMI, and to a lesser extent in SA patients. An aggregate marker including EV concentration and CD62P/CD42a levels achieved non-inferiority to troponin, discriminating STEMI from controls (AUC = 0.969). A random forest model based on EV biomarkers discriminated the two groups with 100% accuracy. EV markers and RF model confirmed high diagnostic performance at validation. In conclusion, patients with acute MI or SA exhibit characteristic EV biomarker profiles. EV biomarkers hold great potential as early markers for the management of patients with MI.

Evaluation and comparison of six GRACE models for the stratification of undifferentiated chest pain in the emergency department

Background

The Global Registry of Acute Coronary Events (GRACE) score is recommended for stratifying chest pain. However, there are six formulas used to calculate the GRACE score for different outcomes of acute coronary syndrome (ACS), including death (Dth) or composite of death and myocardial infarction (MI), while in hospital (IH), within 6 months after discharge (OH6m) or from admission to 6 months later (IH6m). We aimed to perform the first comprehensive evaluation and comparison of six GRACE models to predict 30-day major adverse cardiac events (MACEs) in patients with acute chest pain in the emergency department (ED).

Methods

Patients with acute chest pain were consecutively recruited from August 24, 2015 to September 30, 2017 from the EDs of two public hospitals in China. The 30-day MACEs included death, acute myocardial infarction (AMI), emergency revascularization, cardiac arrest and cardiogenic shock. The correlation, calibration, discrimination, reclassification and diagnostic accuracy at certain cutoff values of six GRACE models were evaluated. Comparisons with the History, ECG, Age, Risk Factors, and Troponin (HEART) and Thrombolysis in Myocardial Infarction (TIMI) scores were conducted.

Results

A total of 2886 patients were analyzed, with 590 (20.4%) patients experiencing outcomes. The GRACE (IHDthMI), GRACE (IH6mDthMI), GRACE (IHDth), GRACE (IH6mDth), GRACE (OH6mDth) and GRACE (OH6mDthMI) showed positive linear correlations with the actual MACE rates (r ≥ 0.568, P < 0.001). All these models had good calibration (Hosmer-Lemeshow test, P ≥ 0.073) except GRACE (IHDthMI) (P < 0.001). The corresponding C-statistics were 0.83(0.81,0.84), 0.82(0.81,0.83), 0.75(0.73,0.76), 0.73(0.72,0.75), 0.72(0.70,0.73) and 0.70(0.68,0.71), respectively, first two of which were comparable to HEART (0.82, 0.80–0.83) and superior to TIMI (0.71, 0.69–0.73). With a sensitivity ≥95%, GRACE (IHDthMI) ≤81 and GRACE (IH6mDthMI) ≤79 identified 868(30%) and 821(28%) patients as low risk, respectively, which were significantly better than other GRACEs and HEART ≤3(22%). With a specificity ≥95%, GRACE (IHDthMI) > 186 and GRACE (IH6mDthMI) > 161 could recognize 12% and 11% patients as high risk, which were greater than other GRACEs, HEART ≥8(9%) and TIMI ≥5(8%).

Conclusions

In this Chinese setting, certain strengths of GRACE models beyond HEART and TIMI scores were still noteworthy for stratifying chest pain patients. The validation and reasonable application of appropriate GRACE models in the evaluation of undifferentiated chest pain should be recommended.

Heart rate n-variability (HRnV) and its application to risk stratification of chest pain patients in the emergency department

Background

Chest pain is one of the most common complaints among patients presenting to the emergency department (ED). Causes of chest pain can be benign or life threatening, making accurate risk stratification a critical issue in the ED. In addition to the use of established clinical scores, prior studies have attempted to create predictive models with heart rate variability (HRV). In this study, we proposed heart rate n-variability (HRnV), an alternative representation of beat-to-beat variation in electrocardiogram (ECG), and investigated its association with major adverse cardiac events (MACE) in ED patients with chest pain.

Methods

We conducted a retrospective analysis of data collected from the ED of a tertiary hospital in Singapore between September 2010 and July 2015. Patients > 20 years old who presented to the ED with chief complaint of chest pain were conveniently recruited. Five to six-minute single-lead ECGs, demographics, medical history, troponin, and other required variables were collected. We developed the HRnV-Calc software to calculate HRnV parameters. The primary outcome was 30-day MACE, which included all-cause death, acute myocardial infarction, and revascularization. Univariable and multivariable logistic regression analyses were conducted to investigate the association between individual risk factors and the outcome. Receiver operating characteristic (ROC) analysis was performed to compare the HRnV model (based on leave-one-out cross-validation) against other clinical scores in predicting 30-day MACE.

Results

A total of 795 patients were included in the analysis, of which 247 (31%) had MACE within 30 days. The MACE group was older, with a higher proportion being male patients. Twenty-one conventional HRV and 115 HRnV parameters were calculated. In univariable analysis, eleven HRV and 48 HRnV parameters were significantly associated with 30-day MACE. The multivariable stepwise logistic regression identified 16 predictors that were strongly associated with MACE outcome; these predictors consisted of one HRV, seven HRnV parameters, troponin, ST segment changes, and several other factors. The HRnV model outperformed several clinical scores in the ROC analysis.

Conclusions

The novel HRnV representation demonstrated its value of augmenting HRV and traditional risk factors in designing a robust risk stratification tool for patients with chest pain in the ED.

Diagnosis and risk stratification of chest pain patients in the emergency department: focus on acute coronary syndromes. A position paper of the Acute Cardiovascular Care Association

This paper provides an update on the European Society of Cardiology task force report on the management of chest pain. Its main purpose is to provide an update on the decision algorithms and diagnostic pathways to be used in the emergency department for the assessment and triage of patients with chest pain symptoms suggestive of acute coronary syndromes.

Comparison of usual care and the HEART score for effectively and safely discharging patients with low-risk chest pain in the emergency department: would the score always help?

Background

Triage decisions for chest pain patients receiving usual care are based on a dynamic and comprehensive strategy performed in the physician's mind. It remains controversial whether simple, structured risk tools can surpass real, complex judgments.

Hypothesis

The potentially used History, Electrocardiogram, Age, Risk factors, Troponin (HEART) score would help identify low‐risk patients for discharge.

Methods

Patients with acute, non‐traumatic chest pain managed according to usual care were consecutively enrolled in a tertiary university hospital in China from August 24, 2015 to September 30, 2017. Major adverse cardiac events (MACE) included death, acute myocardial infarction, revascularization, and significant coronary stenosis (>50%) within 30 days. We compared the efficacy and safety of usual care and the potentially used HEART score in this population.

Results

Of 2185 patients analyzed, 926 (42.4%) patients were directly discharged by usual care, whereas HEART≤3 would have identified 524 (24.0%) patients as low‐risk (P < .001). The MACE rate in discharged patients was 2.2% (20/926) and would have been 5.2% (27/524) in those with HEART≤3 (P = .002). For discharged patients, the MACE rates in HEART≤3 vs HEART>3 groups were not significantly different (1.5% vs 2.7%, P = .225). Negative predictive value (NPV) was higher with usual care than with the HEART score (P = .003), but sensitivity was similar. For 340 patients with serial troponins, usual care was superior to the potentially used HEART score in regard to efficacy.

Conclusions

At this institution, usual care identified many more patients for discharge than the HEART score would have without apparently different outcomes in discharged patients with lower vs higher HEART scores. The HEART score would not appear to provide helpful risk stratification.

High-Sensitivity Troponin and the Application of Risk Stratification Thresholds in Patients With Suspected Acute Coronary Syndrome

BACKGROUND

Guidelines acknowledge the emerging role of high-sensitivity cardiac troponin (hs-cTnl) for risk stratification and the early rule-out of myocardial infarction, but multiple thresholds have been described. We evaluate the safety and effectiveness of risk stratification thresholds in patients with suspected acute coronary syndrome.

METHODS

Consecutive patients with suspected acute coronary syndrome (n=48 282) were enrolled in a multicenter trial across 10 hospitals in Scotland. In a prespecified secondary and observational analysis, we compared the performance of the limit of detection (<2 ng/L) and an optimized risk stratification threshold (<5 ng/L) using the Abbott high-sensitivity troponin I assay. Patients with myocardial injury at presentation, with ≤2 hours of symptoms or with ST-segment elevation myocardial infarction were excluded. The negative predictive value was determined in all patients and in subgroups for a primary outcome of myocardial infarction or cardiac death within 30 days. The secondary outcome was myocardial infarction or cardiac death at 12 months, with risk modeled using logistic regression adjusted for age and sex.

RESULTS

In total, 32 837 consecutive patients (61±17 years, 47% female) were included, of whom 23 260 (71%) and 12,716 (39%) had hs-cTnl concentrations of <5 ng/L and <2 ng/L at presentation. The negative predictive value for the primary outcome was 99.8% (95% CI, 99.7%-99.8%) and 99.9% (95% CI, 99.8%-99.9%) in those with hs-cTnl concentrations of <5 ng/L and <2 ng/L, respectively. At both thresholds, the negative predictive value was consistent in men and women and across all age groups, although the proportion of patients identified as low risk fell with increasing age. Compared with patients with hs-cTnl concentrations of ≥5 ng/L but <99th centile, the risk of myocardial infarction or cardiac death at 12 months was 77% lower in those <5 ng/L (5.3% vs 0.7%; adjusted odds ratio, 0.23 [95% CI, 0.19-0.28]) and 80% lower in those <2 ng/L (5.3% vs 0.3%; adjusted odds ratio, 0.20 [95% CI, 0.14-0.29]).

CONCLUSIONS

Use of risk stratification thresholds for hs-cTnl identify patients with suspected acute coronary syndrome and at least 2 hours of symptoms as low risk at presentation irrespective of age and sex.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT01852123.

Artificial Intelligence for Diagnosis of Acute Coronary Syndromes: A Meta-analysis of Machine Learning Approaches

BACKGROUND

Machine learning (ML) encompasses a wide variety of methods by which artificial intelligence learns to perform tasks when exposed to data. Although detection of myocardial infarction has been facilitated with introduction of troponins, the diagnosis of acute coronary syndromes (ACS) without myocardial damage (without elevation of serum troponin) remains subjective, and its accuracy remains highly dependent on clinical skills of the health care professionals. Application of a ML algorithm may expedite management of ACS for either early discharge or early initiation of ACS management. We aim to summarize the published studies of ML for diagnosis of ACS.

METHODS

We searched electronic databases, including PubMed, Embase, and Web of Science from inception up to January 13, 2019, for studies that evaluated ML algorithms for the diagnosis of ACS in patients presenting with chest pain. We then used random-effects bivariate meta-analysis models to summarize the studies.

RESULTS

We retained 9 studies that evaluated ML in a total of 6292 patients. The prevalence of ACS in the evaluated cohorts ranged from relatively rare (7%) to common (57%). The pooled sensitivity and specificity were 0.95 and 0.90, respectively. The positive predictive values ranged from 0.64 to 1.0, and the negative predictive values ranged from 0.91 to 1.0. The positive and negative likelihood ratios ranged from 1.6 to 33.0 and 0.01 to 0.13, respectively.

CONCLUSIONS

The excellent sensitivity, negative likelihood ratio, and negative predictive values suggest that ML may be useful as an initial triage tool for ruling out ACS.

Combining High-Sensitivity Cardiac Troponin I and Cardiac Troponin T in the Early Diagnosis of Acute Myocardial Infarction

BACKGROUND

Combining 2 signals of cardiomyocyte injury, cardiac troponin I (cTnI) and T (cTnT), might overcome some individual pathophysiological and analytical limitations and thereby increase diagnostic accuracy for acute myocardial infarction with a single blood draw. We aimed to evaluate the diagnostic performance of combinations of high-sensitivity (hs) cTnI and hs-cTnT for the early diagnosis of acute myocardial infarction.

METHODS

The diagnostic performance of combining hs-cTnI (Architect, Abbott) and hs-cTnT (Elecsys, Roche) concentrations (sum, product, ratio, and a combination algorithm) obtained at the time of presentation was evaluated in a large multicenter diagnostic study of patients with suspected acute myocardial infarction. The optimal rule-out and rule-in thresholds were externally validated in a second large multicenter diagnostic study. The proportion of patients eligible for early rule-out was compared with the European Society of Cardiology 0/1 and 0/3 hour algorithms.

RESULTS

Combining hs-cTnI and hs-cTnT concentrations did not consistently increase overall diagnostic accuracy as compared with the individual isoforms. However, the combination improved the proportion of patients meeting criteria for very early rule-out. With the European Society of Cardiology 2015 guideline recommended algorithms and cut-offs, the proportion meeting rule-out criteria after the baseline blood sampling was limited (6% to 24%) and assay dependent. Application of optimized cut-off values using the sum (9 ng/L) and product (18 ng²/L²) of hs-cTnI and hs-cTnT concentrations led to an increase in the proportion ruled-out after a single blood draw to 34% to 41% in the original (sum: negative predictive value [NPV] 100% [95% confidence interval (CI), 99.5% to 100%]; product: NPV 100% [95% CI, 99.5% to 100%]) and in the validation cohort (sum: NPV 99.6% [95% CI, 99.0-99.9%]; product: NPV 99.4% [95% CI, 98.8-99.8%]). The use of a combination algorithm (hs-cTnI <4 ng/L and hs-cTnT <9 ng/L) showed comparable results for rule-out (40% to 43% ruled out; NPV original cohort 99.9% [95% CI, 99.2-100%]; NPV validation cohort 99.5% [95% CI, 98.9-99.8%]) and rule-in (positive predictive value [PPV] original cohort 74.4% [95% Cl, 69.6-78.8%]; PPV validation cohort 84.0% [95% Cl, 79.7-87.6%]).

CONCLUSIONS

New strategies combining hs-cTnI and hs-cTnT concentrations may significantly increase the number of patients eligible for very early and safe rule-out, but do not seem helpful for the rule-in of acute myocardial infarction.

CLINICAL TRIAL REGISTRATION

URL (APACE): https://www.clinicaltrial.gov . Unique identifier: NCT00470587. URL (ADAPT): www.anzctr.org.au . Unique identifier: ACTRN12611001069943.

Machine Learning to Predict the Likelihood of Acute Myocardial Infarction

BACKGROUND

Variations in cardiac troponin concentrations by age, sex, and time between samples in patients with suspected myocardial infarction are not currently accounted for in diagnostic approaches. We aimed to combine these variables through machine learning to improve the assessment of risk for individual patients.

METHODS

A machine learning algorithm (myocardial-ischemic-injury-index [MI3]) incorporating age, sex, and paired high-sensitivity cardiac troponin I concentrations, was trained on 3013 patients and tested on 7998 patients with suspected myocardial infarction. MI3 uses gradient boosting to compute a value (0-100) reflecting an individual's likelihood of a diagnosis of type 1 myocardial infarction and estimates the sensitivity, negative predictive value, specificity and positive predictive value for that individual. Assessment was by calibration and area under the receiver operating characteristic curve. Secondary analysis evaluated example MI3 thresholds from the training set that identified patients as low risk (99% sensitivity) and high risk (75% positive predictive value), and performance at these thresholds was compared in the test set to the 99th percentile and European Society of Cardiology rule-out pathways.

RESULTS

Myocardial infarction occurred in 404 (13.4%) patients in the training set and 849 (10.6%) patients in the test set. MI3 was well calibrated with a very high area under the receiver operating characteristic curve of 0.963 [0.956-0.971] in the test set and similar performance in early and late presenters. Example MI3 thresholds identifying low- and high-risk patients in the training set were 1.6 and 49.7, respectively. In the test set, MI3 values were <1.6 in 69.5% with a negative predictive value of 99.7% (99.5-99.8%) and sensitivity of 97.8% (96.7-98.7%), and were ≥49.7 in 10.6% with a positive predictive value of 71.8% (68.9-75.0%) and specificity of 96.7% (96.3-97.1%). Using these thresholds, MI3 performed better than the European Society of Cardiology 0/3-hour pathway (sensitivity, 82.5% [74.5-88.8%]; specificity, 92.2% [90.7-93.5%]) and the 99th percentile at any time point (sensitivity, 89.6% [87.4-91.6%]); specificity, 89.3% [88.6-90.0%]).

CONCLUSIONS

Using machine learning, MI3 provides an individualized and objective assessment of the likelihood of myocardial infarction, which can be used to identify low- and high-risk patients who may benefit from earlier clinical decisions.

CLINICAL TRIAL REGISTRATION

URL: https://www.anzctr.org.au. Unique identifier: ACTRN12616001441404.

A comprehensive validation of very early rule-out strategies for non-ST-segment elevation myocardial infarction in emergency departments: protocol for a multicentre prospective cohort study

INTRODUCTION

Recent advances in troponin sensitivity enabled early and accurate judgement of ruling-out myocardial infarction, especially non-ST elevation myocardial infarction (NSTEMI) in emergency departments (EDs) with development of various prediction-rules and high-sensitive-troponin-based strategies (hs-troponin). Reliance on clinical impression, however, is still common, and it remains unknown which of these strategies is superior. Therefore, our objective in this prospective cohort study is to comprehensively validate the diagnostic accuracy of clinical impression-based strategies, prediction-rules and hs-troponin-based strategies for ruling-out NSTEMIs.

METHODS AND ANALYSIS

In total, 1500 consecutive adult patients with symptoms suggestive of acute coronary syndrome will be prospectively recruited from five EDs in two tertiary-level, two secondary-level community hospitals and one university hospital in Japan. The study has begun in July 2018, and recruitment period will be about 1 year. A board-certified emergency physician will complete standardised case report forms, and independently perform a clinical impression-based risk estimation of NSTEMI. Index strategies to be compared will include the clinical impression-based strategy; prediction rules and hs-troponin-based strategies for the following types of troponin (Roche Elecsys hs-troponin T; Abbott ARCHITECT hs-troponin I; Siemens ADVIA Centaur hs-troponin I; Siemens ADVIA Centaur sensitive-troponin I). The reference standard will be the composite of type 1 MI and cardiac death within 30 days after admission to the ED. Outcome measures will be negative predictive value, sensitivity and effectiveness, defined as the proportion of patients categorised as low risk for NSTEMI. We will also evaluate inter-rater reliability of the clinical impression-based risk estimation.

ETHICS AND DISSEMINATION

The study is approved by the Ethics Committees of the Kyoto University Graduate School and Faculty of Medicine and of the five hospitals where we will recruit patients. We will disseminate the study results through conference presentations and peer-reviewed journals.

Trimethyllysine, a trimethylamine N-oxide precursor, provides near- and long-term prognostic value in patients presenting with acute coronary syndromes

AIMS

Trimethyllysine (TML) serves as a nutrient precursor of the gut microbiota-derived metabolite trimethylamine N-oxide (TMAO) and is associated with incident cardiovascular (CV) events in stable subjects. We examined the relationship between plasma TML levels and incident CV events in patients presenting with acute coronary syndromes (ACS).

METHODS AND RESULTS

Plasma levels of TML were quantified in two independent cohorts using mass spectrometry, and its relationship with CV events was investigated. In a Cleveland Cohort (N = 530), comprised of patients presenting to the emergency department with chest pain and suspected ACS, TML was associated with major adverse cardiac events (MACE, myocardial infarction, stroke, need for revascularization, or all-cause mortality) over both 30 days [3rd tertile (T3), adjusted odds ratio (OR) 1.77, 95% confidence interval (CI) 1.04-3.01; P < 0.05] and 6 months (T3, adjusted OR 1.95, 95% CI 1.15-3.32; P < 0.05) of follow-up independent of traditional CV risk factors and indices of renal function. Elevated TML levels were also associated with incident long-term (7-year) all-cause mortality [T3, adjusted hazard ratio (HR) 2.52, 95% CI 1.50-4.24; P < 0.001], and MACE even amongst patients persistently negative for cardiac Troponin T at presentation (e.g. 30-day MACE, T3, adjusted OR 4.49, 95% CI 2.06-9.79; P < 0.001). Trimethyllysine in combination with TMAO showed additive significance for near- and long-term CV events, including patients with 'negative' high-sensitivity Troponin T levels. In a multicentre Swiss Cohort (N = 1683) comprised of ACS patients, similar associations between TML and incident 1-year adverse cardiac risks were observed (e.g. mortality, adjusted T3 HR 2.74, 95% CI 1.28-5.85; P < 0.05; and MACE, adjusted T3 HR 1.55, 95% CI 1.04-2.31; P < 0.05).

CONCLUSION

Plasma TML levels, alone and together with TMAO, are associated with both near- and long-term CV events in patients with chest pain and ACS.

Multicentre cross-sectional observational registry to monitor the safety of early discharge after rule-out of acute myocardial infarction by copeptin and troponin: the Pro-Core registry

OBJECTIVES

There is sparse information on the safety of early primary discharge from the emergency department (ED) after rule-out of myocardial infarction in suspected acute coronary syndrome (ACS). This prospective registry aimed to confirm randomised study results in patients at low-to-intermediate risk, with a broader spectrum of symptoms, across different institutional standards and with a range of local troponin assays including high-sensitivity cTn (hs-cTn), cardiac troponin (cTn) and point-of-care troponin (POC Tn).

DESIGN

Prospective, multicentre European registry.

SETTING

18 emergency departments in nine European countries (Germany, Austria, Switzerland, France, Spain, UK, Turkey, Lithuania and Hungary) PARTICIPANTS: The final study cohort consisted of 2294 patients (57.2% males, median age 57 years) with suspected ACS.

INTERVENTIONS

Using the new dual markers strategy, 1477 patients were eligible for direct discharge, which was realised in 974 (42.5%) of patients.

MAIN OUTCOME MEASURES

The primary endpoint was all-cause mortality at 30 days.

RESULTS

Compared with conventional workup after dual marker measurement, the median length of ED stay was 60 min shorter (228 min, 95% CI: 219 to 239 min vs 288 min, 95% CI: 279 to 300 min) in the primary dual marker strategy (DMS) discharge group. All-cause mortality was 0.1% (95% CI: 0% to 0.6%) in the primary DMS discharge group versus 1.1% (95% CI: 0.6% to 1.8%) in the conventional workup group after dual marker measurement. Conventional workup instead of discharge despite negative DMS biomarkers was observed in 503 patients (21.9%) and associated with higher prevalence of ACS (17.1% vs 0.9%, p<0.001), cardiac diagnoses (55.2% vs 23.5%, p<0.001) and risk factors (p<0.01), but with a similar all-cause mortality of 0.2% (95% CI: 0% to 1.1%) versus primary DMS discharge (p=0.64).

CONCLUSIONS

Copeptin on top of cardiac troponin supports safe discharge in patients with chest pain or other symptoms suggestive of ACS under routine conditions with the use of a broad spectrum of local standard POC, conventional and high-sensitivity troponin assays.

TRIAL REGISTRATION NUMBER

NCT02490969.

Early diagnostic value of circulating microRNAs in patients with suspected acute myocardial infarction

BACKGROUND/AIMS

Evidence has shown that several microRNAs (miRNAs) may be involved in coronary plaque rupture and local thrombus. However, the diagnostic ability of these miRNAs in acute myocardial infarction (AMI) is less known. The aim of this study is to explore the diagnostic value of these circulating miRNAs in patients presenting with acute chest pain in the emergency department.

METHODS AND RESULTS

In a nested case-control study, 140 of 1,206 patients finally diagnosed with AMI were matched with 70 unstable angina and 70 noncardiac chest pain patients. Five candidate miRNAs (miR-483-5p, miR-155-5p, miR-451, miR-19b, and miR-223) were selected for validation. Among them, miR-19b, miR-223, and miR-483-5p were significantly higher in AMI patients compared with those without AMI. A multivariate analysis showed that these miRNAs were independent predictors of AMI. The overall areas under the receiver operating curves (AUCs) for miR-19b, miR-223, and miR-483-5p were 0.74, 0.65, and 0.70, respectively. However, serial sampling in AMI patients showed that these miRNAs already peaked on admission, which was earlier than troponin I. Among 170 patients with a negative troponin result at presentation, a panel of three miRNAs improved the discrimination ability to a clinical model. In 119 patients presenting within 3 hr after chest-pain onset, the diagnostic accuracy of each miRNAs was higher than Point of care (POC) troponin assay. And a panel of these miRNAs had an AUC of 0.92.

CONCLUSION

Circulating miR-19b, miR-223, and miR-483-5p may provide clinically useful information for diagnosis in the early phases of AMI.

Correlation of Triiodothyronine Level with In-Hospital Cardiac Function and Long-Term Prognosis in Patients with Acute Myocardial Infarction

Objective

The pathophysiologic mechanism of how thyroid function is related to the development and prognosis of acute myocardial infarction (AMI) remains under explored, and there has been a lack of clinical investigations. In this study, we investigate the relationship between triiodothyronine (T3) level and cardiac ejection fraction (EF) as well as probrain natriuretic peptide (NT-proBNP) on admission and subsequent prognosis in AMI patients.

Methods

We measured admission thyroid function, NT-proBNP, and EF by echocardiography in 345 patients diagnosed with AMI. Simple and multiregression analyses were performed to investigate the correlation between T3 level and EF as well as NT-proBNP. Major adverse cardiovascular events (MACE), including new-onset myocardial infarction, acute heart failure, and cardiac death, were documented during the follow-up. 248 participants were separated into three groups based on T3 and free triiodothyronine (FT3) levels for survival analysis during a 2-year follow-up.

Results

345 patients diagnosed with AMI were included in the initial observational analysis. 248 AMI patients were included in the follow-up survival analysis. The T3 levels were found to be significantly positively correlated with EF (R square = 0.042, P < 0.001) and negatively correlated with admission NT-proBNP levels (R square = 0.059, P < 0.001), which is the same with the correlation between FT3 and EF (R square = 0.053, P < 0.001) and admission NT-proBNP levels (R square = 0.108, P < 0.001). Kaplan-Meier survival analysis revealed no significant difference with regard to different T3 or FT3 levels at the end of follow-up.

Conclusions

T3 and FT3 levels are moderately positively correlated with cardiac function on admission in AMI patients but did not predict a long-time survival rate. Further studies are needed to explain whether longer-term follow-up would further identify the prognosis effect of T3 on MACE and all-cause mortality.

Characteristics and Outcomes of Patients Hospitalized With Suspected Acute Coronary Syndrome in Whom the Diagnosis is not Confirmed

Patients admitted with suspected acute coronary syndrome (ACS) in whom the diagnosis is not confirmed are poorly characterized. In a contemporary registry of consecutive patients hospitalized with suspected ACS as the primary diagnosis, we assessed characteristics on admission and in-hospital and 6-month mortality of patients discharged with other diagnoses and compared this subgroup with true ACS patients. Of 2557 patients included, 9.0% were discharged with a non-ACS diagnosis such as nonspecific chest pain, myopericarditis, stress cardiomyopathy, hemodynamic disturbances, heart failure, myocardial, pulmonary or valvular disease, or others. Compared with true ACS patients, those with other diagnoses were younger, more often female, and had less cardiovascular risk factors. Both groups had comparable rates of nonchest pain presentation and similar hemodynamic characteristics on admission. Non-ACS patients presented less often with Q waves or with ST-segment or T-wave changes and had a lower Global Registry of Acute Coronary Events score than true ACS patients. In-hospital (4.3 vs 4.0%, respectively, p = 0.834) and 6-month (5.4 vs 8.0%, respectively, p = 0.163) mortality rates were comparable in both groups. However, if patients in the non-ACS group were divided into subgroups with nonspecific chest pain (6.2% of total) or other diagnoses (2.8% of total), major differences in in-hospital (0.0 vs 13.9%, respectively, p < 0.001) and 6-month (0.7 vs 15.7%, respectively, p < 0.001) mortality rates would become apparent and remain after multivariable adjustment. In conclusion, in a non-negligible proportion of patients hospitalized with suspected ACS, this diagnosis is not confirmed. Prognosis of these patients follows a bimodal pattern, being excellent in those with nonspecific chest pain but worse than that of true ACS patients in the rest. Efforts are necessary to ensure prompt identification and early risk stratification of these patients allowing appropriate management decisions.

[Essential cardiac biomarkers in the differential diagnosis of acute chest pain : An update]

Cardiac biomarkers are an integral part of the diagnostic work-up and risk stratification of patients with chest pain. Cardiac troponins are highly sensitive diagnostic biomarkers in patients with acute coronary syndrome and have prognostic value in a multitude of acute and chronic diseases. In patients with suspected pulmonary embolism (PE) D‑dimer can be used together with the Wells score for exclusion of PE. In patients with confirmed PE, B‑type natriuretic peptide (BNP), N‑terminal pro-BNP (NT-proBNP) and heart-type fatty acid binding protein (h-FABP) can be used for risk stratification. Although normal D‑dimer levels largely decrease the possibility of acute aortic dissection, clinicians should not rely on D‑dimer alone to exclude the diagnosis of acute aortic syndrome. This continuing medical education article provides an overview of the most important biomarkers recommended in current guidelines for differential diagnoses of patients with chest pain with a focus on cardiac troponins in acute coronary syndrome.

Spontaneous Coronary Artery Dissection: Current State of the Science: A Scientific Statement From the American Heart Association

Spontaneous coronary artery dissection (SCAD) has emerged as an important cause of acute coronary syndrome, myocardial infarction, and sudden death, particularly among young women and individuals with few conventional atherosclerotic risk factors. Patient-initiated research has spurred increased awareness of SCAD, and improved diagnostic capabilities and findings from large case series have led to changes in approaches to initial and long-term management and increasing evidence that SCAD not only is more common than previously believed but also must be evaluated and treated differently from atherosclerotic myocardial infarction. High rates of recurrent SCAD; its association with female sex, pregnancy, and physical and emotional stress triggers; and concurrent systemic arteriopathies, particularly fibromuscular dysplasia, highlight the differences in clinical characteristics of SCAD compared with atherosclerotic disease. Recent insights into the causes of, clinical course of, treatment options for, outcomes of, and associated conditions of SCAD and the many persistent knowledge gaps are presented.