This was a single-center, retrospective cohort study. A total of 298 hospitalized patients diagnosed with STEMI who underwent emergency PCI at our hospital between January 2022 and December 2024 were enrolled.

Inclusion criteria: (1) STEMI was diagnosed by trained clinicians according to the Fourth Universal Definition of Myocardial Infarction; (2) completion of emergency PCI within 24 h of admission; (3) Fasting blood glucose and insulin measured within 48 h after admission were used to calculate the HOMA-IR index, minimizing the influence of stress hyperglycemia; (4) All patients were non-diabetic, with no history of diabetes or use of hypoglycemic agents; abnormal blood glucose (ABG) was defined as fasting glucose ≥7.0 mmol/L or random glucose ≥11.1 mmol/L according to the Fourth Universal Definition of Myocardial Infarction.

Exclusion criteria: (1) a prior diagnosis of diabetes or HbA1c ≥ 6.5%; (2) chronic inflammatory disease, malignancy, or renal insufficiency (eGFR < 30 mL/min·1.73 m², calculated by the CKD-EPI equation); (3) Cardiogenic shock or need for mechanical circulatory support; prior myocardial infarction (MI), PCI, or CABG; emergency PCI for NSTEMI or variant angina; or unstable angina and elective angiography for stable CAD were excluded to ensure a homogeneous population of first-onset STEMI patients treated with emergency PCI; (4) incomplete clinical data or loss to follow-up.

Patients were stratified into three groups based on admission HOMA-IR (Homeostasis Model Assessment of Insulin Resistance) tertiles: low HOMA-IR group, medium HOMA-IR group, and high HOMA-IR group.

This study was conducted in accordance with the ethical principles of the Declaration of Helsinki and its amendments and was approved by the institutional ethics committee. All data were anonymized and used solely for academic research. The original data were obtained from the hospital's electronic medical records and coronary physiology measurement platform.

Fasting blood glucose (FBG) and fasting insulin (FINS) data were retrieved retrospectively from the hospital's electronic laboratory records. All tests had been performed as part of routine clinical assessments within 48 h of admission, according to standardized institutional laboratory procedures. Fasting venous blood samples, obtained the morning after admission following the hospital's standard fasting protocol (≥8 h), were used for laboratory analyses. Glucose and insulin were measured in the hospital's central laboratory using automated biochemical analyzers, and the results were expressed in mmol/L and μU/mL, respectively.

Values considered implausible (e.g., due to data entry or assay errors) were verified against original laboratory reports by two independent investigators before inclusion. The HOMA-IR index was calculated using the formula: The HOMA-IR index was calculated using the formula: HOMA-IR = FINS (μU/mL) × FBG (mmol/L)/22.5.

Immediately after PCI, coronary microcirculatory function was assessed using a pressure/temperature sensor-tipped guidewire (PressureWire X, Abbott, USA). The following parameters were measured: Index of Microcirculatory Resistance (IMR): calculated as distal coronary pressure multiplied by mean transit time; IMR ≥ 25 was defined as elevated microvascular resistance. Coronary Flow Reserve (CFR): defined as the ratio of hyperemic to baseline coronary blood flow; CFR < 2.0 was considered reduced microvascular reserve. All assessments were performed immediately after PCI by experienced technicians using a standard adenosine-induced hyperemia protocol.

All patients were followed for at least one year. Follow-up data were collected via outpatient visits or telephone interviews. MACE included all-cause death, recurrent myocardial infarction, rehospitalization for heart failure, and target vessel revascularization. The first occurrence of any of these events was recorded as MACE.

Primary study endpoints included: immediate post-PCI IMR and CFR values; presence of microcirculatory dysfunction (IMR ≥ 25 and/or CFR < 2.0); and incidence of MACE within one year.

All statistical analyses were performed using SPSS version 26.0 (IBM Corporation, USA). Continuous variables were tested for normality and expressed as mean ± standard deviation. One-way analysis of variance (ANOVA) was used for comparison among the three groups, with Bonferroni correction for pairwise comparisons. Categorical variables were presented as counts and percentages and compared using the chi-square test or Fisher's exact test as appropriate. Pearson correlation coefficients were used to assess linear relationships between HOMA-IR and IMR/CFR. Multivariate logistic regression was used to evaluate the predictive value of HOMA-IR for microcirculatory dysfunction (defined as IMR ≥ 25 and/or CFR < 2.0), with variables selected based on clinical relevance and univariate analysis results. Cox proportional hazards models were used to analyze the relationships between HOMA-IR, IMR, CFR, and 1-year MACE, with hazard ratios (HRs) and 95% confidence intervals (CIs) calculated after adjustment for potential confounders. A two-tailed P value < 0.05 was considered statistically significant.

A total of 298 non-diabetic STEMI patients were included in this study and divided into three groups based on HOMA-IR tertiles: low (n = 99), medium (n = 100), and high (n = 99). There were no statistically significant differences among the three groups in terms of age, sex, BMI, smoking history, hypertension, admission glucose, HbA1c, lipid profile, creatinine, or left ventricular ejection fraction (LVEF) (all P > 0.05), indicating good comparability across groups (Table 1).

To explore the effect of insulin resistance on coronary microcirculatory function, we compared post-PCI IMR and CFR values among the three groups. IMR was significantly higher, and CFR significantly lower, in the high HOMA-IR group (P < 0.001 for both) (Table 2). Bonferroni post hoc comparisons revealed that IMR was significantly higher in the high HOMA-IR group than in the medium (P = 0.004) and low groups (P < 0.001). Similarly, CFR was significantly lower in the high group than in the other two (both P < 0.001), suggesting that higher IR is associated with increased microvascular resistance and decreased coronary flow reserve.

We further analyzed the correlation between HOMA-IR and microvascular indicators. As shown in Table 3, HOMA-IR was significantly positively correlated with IMR (r = 0.436, P < 0.001), and negatively correlated with CFR (r = –0.408, P < 0.001). These findings support a strong association between higher IR and impaired coronary microcirculatory function.

Based on the established correlation between HOMA-IR and microcirculatory parameters, we further explored whether HOMA-IR serves as an independent predictor of coronary microvascular dysfunction. According to previous literature and clinical guidelines, IMR ≥ 25 and CFR < 2.0 were defined as the thresholds for microcirculatory dysfunction. Univariate analysis revealed that the incidence of dysfunction was significantly higher in the high HOMA-IR group (61.6%) than in the low HOMA-IR group (28.3%) (χ² = 21.76, P < 0.001). After adjusting for age, sex, LVEF, and Killip classification, multivariate logistic regression showed that high HOMA-IR was an independent risk factor for elevated IMR (P = 0.001) and a significant predictor of reduced CFR (P = 0.006) (Table 4). These findings suggest that not only is insulin resistance linearly associated with microvascular injury, but its elevation is also an independent risk factor for coronary microcirculatory dysfunction, highlighting its potential value for clinical risk identification.

To further assess the impact of insulin resistance on long-term clinical outcomes, we conducted a 12-month follow-up for all three HOMA-IR groups to monitor MACE, including all-cause mortality, recurrent myocardial infarction (MI), heart failure hospitalization, and target vessel revascularization. As shown in Table 5, a total of 68 MACE events (22.8%) occurred during follow-up, including 18 deaths, 12 recurrent MIs, 26 heart failure hospitalizations, and 12 revascularizations. The incidence of MACE significantly differed among the three groups (χ² = 14.82, P = 0.001), with the highest occurrence in the high HOMA-IR group. Kaplan–Meier survival curves demonstrated that patients in the high HOMA-IR group had the lowest event-free survival, and the difference was statistically significant (Log-rank P < 0.001). These results indicate that elevated HOMA-IR levels are associated with increased risk of MACE in non-diabetic STEMI patients within 1 year post-PCI and may serve as a potential biomarker for long-term risk stratification.

To determine whether HOMA-IR is an independent predictor of long-term adverse cardiovascular outcomes, we constructed a multivariate Cox proportional hazards model, adjusting for potential confounders including age, Killip class, LVEF, peak troponin levels, and pre-procedural TIMI flow grade. The analysis revealed that high HOMA-IR was an independent predictor of MACE (HR = 2.76, P < 0.001). In addition, IMR ≥ 25 (P = 0.013) and CFR < 2.0 (P = 0.011) were also independently associated with higher MACE risk (Table 6). These results underscore the prognostic value of HOMA-IR in non-diabetic STEMI patients and emphasize the importance of assessing coronary microvascular function in postoperative risk stratification. The multivariate Cox regression outcomes are visually summarized in Figure 1, showing that elevated HOMA-IR, IMR ≥ 25, and CFR < 2.0 were all independently associated with increased risk of MACE.