Cardiovascular Biomarkers in the Early Discrimination of Type 2 Myocardial Infarction

Key Points

Question  Can novel cardiovascular biomarkers aid physicians in the early discrimination of type 2 myocardial infarction (T2MI) from type 1 myocardial infarction (T1MI)?

Findings  In this international, multicenter diagnostic study, biomarkers quantifying endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress were higher in individuals with T2MI vs T1MI.

Meaning  In this analysis, biomarkers quantifying endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress provided modest discrimination in the early, noninvasive diagnosis of T2MI vs T1MI; clinical parameters may remain the only reliable means for the identification of patients with T2MI.

Importance  Rapid and accurate noninvasive discrimination of type 2 myocardial infarction (T2MI), which is because of a supply-demand mismatch, from type 1 myocardial infarction (T1MI), which arises via plaque rupture, is essential, because treatment differs substantially. Unfortunately, this is a major unmet clinical need, because even high-sensitivity cardiac troponin (hs-cTn) measurement provides only modest accuracy.

Objective  To test the hypothesis that novel cardiovascular biomarkers quantifying different pathophysiological pathways involved in T2MI and/or T1MI may aid physicians in the rapid discrimination of T2MI vs T1MI.

Design, Setting, and Participants  This international, multicenter prospective diagnostic study was conducted in 12 emergency departments in 5 countries (Switzerland, Spain, Italy, Poland, and the Czech Republic) with patients presenting with acute chest discomfort to the emergency departments. The study quantified the discrimination of hs-cTn T, hs-cTn I, and 17 novel cardiovascular biomarkers measured in subsets of consecutively enrolled patients against a reference standard (final diagnosis), centrally adjudicated by 2 independent cardiologists according to the fourth universal definition of MI, using all information, including cardiac imaging and serial measurements of hs-cTnT or hs-cTnI.

Results  Among 5887 patients, 1106 (18.8%) had an adjudicated final diagnosis of MI; of these, 860 patients (77.8%) had T1MI, and 246 patients (22.2%) had T2MI. Patients with T2MI vs those with T1MI had lower concentrations of biomarkers quantifying cardiomyocyte injury hs-cTnT (median [interquartile range (IQR)], 30 (17-55) ng/L vs 58 (28-150) ng/L), hs-cTnI (median [IQR], 23 [10-83] ng/L vs 115 [28-576] ng/L; P < .001), and cardiac myosin-binding protein C (at presentation: median [IQR], 76 [38-189] ng/L vs 257 [75-876] ng/L; P < .001) but higher concentrations of biomarkers quantifying endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress (median [IQR] values: C-terminal proendothelin 1, 97 [75-134] pmol/L vs 68 [55-91] pmol/L; midregional proadrenomedullin, 0.97 [0.67-1.51] pmol/L vs 0.72 [0.53-0.99] pmol/L; midregional pro–A-type natriuretic peptide, 378 [207-491] pmol/L vs 152 [90-247] pmol/L; and growth differentiation factor 15, 2.26 [1.44-4.35] vs 1.56 [1.02-2.19] ng/L; all P < .001). Discrimination for these biomarkers, as quantified by the area under the receiver operating characteristics curve, was modest (hs-cTnT, 0.67 [95% CI, 0.64-0.71]; hs-cTn I, 0.71 [95% CI, 0.67-0.74]; cardiac myosin-binding protein C, 0.67 [95% CI, 0.61-0.73]; C-terminal proendothelin 1, 0.73 [95% CI, 0.63-0.83]; midregional proadrenomedullin, 0.66 [95% CI, 0.60-0.73]; midregional pro–A-type natriuretic peptide, 0.77 [95% CI, 0.68-0.87]; and growth differentiation factor 15, 0.68 [95% CI, 0.58-0.79]).

Conclusions and Relevance  In this study, biomarkers quantifying myocardial injury, endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress provided modest discrimination in early, noninvasive diagnosis of T2MI.

Myocardial infarction (MI) is one of the most common causes of death worldwide.^1,2 Two different pathophysiological mechanisms underlie spontaneously occurring MI: a supply-demand mismatch because of impaired systemic hemodynamics, including hypotension, hypertension, tachycardia, or hypoxemia (type 2 MI [T2MI]); and coronary atherothrombosis triggered by plaque rupture and plaque erosion, with resulting intraluminal thrombosis (type 1 MI [T1MI]).^1-4 Because treatments differ substantially,^1,5,6 the early and accurate discrimination of T2MI is a major yet largely unmet clinical need.^3,7 Unfortunately, established biomarkers of cardiomyocyte injury, including high-sensitivity cardiac troponin (hs-cTn) T and I levels, have only modest diagnostic discrimination.⁸ We hypothesized that novel cardiovascular biomarkers quantifying different pathophysiological pathways involved in T2MI and/or T1MI, including endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress, may aid physicians to rapidly discriminate T2MI from T1MI.

Advantageous Predictors of Acute Coronary Syndrome Evaluation (APACE) is an ongoing international, multicenter prospective diagnostic study including 12 centers in 5 countries (Switzerland, Spain, Italy, Poland, and the Czech Republic) designed to contribute to improving the management of patients with MI (ClinicalTrials.gov identifier: NCT00470587).^9-11 Adult patients presenting to the emergency department with acute chest discomfort with an onset or peak within the last 12 hours were recruited. The study was carried out according to the principles of the Declaration of Helsinki and approved by the local ethics committees. Written informed consent was obtained from all patients.

While recruitment was independent of kidney function at presentation, patients with end-stage kidney failure who were receiving long-term dialysis were excluded. For this analysis, patients were also excluded if (1) they presented with ST-elevation myocardial infarction, because T2MI rarely presents this way, or (2) the final diagnosis remained unclear after adjudication in patients with elevated hs-cTn concentrations that possibly indicated MI.

The authors designed the studies, gathered, and analyzed the data according to the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines¹² vouched for the data and analysis, wrote the manuscript, and decided to publish. The assays were donated by the manufacturers (QuickSens heart-type fatty acid–binding protein assay [8sens.biognostic GmbH]; AxSym and Architect assays for B-type natriuretic peptide, myeloperoxidase, and hs-cTnI [Abbott Laboratories]; Elecsys pro–B-type natriuretic peptide, hs-cTnT, placental growth factor, pregnancy-associated plasma protein-A, and growth differentiation factor [GDF] 15 assays [Roche Diagnostics]; Maxisorp plates apolipoprotein A-1 IgG autoantibodies AB assay [Nunc]; CVDefine anti-phosphorylcholine IgM assay [Athera Biotechnologies]; cardiac myosin-binding protein C [cMyC] assay [Millipore Sigma]; midregional pro–A-type natriuretic peptide [MR-proANP] LIA assay, midregional proadrenomedullin and C-terminal proendothelin 1[CT-proET-1] assay, and Brahms LUMItest copeptin assay [Brahms AG]), who had no role in the design of the study, data analysis, manuscript preparation, or decision to submit for publication.

All patients underwent clinical assessment that included a standardized and detailed medical history, vital signs, a physical examination, a 12-lead electrocardiogram (ECG), continuous ECG rhythm monitoring, pulse oximetry, standard blood tests, and chest radiography if indicated. Cardiac troponin levels, including hs-cTn levels in some centers, were measured at presentation and serially thereafter if clinically indicated. Treatment of patients was left to the discretion of the attending physician. The estimated glomerular filtration rate was determined using the Chronic Kidney Disease Epidemiology Collaboration formula.¹³

Our objective was to assess the diagnostic discrimination of 17 individual cardiovascular biomarkers quantifying different pathophysiological pathways involved in T2MI and/or T1MI in subsets of consecutively enrolled patients to avoid selection bias. Measurements were performed in batches in a central laboratory from blood samples obtained at emergency department presentation and serial sampling thereafter. For logistic reasons, including remaining sample volume, not all biomarkers could be measured from the same subsets of patients. The Elecsys hs-cTnT and hs-cTnI values were measured as part of routine clinical care and/or from study blood samples.

The following pathophysiological pathways were evaluated: cardiomyocyte injury using alternative signals to hs-cTnT or hs-cTnI levels, including heart-type fatty acid–binding protein, cMyC, and creatine kinase–myocardial band measurements; endothelial dysfunction using CT-proET-1 and midregional proadrenomedullin levels; hemodynamic cardiac stress using B-type natriuretic peptide, N-terminal pro–B-type natriuretic peptide, and MR-proANP levels; endogenous stress using copeptin and glucose levels; plaque instability and angiogenesis using myeloperoxidase, soluble vascular endothelial growth factor receptor 1 or soluble soluble FMS-like tyrosine kinase-1, placental growth factor, pregnancy-associated plasma protein-A, autoantibodies to apolipoprotein A-1, and antibodies to phosphorylcholine levels; inflammation using C-reactive protein levels and leukocyte counts; and the combination of inflammation, hemodynamic stress, and vascular aging using GDF 15 measurements. Detailed information regarding individual immunoassay characteristics is shown in the eAppendix in Supplement 1.

Two independent cardiologists (in variable pairs, including T.N., J.B., M.R.G., L.K., R.T., C.M., 1 nonbyline author [K.W.], and nonauthors) reviewed all available medical records, including the patient history, physical examination, vital signs in the ambulance and within the first hours in the emergency department, results of laboratory testing, radiologic testing, ECG, echocardiography, cardiac exercise stress testing, lesion severity, and morphology on coronary angiography, pertaining to the patient from the time of emergency department presentation to 90-day follow up. In situations of disagreement about the diagnosis, cases were reviewed and adjudicated in conjunction with a third cardiologist (C.M.). Adjudication of the final diagnosis was performed centrally in the core laboratory (University Hospital Basel, Basel, Switzerland) and included 2 sets of serial cTn or hs-cTn measurements: serial cTn or hs-cTn measurements obtained as part of routine clinical care locally (with different cTn or hs-cTn assays) and serial measurements of hs-cTnT from study blood draws performed centrally in the core laboratory to take advantage of the higher sensitivity and higher overall diagnostic accuracy offered by hs-cTnT.¹⁴

Myocardial infarction was defined and hs-cTnT concentrations were interpreted as recommended in current guidelines.¹ In brief, MI was diagnosed when there was evidence of myocardial necrosis in association with a clinical setting consistent with myocardial ischemia. Myocardial necrosis was diagnosed by at least 1 hs-cTnT value greater than the 99th percentile, together with a clinically significant rise and/or fall. Absolute changes in hs-cTnT were used to determine clinically significant changes based on the diagnostic superiority of absolute over relative changes.¹⁵ Based on studies of the biological variation of cTnT,^16,17 as well as data from previous cohort studies on chest pain,^18,19 a significant absolute change was defined as a rise or fall of at least 0.01 ng/mL within 6 hours or 0.006 ng/mL within 3 hours (to convert to micrograms per liter, multiply by 1.0). All other patients were classified in the categories of unstable angina, noncardiac chest pain, cardiac but noncoronary disease (eg, myocarditis, takotsubo cardiomyopathy, heart failure), and symptoms of unknown origin with normal levels of cardiac troponin.

Both T1MI and T2MI were defined according to the fourth universal definition of MI.¹ In addition to the evidence of myocardial necrosis in a clinical setting consistent with acute myocardial ischemia, T1MI was defined as spontaneous MI associated with a primary atherothrombotic coronary event, such as a plaque erosion or rupture, intraluminal coronary thrombus, or distal microembolization. Meanwhile, T2MI was defined as secondary to an oxygen supply-demand mismatch. Conditions reflecting an imbalance between myocardial oxygen supply and demand, including bradyarrhythmias or tachyarrhythmias, hypoxemia, hypotension, hypertension, severe anemia, coronary artery spasm, coronary dissection, or coronary embolism. Underlying coronary artery disease was possible but not required for the diagnosis of T2MI.¹ To qualify for T2MI, the same dynamic changes in cTn level were required as for T1MI. As recommended, the documentation of a clear trigger was essential for the diagnosis of T2MI.¹ Also, coronary angiography was not mandatory for a diagnosis of T1MI, which limited the possible effect of selection bias because of clinical referral to coronary angiography.¹

After hospital discharge, patients were contacted by telephone interview or written form after 3, 12, and 24 months of follow-up. In the case of reported clinical events, in particular cardiovascular events, after presentation to the emergency department, details were reviewed by discussion with the patients and traced by establishing contact with the respective family physician or treating institution. Information regarding death was obtained from the national registry on mortality, hospital’s diagnosis registry, or family physician’s records.

The data are expressed as medians and interquartile ranges (IQRs) for continuous variables and as numbers and percentages for categorical variables. All variables between T1MI and T2MI were compared by the Mann-Whitney U test for continuous variables or Pearson χ² test for categorical variables. Receiver operating characteristic curves were constructed to assess the area under the curve (AUC) for the discrimination between T1MI and T2MI and between MI and no MI. To derive a diagnostic cutoff concentration with clear clinical consequences, a specificity of 90% for T1MI vs T2MI was selected. Because batch measurements of the different assays were always performed in consecutively enrolled patients, the main analyses were performed in all patients with concentrations available for any assay at any point to maximize the number of measurements available for analysis. Binary logistic regression analysis was used for evaluating the association between biomarker concentration levels (log base–10 transformed) and the presence of T2MI. Considering the total number of T2MI in our study and to avoid overfitting in the model, 2 multivariable models were built. Variable selection was based on relevant previous findings and clinical knowledge. The first model included sex, creatinine clearance, and previous MI (model 1) and was applied to all biomarkers. Model 2 included sex, creatinine clearance, previous MI, age, heart rate, systolic blood pressure, hypercholesterolemia, and body mass index and was applied only to the biomarkers with at least 80 T2MI events. Additionally, a sensitivity analysis was performed for biomarkers, with the highest performance in a subset of patients with all biomarkers measured.

All hypothesis testing was 2-tailed, and P values less than .05 were considered to indicate statistical significance. Statistical analyses were performed using SPSS Statistics for Windows version 25.0 (IBM), MedCalc for Windows version 16.8.4 (MedCalc Software), and Stata version 16.1 (Stata Corp). Data collection was performed from April 2006 to April 2020, and data analysis was performed from April 2020 to June 2020.

From April 2006 to April 2018, a total of 5887 patients were eligible for this analysis (median [IQR] age, 61 [49-74] years; 1977 women [32.6%]). In 1106 of the patients (18.8%), MI was the adjudicated final diagnosis, and of these, 246 patients (22.2%) had T2MI and 860 (77.8%) had T1MI.

Patients with T2MI were more frequently women (T2MI, 89 of 246 patients [36.2%]; T1MI, 225 of 860 patients [26.2%]; P = .002), more often had tachycardia (T2MI, 60 [24.4%]; T1MI, 22 [2.6%]; P < .001) and hypotension (T2MI, 7 [2.8%]; T1MI, 7 [0.8%]; P = .02), and had a lower frequency of previous MI (T2MI, 66 [26.8%]; T2MI, 295 [34.3%]; P = .03) (Table 1). Treatment differed markedly between T2MI and T1MI and included coronary revascularization by percutaneous coronary intervention or coronary artery bypass grafting in 2.8% in patients with T2MI (percutaneous coronary intervention, 6 [2.4%]; coronary artery bypass grafting, 1 [0.4%]) vs 72.8% in patients with T1MI (percutaneous coronary intervention, 551 [64.1%]; coronary artery bypass grafting, 75 [8.7%]; P < .001 for both procedures).

Concentrations of Hs-cTnT and hs-cTnI at presentation were significantly lower among patients with T2MI vs patients with T1MI (median [IQR] hs-cTnT, 30 (17-55) ng/L vs 58 (28-150) ng/L); hs-cTnI, 23 [10-83] ng/L vs 115 [28-576] ng/L; P < .001; Figure 1). Additionally, novel biomarkers quantifying cardiomyocyte injury, including cMyC (at presentation: median [IQR], 76 [38-189] ng/L vs 257 [75-876] ng/L; P < .001), heart-type fatty acid–binding protein (median [IQR], 4.57 [2.48-13.33] vs 6.96 [3.20-18.36] ng/mL), and other established markers, such as creatine kinase–myocardial band (median [IQR], 4.8 [3.3-6.5] vs 5.9 [4.3-11.6] ng/mL), were also significantly lower in patients with T2MI vs T1MI (Figure 2; eFigure in Supplement 1). In contrast, biomarkers quantifying endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress were higher in patients with T2MI (median [IQR] values: CT-proET-1, 97 [75-134] pmol/L vs 68 [55-91] pmol/L; midregional proadrenomedullin, 0.97 [0.67-1.51] pmol/L vs 0.72 [0.53-0.99] pmol/L; MR-proANP, 378 [207-491] pmol/L vs 152 [90-247] pmol/L; GDF 15, 2.26 [1.44-4.35] ng/L vs 1.56 [1.02-2.19] ng/L; all P < .001) (Figure 2). Most of the other cardiovascular biomarkers, including copeptin, glucose, C-reactive protein, and B-type natriuretic peptide, had comparable concentrations in patients with T2MI vs T1MI (eFigure in Supplement 1).

The AUC to discriminate T2MI from T1MI was modest for hs-cTnT (0.67 [95% CI, 0.64-0.71]) and hs-cTnI (0.71 [95% CI, 0.67-0.74]) at presentation and slightly higher for subsequent points (eg, at 2 hours: hs-cTnT, 0.71 [95% CI, 0.66-0.75]; hs-cTnI, 0.74 [95% CI, 0.69-0.78]; Table 2). Similar results emerged for cMyC (AUC, 0.67 [95% CI, 0.61-0.73]; Table 2). Biomarkers quantifying endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress also had moderate discrimination (AUCs: CT-proET-1, 0.73 [95% CI, 0.63-0.83]; midregional proadrenomedullin, 0.66 [95% CI, 0.60-0.73]; MR-proANP, 0.77 [95% CI, 0.68-0.87]; GDF 15, 0.68 [95% CI, 0.58-0.79] (Table 2). Diagnostic performance of all biomarkers for differentiation of MI vs no MI are depicted in eTable 1 in Supplement 1. None of the biomarkers tested performed significantly better in discrimination of T2MI vs T1MI when compared with hs-cTnI (eTable 2 in Supplement 1). Multivariable regression analysis revealed that lower concentrations of hs-cTnT (odds ratio [OR], 0.314 [95% CI, 0.154-0.638]) or hs-cTnI (OR, 0.428 [95% CI, 0.280-0.655]), cMyC (OR, 0.317 [95% CI, 0.134-0.746]), creatine kinase–myocardial band (OR, 0.104 [95% CI, 0.019-0.568]), and heart-type fatty acid–binding protein (OR, 0.445 [95% CI, 0.218-0.908]), as well as higher concentrations of MR-proANP (OR, 12.1 [95% CI, 2.1-68.9]), CT-proET-1 (OR, 31.1 [95% CI, 2.078-464.6]), and midregional proadrenomedullin (OR, 35.2 [95% CI, 2.2-553.3]) remained independently associated with T2MI (Table 3). In a sensitivity analysis, the best performing biomarkers (AUC >0.65) were compared head to head in a subset of patients with all biomarkers measured. Performance of biomarkers did not vary significantly (eTable 3 in Supplement 1).

This pilot study tested the hypothesis that novel cardiovascular biomarkers quantifying different pathophysiological pathways involved in T2MI may aid physicians to rapidly discriminate T2MI from T1MI. We report 4 major findings. First, most cardiovascular biomarkers evaluated had comparable concentrations in T2MI vs T1MI and were therefore not helpful in their discrimination. Second, 4 novel cardiovascular biomarkers were higher in T2MI vs T1MI and showed modest promise for the early discrimination of T2MI: MR-proANP, considered to quantify hemodynamic stress; CT-proET-1, considered to quantify endothelial dysfunction; midregional proadrenomedullin, considered to quantify microvascular and endothelial dysfunction; and GDF 15, considered to quantify hemodynamic stress, inflammation, and vascular aging. Third, cMyC concentrations, which may quantify cardiomyocyte injury even more accurately than hs-cTnT or hs-cTnI levels,^20-22 were lower in T2MI vs T1MI and provided modest diagnostic accuracy, comparable with that provided by hs-cTnT and hs-cTnI. Fourth, while none of the tested cardiovascular biomarkers had significantly higher diagnostic discrimination, multivariable regression analysis suggested a possible additive value of MR-proANP to clinical variables.

These findings extend and corroborate previous studies evaluating mainly hs-cTnT or hs-cTnI for this indication,^8,23-25 which have documented lower hs-cTnI concentrations in T2MI, but with a large overlap and a resulting modest AUC of 0.63 to 0.66. Given the suggestive findings observed for MR-proANP, future studies are warranted to develop diagnostic models combining routinely available information such as hs-cTnT or hs-cTnI, medical history, and the 12-lead ECG with selected biomarkers. Until these tools are derived and externally validated, however, most patients will still require coronary angiography and/or noninvasive functional or anatomic testing to achieve a high level of diagnostic discrimination. It is important to highlight that the adjudication of T2MI and T1MI can be challenging and should strictly adhere to the current universal definition of MI. It is important to emphasize that the mechanisms of cardiomyocyte injury in patients with myocarditis, takutsubo cardiomyopathy, pulmonary embolism, or heart failure are usually multifactorial and these patients should not be included in the T2MI category.

Some limitations warrant consideration when interpreting the findings of this study. First, this study was conducted in patients presenting with symptoms suggestive of acute MI to the ED. We cannot comment on the early discrimination of T2MI in other clinical settings, including the perioperative setting and in patients with critical illness. Second, although we used a very stringent method to adjudicate T1MI and T2MI, including central assessment by experienced cardiologists reviewing cardiac imaging and serial measurements of hs-cTn, a small number of patients may have been misclassified. Limitations include the fact that not all patients underwent coronary angiography and that some of the shortcomings intrinsic to coronary angiography, such as the difficulty in correctly identifying rupture, fissure, erosion or dissection of plaque and intracoronary thrombus. Third, the number of patients in whom all (or most) novel biomarkers could be measured was underpowered for full comparison of diagnostic performance and too small to allow assessment of biomarker combinations. Positive predictive value has been calculated for each biomarker in the respective subset of consecutively enrolled patients and therefore does not allow direct comparison. Fourth, because patients receiving chronic hemodialysis were excluded, the generalizability to these patients remains unknown.

In conclusion, cardiovascular biomarkers provided modest diagnostic performance in the early discrimination of T2MI from T1MI. Clinical parameters may remain the only means for reliable identification of patients with T2MI.

Accepted for Publication: January 19, 2021.

Published Online: April 21, 2021. doi:10.1001/jamacardio.2021.0669

Corresponding Author: Christian Mueller, MD, Department of Cardiology, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland (christian.mueller@usb.ch).

Author Contributions: Drs Nestelberger and Boeddinghaus had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Nestelberger and Boeddinghaus contributed equally and are co–first authors.

Concept and design: Nestelberger, Boeddinghaus, Koechlin, Miro, Twerenbold, Mueller.

Acquisition, analysis, or interpretation of data: Nestelberger, Boeddinghaus, Lopez-Ayala, Kaier, Marber, Gysin, Koechlin, Yufera Sanchez, Rubini Giménez, Wussler, Walter, Strebel, Zimmermann, Glarner, Martin-Sanchez, Zehnder, Twerenbold, Mueller.

Drafting of the manuscript: Nestelberger, Boeddinghaus, Lopez-Ayala, Kaier, Zehnder, Mueller.

Critical revision of the manuscript for important intellectual content: Nestelberger, Boeddinghaus, Lopez-Ayala, Kaier, Marber, Gysin, Koechlin, Yufera Sanchez, Rubini Giménez, Wussler, Walter, Strebel, Zimmermann, Glarner, Miro, Martin-Sanchez, Twerenbold, Mueller.

Statistical analysis: Nestelberger, Boeddinghaus, Lopez-Ayala, Kaier, Wussler, Walter, Strebel, Zimmermann.

Obtained funding: Nestelberger, Marber, Twerenbold, Mueller.

Administrative, technical, or material support: Nestelberger, Marber, Koechlin, Yufera Sanchez, Wussler, Mueller.

Supervision: Nestelberger, Rubini Giménez, Miro, Twerenbold, Mueller.

Conflict of Interest Disclosures: Dr Nestelberger has received research support from the Swiss National Science Foundation (grant P400PM_191037/1), the Professor Dr Max Cloëtta Foundation, the Margarete und Walter Lichtenstein-Stiftung (grant 3MS1038), University Basel, and the University Hospital Basel, as well as speaker/consulting honoraria from Siemens, Beckman Coulter, Bayer, Ortho Clinical Diagnostics, and Orion Pharma outside the submitted work. Dr Boeddinghaus has received research grants from the University of Basel and the Division of Internal Medicine, the Swiss Academy of Medical Sciences, and the Gottfried and Julia Bangerter-Rhyner-Foundation and speaker honoraria from Siemens outside the submitted work. Dr Boeddinghaus also reported personal fees from Siemens, Roche, Ortho Clinical Diagnostics, and Quidel Corporation outside the submitted work. Dr Twerenbold has received research support from the Swiss National Science Foundation (grant P300PB-167803/1), the Swiss Heart Foundation, the Swiss Society of Cardiology, the Cardiovascular Research Foundation Basel, the University of Basel, and the University Hospital Basel and speaker/consulting honoraria from Roche, Abbott, Amgen, AstraZeneca, Brahms, Singulex, Siemens, and Thermo Scientific outside the submitted work. Dr Badertscher has received research funding from the Stiftung für Herzschrittmacher und Elektrophysiologie outside the submitted work. Dr Wildi has received research funding from the FAG Basel and the Julia und Gottfried Bangerter-Rhyner Stiftung. Dr Rubini Giménez has received speaker honoraria from Abbott and research support from the Swiss Heart Foundation outside the submitted work. Dr Walter reported receiving research grants from the Swiss Academy of Medical Sciences, the Bangerter Foundation (grant YTCR 23/17), and the Swiss Heart Foundation outside the submitted work. Dr Martin-Sanchez has received speaker, advisory, or consulting fees from Novartis, Merck Sharp & Dohme, Bristol Myers Squibb, Pfizer, the Medicines Company, Otsuka, ThermoFisher, Cardiorentis, and Sanofi and research grants from the Spanish Ministry of Health and FEDER, Mapfre, Novartis, Bayer, Merck Sharp & Dohme, Abbott, and Orion-Pharma outside the submitted work. Dr Kaier was supported by a clinical research fellowship grant by the British Heart Foundation (grant FS/15/13/31320) and a National Institute on Health Research clinical lectureship (grant CL-2019-17-006). Prof Marber was supported by grants from the Medical Research Council (grant G1000737), Guy's and St Thomas' Charity (grants R060701 and R100404), British Heart Foundation (grant TG/15/1/31518), and the UK Department of Health through the National Institute for Health Research Biomedical Research Centre award to Guy's & St Thomas' National Health Service Foundation Trust and is named as an inventor on a patent held by King’s College London for the detection of cardiac myosin-binding protein C as a biomarker of myocardial injury. Dr Reichlin has received research grants from the Goldschmidt-Jacobson Foundation, the Swiss National Science Foundation, the Swiss Heart Foundation, the European Union, the Professor Max Cloëtta Foundation, the Cardiovascular Research Foundation Basel, the University of Basel, the University Hospital Basel, and Biosense-Webster and has received speaker/consulting honoraria or travel support from Abbott, AstraZeneca, Brahms, Bayer, Biosense-Webster, Medtronic, Pfizer/Bristol Myers Squibb, St. Jude Medical, and Roche outside the submitted work. Dr Mueller has received research support from the Swiss National Science Foundation, the Swiss Heart Foundation, the KTI, the Stiftung für Kardiovaskuläre Forschung Basel, Abbott, Alere, AstraZeneca, Beckman Coulter, Biomerieux, Brahms, Roche, Siemens, Singulex, Sphingotec, and the Department of Internal Medicine, University Hospital Basel, as well as speaker/consulting honoraria from Abbott, Alere, AstraZeneca, Biomerieux, Boehringer-Ingelheim, Bristol Myers Squibb, Brahms, Cardiorentis, Novartis, Roche, Siemens, and Singulex outside the submitted work. Dr Mueller reported grants, personal fees, and nonfinancial support from 8sens.biognostic GmbH, Abbott Laboratories, Roche Diagnostics, Nunc, Athera Biotechnologies, Millipore Sigma, and Brahms AG for the measurement of biomarkers and/or reagents during the conduct of the study and outside the submitted work. Dr Koechlin reported grants from University of Basel, Schweizerische Akademie der Medizinischen Wissenschaften, and Freiwillige Akademische Gesellschaft Basel outside of the submitted work. No other disclosures were reported.

Funding/Support: The study was supported by research grants from the Swiss National Science Foundation, the Swiss Heart Foundation, University of Basel, University Hospital of Basel, the Stiftung für Kardiovaskuläre Forschung Basel, Abbott, Beckman Coulter, Biomerieux, Brahms, Roche, Siemens, and Singulex. All investigated assays were donated by the manufacturers (8sens.biognostic GmbH, Abbott Laboratories, Roche Diagnostics, Nunc, Athera Biotechnologies, Millipore Sigma, and Brahms AG).

Role of the Funder/Sponsor: The funders and sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The APACE Investigators are listed in Supplement 2.

Additional Contributions: We are indebted to the patients who participated in the study and the emergency department staff as well as the laboratory technicians of all participating sites for their most valuable efforts.

Additional Information: Millipore Sigma was contracted to undertake the analyses of cardiac myosin-binding protein C on a fee-for-service basis and holds no commercial interest.