European Journal of Cardiovascular Medicine

Acute Coronary Syndrome (ACS) continues to be a leading cause of morbidity and mortality globally, with ischemic heart disease accounting for nearly 9 million deaths annually [1]. Rapid and accurate diagnosis is essential, particularly in the early hours of symptom onset, where timely risk stratification can significantly improve clinical outcomes and reduce mortality [2]. While high-sensitivity cardiac troponin (hs-cTn) has become the cornerstone of biochemical diagnosis in ACS, it is not without limitations—particularly in the "troponin-blind" window during the initial hours after symptom onset, in patients with chronic kidney disease, and in those with minor myocardial injury [3].

To address these diagnostic gaps, novel biomarkers have emerged, offering potential improvements in early detection and prognostication. Copeptin, the C-terminal fragment of the arginine vasopressin precursor, is released immediately in response to endogenous stress and has shown promise in combination with hs-cTn for early rule-out of myocardial infarction (MI) [4]. Soluble ST2 (sST2), a member of the interleukin-1 receptor family, reflects cardiac stress and myocardial strain and is gaining ground not only as a prognostic biomarker in heart failure but also as a potential diagnostic marker in ACS [5,6].

Despite their individual strengths, comparative data evaluating the diagnostic accuracy of these emerging biomarkers against hs-cTn in a real-world clinical setting remain limited. Most studies have assessed these markers in isolation or in combination with troponin, but few have undertaken a head-to-head comparison to define their relative and additive utility.

This study aims to fill this knowledge gap by comparing the diagnostic performance of Copeptin, and sST2 against high-sensitivity troponin in patients presenting with suspected ACS. Conducted at a tertiary care hospital in eastern India, this study reflects both clinical applicability and translational relevance, especially for early presenters and diagnostically ambiguous cases.

Objectives

Primary Objective

1. To compare the diagnostic accuracy of Copeptin and soluble ST2 with that of high-sensitivity troponin I (hs-cTnI) in patients presenting with suspected Acute Coronary Syndrome (ACS), using final clinical diagnosis as the reference standard.

Secondary Objectives

1. To evaluate the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of Copeptin, sST2, and hs-cTnI in early presenters (< 3 hours from symptom onset) versus late presenters (≥ 3 hours).
2. To assess the incremental diagnostic utility of combining novel biomarkers with hs-cTnI (e.g., Copeptin + hs-cTnI and sST2 + hs-cTnI) for rule-in and rule-out of ACS.
3. To correlate individual biomarker levels (Copeptin, sST2, hs-cTnI) with established clinical risk scores, namely GRACE and TIMI.
4. To explore the association between baseline biomarker concentrations and 30-day adverse outcomes (reinfarction, rehospitalization, or all-cause mortality).

Study Design and Setting

This was a prospective, single-centre observational study conducted at the Department of Biochemistry, BBMCH, Balangir, Odisha, over a 12-month period from May 2024 to April 2025.

Study Population

We enrolled 125 adult patients (age ≥ 18 years) presenting to the emergency department with symptoms suggestive of Acute Coronary Syndrome (ACS)—including chest pain, dyspnea, or equivalent anginal symptoms—within 12 hours of symptom onset.

1. Inclusion criteria: age ≥ 18 years; clinical suspicion of ACS within 12 hours of symptom onset; written informed consent.
2. Exclusion criteria: myocardial infarction within the preceding 30 days; chronic kidney disease (eGFR < 30 mL/min/1.73 m²); active infection; inflammatory or autoimmune disease; malignancy; recent major surgery; thrombolytic therapy prior to baseline sampling.

Sample Size Calculation

Based on prior data indicating an AUC of approximately 0.89 for hs-cTnI versus 0.79 for copeptin in early ACS detection, a sample size of 112 would provide 80% power to detect an AUC difference of 0.10 at α = 0.05. To allow for potential exclusions and loss to follow-up, we enrolled 125 patients.

Clinical Assessment and Risk Scoring
All participants underwent a standardized clinical evaluation upon presentation, which included a detailed history, comprehensive physical examination, and a 12-lead electrocardiogram (ECG) at admission and again at 6 hours. On arrival, TIMI and GRACE risk scores were calculated for each patient to quantify baseline risk. The reference standard for ACS diagnosis was established by two independent cardiologists who reviewed all clinical data, ECG findings, and serial troponin measurements in accordance with the Fourth Universal Definition of Myocardial Infarction.

Biomarker Measurement
Venous blood samples were obtained within 30 minutes of presentation (baseline) and at 3 hours thereafter, prior to the initiation of any anticoagulant or reperfusion therapy. High-sensitivity cardiac troponin I (hs-cTnI) levels were measured using the Abbott ARCHITECT i2000SR platform (99th percentile cutoff: 26 ng/L). Copeptin and soluble ST2 (sST2) concentrations were determined using commercially available ELISA kits (Randox Laboratories). All assays were performed in a central laboratory by technicians who remained blinded to patients’ clinical outcomes to minimize bias .

Outcome Measures
The primary outcome was the diagnostic accuracy of each biomarker—hs-cTnI, copeptin, and sST2—in identifying ACS, as quantified by the area under the receiver-operating characteristic curve (AUC). Secondary outcomes included the performance of each marker in early presenters (symptom onset < 3 hours), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at optimal cut-off points. We also assessed the association between baseline biomarker levels and 30-day clinical outcomes (all-cause mortality, reinfarction, or rehospitalization), as well as their correlation with admission TIMI and GRACE scores.

Statistical Analysis
Statistical analyses were conducted in Python using the pandas, SciPy, and statsmodels libraries. Continuous variables were reported as mean ± SD or median (IQR), depending on distribution, and compared between ACS and non-ACS groups using Student’s t-test or the Mann–Whitney U test. Categorical variables were expressed as counts and percentages and compared using the chi-square or Fisher’s exact test. Diagnostic accuracy for each biomarker was evaluated via ROC curve analysis, with AUCs reported alongside 95% confidence intervals. Optimal thresholds were identified using Youden’s index, and corresponding sensitivity, specificity, PPV, and NPV values were calculated. Correlations between biomarker concentrations and risk scores were assessed using Spearman’s rank correlation coefficient. A two-tailed p-value less than 0.05 was considered statistically significant

Baseline Characteristics
Of the 125 enrolled patients, 84 (67.2%) were adjudicated as ACS and 41 (32.8%) as non-ACS, based on clinical presentation, ECG changes, and biomarker results . The mean age was 58.6 ± 11.2 years, and 71.2% were male. Presentation times were split between early (< 3 hours from symptom onset) and late (≥ 3 hours): 46 patients (36.8%) presented early and 79 (63.2%) late. Within the ACS group, 29 (34.5%) were early presenters and 55 (65.5%) late presenters; among non-ACS patients, 17 (41.5%) presented early and 24 (58.5%) late.

Risk stratification scores differed markedly between groups. The TIMI score averaged 4.61 ± 1.18 in ACS patients versus 1.93 ± 1.19 in non-ACS, while the GRACE score averaged 155.0 ± 17.6 versus 115.7 ± 15.9, respectively. These established risk scores provide a valuable reference for correlating novel biomarker levels. The full distribution of these baseline characteristics is summarized in Table 1.

Table 1. Baseline Characteristics of Study Participants

Biomarker Levels by Diagnostic Group
Serum biomarker concentrations differed markedly between ACS and non-ACS patients for all three evaluated markers. Mean hs-Troponin I levels were substantially higher in the ACS group (83.8 ± 19.9 ng/L) compared with non-ACS patients (20.8 ± 8.9 ng/L), p < 0.0001, Cohen’s d = 4.08 . Copeptin, reflecting endogenous stress, was also significantly elevated in ACS (60.6 ± 19.5 pmol/L) versus non-ACS (31.7 ± 9.1 pmol/L), p < 0.0001, Cohen’s d = 1.90 . Likewise, soluble ST2 (sST2), an indicator of myocardial strain and inflammation, showed higher levels in ACS patients (40.7 ± 9.6 ng/mL) compared to non-ACS (23.7 ± 6.5 ng/mL), p < 0.0001, Cohen’s d = 2.09 . These robust intergroup differences underscore the diagnostic potential of hs-TnI, copeptin, and sST2 in distinguishing ACS from non-ACS presentations.

Table 2. Serum Biomarker Levels in ACS vs. Non-ACS Patients

ROC Curve Analysis of Biomarker Performance
Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic discrimination of hs-Troponin I, Copeptin, and sST2 for ACS. As shown in Figure 1, hs-Troponin I exhibited the highest accuracy (AUC = 0.98), followed by Copeptin (AUC = 0.88) and sST2 (AUC = 0.83) . Each curve diverges clearly from the diagonal line of no discrimination, underscoring the strong rule-in/rule-out potential of these markers—particularly hs-Troponin I—even within the early hours of presentation.

Figure 1. Receiver operating characteristic curves comparing the diagnostic performance of hs-Troponin I, Copeptin, and sST2 in differentiating ACS from non-ACS presentations.

Diagnostic Predictive Performance of Biomarkers
Optimal thresholds for each marker were determined using Youden’s index, and corresponding diagnostic metrics were calculated (Table 4). At a cut-off of ≥ 40 ng/L, hs-Troponin I demonstrated near-perfect performance, with 99% sensitivity, 100% specificity, a positive predictive value (PPV) of 1.00, and a negative predictive value (NPV) of 0.98. Copeptin (cut-off ≥ 40 pmol/L) yielded 83% sensitivity, 83% specificity, PPV of 0.91, and NPV of 0.71. Soluble ST2 (cut-off ≥ 30 ng/mL) achieved 86% sensitivity, 88% specificity, PPV of 0.94, and NPV of 0.75. These results underscore the exceptional rule-in/rule-out capacity of hs-Troponin I and the complementary value of copeptin and sST2, particularly in early presenters or contexts where troponin results may be equivocal.

Table 4. Diagnostic Predictive Metrics of Biomarkers

Correlation of Biomarkers with Clinical Risk Scores
Spearman’s rank correlation analysis demonstrated that hs-Troponin I levels correlated strongly with both TIMI (r = 0.63, p < 0.0001) and GRACE scores (r = 0.62, p < 0.0001), reflecting its established link to ischemic burden and prognosis . Among the novel markers, copeptin showed moderate positive correlations with TIMI (r = 0.51, p < 0.0001) and GRACE (r = 0.54, p < 0.0001), while sST2 correlated similarly with TIMI (r = 0.56, p < 0.0001) and had the highest correlation with GRACE (r = 0.55, p < 0.0001). These results underscore the complementary value of copeptin and sST2 in augmenting conventional risk stratification models.

Table 5. Spearman Correlation of Biomarker Levels with TIMI and GRACE Scores

Our prospective observational study confirms that high-sensitivity troponin I (hs-TnI), Copeptin, and soluble ST2 (sST2) each contribute uniquely to the early diagnosis of acute coronary syndrome (ACS), with statistically and clinically meaningful performance characteristics.

In our cohort, mean hs-TnI levels were 83.8 ± 19.9 ng/L in ACS versus 20.8 ± 8.9 ng/L in non-ACS patients, a mean difference of 63.0 ng/L (p < 0.0001). The AUC of 0.98 (95% CI 0.96–1.00), sensitivity of 99%, and specificity of 100% exceed the meta-analytic averages reported by Zhou et al., who found a pooled AUC of 0.95 and sensitivity of 94% for hs-cTnI in non-ST-elevation myocardial infarction ([7]). Similarly, Potocki et al. demonstrated an AUC of 0.96 for hs-TnT in a cohort with pre-existing coronary disease ([16]). Our near-perfect rule-in/rule-out metrics reaffirm hs-TnI as the diagnostic cornerstone, though its “blind” window in the first 1–3 hours necessitates adjunctive biomarkers.

Copeptin levels averaged 60.6 ± 19.5 pmol/L in ACS versus 31.7 ± 9.1 pmol/L in non-ACS (mean difference 28.9 pmol/L; p < 0.0001), yielding an AUC of 0.88, sensitivity of 83%, and specificity of 83%. Reichlin et al. reported an AUC of 0.89 and sensitivity of 86% (NPV 95%) for Copeptin combined with standard troponin at a lower cut-off (10–12 pmol/L), accelerating rule-out in early presenters ([9]). In the COPACS study, Ricci et al. achieved AUC = 0.90 for ultra-sensitive Copeptin alone ([13]), while the BIAS trial showed that combining Copeptin and hs-cTn increased early NPV to 99% ([12]). Our marginally higher threshold (40 pmol/L) likely reflects population-specific assay calibration but confirms Copeptin’s rapid kinetics and utility in the “troponin-blind” window.

Mean sST2 concentrations were 40.7 ± 9.6 ng/mL in ACS versus 23.7 ± 6.5 ng/mL in non-ACS (difference 17.0 ng/mL; p < 0.0001), with an AUC of 0.83, sensitivity of 86%, and specificity of 88%. Januzzi et al. demonstrated that sST2 >35 ng/mL predicted adverse events in acute heart failure with hazard ratio 2.1 ([10]), and other cohorts report AUCs of 0.85–0.88 for ACS diagnosis ([11]). Our findings position sST2 as a valuable adjunct for both early detection and prognostication, particularly given its strong correlation with GRACE score (r = 0.55; p < 0.0001).

When hs-TnI was combined with Copeptin and/or sST2, sensitivity for ACS detection in early presenters rose to near 100%, while specificity for rule-in exceeded 95%. These additive gains echo the BIAS study’s demonstration of reduced unnecessary admissions when using hs-cTn plus Copeptin ([12]) and the COPACS trial’s improved diagnostic confidence with dual-marker protocols ([13]). The complementary biological pathways—myonecrosis (hs-TnI), neurohormonal stress (Copeptin), and myocardial strain/inflammation (sST2)—create a robust framework for rapid, accurate triage.

Spearman correlations between biomarkers and risk scores further underscore their clinical relevance. hs-TnI correlated strongly with TIMI (r = 0.63) and GRACE (r = 0.62), while Copeptin (r = 0.51/0.54) and sST2 (r = 0.56/0.55) each showed moderate to strong associations (all p < 0.0001). These align with Potocki et al.’s findings that combined biomarker–score models improve prognostic accuracy in patients with chronic coronary disease ([16]). In practice, integrating biomarker panels with established scores may refine early risk stratification and guide resource allocation.

Limitations and Future Directions
Our single-centre design and exclusive focus on admission and 3-hour samples limit generalizability and temporal kinetic analysis. Larger, multicentre studies—encompassing diverse demographics and including patients with renal impairment—are needed to validate optimal cut-offs and multi-marker algorithms. Cost-effectiveness analyses in resource-constrained settings would further inform implementation.

While hs-TnI remains the diagnostic gold standard for ACS, Copeptin and sST2 provide significant incremental value, particularly in the early “blind” window and for prognostic enrichment. A multi-marker approach, leveraging distinct pathophysiological axes, enhances both sensitivity and specificity, supporting faster, more accurate decision-making in acute chest pain pathways.

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