Two hundred and ninety-nine patients with acute STEMI with PCI admitted to Jinan Central Hospital from June 2020 to June 2022 were selected, all of whom met the diagnostic criteria for STEMI in the 2023 ESC Guidelines (13) and were diagnosed with coronary angiography (CAG), and all of whom underwent PCI within 12 h of the onset of the disease. The exclusion criteria were: (1) Previous heart transplantation, coronary artery bypass grafting, PCI; (2) Acute or chronic infectious diseases; (3) Combined malignant tumors; (4) Systemic immune disease; (5) Incomplete clinical information or follow-up information. All patients were divided into 81 cases in the LVR group and 218 cases in the non-LVR group according to the occurrence of LVR. The study was reviewed and approved by the Medical Ethics Committee of Jinan Central Hospital (Ethical Review Number: 20240901001). All patients and their families were informed about the study and provided written informed consent. Patient enrollment and study design were shown in Figure 1.

Diagnostic criteria for LVR an increase of >20% in LVEDV over LVEDV at discharge within 6 months of follow-up is ed as LVR (14).

In this 24-month follow-up study of 299 acute STEMI patients post-PCI, we assessed LVR, defined as a >20% increase in LVEDV index, and major adverse cardiovascular events (MACE), MACE was defined as a composite of recurrent myocardial infarction, arrhythmia, stroke, and sudden cardiac death during the follow-up period (15). Endpoints were evaluated using standardized criteria by a blinded clinical events committee, ensuring rigorous data collection and analysis.

The current study evaluated demographic data from medical records, including age, gender, smoking status, and medical history (e.g., history of hypertension and diabetes). Heart rate on admission, procedural status (culprit vessel, infarct site, initial blood flow, terminal blood flow, total stent length, and procedure time) were collected, and information on medication during hospitalization was also included. Initial blood flow and terminal blood flow refer to pre- and post-interventional Thrombolysis in Myocardial Infarction (TIMI) flow grades, as evaluated during coronary angiography (16). All patients underwent one routine blood test as per immediately after admission. Laboratory parameters included complete blood count [white blood cell count (WBC), neutrophil count, lymphocyte count, monocyte count, platelet count (PLT)], lipids (triglycerides, total cholesterol, LDL-C, HDL-C) and markers of myocardial injury (cTnT), MACE and MACE time. In addition, we collected echocardiographic data (LVEF1, LVEDV1, LVESV1) were recorded during MI and six months post-MI (LVEF2, LVEDV2, LVESV2), as well as data related to the CAG (culprit vessel, infarct location, initial blood flow, terminal blood flow, operative time, total length).

All statistical analyses were performed using SPSS software (version 25.0; SPSS Inc., Chicago, IL, USA) and R Studio software (version 4.3.0). Continuous variables were presented as mean ± standard deviation (SD) or median with interquartile range (IQR) based on their distribution and were compared using an independent samples t-test or the Mann–Whitney U-test, as appropriate. Categorical variables were expressed as frequencies and percentages and were compared between groups using the chi-square test or Fisher's exact test when necessary. All statistical tests were two-sided, and a P-value of <0.05 was considered statistically significant.

To assess the relationship between the NHR and LVR, as well as MACE after PCI in patients with acute STEMI, a weighted logistic regression model was employed. This model was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between NHR and LVR. The Cox proportional hazards models were applied to calculate hazard ratios (HRs) and 95% CIs for the incidence of MACE, adjusting for potential confounders, including age, sex, smoking status, and comorbidities.

ROC curve analysis was conducted to evaluate the predictive ability of NHR for both LVR and MACE, with the area under the curve (AUC) values calculated to determine the discrimination ability of NHR as a predictor. The optimal cut-off value for NHR in predicting MACE was determined using the Youden index. Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) metrics were used to compare the predictive performance of NHR against neutrophil count alone. Logistic regression models were applied to assess associations between predictors and outcomes, with Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) used to evaluate model fit.

RCS analysis was performed to explore potential non-linear relationships between NHR and both LVR and MACE, providing a flexible method for visualizing the dose-response relationship. Kaplan–Meier survival analysis was used to compare survival curves for different NHR groups, and the log-rank test was applied to assess differences in survival distributions.

A comparison of the baseline characteristics is shown in Table 1. Patients with LVR had higher NHR, Platelets, Neutrophil, Lymphocyte, TG, cTnT, and WBC levels compared with the non-LVR group (P < 0.05, for all). Additionally, patients in the LVR group had lower LVEF2, higher LVEDV2, LVESV2, and a higher incidence of MACE compared with the non-LVR group (P < 0.05, for all).

The study revealed a strong association between the higher NHR and the development of LVR in patients who underwent PCI for acute STEMI. As shown in Table 1, the LVR group (n = 81) had significantly higher NHR levels (8.19 ± 1.95) compared to the non-LVR group (6.23 ± 1.91), with a P-value<0.001, indicating a substantial difference. Furthermore, multivariate regression analysis, controlling for confounders like age, smoking, infarction location, and medication, demonstrated that for every standard deviation increase in NHR, the OR for LVR was 1.82 (95% CI: 1.45–2.27), confirming NHR as an independent predictor of LVR (Table 2). To further explore the effect of HDL-C alone on LVR and MACE in NHR, we performed stratified regression analyses (Supplementary Table S1). The results showed that HDL-C as a variable alone had limited predictive value for LVR and MACE. After adjusting for confounders, the association of HDL-C on LVR did not reach statistical significance (adjusted OR: 0.56; 95% CI: 0.09–3.36; P = 0.52), and the association on MACE was similarly insignificant (adjusted HR: 0.47; 95% CI: 0.15–1.48; P = 0.20). To visually assess the relationship between NHR and LVR, Figure 2A, employs an RCS model, highlighting a non-linear association. This figure illustrates that the risk of LVR increases exponentially as NHR levels rise beyond a certain threshold, reinforcing the statistical findings. Additionally, the ROC curve analysis in Figure 3A, further supports the predictive capability of NHR for LVR, with an AUC of 0.762, indicating moderate discrimination. These combined statistical and graphical insights emphasize the clinical importance of monitoring NHR in predicting LVR post-PCI.

The study also demonstrated a significant association between elevated NHR and the occurrence of MACE in patients post-PCI. As shown in Table 3, the HR for MACE was 1.43 (95% CI: 1.25–1.64) for each standard deviation increase in NHR, adjusted for factors such as age, smoking status, comorbidities, and medication. Moreover, patients with NHR levels ≥8.13 were at a significantly higher risk of MACE, with an adjusted HR of 4.30 (95% CI: 2.41–7.69), compared to those with lower NHR levels. This underscores the strong predictive value of NHR in determining long-term adverse cardiovascular outcomes. The predictive capability of NHR for MACE is further confirmed by the ROC curve analysis in Figure 3B, which shows an AUC of 0.762. This indicates that NHR is a reliable marker for predicting the risk of MACE, with moderate discrimination ability. The non-linear dose-response relationship between NHR and MACE is also demonstrated in Figure 2B using an RCS model. The curve illustrates a clear increase in the HR for MACE as NHR rises, reinforcing the idea that higher NHR levels are associated with a greater likelihood of adverse cardiovascular events. Additionally, Figure 4B depicts Kaplan–Meier survival curves, highlighting that patients with elevated NHR levels experience a higher cumulative incidence of MACE over time compared to those with lower NHR. This combination of statistical data and visual evidence emphasizes the clinical importance of NHR as a biomarker for predicting MACE in STEMI patients post-PCI and suggests that close monitoring of NHR could guide risk stratification and intervention strategies.

To explore the individual contribution of neutrophils and HDL-C in NHR, we conducted additional analyses using the ROC curve, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) analysis to compare the predictive capabilities of NHR and neutrophil count. The analysis revealed that neutrophils had higher predictive value for LVR and MACE, with AUCs of 0.747 and 0.691, respectively (Supplementary Figures S1C,D). In contrast, HDL-C demonstrated lower predictive value for these outcomes, with AUCs of 0.553 and 0.583, respectively (Supplementary Figures S1A,B). As shown in Supplementary Table S4, NRI and IDI analyses demonstrated that NHR significantly improved prediction for LVR (NRI = 0.1817, IDI = 0.0216) and MACE (NRI = 0.3883, IDI = 0.0424) compared to neutrophil count alone. Furthermore, as shown in Supplementary Table S6, logistic regression models incorporating NHR showed better performance with lower AIC and BIC values, confirming the superior predictive ability of NHR (P < 0.01, Likelihood Ratio Test). These findings indicate that the value of NHR in predicting LVR and MACE is superior to neutrophil count.

In addition, stratified analyses were performed to evaluate the impact of high neutrophil counts (≥8 × 10⁹/L) and low HDL-C levels (<1 mmol/L) on LVR and MACE outcomes. The results demonstrated a progressive increase in risk across subgroups, with the highest risk observed in patients with both high neutrophil counts and low HDL-C levels (Supplementary Tables S2, S3). This underscores the critical interplay between inflammation and lipid metabolism in determining cardiovascular outcomes.

We found that TIMI (pre-PCI to pos-PCI) values of 0–0 and 0–2 had higher median NHRs, while TIMI values of 1–3 and 2–3 had lower NHRs. Therefore, it is speculated that the smaller the improvement of TIMI (pre-PCI to pos-PCI), the higher the NHR value may be (Supplementary Tables S4). To some extent, NHR may have important predictive value for cardiac function and prognosis.