European Journal of Cardiovascular Medicine

Acute ST-elevation myocardial infarction (STEMI), a severe manifestation of acute coronary syndrome (ACS), results from prolonged myocardial ischemia due to coronary artery occlusion, leading to irreversible myocardial damage[1,2]. In India, the incidence of myocardial infarction (MI) has remained stable at approximately 6/1000 in men and 2/1000 in women in urban areas, with higher prevalence in urban compared to rural settings [3]. Diabetes mellitus (DM) is a well-established risk factor for coronary artery disease (CAD) and increases the risk of MI-related mortality by 2–3 times in affected individuals [4, 5]. However, hyperglycemia at admission, even in non-diabetic patients, is a frequent finding in acute MI and is associated with adverse outcomes, including heart failure, cardiogenic shock, and increased mortality[6–8].

Effective risk stratification is essential for managing ACS, particularly STEMI, where timely interventions such as percutaneous coronary intervention (PCI) or fibrinolytic therapy can significantly influence outcomes [9,10]. The Thrombolysis in Myocardial Infarction (TIMI) risk score, a validated tool, stratifies STEMI patients based on clinical and historical factors (e.g., age, blood pressure, heart rate, Killip class) to predict 30-day mortality[11–13]. Admission hyperglycemia, often a stress response, may independently predict poor prognosis, but its diagnostic accuracy compared to established scores like TIMI remains underexplored in non-diabetic STEMI patients.

Previous studies have highlighted the prognostic value of admission glucose levels in MI [14,15], yet optimal cutoffs and their comparative efficacy with TIMI scores are not well-defined. This study aimed to compare the diagnostic accuracy of admission random blood sugar (RBS) levels and TIMI risk scores in predicting prognosis among non-diabetic STEMI patients. The objectives were to assess the individual and combined prognostic utility of these parameters for severity and 30-day mortality, contributing to evidence-based risk stratification in this population.

Study Design and Population

This cross-sectional study was conducted at the Department of General Medicine and Cardiology, ASRAM Medical College, Eluru, Andhra Pradesh, India, from May 2021 to Feb 2025. The study included 50 non-diabetic patients diagnosed with STEMI based on clinical presentation (e.g., chest pain >30 minutes), electrocardiographic evidence (ST-elevation ≥1 mm in two contiguous leads), and elevated cardiac biomarkers (e.g., CK-MB, troponin-I). Exclusion criteria were pre-existing DM (defined by history or HbA1c ≥6.5%), age <18 years, and refusal to consent. Ethical approval was obtained from the ASRAM Bio-Human Research Ethics Committee, and informed consent was secured from all participants.

Data Collection

Demographic data (age, sex), clinical history (hypertension, smoking, alcohol use), and physical examination findings (blood pressure, heart rate, Killip class) were recorded using a standardized proforma (Annexure I). Admission RBS was measured using a glucometer, and lipid profiles (total cholesterol, triglycerides, HDL, LDL) and CK-MB levels were assessed via blood samples. TIMI risk scores were calculated at admission based on eight variables: age (65–74 = 2 points, ≥75 = 3 points), diabetes/hypertension/angina (1 point), systolic blood pressure <100 mmHg (3 points), heart rate >100 bpm (2 points), Killip class II–IV (2 points), weight <67 kg (1 point), anterior ST-elevation or left bundle branch block (1 point), and time to treatment >4 hours (1 point), with a total score ranging from 0–14 [16].

Statistical Analysis

Data were analyzed using SPSS version 23. Continuous variables (e.g., RBS, TIMI score) were expressed as mean ± standard deviation, and categorical variables (e.g., mortality, Killip class) as percentages. Pearson’s correlation assessed relationships between RBS, TIMI scores, and biochemical parameters. Receiver operating characteristic (ROC) curves determined optimal cutoffs for RBS and TIMI scores in predicting severity and 30-day mortality, with area under the curve (AUC) values indicating diagnostic accuracy. A p-value <0.05 was considered statistically significant. The study adhered to the Declaration of Helsinki guidelines.

Baseline Characteristics

The study cohort comprised 50 non-diabetic STEMI patients (70% male, 30% female) with a mean age of 64.1 ± 10.2 years. Hypertension was present in 34% of patients, 28% were smokers, and 20% consumed alcohol. Mean admission RBS was 158.4 ± 72.3 mg/dL, and mean TIMI score was 5.4 ± 2.1. Based on TIMI risk stratification, 40% were mild risk (TIMI 0–3), 50% moderate risk (TIMI 4–6), and 10% high risk (TIMI ≥7). Killip class distribution showed 48% in Class I, 46% in Class II, and 6% in Class III/IV.

Correlation Analyses

Admission RBS showed a significant positive correlation with TIMI score (r = 0.58, p = 0.0001), indicating that higher glucose levels were associated with increased risk. CK-MB levels also correlated positively with TIMI score (r = 0.288, p = 0.025), while HDL-cholesterol exhibited a negative correlation (r = -0.085, p = 0.035). No significant correlation was observed with other lipid parameters or left ventricular ejection fraction (LVEF).

Distribution of RBS and Risk Stratification

RBS distribution at admission revealed 26% of patients with <120 mg/dL, 22% with 120–140 mg/dL, 26% with 140–167 mg/dL, and 26% with >167 mg/dL. Mean RBS levels increased with TIMI risk category: 135.15 ± 41.83 mg/dL in mild risk, 163.04 ± 68.50 mg/dL in moderate risk, and 306 ± 9.62 mg/dL in high-risk groups (p < 0.0001).

Mortality and Clinical Outcomes

Mortality rates varied significantly across TIMI risk groups: 0% in mild risk, 2% in moderate risk, and 100% in high-risk patients (p < 0.0001). Cardiogenic shock occurred in 10% of cases, all within the high-risk group. Hospital events, including arrhythmias, were more frequent in moderate and high-risk categories.

Diagnostic Accuracy

ROC analysis identified an optimal RBS cutoff of 159 mg/dL for predicting disease severity, with sensitivity 81% (95% CI: 55%–95%), specificity 65% (95% CI: 45%–85%), positive predictive value (PPV) 80% (95% CI: 60%–95%), and negative predictive value (NPV) 52% (95% CI: 32%–65%), with an AUC of 0.65 (95% CI: 0.51–0.72, p = 0.004). The optimal TIMI score cutoff was 5.42, with sensitivity 75% (95% CI: 58%–92%), specificity 85% (95% CI: 65%–95%), PPV 97% (95% CI: 91%–100%), and NPV 42% (95% CI: 39%–50%), with an AUC of 0.592 (95% CI: 0.520–0.675, p = 0.0001). Combining RBS and TIMI improved accuracy, with an AUC of 0.624 (95% CI: 0.520–0.720, p = 0.0019), sensitivity 79%, specificity 82%, PPV 95%, and NPV 60%.

Mortality Prediction

For 30-day mortality, the mean admission RBS was 300 mg/dL, and the mean TIMI score was 9.5 in deceased patients. The AUC for TIMI score was 0.46 (95% CI: 0.39–0.49), for RBS 0.62 (95% CI: 0.55–0.69), and for combined parameters 0.59 (95% CI: 0.56–0.69), suggesting moderate predictive power.

Table 1: Area under receiver-operating characteristics curve (AUC) analysis for diagnostic accuracy

Table 2: Screening performance of TIMI score in 30-day outcome prediction of patients with STEMI without diabetes

This study demonstrates that both admission RBS and TIMI risk scores are valuable prognostic tools in non-diabetic STEMI patients, with combined use enhancing predictive accuracy. The significant correlation between RBS and TIMI score (r = 0.58, p = 0.0001) aligns with prior research suggesting hyperglycemia as a stress response amplifying cardiovascular risk [17, 18]. The observed mortality gradient (0% mild, 2% moderate, 100% high risk) underscores the TIMI score’s utility in risk stratification, consistent with its validation in fibrinolysis-eligible STEMI patients [19].

The RBS cutoff of 159 mg/dL (AUC = 0.65) compares favorably with previous studies reporting cutoffs of 140–200 mg/dL for adverse outcomes in MI [20, 21]. However, its lower specificity (65%) suggests it may over-identify at-risk patients, necessitating complementary tools. The TIMI score cutoff of 5.42 (AUC = 0.592) aligns with its established role in predicting short-term mortality [22], though its sensitivity (75%) indicates room for improvement when used alone. The combined model (AUC = 0.624) supports the additive value of integrating metabolic and clinical risk factors, a finding echoed in studies incorporating biomarkers with risk scores [23].

Mortality prediction was modest, with RBS (AUC = 0.62) outperforming TIMI (AUC = 0.46), possibly due to the small sample size or the acute-phase nature of hyperglycemia as a dynamic marker [24]. The 100% mortality in the high-risk group (TIMI ≥7) highlights the severity of advanced risk profiles, consistent with global registries [25]. Limitations include the single-center design, small cohort (n = 50), and lack of long-term follow-up, which may limit generalizability. Future studies should validate these cutoffs in larger, multicenter cohorts and explore dynamic TIMI updates post-discharge.

In non-diabetic STEMI patients, admission RBS and TIMI risk scores are effective prognostic indicators, with optimal cutoffs of 159 mg/dL and 5.42, respectively. Their combined use improves early risk stratification and mortality prediction, advocating for routine assessment in emergency settings. Clinicians should prioritize these parameters to identify high-risk patients promptly, guiding timely interventions and improving outcomes.

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