Abstract
Introduction
New-onset atrial fibrillation (NOAF) represents a significant complication following ST-elevation myocardial infarction (STEMI). Soluble suppression of tumorigenicity 2 (sST2) is a biomarker reflecting myocardial stress and fibrosis. However, its predictive value for post-discharge NOAF in STEMI patients remains inadequately characterized. This study was to investigate whether elevated sST2 levels during hospitalization independently predict post-discharge NOAF in STEMI patients.
Methods
This multicenter, prospective cohort study enrolled 648 consecutive STEMI patients. Serum sST2 concentrations were measured within 24 h of admission using ELISA. Multivariable logistic regression, receiver operating characteristic (ROC) curve analysis, and risk reclassification metrics were employed to assess sST2’s predictive performance.
Results
NOAF occurred in 56 patients (8.64%) during follow-up. Patients developing NOAF exhibited significantly higher sST2 levels compared to those without NOAF (62.84 ± 54.62 vs. 30.37 ± 34.71 ng/mL, p < 0.001). After adjusting for confounders, sST2 remained an independent predictor of NOAF (OR = 1.02, 95% CI: 1.01–1.02, p < 0.001). The area under the ROC curve for sST2 was 0.785 (95% CI: 0.723–0.848). Incorporating sST2 into the clinical model significantly improved discrimination (AUC from 0.718 to 0.810, p < 0.001) and risk reclassification (NRI = 0.084, p = 0.033; IDI = 0.047, p = 0.003). Restricted cubic spline analysis revealed a nonlinear dose-response relationship between sST2 and NOAF risk.
Conclusion
Elevated sST2 levels during hospitalization independently predict post-discharge NOAF in STEMI patients, offering incremental prognostic value beyond traditional risk factors.
Keywords: Soluble ST2, New-onset atrial fibrillation, ST-elevation myocardial infarction, Biomarker, Risk prediction
Introduction
Atrial fibrillation (AF) constitutes one of the most prevalent cardiac arrhythmias encountered in clinical practice, the incidence of AF escalates markedly in the context of acute myocardial infarction (AMI) [1, 2]. Evidence consistently demonstrates that AMI patients who develop AF experience substantially higher mortality rates, increased heart failure incidence, and elevated risk of recurrent ischemic events compared to those maintaining sinus rhythm [2, 3]. Despite advances in cardiovascular therapeutics, the management of AF complicating AMI remains a formidable clinical challenge [4]. Consequently, identifying reliable biomarkers capable of early risk stratification assumes paramount importance for implementing preventive strategies and optimizing patient outcomes.
Suppression of tumorigenicity 2 (ST2) represents a member of the interleukin-1 receptor superfamily and functions as an integral component of the interleukin-33 (IL-33) signaling pathway [5]. The soluble ST2 (sST2), predominantly secreted by cardiac myocytes and fibroblasts, exhibits marked elevation under conditions of mechanical stretch, inflammatory stimulation, and oxidative stress [6]. Functioning as a decoy receptor for IL-33, sST2 effectively antagonizes the cardioprotective IL-33/ST2L signaling axis, thereby attenuating the heart’s inherent anti-fibrotic, anti-inflammatory, and antiapoptotic capabilities [7]. Substantial evidence has established sST2 as a robust prognostic biomarker across the spectrum of cardiovascular diseases, including heart failure, acute coronary syndromes, and adverse cardiac remodeling, with elevated levels strongly correlating with mortality and rehospitalization risks [8–10]. While previous investigations have explored the relationship between sST2 and in-hospital new-onset atrial fibrillation (NOAF) in AMI patients, the chronic-phase AF following MI may carry greater clinical significance than acute-phase occurrences [11, 12]. Furthermore, considering the distinct pathophysiological mechanisms underlying acute versus chronic phases post-AMI, systematic investigation of the independent association between sST2 and post-discharge NOAF remains warranted.
This study aimed to comprehensively evaluate the relationship between admission sST2 levels and subsequent post-discharge NOAF risk in ST-elevation myocardial infarction (STEMI) patients, thereby elucidating its independent predictive value. Through this investigation, we aspire to provide clinicians with a novel risk stratification tool for optimizing post-STEMI rhythm management strategies.
Methods
Study Design and Population
This multicenter, prospective cohort investigation was conducted at the First Affiliated Hospital of Zhejiang University School of Medicine and Yuhang District First People’s Hospital between January 2023 and December 2024. Inclusion criteria encompassed (1) age ≥18 years; (2) confirmed STEMI diagnosis according to the European Society of Cardiology guidelines [13]; (3) serum sST2 measurement completed within 24 h of admission; (4) successful primary percutaneous coronary intervention achieved within 12 h of symptom onset with thrombolysis in myocardial infarction flow grade >2; and (5) complete clinical documentation. Exclusion criteria included (1) previous documented AF or atrial flutter (including AF occurring during hospitalization); (2) recent (within 3 months) or current antiarrhythmic therapy excluding beta-blockers; (3) severe hepatic or renal dysfunction; (4) active infection, rheumatic heart disease, or autoimmune disorders; (5) malignancy; and (6) thyroid dysfunction. Following rigorous screening, 648 eligible patients were enrolled (Fig. 1).
Fig. 1.
Study flowchart. sST2, soluble suppression of tumorigenicity 2; NOAF, new-onset atrial fibrillation; STEMI, ST-elevation myocardial infarction.
Clinical Data Collection
Comprehensive baseline characteristics were systematically collected, including demographics (age, sex, BMI, smoking status), comorbidities (hypertension, diabetes mellitus, prior stroke), and procedural details. Laboratory assessments performed within 24 h of admission encompassed high-sensitivity troponin T (hs-TnT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), C-reactive protein (CRP), serum creatinine, and comprehensive lipid profiles. Due to their skewed distributions, NT-proBNP and hs-TnT were log-transformed before inclusion in the regression analyses. Left ventricular ejection fraction (LVEF) and left atrial diameter were obtained by transthoracic echocardiography. The sST2 concentration was measured using a double-antibody sandwich ELISA method (Byabscience Biotechnology Co., Ltd., Nanjing, China). Fasting venous blood samples (2 mL) were centrifuged at 3,000 rpm for 10 min, with supernatants stored at −80°C until analysis. All measurements were performed in a single laboratory with intra-assay and inter-assay coefficients of variation <8% and <10%, respectively. Laboratory personnel remained blinded to clinical outcomes to minimize bias.
Follow-Up and Outcome Assessment
Structured follow-up visits were conducted at 3, 6, and 12 months post-discharge and then annually thereafter. All participants underwent minimum 24-h Holter monitoring and 12-lead electrocardiography at each visit. The primary endpoint was documented NOAF, defined as AF lasting ≥30 s on single-lead recordings or characteristic findings on 12-lead electrocardiography (absence of P waves, presence of irregular fibrillatory waves, and completely irregular RR intervals) in patients without prior AF history [14].
Statistical Analysis
Statistical analyses were performed using SPSS version 27.0 (IBM Corp., Armonk, NY, USA) and R version 4.3.1 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables with normal distribution were expressed as mean ± standard deviation and compared using Student’s t test. Non-normally distributed variables were presented as median (interquartile range) and analyzed using Mann-Whitney U test. Categorical variables were reported as frequencies (percentages) and compared using chi-square or Fisher’s exact tests as appropriate. The primary endpoint of this study was defined as the occurrence of NOAF within a fixed follow-up period. Given the relatively consistent follow-up duration across participants, the outcome was treated as a binary variable. Therefore, logistic regression was used to evaluate the association between baseline sST2 levels and the risk of NOAF. Multivariable logistic regression analysis was employed to identify independent predictors of NOAF, with selection of significant variables or traditional clinical risk factors. Receiver operating characteristic curves assessed sST2’s discriminative ability, with DeLong’s test comparing areas under the curve (AUCs). Restricted cubic spline models evaluated the continuous relationship between sST2 and NOAF risk. Net reclassification improvement (NRI) and integrated discrimination index (IDI) quantified the incremental value of adding sST2 to conventional risk models. Statistical significance was defined as p < 0.05 (two-tailed).
Results
Baseline Characteristics
Among 648 enrolled STEMI patients, 56 (8.64%) developed NOAF during follow-up. The cohort’s mean age was 64.73 ± 10.41 years, with males comprising 58.18%. Patients developing NOAF demonstrated significantly lower LVEF (44.39 ± 9.02% vs. 47.64 ± 11.75%, p = 0.014), markedly elevated sST2 levels (median 46.34 vs. 24.57 ng/mL, p < 0.001), and higher NT-proBNP concentrations (median 2,013.5 vs. 1,125.8 pg/mL, p = 0.006) compared to those without NOAF. While hs-TnT and CRP showed increasing trends in the NOAF group, these differences did not achieve statistical significance. Coronary angiography revealed significantly higher prevalence of left anterior descending (LAD) artery involvement as the culprit vessel in NOAF patients (67.86% vs. 43.75%, p < 0.001), whereas distributions of left circumflex, right coronary artery (RCA), and left main lesions showed no significant differences (Table 1).
Table 1.
Baseline characteristics
| Variables | Total (n = 648) | Non-NOAF (n = 592) | NOAF (n = 56) | p value |
|---|---|---|---|---|
| Age, years | 64.73±10.41 | 64.60±10.45 | 66.07±10.02 | 0.312 |
| LVEF, % | 47.36±11.57 | 47.64±11.75 | 44.39±9.02 | 0.014 |
| Left atrial diameter, mm | 39.46±6.62 | 39.34±6.62 | 40.64±6.53 | 0.161 |
| Heart rate, bpm | 71.73±13.43 | 71.71±13.35 | 71.93±14.40 | 0.907 |
| SBP, mmHg | 135.38±19.89 | 135.61±20.00 | 133.00±18.67 | 0.348 |
| DBP, mmHg | 77.78±12.52 | 77.75±12.42 | 78.12±13.64 | 0.831 |
| sST2, ng/mL | 25.41 (16.34, 36.69) | 24.57 (15.91, 34.37) | 46.34 (32.06, 63.87) | <0.001 |
| BMI, kg/m2 | 25.71±2.49 | 25.74±2.38 | 25.40±3.40 | 0.470 |
| eGFR, mL/min/1.73 m2 | 102.51±20.75 | 102.37±20.96 | 104.07±18.46 | 0.556 |
| FBG, mmol/L | 6.83±2.91 | 6.81±2.94 | 7.07±2.61 | 0.529 |
| TC, mmol/L | 4.33±1.00 | 4.32±1.01 | 4.44±0.95 | 0.376 |
| TG, mmol/L | 1.50±1.09 | 1.48±0.97 | 1.72±1.91 | 0.116 |
| HDL, mmol/L | 0.99±0.23 | 0.99±0.24 | 0.97±0.20 | 0.475 |
| LDL, mmol/L | 2.79±0.87 | 2.78±0.88 | 2.89±0.79 | 0.367 |
| hs-TnT, pg/mL | 2,264.0 (784.0, 4,259.9) | 2,207.5 (725.7, 4,190.3) | 2,523.8 (1,406.1, 5,417.3) | 0.093 |
| CRP, mg/L | 8.09 (1.67, 36.00) | 7.90 (1.78, 32.85) | 12.85 (1.40, 91.40) | 0.178 |
| NT-proBNP, pg/mL | 1,194.2 (486.3, 2,963.2) | 1,125.8 (451.6, 2,864.0) | 2,013.5 (751.5, 3,713.9) | 0.006 |
| Male, n (%) | 377 (58.18) | 350 (59.12) | 27 (48.21) | 0.114 |
| Hypertension, n (%) | 369 (56.94) | 332 (56.08) | 37 (66.07) | 0.149 |
| Diabetes mellitus, n (%) | 170 (26.23) | 152 (25.68) | 18 (32.14) | 0.293 |
| Smoking, n (%) | 217 (33.49) | 200 (33.78) | 17 (30.36) | 0.604 |
| Killip >1, n (%) | 93 (14.35) | 81 (13.68) | 12 (21.43) | 0.114 |
| LAD, n (%) | 297 (45.83) | 259 (43.75) | 38 (67.86) | <0.001 |
| LCX, n (%) | 89 (13.73) | 84 (14.19) | 5 (8.93) | 0.274 |
| RCA, n (%) | 227 (35.03) | 214 (36.15) | 13 (23.21) | 0.052 |
| LM, n (%) | 35 (5.40) | 35 (5.91) | 0 (0.00) | 0.118 |
| Aspirin, n (%) | 646 (99.69) | 590 (99.66) | 56 (100.00) | 1.000 |
| P2Y12 inhibitors, n (%) | 647 (99.85) | 591 (99.83) | 56 (100.00) | 1.000 |
| Statins, n (%) | 644 (99.38) | 588 (99.32) | 56 (100.00) | 1.000 |
| ACEI/ARB, n (%) | 311 (47.99) | 284 (47.97) | 27 (48.21) | 0.972 |
| Beta-blockers, n (%) | 559 (86.27) | 514 (86.82) | 45 (80.36) | 0.179 |
NOAF, new-onset atrial fibrillation; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; hs-TnT, high-sensitivity troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; CRP, C-reactive protein; LDL, low-density leptin cholesterol; HDL, high-density leptin cholesterol; ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; LVEF, left ventricular ejection fraction; LAD, left anterior descending; LCX, left circumflex artery; RCA, right coronary artery; LM, left main coronary artery; sST2, soluble suppression of tumorigenicity 2.
Determinants of NOAF Development
Univariable logistic regression identified LAD involvement, LVEF, NT-proBNP, hs-TnT, CRP, and sST2 (OR = 1.01, 95% confidence interval [CI]: 1.01–1.02) as factors associated with NOAF. Multivariable analysis incorporating clinically and statistically significant variables revealed sST2 (OR = 1.02, 95% CI: 1.01–1.02, p < 0.001), NT-proBNP (OR = 2.21, 95% CI: 1.25–3.91, p = 0.006), LAD involvement (OR = 3.00, 95% CI: 1.61–5.59, p < 0.001), and CRP (OR = 1.01, 95% CI: 1.00–1.01, p = 0.007) as independent predictors of NOAF (Table 2). Restricted cubic spline analysis demonstrated a significant nonlinear dose-response relationship between sST2 and NOAF risk, in both unadjusted and adjusted models (P for overall <0.001, P for nonlinearity <0.001) (Fig. 2).
Table 2.
Univariate and multivariate logistic regression analysis
| Variables | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
| OR (95% CI) | p value | OR (95% CI) | p value | |
| Male, n (%) | 1.55 (0.90∼2.69) | 0.116 | | |
| Hypertension, n (%) | 1.53 (0.86∼2.71) | 0.151 | | |
| Diabetes mellitus, n (%) | 1.37 (0.76∼2.47) | 0.295 | | |
| Smoking, n (%) | 0.85 (0.47∼1.55) | 0.604 | | |
| Killip >1, n (%) | 1.72 (0.87∼3.40) | 0.118 | | |
| LAD, n (%) | 2.71 (1.51∼4.87) | <0.001 | 3.00 (1.61∼5.59) | <0.001 |
| LCX, n (%) | 0.59 (0.23∼1.53) | 0.279 | | |
| RCA, n (%) | 0.53 (0.28∼1.02) | 0.056 | | |
| ACEI/ARB, n (%) | 1.01 (0.58∼1.75) | 0.972 | | |
| Beta-blockers, n (%) | 0.62 (0.31∼1.25) | 0.183 | | |
| Age, years | 1.01 (0.99∼1.04) | 0.312 | | |
| Heart rate, bpm | 1.00 (0.98∼1.02) | 0.907 | | |
| SBP, mmHg | 0.99 (0.98∼1.01) | 0.348 | | |
| DBP, mmHg | 1.00 (0.98∼1.02) | 0.830 | | |
| LVEF, % | 0.98 (0.96∼1.00) | 0.045 | 0.98 (0.95∼1.00) | 0.077 |
| Left atrial diameter, mm | 1.03 (1.00∼1.07) | 0.162 | | |
| CRP, mg/L | 1.01 (1.00∼1.01) | 0.015 | 1.01 (1.00∼1.01) | 0.007 |
| hs-TnT, pg/mL | 1.75 (1.01∼3.05) | 0.049 | 1.76 (0.96∼3.24) | 0.067 |
| sST2, ng/mL | 1.01 (1.01∼1.02) | <0.001 | 1.02 (1.01∼1.02) | <0.001 |
| BMI, kg/m2 | 0.95 (0.85∼1.06) | 0.330 | | |
| NT-proBNP, pg/mL | 2.04 (1.21∼3.42) | 0.007 | 2.21 (1.25∼3.91) | 0.006 |
| eGFR, mL/min/1.73 m2 | 1.00 (0.99∼1.02) | 0.556 | | |
| FBG, mmol/L | 1.03 (0.94∼1.12) | 0.529 | | |
| TC, mmol/L | 1.13 (0.86∼1.48) | 0.375 | | |
| TG, mmol/L | 1.16 (0.96∼1.41) | 0.126 | | |
| HDL, mmol/L | 0.64 (0.19∼2.16) | 0.475 | | |
| LDL, mmol/L | 1.15 (0.85∼1.56) | 0.366 | | |
NOAF, new-onset atrial fibrillation; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; hs-TnT, high-sensitivity troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; CRP, C-reactive protein; LDL, low-density leptin cholesterol; HDL, high-density leptin cholesterol; ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; LVEF, left ventricular ejection fraction; LAD, left anterior descending; LCX, left circumflex artery; RCA, right coronary artery; LM, left main coronary artery; sST2, soluble suppression of tumorigenicity 2.
Fig. 2.
Dose-response relationship between sST2 levels and NOAF in patients with STEMI. a Unadjusted dose-response relationship between sST2 levels and NOAF. b Adjusted dose-response relationship between sST2 levels and NOAF (adjusted for LAD artery, LVEF, hs-TnT, NT-proBNP, CRP, and sST2). sST2, soluble suppression of tumorigenicity 2; NOAF, new-onset atrial fibrillation; STEMI, ST-elevation myocardial infarction.
Discriminative Performance of sST2
Receiver operating characteristic curve analysis revealed an AUC of 0.785 (95% CI: 0.723–0.848, p < 0.001) for sST2 in predicting NOAF, with an optimal cutoff of 31.59 ng/mL yielding 76.8% sensitivity and 71.3% specificity. The base model incorporating NT-proBNP, CRP, and LAD involvement achieved an AUC of 0.718. Addition of sST2 significantly enhanced discrimination to 0.810, with DeLong’s test confirming significant improvement (z = 3.67, p < 0.001) (Fig. 3; Table 3). Risk reclassification metrics further substantiated sST2’s incremental value, with NRI of 0.084 (95% CI: 0.007–0.162, p = 0.033) and IDI of 0.047 (95% CI: 0.015–0.078, p = 0.003). These findings underscore sST2’s substantial contribution to both discrimination and risk reclassification for NOAF prediction (Table 4).
Fig. 3.
ROC analysis of sST2 levels for NOAF in patients with STEMI. sST2, soluble suppression of tumorigenicity 2; NOAF, new-onset atrial fibrillation; STEMI, ST-elevation myocardial infarction; NT-proBNP, N-terminal pro-B-type natriuretic peptide; CRP, C-reactive protein; LAD, left anterior descending; AUC, area under the curve; ROC, receiver operating characteristic.
Table 3.
ROC curve for NOAF
| | AUC | 95% CI | p value | Cutoff | Sensitivity | Specificity |
|---|---|---|---|---|---|---|
| sST2, ng/mL | 0.785 | 0.723–0.848 | <0.001 | 31.59 | 0.768 | 0.713 |
| Base model | 0.718 | 0.650–0.786 | <0.001 | – | 0.643 | 0.742 |
| Base model + sST2 | 0.810 | 0.759–0.861 | <0.001 | – | 0.911 | 0.600 |
Base model included NT-proBNP, CRP, and LAD.
NOAF, new-onset atrial fibrillation; sST2, soluble suppression of tumorigenicity 2; ROC, receiver operating characteristic.
Table 4.
Discrimination accuracy and reclassification of sST2 for NOAF
| | NRI | IDI | ||
|---|---|---|---|---|
| Estimate (95% CI) | p value | Estimate (95% CI) | p value | |
| Base model | Reference | – | Reference | – |
| Base model + sST2 | 0.084 (0.007∼0.162) | 0.033 | 0.047 (0.015∼0.078) | 0.003 |
Base model included NT-proBNP, CRP, and LAD.
NOAF, new-onset atrial fibrillation; sST2, soluble suppression of tumorigenicity 2; CI, confidence interval; IDI, integrated discrimination index; NRI, net reclassification improvement.
Discussion
To our knowledge, this investigation represents the first comprehensive evaluation of admission sST2 levels as a predictor of post-discharge NOAF in STEMI patients. Our principal finding demonstrates that elevated sST2 independently predicts NOAF development, with its incorporation into risk models significantly enhancing predictive performance.
As a soluble receptor within the IL-33/ST2 signaling pathway, sST2 has garnered increasing attention in cardiovascular research [7–10]. While previous reports have documented associations between sST2 and AF, the distinct pathophysiology of chronic-phase NOAF post-AMI necessitated dedicated investigation [11, 12]. In our study, it was found that elevated admission sST2 levels independently predict post-discharge NOAF, even after adjusting for established risk factors. Incorporating sST2 into clinical models significantly improves risk prediction. Our findings provide crucial evidence supporting the inflammation-fibrosis axis as central to AF pathogenesis in this specific context.
The mechanistic underpinnings of AF development are multifaceted, with sST2 potentially exerting multiple effects as an IL-33/ST2 signaling antagonist. First, sST2 reflects myocardial stress and fibrosis levels. Following myocardial infarction, myocyte necrosis and mechanical stretch activate IL-33/ST2L signaling, which confers anti-fibrotic and cardioprotective effects. However, soluble sST2 competitively binds IL-33, preventing its interaction with membrane-bound ST2L receptors and thereby attenuating anti-fibrotic responses. This accelerates atrial and ventricular fibrosis, creating conduction heterogeneity and electrical substrate for AF maintenance [15, 16]. Second, sST2 participates in inflammatory regulation. Postinfarction inflammatory infiltration upregulates multiple pro-inflammatory cytokines in atrial tissue, promoting electrical remodeling and interstitial changes [17, 18]. Studies have demonstrated positive correlations between sST2 and inflammatory markers including CRP and IL-6, suggesting that elevated sST2 reflects persistent inflammatory activation conducive to NOAF development [9, 19]. Third, sST2 correlates with cardiac pressure loading and mechanical stretch. Post-MI left ventricular dysfunction increases left atrial pressure and volume loading, perpetuating atrial wall stress [20]. Mechanical stretch itself stimulates sST2 release from cardiomyocytes, establishing a vicious cycle [21, 22]. Therefore, sST2 may promote post-AMI atrial structural and electrophysiological alterations through convergent inflammatory, fibrotic, and mechanical pathways, providing novel biological insights into NOAF pathogenesis.
Notably, while previous studies demonstrated associations between sST2 and in-hospital NOAF, our findings reveal LAD rather than RCA involvement as an independent risk factor for post-discharge NOAF [23, 24]. This discrepancy likely reflects distinct pathophysiological mechanisms operating during acute versus chronic phases post-AMI. During the acute phase, RCA-related atrial ischemia predominates in NOAF genesis, whereas chronic-phase mechanisms emphasize ventricular dysfunction and adverse remodeling more closely associated with LAD territory infarction [25–27]. Indeed, the prior study has established that atrial ischemia serves as a contributing factor to acute-phase AF, but not to late-phase AF [28].
In the present study, although the left atrial diameter was higher in the NOAF group, no statistically significant difference was observed compared with the non-NOAF group. This lack of significance may be attributed to the relatively small sample size and the fact that left atrial diameter was measured during the acute phase. Structural remodeling, such as atrial enlargement, typically requires prolonged exposure to pressure or volume overload and may not yet be manifest during the acute stage of AMI. Consistent with established studies, our study confirms NT-proBNP, LAD involvement, and CRP as independent NOAF predictors [29–31]. Through NRI and IDI analyses, we demonstrate that incorporating sST2 into conventional prediction models significantly enhances NOAF risk discrimination in AMI patients. Clinically, this facilitates predischarge risk stratification, enabling identification of high-risk individuals for optimized monitoring and preventive strategies. However, it should be recognized that the discriminatory ability of sST2 as a standalone marker may be limited, and its use as an independent basis for clinical decision-making should be approached with caution. Instead, its value may be better reflected in its incremental contribution to established risk prediction models, supporting its role as a component within a multimodal risk assessment framework.
Study Limitations
Despite its novelty and clinical relevance, several limitations warrant consideration. First, the relatively modest sample size necessitates validation in larger cohorts. Second, single-timepoint sST2 measurement precludes assessment of temporal dynamics; future studies should incorporate serial measurements to evaluate trajectory-based prediction. Third, AF was assessed using intermittent 24-h Holter and standard electrocardiography, which may miss paroxysmal or asymptomatic episodes and underestimate the true incidence of NOAF. Although our observed rate is consistent with previous studies, more intensive monitoring (e.g., wearable or implantable devices) may detect a higher AF burden. Continuous monitoring is warranted in future studies. Fourth, the precise mechanistic links between chronic-phase sST2 elevation and NOAF development require further basic science investigation. Fifth, in this study, logistic regression was applied; however, this approach does not account for time-to-event information. Future studies with more rigorous prospective follow-up designs may benefit from using Cox proportional hazards models to further validate these findings.
Conclusions
Elevated admission sST2 levels independently predict post-discharge NOAF in STEMI patients, maintaining prognostic significance after adjustment for traditional risk factors. Integration of sST2 into conventional risk models substantially improves NOAF risk discrimination. Given its accessibility and reproducibility, sST2 measurement holds promise as a clinical risk stratification tool, potentially guiding individualized management strategies for post-AMI patients.
Statement of Ethics
The study protocol adhered to the Declaration of Helsinki principles and received approval by the Institutional Ethics Committees of the First People’s Hospital of Yuhang District (Ethics Approval No. yhqy221210) and the Institutional Ethics Committees of the First Affiliated Hospital of Zhejiang University School of Medicine (Ethics Approval No. yhqy2023-006-06). Verbal informed consent was obtained from all participants, and this protocol was in line with local guidelines.
Conflict of Interest Statement
The authors have no conflicts of interest to declare.
Funding Sources
This work was partly supported by Zhejiang Provincial Medical and Health Technology Project (Grant No. 2024KY1447). The funder had no role in the design, data collection, data analysis, and reporting of this study.
Author Contributions
W.L., M.X., Y.S., D.C., X.Z., S.W., R.B., and Y.L. analyzed the data and wrote the manuscript. W.L., X.Z., S.W., R.B., and J.Y. were involved in data collection. W.L., M.X., and Y.L. directed the entire research work and corrected the articles.
Funding Statement
This work was partly supported by Zhejiang Provincial Medical and Health Technology Project (Grant No. 2024KY1447). The funder had no role in the design, data collection, data analysis, and reporting of this study.
Data Availability Statement
The data that support the findings of this study are not publicly available due to privacy reasons but are available from the corresponding author upon request (liyonghzlz@163.com).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are not publicly available due to privacy reasons but are available from the corresponding author upon request (liyonghzlz@163.com).
