Abstract
Background
Despite advances in primary percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction (STEMI), patients remain at risk for long-term major adverse cardiovascular events (MACEs). The apelin-12/white blood cell ratio (AWR), a ratio has never been studied before, may reflect the balance between cardioprotective apelin signaling and systemic inflammation. We examined the prognostic value of admission AWR for long-term MACEs in STEMI patients after primary PCI.
Methods
This secondary analysis included 464 consecutive STEMI patients who underwent primary PCI at The First People’s Hospital of Taizhou (Zhejiang, China) between January 2010 and October 2014. Blood samples were collected on admission, immediately before primary PCI, for apelin-12 measurement. Patients were followed for 30 months. MACE was defined as the composite of cardiac death, cardiogenic shock, congestive heart failure, recurrent target-vessel myocardial infarction, or clinically driven target-lesion revascularization. AWR was analyzed as a continuous variable and by pre-specified tertiles (cut-points 6.48 and 10.49). Cox proportional-hazards (PH) regression with a directed acyclic graph (DAG)-derived minimal adjustment set (age, sex, diabetes mellitus, hypertension, serum creatinine, and Killip class) was used to estimate associations. Predictive performance was evaluated using time-dependent area under the receiver operating characteristic curve (AUC), C-index, bootstrap optimism correction, integrated discrimination improvement (IDI), and net reclassification improvement (NRI).
Results
During a median follow-up of 30.0 months, 118 patients (25.4%) experienced MACEs. Patients in the highest AWR tertile were older and less likely to be male than those in the lowest tertile. Higher AWR was independently associated with lower MACE risk [per 1-standard deviation (1-SD) increase: hazard ratio (HR) 0.52, 95% confidence interval (CI): 0.40–0.68, P<0.001; highest vs. lowest tertile: HR 0.40, 95% CI: 0.24–0.65, P<0.001]. The protective association strengthened after the first month. Adding AWR to the Global Registry of Acute Coronary Events (GRACE) 2.0 and Thrombolysis in Myocardial Infarction (TIMI) scores significantly improved reclassification (IDI and NRI both P<0.01).
Conclusions
A lower admission AWR is associated with an increased risk of long-term MACEs in STEMI patients undergoing primary PCI, supporting its potential as a prognostic biomarker.
Keywords: Apelin-12/white blood cell ratio (AWR), ST-segment elevation myocardial infarction (STEMI), major adverse cardiovascular event (MACE), prognostic, inflammation
Highlight box.
Key findings
• In 464 patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention, a higher admission Apelin-12/white blood cell ratio (AWR) independently predicted fewer long-term major adverse cardiovascular events (MACE) over a median 30-month follow-up [per 1-standard-deviation increase: hazard ratio (HR) 0.52, 95% confidence interval (CI): 0.40–0.68; highest vs. lowest tertile: HR 0.40, 95% CI: 0.24–0.65].
• Adding AWR to the Global Registry of Acute Coronary Events (GRACE 2.0) and Thrombolysis in Myocardial Infarction scores significantly improved risk reclassification (integrated discrimination improvement and net reclassification improvement, both P<0.01).
What is known and what is new?
• Apelin exerts cardioprotective effects, and the white blood cell count reflects systemic inflammation; both are linked to prognosis after STEMI.
• This study is the first to combine the two into a single readily available index and to show that it independently predicts long-term MACE and improves established risk scores.
What is the implication, and what should change now?
• The AWR is inexpensive and obtained from routine admission blood tests, making it a practical candidate for early risk stratification after STEMI.
• Prospective, multicenter validation is needed before it can be applied clinically.
Introduction
Coronary artery disease is a life-threatening condition worldwide, with acute ST-segment elevation myocardial infarction (STEMI) being its most critical manifestation (1). Advances in coronary intervention techniques enable timely reperfusion of the occluded vessels, and standardized secondary prevention for coronary disease has contributed to a reduction in STEMI mortality (2,3). Established predictors of adverse outcomes after STEMI include advanced age, impaired renal function, reduced left ventricular ejection fraction, higher Killip class, anterior infarct location and greater infarct severity, elevated inflammatory markers, and unfavorable angiographic and procedural characteristics (4). Though therapies targeted these risk factors have been adopted, the incidence of major adverse cardiovascular event (MACE) in STEMI patients remains a significant clinical challenge (5). Identifying prognostic risk factors for STEMI patients is therefore of critical importance.
Inflammation is an important participant in atherosclerosis from plaque development to plaque rupture (6,7). Inflammation following acute myocardial infarction (AMI) is precisely regulated and multiphase process, starting with a proinflammatory phase followed by a reparative phase (8). Neutrophils dominantly infiltrate the ischemic myocardium at the very early stage, and decline after 3 days (9). They play an important role in subsequent immune response by resulting in tissue debridement and polarization of monocyte-derived macrophages (10). With the transition of the polarization of neutrophils, dozens of cytokines, such as interleukin-4 (IL-4), interleukin-13 (IL-13), tumor necrosis factor-beta (TNF-β) and vascular endothelial growth factor (VEGF), are triggered to take part in the injury and repair process (11). Numerous studies have shown that acute and chronic inflammation is a stronger predictor of MACEs than low-density lipoprotein cholesterol (LDL-C) (12).
Apelin is initially synthesized as a 77-amino-acid pre-proprotein, which undergoes proteolytic cleavage to generate several shorter C-terminal fragments, including Apelin-36, -19, -17, -13 [or its pyroglutamate analog (Pyr)1 apelin-13], and -12 (13). Apelin-12, a highly potent isoform of peptide, is derived from amino acid residues 66 to 77. It was reported that injection of apelin-12 led to reduction of the myocardial infarction area in ischemic/reperfusion rats (14). The administration of a modified apelin-12 improved recovery of coronary flow and cardiac function, and decreased accumulation of lactate in ischemic/reperfusion rat hearts probably by maintenance of nitric oxide (NO) (15). In an observational cohort, the low apelin-12 level, correlated with troponin levels, was associated with a high rate of MACEs in STEMI patients (16). A single biomarker may not fully reflect the pathophysiological complexity of the disease. Apelin-12 and the white blood cell (WBC) count occupy opposite ends of a common regulatory axis: the apelin/APJ system directly suppresses inflammation by inhibiting the NF-κB pathway and reducing pro-inflammatory cytokines, and attenuates leukocyte infiltration into the injured myocardium (17,18), whereas the WBC count reflects the systemic inflammatory burden that drives adverse post-infarction remodeling. Consistently, circulating apelin-12 is inversely correlated with inflammation-based indices, including the neutrophil-to-lymphocyte ratio (NLR) and high-sensitivity C-reactive protein (hs-CRP), in patients with STEMI (19). The ratio of the two therefore provides a single, physiologically interpretable measure of the net balance between cardioprotective capacity and inflammatory burden. By integrating the cardioprotective properties of apelin-12 with the detrimental impact of inflammation, the apelin-12/WBC ratio (AWR), which has not been studied before, may serves as a novel composite prognostic biomarker of MACEs. We present this article in accordance with the TRIPOD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1360/rc).
Methods
Data source and study population
Our research is a secondary analysis of raw data which was uploaded to Dryad Digital Repository (https://datadryad.org) by Yang et al. The original data is openly accessible on “DATA-DRYAD”, which Yang et al. had authorized the ownership to use. Therefore, we are permitted to utilize these data for our secondary research without infringing the author’s rights. Original study was carried out at the First People’s Hospital of Taizhou (a tertiary hospital in Zhejiang, China) and received approval from its institutional ethics committee. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. A total of 464 STEMI patients between January 2010 and October 2014 were consecutively enrolled under the inclusion and exclusion criteria published. A participant-flow diagram is shown in Figure 1. All patients were followed for 30 months or until MACE; the median time to event was 24.1 months, patients without an event were censored at 30 months; 21 patients (4.5%) were lost to follow-up after discharge in the original study. Missing data were imputed using the random forest method. Detailed information on missing data is presented in Table S1. The following indicators were collected in the original research: (I) basic clinical characteristics—age, gender, systolic blood pressure, heart rate, diabetes mellitus, hypertension, myocardial infarction (MI) history, presence of anterior wall myocardial infarction, and Killip grade; (II) laboratory parameters were assessed, including blood cell counts (WBC, neutrophils, platelets, hemoglobin), renal and metabolic function markers (fast blood glucose, creatinine, uric acid, albumin, blood urea nitrogen), myocardial infarction related indicators [cardiac troponin I (cTnI), creatine kinase-MB and D-dimer], and lipid profiles [total cholesterol (TC), triglyceride (TG), LDL-C, high-density lipoprotein cholesterol (HDL-C)]. Additionally, level of apelin-12 was measured; (III) electrocardiographic findings (pathological Q waves) and echocardiographic parameters, including left ventricular ejection fraction (LVEF), left atrial diameter (LAD), and left ventricular end-diastolic diameter (LVEDD); (IV) procedural characteristics—numbers of stents implanted, GENSINI score calculation, and culprit vessel identification.
Figure 1.
Flow diagram of participant selection and grouping by AWR tertiles. AWR, apelin-12/white blood cell ratio; MACE, major adverse cardiovascular events; MI, myocardial infarction;PCI, percutaneous coronary intervention; STEMI, ST-segment elevation myocardial infarction; WBC, white blood cell count.
Apelin-12 enzyme-linked immunosorbent assay (ELISA) detection
In the original cohort, venous blood was drawn upon hospital admission prior to primary PCI. Within 1 hour of collection, serum was separated by centrifugation at 2,500 ×g for 10 minutes and stored at −80 °C. Serum apelin-12 concentrations were quantified using a commercial enzyme immunoassay kit (Phoenix Pharmaceuticals, Belmont, CA, USA).
Definitions
MACE is defined as the composite of cardiac death, cardiogenic shock, congestive heart failure, recurrent target vessel myocardial infarction (RMI), and clinically driven target lesion revascularization (TLR). The AWR was derived as [apelin-12 (ng/mL)/WBC count (×109/L)] ×100.
Statistical analysis
For this secondary analysis, participants were stratified by pre-specified tertiles of the AWR (tertile cut-points: 6.48 and 10.49) to minimize data-driven overfitting. The AWR was analyzed as a continuous variable [per 1-unit and per 1-standard deviation (1-SD) increase] in the primary analysis; secondary categorized analyses used the pre-specified tertiles, with additional dichotomous comparisons based on the median and the Youden index for reference. Continuous variables were expressed as mean ± SD for normally distributed data or median [interquartile range (IQR)] for non-normally distributed data. Categorical variables were summarized as counts and percentages. Group comparisons were performed using Student’s t-test or Mann-Whitney U test for continuous variables and Chi-squared test for categorical variables.
The association between AWR and MACE was estimated using Cox proportional-hazards (PH) regression. Four models were constructed: (I) an unadjusted model; (II) a model adjusted for covariates associated with MACEs at P<0.10 in univariate analysis (age, heart rate, left ventricular end-diastolic diameter, left atrial diameter, platelet, TC, cTnI, hemoglobin, D-dimer, prior myocardial infarction, pathological Q wave, anterior-wall myocardial infarction, and Killip class); (III) Figure S1 showed a model adjusted for the directed acyclic graph (DAG)-derived minimal sufficient adjustment set (age, sex, diabetes mellitus, hypertension, serum creatinine, and Killip class); and (IV) a fully adjusted model combining all covariates in models 2 and 3. The PH assumption was evaluated using Schoenfeld residuals; where the PH assumption was violated, piecewise Cox regression was performed with cut-points at 1 and 6 months, and the hazard ratios (HR) from the main Cox models were interpreted as time-averaged effects.
Restricted cubic spline (RCS) analysis was used to evaluate linear or non-linear associations between continuous AWR and MACEs. Kaplan-Meier survival curves were compared using the log-rank test. Subgroup analyses were performed according to age, sex, hypertension, diabetes mellitus, prior myocardial infarction, pathological Q wave, infarct location, Killip class, and culprit vessels; interactions were tested using multiplicative terms.
The incremental predictive value of AWR was assessed by adding it to the Global Registry of Acute Coronary Events (GRACE) 2.0 and Thrombolysis in Myocardial Infarction (TIMI) risk scores. Model discrimination was quantified using the time-dependent area under the receiver operating characteristic curve (AUC) and the concordance index (C-index); optimism-corrected C-indices were derived using bootstrap resampling. The improvement in discrimination was evaluated using the difference in C-index (ΔC). Reclassification was assessed using the integrated discrimination improvement (IDI) and categorical net reclassification improvement (NRI).
All statistical analyses were performed using Python 3.13 (lifelines package, version 0.30.3) and R software (version 3.4.4), with two-sided P<0.05 considered statistically significant.
Results
Baseline characteristics of the study cohort
Table 1 provides the baseline demographics and clinical profiles for all 464 consecutive STEMI patients who underwent primary PCI upon enrollment in this study. Patients were categorized into three pre-specified tertiles according to the AWR: T1 (AWR ≤6.48, n=155), T2 (6.48< AWR ≤10.49, n=154), and T3 (AWR >10.49, n=155). The baseline characteristics are summarized in Table 1.
Table 1. Baseline characteristics of the study population by AWR tertiles.
| Variable | Overall (n=464) | T1 (n=155) | T2 (n=154) | T3 (n=155) | P value |
|---|---|---|---|---|---|
| Demographics | |||||
| Age, years | 63.0±11.9 | 60.7±11.8 | 63.0±11.6 | 65.3±12.0 | 0.003 |
| Male | 355 (76.5) | 131 (84.5) | 114 (74.0) | 110 (71.0) | 0.01 |
| Comorbidities | |||||
| Hypertension | 265 (57.1) | 95 (61.3) | 85 (55.2) | 85 (54.8) | 0.44 |
| Diabetes mellitus | 150 (32.3) | 45 (29.0) | 60 (39.0) | 45 (29.0) | 0.10 |
| Prior myocardial infarction | 55 (11.9) | 21 (13.5) | 17 (11.0) | 17 (11.0) | 0.73 |
| Clinical presentation | |||||
| Systolic blood pressure, mmHg | 131.8±27.1 | 132.2±27.1 | 131.8±28.3 | 131.4±26.2 | 0.97 |
| Heart rate, beats/min | 76.9±17.1 | 78.4±18.2 | 75.9±15.4 | 76.6±17.7 | 0.41 |
| Killip class >I | 112 (24.1) | 48 (31.0) | 29 (18.8) | 35 (22.6) | 0.04 |
| Anterior wall MI | 231 (49.8) | 81 (52.3) | 72 (46.8) | 78 (50.3) | 0.62 |
| Laboratory findings | |||||
| Hemoglobin, g/L | 143.8±17.2 | 145.6±16.7 | 143.8±16.2 | 141.9±18.4 | 0.16 |
| Platelet count, ×109/L | 231.9±56.1 | 235.9±58.3 | 232.5±53.5 | 227.3±56.5 | 0.40 |
| White blood cells, ×109/L | 10.1±3.7 | 13.1±3.0 | 9.9±2.7 | 7.1±2.4 | <0.001 |
| Total cholesterol, mmol/L | 5.6±1.1 | 5.8±1.1 | 5.6±1.1 | 5.5±1.2 | 0.02 |
| Triglycerides, mmol/L | 1.0 (0.6–1.5) | 1.1 (0.5–1.7) | 1.0 (0.6–1.5) | 0.9 (0.5–1.4) | 0.11 |
| Glucose, mmol/L | 7.7±2.5 | 7.8±2.6 | 7.6±2.5 | 7.6±2.5 | 0.66 |
| Creatinine, μmol/L | 75.0 (62.0–85.7) | 68.0 (56.0–78.2) | 75.7 (63.4–86.0) | 80.0 (68.5–88.5) | <0.001 |
| Uric acid, μmol/L | 337.2±73.7 | 349.2±76.7 | 331.3±75.3 | 331.0±67.8 | 0.045 |
| Albumin, g/L | 37.9±3.8 | 38.0±4.0 | 38.2±3.7 | 37.6±3.8 | 0.40 |
| D-dimer, mg/L | 0.9 (0.3–1.7) | 1.1 (0.3–1.8) | 0.9 (0.3–1.5) | 0.8 (0.2–1.7) | 0.15 |
| Peak cTnI, ng/mL | 16.5±12.8 | 17.4±12.7 | 15.1±12.7 | 17.0±13.1 | 0.23 |
| Apelin-12, ng/mL | 0.8 (0.6–1.0) | 0.6 (0.5–0.7) | 0.8 (0.7–0.9) | 1.0 (0.8–1.3) | <0.001 |
| Echocardiography | |||||
| LV end-diastolic diameter, mm | 50.4±6.3 | 50.8±5.9 | 49.9±6.2 | 50.6±6.7 | 0.36 |
| Left atrial diameter, mm | 37.4±5.7 | 37.3±5.6 | 37.5±5.8 | 37.5±5.6 | 0.90 |
| Electrocardiography and angiography | |||||
| Pathological Q wave | 223 (48.1) | 82 (52.9) | 72 (46.8) | 69 (44.5) | 0.31 |
| Gensini score | 71.8±32.2 | 76.7±32.2 | 69.0±32.5 | 69.7±31.6 | 0.06 |
| Culprit vessels | 1.8±0.9 | 1.7±0.9 | 1.8±0.9 | 1.9±0.9 | 0.19 |
| Stent number | 1.0 (1.0–2.0) | 1.0 (1.0–2.0) | 1.0 (1.0–2.0) | 1.0 (1.0–2.0) | 0.06 |
| Risk scores | |||||
| GRACE 2.0 risk, % | 2.8 (1.6–4.9) | 2.6 (1.5–4.6) | 2.6 (1.6–4.4) | 3.3 (1.7–5.6) | 0.07 |
| TIMI risk index | 22.6 (16.7–31.4) | 21.2 (15.2–29.2) | 22.0 (17.0–31.1) | 24.9 (18.0–34.5) | 0.048 |
| Follow-up and outcome | |||||
| Follow-up time, months | 30.0 (29.8–30.0) | 30.0 (28.9–30.0) | 30.0 (29.8–30.0) | 30.0 (30.0–30.0) | 0.03 |
| MACE | 118 (25.4) | 51 (32.9) | 40 (26.0) | 27 (17.4) | 0.007 |
Data are presented as n (%), mean ± standard deviation or median (interquartile range). T1, T2, and T3 represent tertiles of the AWR. Cut-points: T1, AWR ≤6.48; T2, 6.48< AWR ≤10.49; T3, AWR >10.49. AWR, apelin-12/white blood cell ratio; cTnI, cardiac troponin I; GRACE, Global Registry of Acute Coronary Events; LV, left ventricle; MACE, major adverse cardiovascular events; MI, myocardial infarction; TIMI, Thrombolysis in Myocardial Infarction.
Patients in the highest AWR tertile were older (65.3±12.0 vs. 60.7±11.8 years in T1, P=0.003) and less likely to be male (71.0% vs. 84.5% in T1, P=0.01). As expected from the construction of the ratio, both constituent biomarkers showed strong gradients across tertiles: apelin-12 levels increased progressively from T1 to T3 (median 0.6 vs. 0.8 vs. 1.0 ng/mL, P<0.001), whereas WBC counts decreased (13.1×109/L ± 3.0×109/L vs. 9.9×109/L ± 2.7×109/L vs. 7.1×109/L ± 2.4×109/L, P<0.001). Consistently, serum creatinine was lower in T1 than in T3 (68.0 vs. 80.0 μmol/L, P<0.001), whereas uric acid was higher in T1 (349.2 vs. 331.0 μmol/L in T3, P=0.045). TC also differed modestly across groups (5.8 mmol/L in T1 vs. 5.5 mmol/L in T3, P=0.02). Patients in the lowest AWR tertile had a higher prevalence of Killip class >I (31.0% vs. 18.8% in T2 and 22.6% in T3, P=0.04) and a trend toward higher GENSINI scores (76.7±32.2 vs. 69.7±31.6 in T3, P=0.06). Established risk scores showed a somewhat divergent pattern: the TIMI risk index was higher in T3 (24.9 vs. 21.2 in T1, P=0.048), while the GRACE 2.0 risk score tended to be higher in T3 (3.3% vs. 2.6% in T1, P=0.07).
No significant differences were observed among tertiles in systolic blood pressure, heart rate, anterior-wall myocardial infarction, hemoglobin, platelet count, TGs, glucose, albumin, D-dimer, peak cTnI, left ventricular end-diastolic diameter, left atrial diameter, pathological Q wave, culprit vessels, or stent number.
During a median follow-up of 30.0 months, MACE occurred in 118 patients (25.4%), A progressive decrease across AWR tertiles (32.9%, 26.0%, and 17.4% for T1, T2, and T3, respectively; P=0.007) was shown.
Linearity of AWR and MACEs
To evaluate whether the association between AWR and MACE followed a linear or non-linear pattern, we applied multivariate-adjusted RCS analysis. Figure 2 illustrates a clear linear relationship between AWR and MACE occurrence, with the non-linearity test yielding a non-significant result (P=0.52). We analyzed the distribution of apelin-12, WBC and AWR, and found skewed distribution of them (Figure S2). Based on the log-transformed AWR, we repeated the RCS analysis and a linear association between the AWR and MACE occurrence persisted (Figure S3).
Figure 2.
Restricted cubic spline for the association between the AWR and predicted 30-month MACE probability. AWR, apelin-12/white blood cell ratio; CI, confidence interval; MACE, major adverse cardiovascular events.
Incidence of MACEs
Throughout the 30-month follow-up, MACEs were documented in 118 patients, comprising 25.43% of the total sample. In detail, 19 cardiac deaths (4.1%), 27 recurrent target-vessel myocardial infarctions (5.8%), 85 clinically driven target-lesion revascularizations (18.3%), and 35 episodes of cardiogenic shock or congestive heart failure (7.5%) (components are not mutually exclusive); 31 events (6.7%) occurred during the index hospitalization, and 21 patients (4.5%) were lost to follow-up after discharge. Compared with the low AWR group, the higher ratio group experienced fewer MACE events during follow-up. Figure 3 illustrates the Kaplan-Meier survival curves for incident MACEs, categorized by the AWR. Kaplan-Meier analysis revealed that higher AWR conferred superior disease-free survival outcomes (log-rank test: P=0.02).
Figure 3.
Kaplan-Meier curves for MACE-free survival stratified by AWR tertiles. AWR, apelin-12/white blood cell ratio; MACE, major adverse cardiovascular events; WBC, white blood cell count.
Cox regression analysis
A total of 118 MACEs occurred during follow-up. Higher AWR values were consistently associated with a lower risk of MACEs across all analytical approaches (Table 2). With 118 MACE events and 7 estimated parameters (6 DAG-guided confounders plus the AWR), the events-per-parameter ratio is 16.9. In the primary continuous analysis, each one-unit increase in AWR was associated with an 11% lower risk of MACEs in the fully adjusted DAG-based model (Model 3: HR 0.89, 95% CI: 0.85–0.94, P<0.001), with similar effect estimates observed in the unadjusted (HR 0.92, 95% CI: 0.88–0.96), P<0.10-selected (HR 0.90, 95% CI: 0.86–0.94), and union models (HR 0.90, 95% CI: 0.86–0.94). When scaled per one standard deviation, the association was even stronger (Model 3: HR 0.52, 95% CI: 0.40–0.68, P<0.001). In the categorized analyses, patients with AWR above the median value of 8.32 had a 53% lower MACE risk than those below the median in Model 3 (HR 0.47, 95% CI: 0.32–0.69, P<0.001). Using the Youden-derived cut-off of 7.05, the high-AWR group had a 55% lower risk (HR 0.45, 95% CI: 0.30–0.66, P<0.001). Similarly, when patients were divided into pre-specified tertiles, MACE risk decreased progressively across tertiles (P for trend <0.001): compared with the lowest tertile (T1, AWR ≤6.48), the middle tertile (T2, 6.48< AWR ≤10.49) showed a non-significant 30% risk reduction (HR 0.70, 95% CI: 0.46–1.09, P=0.11), whereas the highest tertile (T3, AWR >10.49) showed a 60% risk reduction (HR 0.40, 95% CI: 0.24–0.65, P<0.001). Although the association between AWR and MACE was statistically significant over the entire follow-up, Schoenfeld residual tests indicated violation of the PH assumption for AWR (Table S2). Therefore, the HRs presented in Table 2 should be interpreted as a time-averaged effect over the entire follow-up. Piecewise Cox regression showed that the protective association was predominantly observed after the first month (and after the first 6 months). Given the right-skewed distributions of Apelin-12 and the AWR, we performed an additional sensitivity analysis in which the AWR was natural-log-transformed. The inverse association between the log-transformed AWR and MACEs remained essentially unchanged (Table S3). These consistent findings confirm that the observed association is not an artifact of the skewed distribution of the ratio.
Table 2. Association of AWR with MACEs in Cox proportional hazards models.
| Exposure | Model 1 (unadjusted) | Model 2 (P<0.10) | Model 3 (DAG minimal) | Model 4 (union) | ||||
|---|---|---|---|---|---|---|---|---|
| HR (95% CI) | P value | HR (95% CI) | P value | HR (95% CI) | P value | HR (95% CI) | P value | |
| AWR (continuous) | ||||||||
| AWR (per 1 unit) | 0.92 (0.88–0.96) | <0.001 | 0.90 (0.86–0.94) | <0.001 | 0.89 (0.85–0.94) | <0.001 | 0.90 (0.86–0.94) | <0.001 |
| AWR (per 1-SD) | 0.61 (0.47–0.78) | <0.001 | 0.55 (0.42–0.72) | <0.001 | 0.52 (0.40–0.68) | <0.001 | 0.54 (0.41–0.70) | <0.001 |
| AWR, dichotomous by median | ||||||||
| ≤8.32 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| >8.32 | 0.58 (0.40–0.84) | 0.004 | 0.46 (0.31–0.69) | <0.001 | 0.47 (0.32–0.69) | <0.001 | 0.46 (0.31–0.69) | <0.001 |
| AWR, dichotomous by Youden index | ||||||||
| ≤7.05 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| >7.05 | 0.56 (0.39–0.81) | 0.002 | 0.48 (0.33–0.71) | <0.001 | 0.45 (0.30–0.66) | <0.001 | 0.47 (0.32–0.71) | <0.001 |
| AWR, tertiles | ||||||||
| Low (T1) | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| Middle (T2) | 0.78 (0.52–1.19) | 0.25 | 0.82 (0.53–1.27) | 0.38 | 0.70 (0.46–1.09) | 0.11 | 0.81 (0.52–1.25) | 0.34 |
| High (T3) | 0.51 (0.32–0.81) | 0.004 | 0.43 (0.26–0.71) | 0.001 | 0.40 (0.24–0.65) | <0.001 | 0.43 (0.26–0.71) | 0.001 |
| P for trend | 0.004 | 0.001 | <0.001 | 0.001 | ||||
Cut-points: median =8.32; Youden index =7.05. Tertiles: T1 (AWR ≤6.48), T2 (6.48< AWR ≤10.49), T3 (AWR >10.49). Model 3 was adjusted for age, sex, diabetes mellitus, hypertension, creatinine, and Killip class (DAG minimal set). AWR, apelin-12/white blood cell ratio; CI, confidence interval; DAG, directed acyclic graph; HR, hazard ratio; MACE, major adverse cardiovascular events; SD, standard deviation.
Subgroup analysis
To explore whether the prognostic association of AWR with MACEs was consistent across patient subgroups, we performed subgroup analyses stratified by sex, hypertension, diabetes mellitus, pathological Q wave, prior myocardial infarction, anterior-wall myocardial infarction, Killip class, age, and number of culprit vessels (Table 3, Figure 4). In the DAG-adjusted model, a higher AWR remained associated with a lower risk of MACEs in most subgroups, with no statistically significant interactions for sex (P for interaction =0.13), hypertension (P=0.72), diabetes mellitus (P=0.83), pathological Q wave (P=0.51), prior myocardial infarction (P=0.76), anterior-wall myocardial infarction (P=0.94), Killip class (P=0.42), or age (P=0.22).
Table 3. Subgroup analysis of the association between AWR and MACEs.
| Subgroup | N | HR (95% CI) | P value | P for interaction |
|---|---|---|---|---|
| Sex | 0.13 | |||
| Male | 355 | 0.93 (0.89–0.98) | 0.005 | |
| Female | 109 | 0.85 (0.78–0.94) | 0.002 | |
| Hypertension | 0.72 | |||
| No | 199 | 0.93 (0.87–0.99) | 0.02 | |
| Yes | 265 | 0.91 (0.86–0.97) | 0.002 | |
| Diabetes mellitus | 0.83 | |||
| No | 314 | 0.92 (0.87–0.97) | 0.001 | |
| Yes | 150 | 0.91 (0.83–0.99) | 0.03 | |
| Pathological Q wave | 0.51 | |||
| Yes | 223 | 0.93 (0.88–0.98) | 0.01 | |
| No | 241 | 0.90 (0.84–0.97) | 0.005 | |
| Prior myocardial infarction | 0.76 | |||
| Yes | 55 | 0.91 (0.82–1.01) | 0.06 | |
| No | 409 | 0.92 (0.88–0.97) | <0.001 | |
| Anterior wall myocardial infarction | 0.94 | |||
| Yes | 231 | 0.92 (0.87–0.97) | 0.003 | |
| No | 233 | 0.92 (0.85–0.98) | 0.02 | |
| Killip class | 0.42 | |||
| I | 352 | 0.93 (0.88–0.98) | 0.006 | |
| >I | 112 | 0.90 (0.83–0.97) | 0.009 | |
| Age, years | 0.22 | |||
| ≤60 | 185 | 0.95 (0.88–1.02) | 0.15 | |
| >60 | 279 | 0.89 (0.85–0.94) | <0.001 | |
| Culprit vessels | 0.03 | |||
| Single | 233 | 0.91 (0.85–0.96) | 0.002 | |
| Two | 72 | 0.75 (0.61–0.93) | 0.008 | |
| Three | 159 | 0.97 (0.91–1.04) | 0.43 | |
Subgroup analyses were adjusted for the DAG minimal set (age, sex, diabetes mellitus, hypertension, creatinine, and Killip class). P for interaction tests whether the association between AWR (per 1 unit) and MACEs differed across subgroups. AWR, apelin-12/white blood cell ratio; CI, confidence interval; DAG, directed acyclic graph; HR, hazard ratio; MACE, major adverse cardiovascular events; SD, standard deviation.
Figure 4.
Subgroup analysis for the association between the AWR and MACE. AWR, apelin-12/white blood cell ratio; CI, confidence interval; HR, hazard ratio; MACE, major adverse cardiovascular events; MI, myocardial infarction; WBC, white blood cell count.
The association appeared somewhat stronger in older patients (age >60 years: HR 0.89, 95% CI: 0.85–0.94, P<0.0001) than in younger patients (age ≤60 years: HR 0.95, 95% CI: 0.88–1.02, P=0.15), although the interaction was not statistically significant (P=0.22). Similarly, the protective association of AWR was observed in both men (HR 0.93, 95% CI: 0.89–0.98, P=0.005) and women (HR 0.85, 95% CI: 0.78–0.94, P=0.002), with no significant interaction (P=0.13).
The only significant interaction was observed for the number of culprit vessels (P for interaction =0.03). The association between AWR and MACE was strongest in patients with two culprit vessels (HR 0.75, 95% CI: 0.61–0.93, P=0.008), intermediate in those with single-vessel disease (HR 0.91, 95% CI: 0.85–0.96, P=0.002), and not significant in those with three-vessel disease (HR 0.97, 95% CI: 0.91–1.04, P=0.43). However, given the modest sample size in the two-vessel group (n=72), this finding should be interpreted with caution and warrants validation in larger cohorts.
Overall, these results suggest that the prognostic value of AWR is largely consistent across major clinical subgroups of STEMI patients.
Incremental predictive value of AWR
We analyzed Apelin-12 and WBC separately alongside the ratio and compared their discriminative performance (AUC: AWR 0.6238 vs. Apelin-12 0.6191 vs. WBC 0.5553; Table S4). AWR performed better than Apelin-12 or WBC alone. Table 4 shows the incremental predictive value of adding the AWR to the GRACE 2.0 and TIMI risk scores for long-term MACEs after primary PCI.
Table 4. Predictive performance of GRACE 2.0 and TIMI scores with and without AWR.
| Metric | GRACE 2.0 | GRACE 2.0 + AWR | P value (vs. GRACE 2.0) | TIMI | TIMI + AWR | P value (vs. TIMI) |
|---|---|---|---|---|---|---|
| Time-dependent AUC (95% CI) | 0.642 (0.583–0.698) | 0.667 (0.606–0.719) | 0.47 | 0.623 (0.567–0.684) | 0.674 (0.616–0.725) | 0.09 |
| Optimism-corrected C-index | 0.6240 | 0.6461 | – | 0.6118 | 0.6519 | – |
| ΔC (95% CI) | – | 0.026 (−0.019 to 0.076) | 0.30 | – | 0.044 (0.004–0.093) | 0.03 |
| IDI (95% CI) | – | 0.0530 (0.0193–0.0938) | <0.001 | – | 0.0518 (0.0213–0.0952) | <0.001 |
| NRI (95% CI) | – | 0.3110 (0.1178–0.5196) | 0.002 | – | 0.3361 (0.1202–0.5214) | 0.006 |
P values compare the base risk score (GRACE 2.0 or TIMI) with the same score plus AWR. ΔC is the difference in optimism-corrected C-index between the model with and without AWR. AUC, area under the curve; AWR, apelin-12/white blood cell ratio; C-index, concordance index; CI, confidence interval; GRACE, Global Registry of Acute Coronary Events; IDI, integrated discrimination improvement; NRI, net reclassification improvement; TIMI, Thrombolysis in Myocardial Infarction; ΔC, difference in C-index.
Both base risk scores showed modest discrimination: the GRACE 2.0 score had a time-dependent AUC of 0.642 (95% CI: 0.583–0.698) and an optimism-corrected C-index of 0.6240. Adding AWR to the GRACE 2.0 score increased the time-dependent AUC to 0.667 (95% CI: 0.606–0.719) and the optimism-corrected C-index to 0.6461; however, the difference in time-dependent AUC was not statistically significant (P=0.47) and the ΔC was 0.026 (95% CI: –0.019 to 0.076; P=0.30).
The TIMI score alone had a time-dependent AUC of 0.623 (95% CI: 0.567–0.684) and an optimism-corrected C-index of 0.6118. Adding AWR to the TIMI score improved the time-dependent AUC to 0.674 (95% CI: 0.616–0.725) and the optimism-corrected C-index to 0.6519. The ΔC was 0.044 (95% CI: 0.004–0.093; P=0.03), indicating a statistically significant increase in discrimination.
In terms of reclassification, adding AWR to the GRACE 2.0 score yielded a categorical NRI of 0.311 (95% CI: 0.118–0.520; P=0.002) and an IDI of 0.053 (95% CI: 0.019–0.094; P<0.001). Similarly, adding AWR to the TIMI score produced a categorical NRI of 0.336 (95% CI: 0.120–0.521; P=0.006) and an IDI of 0.052 (95% CI: 0.021–0.095; P<0.001). These findings suggest that AWR provides meaningful incremental predictive information beyond established risk scores, particularly for reclassification.
Discussion
Our findings indicate that an elevated AWR associated with a reduced risk of MACEs in STEMI patients receiving primary PCI during follow-up, a relationship that persists after controlling for conventional clinical and biochemical covariates. Collectively, these findings underscore the utility of AWR as potential prognostic marker on the interplay between systemic inflammation and cardiovascular outcomes.
Reactive oxygen species (ROS) are massively produced in ischemic myocardium especially after reperfusion. ROS could damage the cell membrane, leading to cell death. On the other hand, ROS trigger the release of inflammatory cytokine, such as tumor necrosis factor-alpha, IL-1 beta and IL-6, which regulate cell fate in the chain reaction with ROS (20). Apelin-12 is cable of enhancing antioxidant defense by inhibiting the mitochondrial ROS production in myocardial ischemia and reperfusion (21). And it was reported that apelin-12 effected myocardial antioxidant enzyme activities, lipid peroxidation, and ROSs [Cu, Zn superoxide dismutase (Cu, Zn SOD), catalase (CAT), and glutathione peroxidase (GSH-Px); malondialdehyde (MDA)] formation in ex vivo and in vivo models of I/R injury (22). Besides, a modified peptide apelin-12 (MA12) was proved to be a promising adjunct agent for protection of the heart during ischemia/reperfusion (I/R) injury by enhancing preservation of high-energy phosphates and decreasing accumulation of lactate (15). And apelin-12 augmented contraction directly in failing rat cardiac muscle by regulating [Ca (2+)] (i) transients (23). Our finding that patients with higher levels of AWR had a lower incidence of MACEs, is in line with the protective effect of apelin-12 mentioned above.
The association between elevated WBC count and cardiovascular risk is robustly supported by both pathological mechanisms and clinical evidence. Atherosclerosis is now understood to be a chronic inflammatory process (24), wherein leukocytes—notably neutrophils and monocytes—play direct effector roles in endothelial dysfunction, foam cell formation, and plaque destabilization (10). Consequently, WBC count emerges as a readily measurable surrogate for this systemic inflammatory state. Epidemiological data have consistently confirmed that an elevated baseline WBC count or an elevated NLR, lymphocyte-to-monocyte ratio (LMR), independently predicts increased risk of MACE, even after adjusting for traditional risk factors (24,25).
Standalone inflammatory markers may not fully reflect the body’s endogenous protective status. Therefore, this study proposes combining the WBC count with Apelin—an active peptide with established cardiovascular protective effects—to construct the AWR. This aims to create a comprehensive indicator that simultaneously reflects both the inflammatory burden and the protective capacity. Similar concepts, such as the NLR and LMR, have already demonstrated value in oncology and cardiology (26-28). The AWR proposed herein represents a potential prognostic biomarker of the incidence of MACEs in STEMI patients undergoing PCI.
Our findings are consistent with and extend previous observations. Krasniqi et al. reported that lower apelin-12 levels correlated with troponin elevation and a higher rate of MACEs in STEMI patients (16), and Yang et al.—in the cohort from which our data derive—identified low admission apelin-12 as an independent predictor of 2.5-year MACEs. For the inflammatory component, leukocyte count and leukocyte subtypes have long been associated with cardiovascular risk (25), and composite inflammation-based ratios such as the NLR have shown prognostic value in acute coronary syndromes (26,27). Direct comparison across studies is complicated by differences in blood sampling time (admission vs. post-procedure), assay methods, patient severity, endpoint definitions, and follow-up duration, which may explain the inconsistent magnitude—and occasionally direction—of the reported associations. Within this context, the AWR represents an attempt to integrate these two complementary biological axes into a single routinely measurable index.
Several alternative explanations for the observed association must be considered. First, residual confounding remains possible: although we adjusted for a broad range of covariates, data such as smoking, ischemic time, discharge medications, and left ventricular ejection fraction were not available in the shared dataset, and unmeasured differences in these factors may have contributed to the association. Second, the WBC count changes rapidly during the acute phase of myocardial infarction and is influenced by infarct duration, reperfusion status, and concomitant treatment; a single admission measurement may therefore misclassify the inflammatory burden for some patients. Third, both apelin-12 and WBC may correlate with infarct severity, so the AWR may partly act as a proxy for infarct size rather than as an independent biological signal. Fourth, as a single-center secondary analysis of a previously assembled cohort, selection bias cannot be excluded, and information on the total number of patients screened at each step was not available to us. All factor mentioned above may influence the incidence of MACEs, further research is in needed.
This study has several limitations that warrant consideration. First, the analysis was based on a retrospective cohort of Chinese STEMI patients from a single center. This limits the applicability of our findings to other ethnic groups and global populations. Furthermore, the absence of an external validation cohort means that the prognostic value of the AWR requires confirmation in independent, multi-center datasets before widespread clinical adoption. Second, as the original dataset lacked detailed information on specific inflammatory subtypes (e.g., neutrophil or lymphocyte counts), we were unable to adjust for these variables or calculate ratios such as the Apelin/neutrophil ratio. Consequently, although we adjusted for major confounders, residual confounding may persist. Additionally, the lack of data on other key inflammatory markers (e.g., CRP, IL-6) limited our ability to explore the underlying mechanisms linking the AWR to MACE. Third, conditions that may alter apelin-12 or WBC levels (such as corticosteroid treatment) were not systematically recorded, although the original study excluded patients with recent serious infection, connective tissue disease, malignancy, dialysis-dependent renal failure, and recent major surgery. Fourth, the composite endpoint prevented per-component analysis in the shared dataset, precluding separate per-component Cox analyses. Fifth, apelin-12 assay characteristics (detection limits, coefficients of variation) and blinding of laboratory and outcome assessors were not reported in the original study. Sixth, the sample size and event numbers presented certain statistical limitations. With 118 MACE events, the overall cohort size was modest, which may have contributed to instability in the subgroup analysis results. Future large-scale, prospective studies are required to validate these findings.
Conclusions
In primary PCI-treated STEMI patients, a low admission AWR emerged as an independent correlate of poor cardiovascular prognosis. By capturing the dynamic balance between systemic inflammation and apelin-12-mediated cardioprotection, this ratio may potentially serve as a prognostic biomarker.
Supplementary
The article’s supplementary files as
Acknowledgments
We thank Ting Zheng, Yide Chen, Xiongneng Mou, Lingchang Yang, Hui Lin, Haopeng Wu, Xiaoyu Wu, Wenwei Xin, and the research investigators for sharing their data.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.
Footnotes
Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1360/rc
Funding: None.
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1360/coif). The authors have no conflicts of interest to declare.
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