Development of a Diagnostic Model Based on Serum ST2 and Left Atrial Strain for Left Ventricular Systolic Dysfunction in Patients With Chronic Coronary Syndrome

ABSTRACT

Aims

The study investigated the predictive value of serum soluble ST2 (sST2) and left atrial strain parameters for left ventricular systolic dysfunction (LVSD), and the correlation analysis with corresponding indicators in patients with chronic coronary syndrome (CCS).

Methods

A total of 135 patients with CCS who presented to the Cardiology Department Zhongda hospital and underwent echocardiographic examinations from January 2025 to December 2025 were ultimately included. Based on two‐dimensional speckle tracking echocardiography, left ventricular global longitudinal strain and left atrial strain were measured within 72 h of CCS diagnosis, and the patients were categorized into two groups: LV GLS > −17%, LVSD group; and LV GLS≤−17%, non‐ LVSD group. Baseline data were collected from all patients and compared between the two groups. The correlation between sST2 and LA parameters in CCS patients was evaluated using Spearman correlation.  Based on the results of the multivariate logistic regression analysis, a predictive model for LVSD in CCS patients was established.

Results

In the LVSD group, sST2 levels, early diastolic mitral inflow velocity (E)/ early diastolic mitral annular velocity (e') ratio, left atrial volume index (LAVI), and left atrial stiffness index (LASI) were increased. In the CCS patients, sST2, E/e', LAVI, and LASI demonstrated good correlation. sST2 and LASI were independent predictors for diagnosing LVSD in patients with CCS. ROC curve analysis showed that ST2 and LASI had diagnostic value for left ventricular systolic dysfunction in patients with CCS.

Conclusion

This study found that in patients with CCS complicated by LVSD, sST2 levels were elevated, left atrial strain parameters were impaired, and a certain correlation was observed between the two. Furthermore, we investigated whether sST2 and LASI are independent predictors for diagnosing LVSD in CCS patients. By combining these two indicators, a diagnostic model can be constructed.

Study groups, data collection, and main results of this study. sST2 levels demonstrated significant correlations with E/e', LAVI, and LASI. A diagnostic model for left ventricular systolic dysfunction was subsequently developed in patients with chronic coronary syndrome. LVSD, left ventricular systolic dysfunction; sST2, soluble suppression of tumorigenicity‐2. LASI, left atrial stiffness index; E/e', early mitral inflow/mitral annulus early diastolic velocity ratio; LAVI, left atrial volume index; LASr, left atrial reservoir strain.

Abbreviations

2D

two‐dimensional

ACEI

angiotensin‐converting enzyme inhibitors

ACS

acute coronary syndrome

ARB

angiotensin receptor blockers

AUC

area under the curve

BMI

body mass index

BNPs

B‐type natriuretic peptides

CCS

chronic coronary syndrome

CMR

cardiac magnetic resonance

Cr

creatinine

EF

ejection fraction

GLS

global longitudinal strain

Glu

blood glucose

Hb

hemoglobin

HF

heart failure

HFpEF

heart failure with preserved ejection fraction

LA

left atrium

LAScd

left atrial conduit strain

LASct

left atrial contraction strain

LASI

left atrial stiffness index

LASr

left atrial strain reserve

LAVI

left atrial volume index

LDL‐C

low‐density lipoprotein cholesterol

LV

left ventricular

LVD

left ventricular dysfunction

LVGLS

Left ventricular overall longitudinal strain

LVSD

left ventricular systolic dysfunction

MR

mitral regurgitation

NT‐proBNP

N‐terminal pro‐B‐type natriuretic peptide

ROC

Receiver Operating Characteristic

sST2

soluble suppression of tumorigenicity‐2

TC

total cholesterol

TG

Triglycerides

1. Introduction

Chronic coronary syndrome (CCS) is a prevalent cardiovascular condition characterized by symptoms such as angina pectoris and myocardial ischemia, significantly impairing patients' quality of life. Despite the significant benefits that revascularization techniques and optimal medical therapy have brought to patients with CCS, the risk of various cardiovascular diseases remains high for CCS patients, including atrial fibrillation (AF), heart failure (HF), acute coronary syndrome (ACS), and stroke. This highlights the necessity of early identification of patients at high risk of cardiovascular events [1, 2]. Laboratory and imaging tests play a major role in the diagnosis, risk stratification, treatment decision‐making, and monitoring of CCS.

Echocardiographic measurement of left ventricular (LV) ejection fraction (EF) is a commonly used method and parameter for evaluating cardiac systolic function. A reduction in LVEF values significantly affects the prognosis of patients with CCS. With the development of echocardiographic technology, global longitudinal strain (GLS) has become one of the new cardiac function evaluation indicators, and it is more sensitive to left ventricular dysfunction (LVD) than LVEF and can provide additional prognostic information [3]. The left atrium (LA) regulates ventricular filling and maintains normal cardiac hemodynamics through its reservoir, conduit and booster pump functions [4, 5]. Left atrial dysfunction can lead to decreased cardiac function and impact patient prognosis, even in patients with CCS who have preserved left ventricular systolic function [2]. In recent years, the development of two‐dimensional speckle tracking technology has made the assessment of left atrial function more comprehensive. Multiple studies have shown that in various diseases such as hypertension, heart failure with preserved ejection fraction (HFpEF), and severe degenerative mitral regurgitation (MR), LA reservoir strain emerges as the strongest predictor of various diseases [6, 7, 8]. The LA stiffness index (LASI), estimated by LA strain and E/e′, is a relatively simple, noninvasive parameter to represent LA remodeling during various diseases [7, 9, 10].

Growing evidence highlights the clinical value of soluble suppression of tumorigenicity‐2 (sST2): initially classified as a cardiac stress marker, it is primarily produced in non‐cardiac tissues in response to inflammatory and fibrotic stimuli [11]. Some scholars believe that sST2 can serve as a strong and independent predictor of mortality and hospitalization for heart failure in patients with acute or chronic heart failure [12].

However, no studies to date have described the association between sST2 and left atrial strain parameters in patients with CCS, or whether these markers possess predictive value for left ventricular systolic function. Therefore, this study aims to investigate the characteristics of sST2 and left atrial strain indicators in CCS patients, particularly those with preserved ejection fraction but underlying systolic dysfunction.

2. Methods

2.1. Study Design and Patients

This monocentric prospective study was carried out in the Zhongda Hospital, China, between January 2025 and December 2025. Inclusion criteria: (1) adult patients aged 18 to 80 years; (2) meeting the criteria for CCS from the 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes [1]; (3) LVEF > 45%. Exclusion criteria: (1) primary cardiomyopathies (such as dilated cardiomyopathy, hypertrophic cardiomyopathy, amyloidosis); (2) significant valvular heart disease (at least mild stenosis or at least moderate left‐sided regurgitation); (3) severe arrhythmias (such as persistent or permanent atrial fibrillation); (4) pregnancy; (5) poor image quality (Figure 1).

FIGURE 1.

Flow chart of participants selection.

2.2. Statistical Collection

The general conditions of the patients, including age, gender, height, body weight, and blood pressure, were recorded, as well as their medical history and clinical medication history, including angiotensin‐converting enzyme inhibitors (ACEI)/angiotensin receptor blockers (ARB), beta‐blocker, calcium‐channel blockers, diuretics, oral anti‐diabetic agents, insulin and coronary interventional history. Laboratory tests included for blood lipids, blood glucose, creatinine, N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP). Serum sST2 levels were measured by dry immunofluorescence assay.

An echocardiographic examination was performed and the images were analyzed by an experienced sonographer with over 5 years of experience, using a GE Vivid E95 ultrasound diagnostic instrument with an M5S probe (frequency 1.7–3.3 MHz). As recommended, two‐dimensional (2D), color, pulsed‐wave, and continuous‐wave Doppler images were obtained from the anterior chest wall, apical, and subcostal views. The early diastolic peak velocity of mitral valve blood flow (E), the late diastolic peak velocity of mitral valve blood flow (A), and the early diastolic velocity of the mitral annulus (e') were recorded. Two‐dimensional strain analysis (2D‐ST) was performed using EchoPAC Software Only (version 204) and was based solely on views obtained over four consecutive cardiac cycles. Left ventricular overall longitudinal strain (LVGLS) was calculated as the average of the four‐chamber (4CH), two‐chamber (2CH), and APLAX curves. Left atrial strain was evaluated using specialized paravalvular analysis modes on the non‐shortened apical 4CH and 2CH views of the left atrium. Based on the previous results [13, 14, 15], LVGLS greater than −17% was defined as left ventricular systolic dysfunction in the current study. The LASI was calculated as the ratio of the septal E/e' ratio to the left atrial strain reserve (LASr) [16]

2.3. Statistical Analysis

Data are presented as median (IQR) or number (%). When the data met the assumptions of normal distribution and homogeneity of variance, the method for comparing two groups was the t‐test. If the data did not meet the normal distribution assumption, the method for comparing two groups was the Wilcoxon test. The correlation between sST2 levels and left ventricular diastolic function parameters in CCS patients was evaluated using Spearman correlation analysis. To evaluate whether beta‐blocker therapy modified the association of sST2 and LASI with LVSD, interaction analyses were performed. Logistic regression models were constructed including sST2, LASI, beta‐blocker use status, adjusting for age, sex, NT‐proBNP and previous PCI. Because NT‑proBNP exhibited a skewed distribution, natural logarithmic (ln) transformation was applied prior to inclusion in the logistic regression models. The reported odds ratios for NT‑proBNP therefore represent the change in risk per 1‑unit increase in ln‑transformed NT‑proBNP. Additionally, subgroup analyses stratified by beta‐blocker use were performed to examine the independent effects of sST2 and LASI within each stratum. Internal validation was performed using bootstrap resampling with 1000 repetitions.

Statistical analysis and visualization were performed using R Statistical Software (4.2.1.) and Python (3.13.2). P < 0.05 was considered statistically significant.

3. Results

3.1. Clinical Characteristics and Laboratory Parameters of Two Groups

The baseline characteristics and laboratory parameters are summarized in Table 1. A total of 52 patients presented with left ventricular systolic dysfunction. The mean age was 63.5 years and 37 patients (71%) were men. There were no statistically significant differences in age, gender, body mass index (BMI), and risk factors such as history of hypertension, diabetes between patients with and without left ventricular systolic dysfunction (p > 0.05). Similarly, no significant differences were observed in the laboratory parameters of hemoglobin (Hb), blood glucose (Glu), total cholesterol (TC), creatinine (Cr), and low‐density lipoprotein cholesterol (LDL‐C). D‐dimer and triglycerides (TG) was slightly higher in the LVSD group than in the normal group. However, NT‐proBNP and sST2 were significantly higher in the LVSD group compared to the non‐LVSD group. In terms of treatment, the proportion of patients using beta‐blockers in the LVSD group was higher than that in the non‐LVSD group (p < 0.05).

TABLE 1.

Baseline characteristics and echocardiographic parameters of patients with left ventricular systolic dysfunction and non‐left ventricular systolic dysfunction.

Characteristics	Non‐LVSD (n = 83)	LVSD (n = 52)	p value
Basic characteristic
Sex, male, n (%)	55 (66%)	37 (71%)	0.553
Age, years	61 (56, 66.5)	63.5 (56, 71)	0.274
BMI, kg/m2	24.816 (22.995, 25.907)	24.918 (22.927, 26.166)	0.380
Hypertension, n (%)	50 (62%)	38 (73%)	0.091
Diabetes mellitus, n (%)	26 (31%)	22 (42%)	0.195
SBP, mmHg	131 (118.75, 140.25)	136.5 (116.5, 148)	0.399
DBP, mmHg	79 (70, 87)	82.5 (71.75, 90.75)	0.251
PCI, n (%)	22 (26%)	23 (44%)	0.025 *
Laboratory data
Hb, g/L	134.41 ± 16.486	137.79 ± 20.694	0.336
Glu, mmol/L	5.52 (4.83, 6.55)	5.345 (4.635, 6.86)	0.665
TG, mmol/L	1.33 (0.86, 1.72)	1.43 (1.05, 2.04)	0.041 *
TC, mmol/L	3.8475 ± 1.1376	3.8131 ± 1.119	0.882
LDL‐C, mmol/L	2.1077 ± 0.85938	2.0547 ± 0.91063	0.772
Cr, µmol/L	71.5 (58, 87.5)	83 (65, 104.75)	0.097
NT‐proBNP, pg/mL	66 (52, 134)	164 (109, 1250)	< 0.001 *
D‐dimer, ng/mL	283.5 (139.25, 448.75)	329 (224, 595.5)	0.036 *
sST2, ng/mL	16.75 (12.1, 25.2)	32.1 (20.6, 39.5)	< 0.001 *
Medications
RAS, n (%)	26 (31%)	23 (44%)	0.103
Beta‐blocker, n (%)	15 (18%)	20 (38%)	0.006 *
Calcium‐channel blocker, n (%)	27 (32%)	13 (25%)	0.419
Diuretics, n (%)	4 (5%)	4 (7%)	0.734
Oral anti‐diabetic agents, n (%)	21 (25%)	19 (36%)	0.138
Insulin, n (%)	2 (3%)	4 (7%)	0.296

Abbreviations: BMI, body mass index; Cr, creatinine; DBP, diastolic pressure; Glu, blood glucose; Hb, hemoglobin; LDL‐C, low‐density lipoprotein cholesterol; LVSD, left ventricular systolic dysfunction; NT‐proBNP, N‐terminal pro‐brain natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic pressure; sST2, soluble suppression of tumorigenicity‐2; TC, total cholesterol; TG, triglycerides.

^* p < 0.05.

3.2. Echocardiographic Characteristics of Two Groups

Echocardiographic parameters are summarized in Table 2. As expected, LV GLS was significantly impaired in the LVSD group compared with the non‐LVSD group, supporting the validity of the grouping strategy (p < 0.001). Overall, although EF values were above the normal range in both groups, the LVSD group demonstrated mild left ventricular dilation with slightly lower EF values than those in the non‐LVSD group (p < 0.05). Significant differences were observed between the two groups across multiple left atrial functional parameters. In the LVSD group, left ventricular diastolic function parameters such as left atrial volume index (LAVI) were elevated (p < 0.05), whereas left atrial reservoir strain (LASr), left atrial contraction strain (LASct), and left atrial conduit strain (LAScd) were lower, while the left atrial stiffness index, LASI (E/e'/LASr), was higher (p < 0.001).

TABLE 2.

Baseline echocardiographic characteristics of population according to groups: Non‐LVSD patients(n = 83) and LVSD patients(n = 52).

Echocardiographic parameters	Non‐LVSD (n = 83)	LVSD (n = 52)	p value
LV GLS, %	−19.3 (−20.7, −18.6)	−14.3 (−15.825, −11.425)	<0.001 *
LVEDV, mm	68 (55, 85)	79 (63, 104.2)	0.008 *
LVESV, mm	21 (16, 28)	30 (22.5, 47.5)	<0.001 *
EF, %	67 (63, 70)	58 (47.5, 63)	<0.001 *
LASr, %	29 (27, 34)	22.5 (17, 27)	<0.001 *
LASct, %	−14 (−17, −11)	−8 (−12, −5.75)	<0.001 *
LAScd, %	−15 (−18, −13)	−13 (−16.25, −10.75)	0.004 *
Transmitral E velocity, m/s	0.7 (0.64, 0.8)	0.615 (0.5, 0.78)	0.037 *
Mitral septal e' velocity, cm/s	0.08 (0.06, 0.0825)	0.05 (0.04, 0.06))	<0.001 *
E/septal e'	9.4 (8.3542, 10.9)	12.833 (10, 18.083)	<0.001 *
LAVI, mL/m2	26.397 ± 6.4302	31.234 ± 9.0085	0.001 *
LASI	0.31048 (0.25544, 0.4)	0.53841 (0.377, 0.824)	<0.001 *

Abbreviations:E, early mitral inflow; e', mitral annulus early diastolic velocity; EF, ejection fraction; LAScd, left atrial conduit strain; LASct, left atrial contraction strain; LASI, left atrial stiffness index; LASr, left atrial reservoir strain; LAVI, left atrial volume index; LVEDV, left ventricular end‐diastolic dimension; LVESV, left ventricular end‐systolic dimension; LVGLS, left ventricular overall longitudinal strain;

^* p <0.05.

3.3. Correlation between sST2 and Left Atrial Strain Parameters

In patients with CCS, the left atrial stiffness index, LASI, demonstrates a strong correlation with traditional diastolic function indices. LASI is positively correlated with the E/e' ratio (r = 0.87, p <0.001) and LAVI (r = 0.51, p <0.001). These findings suggest that LASI may serve as a novel indicator for evaluating left ventricular diastolic function in patients with CCS. Furthermore, this study indicated that sST2 is associated with multiple left ventricular diastolic function indices. sST2 is positively correlated with the E/e' ratio (r = 0.44, p <0.001) and LAVI (r = 0.33, p <0.001). In contrast, sST2 shows a significant negative correlation with left atrial strain parameters, LASr (r = −0.44, p <0.001), and positively correlated with LASI (r = 0.34, p <0.001) (Figure 2).

FIGURE 2.

Correlation between sST2, E/e', LAVI, LASr, and LASI in patients with CCS. sST2, serum growth stimulation expressed gene 2 protein; E/e', early mitral inflow/mitral annulus early diastolic velocity ratio; LAVI, left atrial volume index; LASr, left atrial reservoir strain; LASI, left atrial stiffness index.

3.4. Multivariable and Subgroup Analyses

Given the unbalanced distribution of beta‐blocker use between groups, a multivariable logistic regression model was constructed to include sex, age, beta‐blocker use, previous PCI, sST2, NT‐proBNP and LASI. After adjustment, sST2 (OR = 1.068, 95% CI: 1.013 – 1.126, p = 0.015) and LASI (OR = 1.592, 95% CI: 1.115 – 2.273, p = 0.015) remained independent predictors of subclinical LVSD. In contrast, although NT‐proBNP showed a significant association with the outcome in the univariate analysis (OR = 2.580, 95% CI 1.697–3.923, p <0.001), this association was no longer statistically significant in the multivariate model (OR = 1.565, 95% CI 0.863–2.838, p = 0.140) (Table 3). Consistently, in subgroup analyses stratified by beta‐blocker use, both sST2 (adjusted OR = 1.100, 95% CI: 1.002 – 1.207, p = 0.045 in the beta‐blocker group; adjusted OR = 1.077, 95% CI: 1.003 – 1.157, p = 0.042 in the non‐beta‐blocker group) and LASI (beta‐blocker group: adjusted OR = 2.856, 95% CI: 1.046 – 7.798, p = 0.041; non‐beta‐blocker group: adjusted OR = 1.640, 95% CI: 1.088 – 2.472, p = 0.018) remained independent predictors of LVSD (Table 4). These results indicate that beta‐blocker use did not significantly modify the predictive value of sST2 or LASI for LVSD (Table 4).

TABLE 3.

Univariable and Multivariable Logistic Regression Analyses for Factors Associated with Left Ventricular Systolic Dysfunction.

Characteristics	N	Univariable analysis		Multivariable analysis
		OR (95% CI)	p value	OR (95% CI)	p value
Sex	135
Male	92	Reference		Reference
Female	43	0.621 (0.287 – 1.345)	0.227	0.398 (0.126 – 1.259)	0.117
Age	135	1.018 (0.985 –‐ 1.052)	0.280	1.014 (0.969 – 1.060)	0.559
PCI	135
No	90	Reference		Reference
Yes	45	0.962 (0.434 – 2.129)	0.923	0.704 (0.235 – 2.111)	0.531
Beta‐blocker	135
No	100	Reference		Reference
Yes	35	1.472 (0.639 – 3.394)	0.364	1.712 (0.554 – 5.296)	0.351
sST2, ng/mL	135	1.094 (1.056 – 1.134)	<0.001 *	1.068 (1.013 – 1.126)	0.015 *
ln (NT‐proBNP, pg/mL)	135	2.580 (1.697 – 3.923)	<0.001 *	1.565 (0.863 – 2.838)	0.140
LASI †	135	1.834 (1.438 – 2.338)	<0.001 *	1.592 (1.115 – 2.273)	0.011 *

Note: Variables with P<0.05 in univariable analysis were entered into the multivariable logistic regression model.

Abbreviations: CI, confidence interval; LASI, left atrial strain index; NT‐proBNP was log‐transformed using the natural logarithm [ln (NT‐proBNP)] and entered into the model; OR, odds ratio; PCI, percutaneous coronary intervention; sST2, soluble suppression of tumorigenicity‐2;

^† OR expressed per 0.1‐unit increment in LASI.

^* p <0.05

TABLE 4.

Interaction and Subgroup Analyses of sST2, NT‐proBNP and LASI with beta‐Blocker Use for the Prediction of Left Ventricular Systolic Dysfunction.

Variable	Subgroup	N	OR (95% CI)	p value
sST2, ng/mL	beta‐blocker (+)	35	1.100 (1.002 – 1.207)	0.045 *
	beta‐blocker (‐)	100	1.077 (1.003 – 1.157)	0.042 *
ln (NT‐proBNP, pg/mL)	beta‐blocker (+)	35	0.821 (0.333 – 2.026)	0.669
	beta‐blocker (‐)	100	1.263 (0.637 – 2.503)	0.504
LASI †	beta‐blocker (+)	35	2.856 (1.046 – 7.798)	0.041 *
	beta‐blocker (‐)	100	1.640 (1.088 – 2.472)	0.018 *

Note: ORs and p values were estimated using subgroup‐specific logistic regression models adjusted for age, sex, and previous PCI.

Abbreviations: AUC, area under the curve; CI, confidence interval; LASI, left atrial strain index; NT‐proBNP was log‐transformed using the natural logarithm [ln (NT‐proBNP)] and entered into the model; OR, odds ratio; ROC, receiver operating characteristic; sST2, soluble suppression of tumorigenicity‐2;

^† OR expressed per 0.1‐unit increment in LASI.

^* p <0.05

3.5. Diagnostic Value of Risk Factors for CCS Patients With LVSD

To evaluate the diagnostic value of sST2 levels and LASI for LVSD in patients with CCS, ROC curves were constructed for sST2 and LASI separately (Figure 3A). The area under the curve (AUC) of sST2 in the diagnosis of LVSD was 0.767 (95%CI: 0.680 – 0.854), the optimal cut‐off value was 26.5 ng/ml. For LASI, the AUC was 0.776 (95% CI: 0.692 – 0.861), with an optimal cut‐off of 0.36. A logistic regression model incorporating sST2 and LASI was constructed, and ROC analysis was performed to obtain the combined index results. The AUC of the predictive model was 0.821 (95%CI: 0.749–0.894) (Figure 3B). In the beta‐blocker subgroup (n = 35), sST2 had an AUC of 0.793 (95% CI: 0.631 – 0.955) and LASI had an AUC of 0.829 (95% CI: 0.688 – 0.969) (Figure A). When the two indicators were combined using a logistic regression model, the AUC increased to 0.896 (95% CI: 0.795 – 0.998) (Figure C). In the non‐beta‐blocker subgroup (n = 100), sST2 showed an AUC of 0.798 (95% CI: 0.692 – 0.903) and LASI an AUC of 0.806 (95% CI: 0.701 – 0.910) (Figure B). When the two indicators were combined using a logistic regression model, the AUC increased to 0.855 (95% CI: 0.770 – 0.939) (Figure D). The results suggested that the diagnostic value of the model was independent of beta‐blocker therapy.

FIGURE 3.

A. Receiver operating characteristic curve for diagnosis of left ventricular systolic dysfunction in patients with CCS. sST2, soluble suppression of tumorigenicity‐2; LASI, left atrial stiffness index. B. Receiver operating characteristic curves showing the predictions of the model for left ventricular systolic dysfunction in patients with CCS.

3.6. Internal Bootstrap Validation of the Prediction Model

In the internal validation using 1000 bootstrap resamples, the model demonstrated good discrimination, with an apparent AUC of 0.827 and an optimism‐corrected AUC of 0.819. After optimism correction, the calibration intercept was −0.011, the calibration slope was 0.963 and the mean absolute calibration error was 0.032, indicating satisfactory calibration and overall predictive accuracy (Figure 4). The bias‐corrected calibration curve was close to the ideal 45‐degree line, suggesting good agreement between predicted and observed probabilities.

FIGURE 4.

Calibration curve of the prediction model for LVSD. The dotted line represents the apparent calibration curve, the solid line represents the bootstrap bias‐corrected calibration curve, and the dashed diagonal line represents ideal calibration. Bootstrap validation was performed with 1000 resamples. The rug plot at the top indicates the distribution of predicted probabilities.

4. Discussions

This study found that: (1) In the group with left ventricular systolic dysfunction, the expression levels of sST2 and LASr were reduced, while the LASI was increased. (2) The expression of sST2 was positively correlated with left ventricular diastolic function indices and LASI. (3) sST2 and LASI are independent predictors for diagnosing LVSD in patients with CCS. (4) The combination of sST2 and LASI can predict left ventricular systolic dysfunction in patients with CCS. This finding emphasizes the predictive value of sST2 and left atrial strain for left ventricular contractile dysfunction in patients with CCS. For some patients with coronary heart disease, left ventricular systolic function cannot be restored even after revascularization. Therefore, early identification and diagnosis of such patients is of great significance. Previous studies have shown that an increase in sST2 levels over one year can identify patients at higher risk for progressive left ventricular dysfunction [17]. Meanwhile, left atrial functional indices have diagnostic and prognostic value for HFpEF; however, larger‐scale studies are still needed to better assess whether these indices can truly optimize diagnosis or prognosis [18]. This study aims to combine sST2 with echocardiographic LV, LA strain parameters in patients with CCS to explore its predictive value for early left ventricular systolic dysfunction, which may indicate myocardial remodeling.

sST2 is a biomarker that is released in response to vascular congestion, inflammation, and proliferative stimuli, and can predict the risk of death and hospitalization in patients with acute or chronic heart failure [11]. In clinical practice, B‐type natriuretic peptides (BNPs) are one of the most commonly used biomarkers for the diagnosis, risk stratification, and treatment of HF. However, BNPs have certain limitations, such as being influenced by renal insufficiency, age, obesity, atrial fibrillation, and various cardiac and non‐cardiac diseases beyond heart failure. Additionally, their role in guiding treatment is still not well defined [19]. Recently, there has been growing interest in risk stratification for HF and the use of multiple biomarkers to identify different pathophysiological processes associated with the disease. Previous studies have shown that in patients with acute heart failure, sST2 has a strong prognostic value independent of NT‐proBNP. Subsequent studies have confirmed that mortality increases progressively with sST2 deciles. When sST2 levels are low, natriuretic peptides do not predict mortality [11, 20]. Furthermore, combining ST2 and NT‐proBNP can significantly improve mortality risk stratification beyond models based solely on established mortality risk factors [21]. In addition to research in heart failure, sST2, high‐sensitivity (hs)‐cTnI, and NT‐proBNP are associated with 15‐year mortality and cardiovascular events in patients with type 2 diabetes [22]. In this study, the enrolled patients were predominantly those with CCS, where left ventricular filling pressures may be only mildly or intermittently elevated. Therefore, NT‐proBNP is less specific for structural remodeling and early systolic impairment. In contrast, sST2 is a mechanistically distinct biomarker that directly reflects myocardial fibrosis and maladaptive remodeling triggered by biomechanical strain, robustly associating with progressive ventricular dysfunction irrespective of loading conditions [23, 24]. Meanwhile, LASI is an exquisitely sensitive index of left atrial reservoir function that integrates the chronic burden of elevated left ventricular filling pressure and subtle diastolic abnormalities, even when ejection fraction is still preserved [7]. Therefore, the inclusion of LASI and sST2 in our diagnostic model likely captures both the upstream hemodynamic drivers and the downstream fibrotic processes that lead to LVSD, thereby compensating for the diagnostic limitations of NT‐proBNP. Meanwhile, our study identified an optimal sST2 cutoff of 26.5 ng/mL for LVSD in patients with CCS, lower than the conventional 35 ng/mL threshold established HF hospitalization. This finding aligns with reports from independent cohorts, where sST2 ≥ 26.8 ng/mL was associated with significantly lower MACE‐free survival in coronary artery disease patients [25]. The convergence of these results underscores the need to adopt a lower sST2 baseline when evaluating early subclinical myocardial remodeling in CCS patients with preserved ejection fraction.

Multiple echocardiographic parameters, including left atrial volume, mitral inflow velocities, E/e′ ratio, and peak tricuspid regurgitation velocity, can be used to assess left ventricular diastolic function. With the development of two‐dimensional speckle tracking imaging, left atrial strain can also be added to this assessment [26]. The LASI estimated by left atrial strain and E/e′ is a simple, noninvasive, and readily obtainable parameter that demonstrates a strong correlation with NT‐proBNP and conventional echocardiographic diastolic function parameters (including E/e′, left atrial volume index, and right ventricular systolic pressure) during HFpEF progression [7]. Previous studies have suggested that since the ventricle and atrium are anatomically connected and the LV apex remains essentially stationary during the cardiac cycle, longitudinal shortening of the LV results in LA stretching [26, 27, 28, 29, 30]. In patients with LVSD, there is a continued need for non‐invasive imaging modalities for assessment and diagnosis, for which echocardiography remains the preferred choice [31, 32]. Our study demonstrated that in patients with CCS, decreased LASr and increased LASI are important determinants of reduced LV GLS. Studies have shown that sST2 level and 3D speckle tracking are predictive factors for coronary artery disease severity in patients with CCS [33]. Additionally, sST2 plasma levels correlate with features of left ventricular dysfunction as assessed by cardiac magnetic resonance (CMR) and echocardiography in patients with inflammatory cardiomyopathy [34, 35]. However, no studies have examined the combined predictive value of sST2 and LA strain for left ventricular systolic function; addressing this gap constitutes the primary objective of our study. The results of this study indicate that left atrial function is also impaired during LV systolic dysfunction in CCS patients, which may be related to myocardial remodeling. The combination of this biomarker with strain parameters exhibits high sensitivity and specificity for diagnosing left ventricular systolic dysfunction, with the area under the curve of the combined index reaching 0.821.

Confounding effect of beta‐blocker therapy and rate‐dependence of LA strain parameters [36]. In our cohort, beta‐blocker use was more prevalent in the LVSD group than in the non‐LVSD group (38% vs. 18%, p = 0.006), reflecting clinical practice in which patients with more advanced ischemic burden or impaired ventricular function are more likely to receive guideline‐directed therapy. beta‐blockers reduce heart rate, prolong diastolic filling time, and may thereby influence LA reservoir and conduit strain through alterations in atrial loading conditions [36]. This raises a legitimate concern that the differences in left atrial strain‐derived indices between the two groups are due to medication use. Two lines of evidence from our study mitigate this concern. First, in a multivariable logistic regression model adjusting for beta‐blocker use, both sST2 and LASI remained independent predictors of subclinical LVSD, while beta‐blocker use itself did not reach statistical significance. Second, subgroup analysis stratified by beta‐blocker therapy demonstrated that sST2 and LASI were independent diagnostic factors in each subgroup. An additional consideration is that patients with persistent or permanent atrial fibrillation were excluded from this study because irregular RR intervals distort strain processing and reduce the feasibility of reliable left atrial reservoir strain measurement. Given that atrial fibrillation is highly prevalent in patients with chronic coronary syndrome and shares common pathophysiological ground with elevated filling pressures and left atrial remodeling, this exclusion narrows the clinical applicability of our model to patients in sinus rhythm. Dedicated strain analysis algorithms or alternative atrial functional indices are needed before the model can be safely extrapolated to the atrial fibrillation population.

4.1. Limitations

Several limitations of the present study should be acknowledged. First, the total sample size of 135 patients is relatively modest for developing a multivariable diagnostic model, and the beta‐blocker subgroup comprised only 35 individuals. Consequently, subgroup analyses are likely underpowered, and the stability of regression coefficients may be affected. While internal bootstrap validation demonstrated good calibration and discrimination, external validation in an independent multicenter cohort is still lacking. This limits the immediate generalizability of the proposed diagnostic equation to other clinical settings with different patient demographics and echocardiographic equipment. Future prospective studies with larger, more diverse populations are required to confirm the robustness and transportability of the sST2–LASI model. A further practical limitation is the sinus‐rhythm‐only design, as atrial fibrillation precludes reproducible left atrial strain measurement. Given the frequent coexistence of chronic coronary syndrome and atrial fibrillation, this restricts the current diagnostic algorithm to the sinus‐rhythm population and highlights the need for strain tools validated in arrhythmia before wider application.

Funding

This report was supported by Jiangsu Provincial Key Research and Development Program (BE2022852).

Ethics Statement

This study was approved by the Ethics Committee of Zhongda Hospital, Affiliated to Southeast University (approval number: 2022ZDSYLL407‐P01). Written informed consent was obtained from all participants prior to enrollment.

Conflicts of Interest

The authors declare that they currently have no potential conflicts of interest or personal relationships that could influence the study results reported herein.

Supporting information

Supporting File: echo70583‐sup‐0001‐figureS1.tif

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.