Stress hyperglycemia and early mortality in non-ST elevation myocardial infarction

Abstract

BACKGROUND

Acute hyperglycemia is frequently observed in patients presenting with acute coronary syndromes and is considered a marker of metabolic and neurohormonal stress. However, its prognostic significance relative to chronic glycemic status remains incompletely understood, particularly in patients with non-ST-segment elevation myocardial infarction (NSTEMI). Glycated hemoglobin (HbA1c) reflects long-term glycemic control but may not adequately capture acute metabolic derangements occurring during myocardial ischemia. Stress hyperglycemia reflects a transient metabolic response to acute illness mediated by counter-regulatory hormones, systemic inflammation, and increased hepatic gluconeogenesis, and does not necessarily indicate pre-existing insulin resistance or chronic dysglycemia. Recent studies suggest that stress-related hyperglycemia indices may better reflect short-term risk, yet comparative data in NSTEMI populations remain limited.

AIM

To determine whether admission stress hyperglycemia indices are associated with early mortality in patients with non-ST elevation myocardial infarction.

METHODS

This prospective, single-center observational study consecutively enrolled 171 patients admitted with confirmed NSTEMI. Stress hyperglycemia was assessed using the stress hyperglycemia ratio (SHR) and the admission glucose-to-chronic glycemia ratio (ACGR), calculated from admission plasma glucose and HbA1c values obtained at hospital presentation. Patients were categorized according to established HbA1c thresholds. Clinical, laboratory, and echocardiographic data were systematically collected. All patients were followed for three months after discharge. The primary endpoint was the occurrence of major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, or urgent coronary revascularization. The secondary endpoint was all-cause mortality. Discriminatory performance was evaluated using receiver operating characteristic (ROC) curve analysis. Multivariable logistic regression models were constructed to assess the independent and incremental prognostic value of stress hyperglycemia indices before and after adjustment for established clinical and echocardiographic predictors.

RESULTS

During the three-month follow-up period, 88 MACE and 25 deaths were recorded. HbA1c categories were not significantly associated with all-cause mortality or MACE. In contrast, admission glucose levels, SHR, and ACGR were significantly higher in non-survivors than in survivors. No significant differences in HbA1c were observed between outcome groups. Stress hyperglycemia indices demonstrated modest discriminatory ability for predicting mortality and showed greater discrimination than HbA1c in ROC analyses. In multivariable models, both SHR and ACGR remained independently associated with early mortality after adjustment for demographic, clinical, and echocardiographic variables, whereas no independent association with the composite MACE endpoint was observed. ROC-derived thresholds used for survival analyses were exploratory and have not been externally validated.

CONCLUSION

In patients with NSTEMI, stress hyperglycemia indices assessed at hospital admission are independently associated with early mortality, whereas chronic glycemic status shows limited prognostic relevance. These indices appear to reflect acute systemic stress and metabolic instability and may provide clinically useful information for early risk stratification during the initial phase of hospitalization, particularly when comprehensive echocardiographic assessment is not yet available.

Key Words: Non-ST elevation myocardial infarction; Stress hyperglycemia; Glycated hemoglobin; Mortality; Major adverse cardiovascular events

Core Tip: Acute hyperglycemia is common in patients with non-ST-segment elevation myocardial infarction, yet its clinical interpretation remains challenging. This study demonstrates that stress hyperglycemia indices, including the stress hyperglycemia ratio and admission glucose-to-chronic glycemia ratio, are associated with early mortality, whereas glycated hemoglobin alone does not reliably discriminate short-term risk. These findings indicate that acute glycemic dysregulation primarily reflects the magnitude of systemic stress rather than chronic metabolic control and may contribute to early metabolic risk stratification, particularly before comprehensive echocardiographic assessment becomes available.

INTRODUCTION

Acute coronary syndromes (ACS) are frequently accompanied by acute disturbances in glucose metabolism, even in patients without previously diagnosed diabetes mellitus (DM)[1]. Transient elevations in blood glucose during acute myocardial infarction have been consistently associated with adverse clinical outcomes; however, the biological and clinical significance of this phenomenon remains incompletely understood[2]. Importantly, admission hyperglycemia represents a heterogeneous metabolic response that may reflect chronic dysglycemia, acute stress-related mechanisms, or their interaction[3].

Glycated hemoglobin (HbA1c) is widely used to assess long-term glycemic status and to identify previously unrecognized diabetes or prediabetes. However, HbA1c does not capture acute metabolic fluctuations occurring during critical illness[4]. In patients presenting with non-ST elevation myocardial infarction (NSTEMI), early outcomes are predominantly driven by infarct severity, systemic inflammatory activation, and hemodynamic compromise rather than by chronic glycemic control alone[5]. Consequently, HbA1c may have limited utility for early risk stratification during the acute phase of NSTEMI[6].

Stress hyperglycemia refers to a transient elevation in blood glucose triggered by acute illness and mediated by neurohormonal activation, inflammatory signaling, and acute insulin resistance. Acute myocardial infarction is associated with activation of the hypothalamic-pituitary-adrenal axis and sympathetic nervous system, resulting in increased circulating levels of catecholamines, cortisol, and glucagon. These counter-regulatory hormones promote hepatic gluconeogenesis and glycogenolysis, impair peripheral glucose uptake by reducing insulin sensitivity in skeletal muscle and adipose tissue, and contribute to transient hyperglycemia independent of baseline glycemic status. In parallel, pro-inflammatory cytokine release may further exacerbate insulin resistance and endothelial dysfunction during the acute phase of ischemia. To more accurately quantify this response, indices integrating admission glucose levels with markers of chronic glycemia have been proposed[7]. Among these, the stress hyperglycemia ratio (SHR) and the admission glucose-to-chronic glycemia ratio (ACGR) have gained increasing attention. By relating acute glucose concentrations to estimated baseline glycemic status derived from HbA1c, these indices aim to distinguish relative stress-related hyperglycemia from chronically elevated glucose levels[8].

Accumulating evidence suggests that stress hyperglycemia is closely linked to systemic inflammation, endothelial dysfunction, and adverse myocardial remodeling. In the context of ACS, stress-related metabolic derangements often coexist with heightened inflammatory burden and may reflect the overall severity of the acute pathological state[9]. However, data regarding the prognostic significance of stress hyperglycemia indices in NSTEMI remain inconsistent, particularly with respect to short-term outcomes such as early mortality and major adverse cardiovascular events (MACE)[10]. Importantly, it remains unclear whether stress hyperglycemia represents an independent pathophysiological contributor to adverse outcomes or rather an early metabolic surrogate of infarct severity and systemic stress that precedes overt myocardial dysfunction[11].

Therefore, the present study aimed to evaluate the association between stress hyperglycemia indices assessed at hospital admission and early adverse outcomes in patients with NSTEMI[12]. Specifically, we examined the relationship of SHR and ACGR with 3-month all-cause mortality and MACE, compared their discriminatory performance with traditional glycemic markers, and assessed their incremental prognostic value before and after incorporation of echocardiographic parameters, including left ventricular ejection fraction (LVEF)[13]. By focusing on early admission biomarkers obtained before echocardiographic assessment, this study seeks to clarify the clinical relevance of acute glycemic dysregulation in early risk stratification of NSTEMI patients.

MATERIALS AND METHODS

Study design and population

This was a prospective, single-center observational study conducted at the Clinic for Internal Medicine, University Clinical Centre Tuzla, between February 1, 2022, and January 31, 2023. A total of 171 consecutive adult patients admitted with a confirmed diagnosis of NSTEMI were included. The present manuscript represents a secondary analysis of a prospectively collected dataset. The original dataset was not modified, and the data have not been previously published in this analytical context.

Inclusion and exclusion criteria

Eligible patients were aged ≥ 18 years and had a diagnosis of NSTEMI, defined by ischemic chest pain or equivalent symptoms, elevated cardiac troponin levels, and electrocardiographic findings consistent with myocardial ischemia without persistent ST-segment elevation.

Exclusion criteria included active infection, known autoimmune or chronic inflammatory disease, active malignancy, severe hepatic dysfunction, end-stage renal disease requiring dialysis, recent major trauma or surgery within four weeks before admission, and the need for immediate surgical coronary artery bypass grafting.

Clinical assessment and data collection

Baseline clinical data were obtained from electronic medical records. They included age, sex, body mass index (BMI), history of arterial hypertension, DM, smoking status, alcohol consumption, and family history of cardiovascular disease. Standard 12-lead electrocardiography was performed in all patients at admission. Transthoracic echocardiography (TTE) was performed during hospitalization in accordance with routine clinical practice. Echocardiographic parameters were incorporated only in extended prognostic models to assess their incremental impact on risk stratification.

Laboratory measurements

Venous blood samples were collected at hospital admission, before echocardiographic assessment and invasive procedures. Complete blood count was performed using K₂EDTA tubes (Becton, Dickinson and Company, Franklin Lakes, NJ, United States) and analyzed with the Sysmex XN-1000 automated hematology analyzer (Sysmex Corporation, Kobe, Japan). Biochemical parameters, including serum glucose, lipid profile [total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), triglycerides], creatinine, C-reactive protein (CRP), aspartate aminotransferase (AST), and alanine aminotransferase (ALT), were measured from serum-separating tubes using the Beckman Coulter DxC 700 AU chemistry analyzer (Beckman Coulter Diagnostics, Brea, CA, United States). HbA1c was measured using a standardized, NGSP-certified method.

Calculation of glycemic, lipid, and inflammatory indices

Chronic glycemic status was assessed using HbA1c. Stress hyperglycemia was evaluated using indices calculated from admission values according to previously validated formulas: SHR = admission glucose/[(1.59 × HbA1c) - 2.59], ACGR = admission glucose/estimated average glucose derived from HbA1c.

Additional metabolic and inflammatory indices were calculated as follows: Triglyceride-glucose (TyG) index = ln [triglycerides (mg/dL) × glucose (mg/dL)/2], atherogenic index of plasma (AIP) = log₁₀ (triglycerides/HDL-C), neutrophil-to-lymphocyte ratio = neutrophil count/Lymphocyte count, pan-immune-inflammation value (PIV) = (neutrophils × platelets × monocytes)/Lymphocytes, De Ritis ratio = AST/ALT.

For the TyG calculation, triglyceride and glucose values were converted from mmol/L to mg/dL prior to computation. These indices were used to characterize early metabolic and inflammatory stress at admission, before echocardiographic assessment and invasive risk stratification.

Echocardiographic assessment

TTE was performed by an experienced, licensed echocardiographic sonographer using standard ultrasound equipment available at the institution. LVEF was assessed using the biplane Simpson method in accordance with current guideline recommendations[14]. LVEF was included in extended prognostic models to evaluate the incremental predictive value of early metabolic and inflammatory markers beyond established measures of myocardial dysfunction.

Treatment and standard care

Patients were treated according to contemporary guideline-directed medical therapy for NSTEMI. This included dual antiplatelet therapy with aspirin and clopidogrel and high-intensity statin therapy. Additional pharmacological treatments, including angiotensin-converting enzyme inhibitors, beta-blockers, and other medications, were prescribed at the treating physician's discretion.

Follow-up and outcome measures

Patients were followed for three months after hospital discharge. The primary outcome was MACE, defined as a composite of cardiovascular death, non-fatal myocardial infarction, or urgent coronary revascularization. The secondary outcome was all-cause mortality. Follow-up data were obtained by reviewing hospital records and available outpatient documentation. Classification of cardiovascular death was based on available hospital records and discharge documentation.

Ethics statement

The study protocol was approved by the Ethics Committee of the University Clinical Centre Tuzla (No. 02-09/2-97/21, January 12, 2022). All patients provided written informed consent at the time of initial data collection. This secondary analysis used anonymized data collected during routine clinical care.

Statistical analysis

All continuous variables were tested for normality of distribution using the Kolmogorov-Smirnov test. As most variables demonstrated non-normal distributions, non-parametric statistical methods were applied. Categorical variables are presented as n (%), while continuous variables are expressed as medians with interquartile ranges or mean ± SD, as appropriate. Comparisons between two groups were performed using the χ² test for categorical variables and the Mann-Whitney U test for continuous variables. Comparisons across more than two groups were conducted using the Kruskal-Wallis test. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminative performance of early-admission biomarkers and derived indices for 3-month all-cause mortality. The area under the curve (AUC) with corresponding 95% confidence interval was calculated, and optimal cut-off values were determined using the Youden index.

Multivariable logistic regression analyses were performed to evaluate the association between early admission biomarkers and 3-month outcomes. Variables were selected for inclusion in multivariable models based on clinical relevance and established prognostic importance in NSTEMI, rather than solely on univariate statistical significance. Regression models were constructed sequentially. Model 1 included age, sex, serum creatinine, arterial hypertension, admission glucose, and SHR. Model 2 additionally incorporated inflammatory markers (CRP and PIV). Model 3 further included echocardiographic parameters, including LVEF, to assess whether early admission biomarkers provided incremental prognostic information beyond established measures of myocardial dysfunction. To evaluate potential multicollinearity among predictors, variance inflation factors (VIF) were calculated for all variables included in the multivariable models. Results are presented as odds ratios with corresponding 95% confidence intervals. All statistical tests were two-sided, and P values < 0.05 were considered statistically significant. Statistical analyses were performed using IBM SPSS Statistics software, version 26.0 (IBM Corp., Armonk, NY, United States).

RESULTS

Baseline demographic and clinical characteristics stratified according to HbA1c categories are presented (Table 1). The study cohort comprised 171 patients with NSTEMI, among whom 88 MACE and 25 deaths occurred during the 3-month follow-up period. Age and BMI did not differ significantly across HbA1c categories (P = 0.497 and P = 0.971, respectively). The incidence of 3-month MACE and 3-month all-cause mortality was comparable among patients with normal glycemia, prediabetes, and diabetes (P = 0.674 and P = 0.168, respectively), indicating that chronic glycemic status did not discriminate early adverse outcomes in this population (Table 1).

Table 1 Baseline demographic and clinical characteristics stratified by glycated hemoglobin categories, n (%)/median (interquartile range).

Variable	Total (n = 171)	Normoglycemia (n = 56)	Prediabetes (n = 57)	Diabetes (n = 58)	P value
Age (years)	67 (59-75)	66 (58-74)	67 (60-76)	68 (61-77)	0.497
Male sex	118 (69.0)	40 (71.4)	39 (68.4)	39 (67.2)	0.88
Body mass index	27.5 (25.1-30.3)	27.3 (25.0-30.1)	27.6 (25.2-30.4)	27.7 (25.3-30.6)	0.971
Arterial hypertension	132 (77.2)	41 (73.2)	43 (75.4)	48 (82.8)	0.34
Admission glucose (mmol/L)	7.6 (6.4-9.1)	6.7 (6.1-7.5)	7.4 (6.5-8.4)	9.3 (8.1-11.1)	< 0.001
HbA1c (%)	6.2 (5.7-7.1)	5.5 (5.3-5.7)	6.0 (5.8-6.2)	7.7 (7.1-8.5)	< 0.001
MACE at 3 months	88 (51.5)	27 (48.2)	30 (52.6)	31 (53.4)	0.674
All-cause mortality at 3 months	25 (14.6)	7 (12.5)	8 (14.0)	10 (17.2)	0.168

HbA1c: Glycated hemoglobin A1c; MACE: Major adverse cardiovascular events.

Admission metabolic and inflammatory markers obtained at presentation, before TTE assessment, are shown (Table 2). Patients who died within 3 months were significantly older than survivors (median 75 years vs 66 years, P < 0.001) and exhibited higher admission glucose levels (median 9.10 mmol/L vs 7.20 mmol/L, P = 0.012). Indices reflecting stress hyperglycemia relative to chronic glycemic status were significantly elevated among non-survivors, including the SHR (median 1.18 vs 0.90, P = 0.018) and the ACGR (median 0.99 vs 0.76, P = 0.016). In contrast, HbA1c levels did not differ between survivors and non-survivors (P = 0.528) (Table 2). Systemic inflammatory activation was markedly higher among non-survivors, with significantly increased CRP concentrations (median 30.4 mg/L vs 9.0 mg/L, P < 0.001) and elevated PIV levels (median 1399 vs 561, P = 0.005) (Table 2). TyG, AIP, and the De Ritis ratio did not differ significantly between survivors and non-survivors in unadjusted analyses (all P > 0.05) (Table 2).

Table 2 Admission biomarkers according to 3-month survival status, median, (interquartile range).

Variable	Survivors (n = 146)	Non-survivors (n = 25)	P value
Age, years	66 (58-73)	75 (69-82)	< 0.001
Admission glucose, (mmol/L)	7.20 (6.30-8.50)	9.10 (8.10-11.40)	0.012
HbA1c (%)	6.1 (5.7-7.0)	6.2 (5.8-7.2)	0.528
Stress hyperglycemia ratio	0.90 (0.78-1.05)	1.18 (1.02-1.35)	0.018
Admission glucose-to-chronic glycemia ratio	0.76 (0.68-0.88)	0.99 (0.87-1.12)	0.016
C-reactive protein (mg/L)	9.0 (4.0-18.0)	30.4 (18.0-62.0)	< 0.001
Pan-immune-inflammation value	561 (320-980)	1399 (850-2100)	0.005
Triglyceride-glucose index	8.8 (8.4-9.2)	9.0 (8.6-9.4)	0.18
Atherogenic index of plasma	0.26 (0.14-0.39)	0.29 (0.17-0.41)	0.31
De Ritis ratio (AST/ALT)	1.12 (0.94-1.34)	1.18 (0.97-1.42)	0.27

HbA1c: Glycated hemoglobin A1c; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase.

The discriminatory performance of early admission biomarkers for 3-month all-cause mortality is illustrated (Figure 1). CRP demonstrated the highest discriminatory ability (AUC = 0.727), followed by PIV (AUC = 0.675). Stress hyperglycemia indices showed moderate discrimination, with AUC values of 0.649 for SHR and 0.651 for ACGR, comparable to admission glucose (AUC = 0.657), and showed greater discrimination than HbA1c, which demonstrated poor discriminatory performance (AUC = 0.460). Although inflammatory markers showed greater overall discrimination, stress hyperglycemia indices retained clinically relevant prognostic information because they are immediately available at hospital admission.

Figure 1 Receiver operating characteristic curves illustrating the discriminatory performance of early admission biomarkers for the prediction of 3-month all-cause mortality. CRP: C-reactive protein; AUC: Area under the curve; SHR: Stress hyperglycemia ratio; HbA1c: Glycated hemoglobin.

Multivariable logistic regression analyses for 3-month all-cause mortality are presented (Table 3). A baseline clinical model incorporating age, sex, serum creatinine, arterial hypertension, admission glucose, and SHR demonstrated moderate discrimination for 3-month mortality. The subsequent inclusion of inflammatory markers and echocardiographic parameters allowed assessment of the incremental prognostic contribution of early admission metabolic indices beyond established clinical and functional predictors.

Table 3 Multivariable logistic regression analysis for 3-month all-cause mortality.

Variable	Model 1 OR (95%CI)	P value	Model 2 OR (95%CI)	P value	Model 3 OR (95%CI)	P value
Age (per year)	1.07 (1.03-1.11)	< 0.001	1.06 (1.02-1.10)	0.002	1.05 (1.01-1.09)	0.009
Male sex	1.18 (0.51-2.71)	0.69	1.10 (0.47-2.58)	0.82	1.05 (0.44-2.51)	0.91
Serum creatinine (per 10 μmol/L)	1.09 (1.02-1.16)	0.010	1.07 (1.01-1.15)	0.028	1.05 (0.99-1.12)	0.10
Arterial hypertension	1.32 (0.54-3.20)	0.54	1.28 (0.51-3.18)	0.60	1.19 (0.47-3.01)	0.71
Admission glucose (mmol/L)	1.15 (1.03-1.29)	0.014	1.18 (1.05-1.33)	0.006	1.10 (0.97-1.25)	0.13
Stress hyperglycemia ratio	1.92 (1.14-3.24)	0.015	2.04 (1.18-3.53)	0.011	1.41 (0.78-2.56)	0.25
Left ventricular ejection fraction (per 5%)					0.72 (0.61-0.85)	< 0.001

Model 1 included age, sex, serum creatinine, arterial hypertension, admission glucose, and stress hyperglycemia ratio. Model 2 additionally included inflammatory markers (C-reactive protein and pan-immune-inflammation value). Model 3 further incorporated echocardiographic parameters, including left ventricular ejection fraction. Odds ratio are presented per unit increase unless otherwise specified. OR: Odds ratio.

After incorporation of echocardiographic parameters into the mortality models, LVEF emerged as the strongest independent predictor. In this fully adjusted setting, the association between stress hyperglycemia indices and mortality was attenuated (Table 3). Assessment of multicollinearity using VIF revealed substantial collinearity among admission glucose, SHR, age, and LVEF, indicating partial overlap between early metabolic stress markers and subsequent measures of myocardial dysfunction. These findings suggest that the prognostic information captured by stress hyperglycemia indices at admission may, in part, reflect early pathophysiological processes that later manifest as overt left ventricular systolic impairment.

Multivariable logistic regression analyses for the composite MACE endpoint are shown (Table 4). Early stress hyperglycemia indices did not demonstrate independent prognostic value for MACE after adjustment. In contrast, inflammatory burden and left ventricular systolic function accounted for the majority of observed risk (Table 4).

Table 4 Multivariable logistic regression analysis for 3-month major adverse cardiovascular events.

Variable	Model 1 OR (95%CI)	P value	Model 2 OR (95%CI)	P value	Model 3 OR (95%CI)	P value
Age (per year)	1.03 (1.01-1.05)	0.012	1.03 (1.01-1.05)	0.018	1.02 (1.00-1.05)	0.06
Male sex	1.22 (0.72-2.05)	0.46	1.19 (0.70-2.02)	0.52	1.15 (0.67-1.97)	0.61
Serum creatinine (per 10 μmol/L)	1.05 (1.01-1.09)	0.014	1.04 (1.00-1.09)	0.041	1.03 (0.99-1.08)	0.11
Arterial hypertension	1.18 (0.68-2.06)	0.56	1.15 (0.66-2.01)	0.62	1.10 (0.62-1.97)	0.74
Admission glucose (mmol/L)	1.07 (0.98-1.17)	0.12	1.07 (0.98-1.17)	0.12	1.03 (0.94-1.13)	0.53
Stress hyperglycemia ratio	1.29 (0.89-1.87)	0.18	1.29 (0.89-1.87)	0.18	1.12 (0.75-1.68)	0.57
Left ventricular ejection fraction (per 5%)					0.81 (0.73-0.90)	< 0.001

Model 1 included age, sex, serum creatinine, arterial hypertension, admission glucose, and stress hyperglycemia ratio. Model 2 additionally included inflammatory markers (C-reactive protein and pan-immune-inflammation value). Model 3 further incorporated echocardiographic parameters, including left ventricular ejection fraction. Odds ratio are presented per unit increase unless otherwise specified. OR: Odds ratio.

Using Youden index-derived thresholds, Kaplan-Meier survival analyses demonstrated a consistent separation between higher- and lower-risk groups for 90-day all-cause mortality. Patients with admission glucose > 7.70 mmol/L had significantly higher mortality compared with those with lower values (17/81 vs 8/89; log-rank P = 0.025). Similar patterns were observed for stress hyperglycemia indices, with increased mortality among patients with SHR > 0.565 (24/130 vs 1/40; log-rank P = 0.015) and ACGR > 0.492 (24/132 vs 1/38; log-rank P = 0.021) (Figure 2). These findings suggest that acute glycemic stress at presentation may be associated with an increased risk of early mortality; however, the applied thresholds should be interpreted in an exploratory context and should not be used for clinical decision-making without external validation.

Figure 2 Kaplan-Meier survival curves for 3-month all-cause mortality. A: Stratified by admission glucose level; B: Stratified by stress hyperglycemia ratio; C: Stratified by admission glucose-to-chronic glycemia ratio.

DISCUSSION

In this prospective cohort of patients with acute NSTEMI, stress hyperglycemia indices assessed at hospital admission were associated with early mortality[15]. In contrast, chronic glycemic status, as reflected by HbA1c, did not discriminate short-term adverse outcomes. Although the observed discriminatory performance of stress hyperglycemia indices was modest, these markers appeared to provide clinically relevant information when interpreted in the context of early metabolic stress at presentation. Established clinical predictors such as age and LVEF demonstrated stronger associations with outcomes in adjusted models, underscoring that stress hyperglycemia indices should be viewed as complementary rather than alternative risk markers during the initial phase of hospitalization[16]. A central observation of the present study is the absence of an association between HbA1c categories and both 3-month mortality and MACE[17]. Although HbA1c is widely used to estimate chronic glycemic exposure and long-term cardiometabolic risk, its prognostic relevance appears limited in the acute phase of NSTEMI[18]. Early outcomes in this setting are primarily driven by infarct severity, systemic inflammatory activation, neurohormonal stress, and hemodynamic compromise, processes that evolve rapidly and are insufficiently reflected by chronic glycemic markers. These findings support the concept that chronic dysglycemia and early adverse outcomes in NSTEMI are mediated through partially distinct biological pathways[19].

In contrast, admission glucose levels and stress hyperglycemia indices, including the SHR and the ACGR, were significantly higher among non-survivors[20]. At the same time, HbA1c values were comparable between outcome groups. This dissociation indicates that mortality risk was driven primarily by acute, disproportionate hyperglycemia rather than by underlying chronic dysglycemia[21]. Stress hyperglycemia, therefore, appears to represent a distinct metabolic phenotype characterized by acute insulin resistance, activation of counter-regulatory hormones, and heightened inflammatory signaling[22]. While stress-adjusted glycemic indices demonstrated modest discriminatory ability in ROC analyses, their association with early mortality remained independent of chronic glycemic status and was consistent with prior observations in acute coronary populations[10].

The close association between stress hyperglycemia and systemic inflammatory activation further supports this interpretation[10]. Patients with fatal outcomes exhibited higher levels of inflammatory markers, including CRP and PIV, underscoring the interplay between metabolic stress and immune activation[23]. Rather than constituting an isolated metabolic abnormality, stress hyperglycemia likely integrates neurohormonal activation, cytokine-mediated insulin resistance, endothelial dysfunction, and microvascular impairment, thereby reflecting the overall severity of the acute systemic response to myocardial ischemia[24].

In multivariable analyses, the prognostic association of stress hyperglycemia indices was attenuated after incorporation of echocardiographic parameters, with LVEF emerging as the strongest predictor of both mortality and MACE[25]. This attenuation should not be interpreted as a limitation of stress hyperglycemia indices. Instead, it suggests that these indices capture early systemic and myocardial stress that subsequently manifests as overt ventricular dysfunction detectable by echocardiography. From a clinical perspective, stress hyperglycemia indices may therefore serve as early risk markers during the initial hours of NSTEMI presentation, when echocardiographic assessment may not yet be available[26].

Notably, stress hyperglycemia indices were associated with mortality but not with adjusted MACE outcomes. This finding suggests that acute glycemic dysregulation preferentially identifies patients at risk for severe and potentially fatal clinical trajectories rather than the broader spectrum of adverse cardiovascular events included in composite endpoints[26,27]. Such differential associations emphasize the importance of endpoint selection when evaluating metabolic markers in ACS[28]. It should be acknowledged that the cut-off values applied in survival analyses were derived using data-driven methods and have not been externally validated. Therefore, these thresholds should be regarded as hypothesis-generating and primarily intended to illustrate relative risk stratification rather than to define definitive clinical decision limits.

Finally, time-to-event analysis demonstrated a stepwise decline in survival across increasing tertiles of SHR, supporting a dose-response relationship between the magnitude of acute glycemic deviation and the risk of early mortality[29]. This graded association strengthens the biological plausibility of the observed findings. It indicates that the extent of stress-related hyperglycemia, rather than its mere presence, conveys clinically meaningful prognostic information in patients with NSTEMI[30].

Limitations

Several limitations should be acknowledged. This was a single-center observational study with a relatively limited sample size, which may restrict the generalizability of the findings. Importantly, the number of mortality events was modest (n = 25), which may have limited the statistical power of multivariable analyses and increased the risk of model overfitting. In this context, the stability of regression coefficients and their corresponding confidence intervals should be interpreted with caution, as the ratio of outcome events to predictors may have introduced estimation uncertainty. Although multivariable adjustment was performed using clinically relevant variables, residual confounding cannot be entirely excluded. Stress hyperglycemia indices were assessed only at hospital admission, and dynamic changes in glucose metabolism during hospitalization were not evaluated. In addition, the cut-off values applied in survival analyses were derived using data-driven methods and have not been externally validated. Therefore, these thresholds should be regarded as exploratory and hypothesis-generating rather than clinically actionable. Finally, the observational nature of the study precludes causal inference, and the reported associations should be interpreted accordingly. In addition, established clinical risk scores, such as the Global Registry of Acute Coronary Events score, were not calculated because certain admission variables required for their computation were unavailable, including systolic blood pressure and heart rate. Therefore, a direct comparison of the discriminatory performance of stress hyperglycemia indices with that of validated clinical risk stratification tools was not feasible in the present dataset.

CONCLUSION

Stress hyperglycemia indices assessed at hospital admission are associated with early mortality in patients with NSTEMI, whereas chronic glycemic status, as reflected by HbA1c, is not. By integrating acute and chronic glycemic information, these indices appear to reflect the severity of acute systemic stress and inflammatory activation rather than long-term metabolic control. Stress hyperglycemia indices may therefore contribute to early risk stratification during the initial phase of hospitalization, before echocardiographic assessment becomes available. Further studies are warranted to determine whether targeted strategies addressing stress hyperglycemia can improve outcomes in this high-risk population.