Pre-percutaneous coronary intervention hemoglobin as a prognostic indicator for 6-month mortality in acute myocardial infarction patients: a secondary analysis of the Korea Acute Myocardial Infarction Registry National Institutes of Health cohort

Introduction

Acute myocardial infarction (AMI) remains one of the leading causes of morbidity and mortality worldwide, despite major advances in pharmacological therapy and revascularization techniques (1-5). Among treatment strategies, percutaneous coronary intervention (PCI) has become the standard of care for AMI; however, mortality rates remain substantial. Effective risk stratification is critical to improving outcomes, as it enables timely intervention and informed clinical decision-making (6). Numerous factors have been identified as predictors of adverse outcomes in AMI patients undergoing PCI, including age, renal dysfunction, left ventricular ejection fraction, Killip class, and inflammatory markers.

Hemoglobin is a stable protein in red blood cells (RBCs) that is responsible for transporting oxygen to body tissues (7-9). During AMI, low hemoglobin aggregates ischemic injury by reducing the amount of oxygen supplying the damaged myocardium and requiring an increase in cardiac output to sustain systemic oxygenation. Previous studies have shown that patients with acute coronary syndrome (ACS) with hemoglobin levels less than 10 g/dL have a significant risk of cardiac death (10-13). Meanwhile, patients with higher RBC volume have a lower risk of cardiac death; that is, every 1% increase in RBC volume can reduce the occurrence of cardiac death events by 4% (14,15). If the hemoglobin level is >17 g/dL, the risk of adverse events is significant (16).

Despite these findings, the prognostic value of baseline hemoglobin levels in AMI patients undergoing PCI remains inadequately defined, especially in Asian populations such as those in Korea. Furthermore, the potential influence of hemoglobin levels on clinical outcomes and medication adherence in this population has not been thoroughly explored. In this study, we aimed to evaluate the association between pre-PCI hemoglobin levels and 6-month clinical outcomes in a large, contemporary Korean cohort of nearly 10,000 AMI patients, to provide further insight into its potential role in risk stratification and management. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-665/rc).

Methods

Patients and data

We conducted secondary analysis based on the study by Kim et al., who analyzed the Korea Acute Myocardial Infarct Ion Registry National Institutes of Health (KAMIR-NIH) data in South Korea (17). The flowchart of this clinical trial is shown in Figure 1. A total of 13,104 patients with AMI undergoing successful PCI or balloon angioplasty from the KAMIR-NIH database, which is a web-based, prospective, observational, multicenter cohort study. The study, funded by the Korea Centers for Disease Control and Prevention, was conducted from May 2010 to June 2015 and was aimed at identifying the prognostic and surveillance indicators for Korean patients with AMI from 15 centers.

Figure 1 Flowchart of study inclusion. Hb, hemoglobin; PCI, percutaneous coronary intervention.

As indicated by the study authors, all participating centers applied the same research approach, which was approved by the institutional review board (IRB) of each institution and all patients signed written informed consent. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The research coordinators of the participating institutions obtained the data in compliance with a standardized protocol. Standardized definitions of all variables were defined by the steering committee of KAMIR-NIH.

Of the 13,104 patients, 199 with missing data and 1,372 without PCI were excluded. The remaining 11,533 patients were divided into four groups according to hemoglobin level quartiles.

Statistical analysis

In the secondary analysis, the continuous variables were age, body mass index, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol (TC), triglycerides (TG), and left ventricular ejection fraction, among others. Categorical variables included sex, risk factors [hypertension, diabetes mellitus, Killip classification, smoking status, hyperlipidemia, family history of coronary artery disease (CAD), history of cardiovascular disease (CVD), and in-hospital medications].

Consecutive variables are expressed as the mean ± standard deviation, and categorical variables are reported as frequencies and percentages. Comparisons among groups were performed using analysis of variance (ANOVA) and the Kruskal-Wallis test. Categorical variables among the groups were performed using the Pearson chi-squared test. The “P value” and “P value*” in Table 1 represent the outcomes of the parametric and nonparametric test, respectively. A total of 11,533 patients were divided into four groups according to hemoglobin level quartiles: group 1 accounted for 24.3% of all individuals (n=2,806), group 2 accounted for 24.6% (n=2,840), group 3 accounted for 26.8% (n=3,096), and group 4 accounted for 24.3% (n=2,791). Weighted univariate and multivariate binary logistic regression was used to investigate the correlation between pre-PCI hemoglobin and 6-month all-cause death. We then built three models: model 1, without adjustment for covariates; model 2, adjustments only age and gender; and model 3, adjustment for all covariates presented in Table 1. To address for the linearity of hemoglobin level and 6-month all-cause mortality and ensure the robustness of the data analysis, we converted hemoglobin level into a categorical variable and calculated the P value to validate the results of hemoglobin as a continuous variable.

To address the nonlinear relationship between hemoglobin and mortality, we used a weighted generalized additive model (GAM) and smooth curve fitting (penalty spline method). If nonlinearity was observed, we used the recursive algorithm, with inflection on both sides of the construction of a weighted two-piecewise logistic model. A stratified analysis with interaction test was used to assess the concordance of the correlation between pre-PCI hemoglobin levels and 6-month outcomes after PCI in the subgroups.

SSPS software (IBM Corp., Armonk, NY, USA) was used to analyze the data. Weighted univariate and multivariate binary logistic regression was performed via R (http://www.R-project.org; The R Foundation for Statistical Computing). A two-sided P value of <0.05 was considered statistically significant.

Results

Baseline characteristics of the study population

Baseline demographic, clinical, and laboratory characteristics are presented according to the hemoglobin level (Table 1). Patients were divided into four groups by hemoglobin level quartiles: group 1 accounted for 24.3% of all individuals (n=2,806), group 2 accounted for 24.6% (n=2,840), group 3 accounted for 26.8% (n=3,096), and group 4 accounted for 24.3% (n=2,791). The population distributions for age, sex, BMI, Killip classification, family history of CAD, smoking status, hypertension, prior congestive heart failure (CHF), cerebrovascular disease, TG level, TC, LDL cholesterol, HDL cholesterol, the use of ticagrelor, clopidogrel, angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), statins, BBs, calcium channel blockers, and glycoprotein (Gp) IIb/IIIa inhibitor were significantly different between the four groups.

Patients with lower hemoglobin levels tended to be older and have a diabetes history, hypertension history and family history of CAD, myocardial infarction history, CHF history, cerebrovascular disease history, a lower smoking rate, and a lower TC at baseline during the trial period. These patients also had a lower baseline BMI, TG level (mg/dL), and LDL cholesterol (mg/dL) but higher HDL cholesterol (mg/dL). Meanwhile, the proportions of agents including strong antiplatelet agents (ticagrelor), ACE inhibitors, BBs, ARBs, statins, Gp IIb/IIIa inhibitors, oral anticoagulants, and clopidogrel were similar in all four groups. However, no significant differences in other characteristics between the four groups were observed (Table 1).

Univariate analysis

The results of univariate analysis are shown in Table 2. Without adjustment, sex, age, BMI, Killip classification, family history of CAD, diabetes, hyperlipidemia, hypertension, smoking status (current/recent), myocardial infarction history, CHF history, cerebrovascular events, TG level, TC, LDL cholesterol, HDL cholesterol, hemoglobin, the use of ticagrelor, clopidogrel, ACEIs, ARBs, statins, BBs, and oral anticoagulants were associated with all-cause mortality at 6 months in patients with ACS.

Patients who were older and female and who had a lower BMI, Killip classification, family history of CAD, diabetes, hypertension, history of myocardial infarction, history of CHF, and cerebrovascular events tended have a higher risk of death.

Association between pre-PCI hemoglobin levels and 6-month outcomes in patients with AMI

A binary logistic regression model was employed to assess the correlation between pre-PCI hemoglobin levels and clinical outcomes (Table 3). In the non-adjusted model, an increase of 1 g/dL of hemoglobin was correlated with a 30% reduction in the risk of 6-month all-cause death. In the minimally adjusted model (adjusted only for age and sex), the risk of 6-month all-cause mortality was decreased by 30% [hazard ratio (HR) =0.7, 95% confidence interval (95% CI): 0.7–0.8; P<0.001]. In the fully adjusted model (adjusted for age, sex, BMI, smoking status, Killip classification, hypertension, diabetes mellitus, dyslipidemia, history of CAD, history of cardiac congestive failure, cerebrovascular disease, TG level, TC, LDL cholesterol, HDL cholesterol, ticagrelor, clopidogrel, ACE inhibitors, beta blockers, ARBs, statins, Gp IIb/IIIa inhibitors, and calcium channel blockers), the HR was not significantly different (HR =0.8, 95% CI: 0.7–0.9; P<0.001).

For the further sensitivity analysis, we converted hemoglobin from a continuous variable to a categorical variable into quartiles and calculated the P for the trend. In patients with AMI undergoing PCI classified according to hemoglobin, the cumulative rate of 6-month all-cause mortality was significantly higher in the lower hemoglobin level group (hemoglobin <12.6 g/dL) than in the higher hemoglobin level group (hemoglobin ≥25.4 g/dL) at 6 months [182 (6.5%) vs. 21 (0.8%), P<0.001; Table 3]. A similar observation was found for clinical events such as cardiac death, myocardial infarction, cerebrovascular disease, and target vessel reconstruction. The P for trend of the non-adjusted model, minimally adjusted model, and fully adjusted models for cardiac death, myocardial infarction, and cerebrovascular events were significantly different. However, for the target vessel revascularization event, the P for trend of the adjusted model was not significant.

Nonetheless, the different categories showed nonisometric variations, indicating the possibility of a nonlinear relationships between hemoglobin and 6-month all-cause mortality (Table 3).

Analyses of nonlinear relationships and threshold effects of hemoglobin and 6-month all-cause mortality

Adjusted smoothed plots between pre-PCI hemoglobin and 6-month all-cause mortality were used to determine whether a nonlinear relationship was present. In our study (Figure 2), a nonlinear correlation between pre-PCI hemoglobin and 6-month all-cause mortality was found (adjusted for age, sex, BMI, smoking status, Killip classification, hypertension, diabetes mellitus, dyslipidemia, history of CAD, history of cardiac congestive failure, cerebrovascular disease, TG level, TC, LDL cholesterol, HDL cholesterol, ticagrelor, clopidogrel, Gp IIb/IIIa inhibitor, ACE inhibitors, BBs, ARBs, statins, and calcium channel blockers). With a hemoglobin <10.3 g/dL, the relationships between pre-PCI hemoglobin and mortality at 6-month was not significant (P>0.05). However, the 6-month all-cause mortality reduced with increasing hemoglobin level up to an inflection point (hemoglobin ≥10.3 g/dL). The OR, 95% CI, and P values were 0.7, 0.6–0.8 and P<0.001, respectively (Figure 2 and Table 4).

Figure 2 The nonlinear relationship between hemoglobin and all-cause mortality (A), cardiac death (B), myocardial infarction (C), and cerebrovascular events (D). Covariates which were adjusted of the same with fully-adjusted model. The red solid line represents the fitted nonlinear association between hemoglobin and all-cause mortality, cardiac death, myocardial infarction, cerebrovascular events. The blue dotted lines indicate the 95% confidence intervals for the estimated relationship. Hb, hemoglobin; OR, odds ratio.

Stratified analysis of 6-month all-cause mortality

Stratified analyses were performed by age (25–56, 57–70, and 71–98 years), gender, smoking status Killip classification (I, II, III, and IV), BMI (12.8–22.7, 22.7–25.2, and 25.2–49.3 kg/m²), history of hypertension, diabetes mellitus, hyperlipidemia, heart failure, myocardial infarction, angina, and diseases classification [non-ST-segment elevation myocardial infarction (NSTEMI) and ST-segment elevation myocardial infarction (STEMI)] to further assess the correlation between hemoglobin and 6-month all-cause mortality in various subgroups. The revealed that the association between hemoglobin and 6-month all-cause mortality were robust among all subgroups. The directions and values of odds ratios (ORs) were not significantly different between various subgroups, the magnitude was small (<5%), and the 95% CI was relatively stable (Figure 3).

Figure 3 Subgroup analysis of the primary outcome. HRs and 95% CIs are shown for the primary end point of all-cause mortality in subgroups of patients in the hemoglobin group. The P value for interaction represents the likelihood of interaction between the variable and the relative hemoglobin effect. BMI, body mass index; CI, confidence interval; CVD, cerebrovascular disease; DM, diabetes; DL, dyslipidemia; HR, hazard ratio; HTN, hypertension; NSTEMI, non-ST segment elevation myocardial infarction; pre-MI, pre-myocardial infarction; STEMI, ST segment elevation myocardial infarction.

Discussion

A secondary analysis of 11,533 patients who underwent PCI showed a strong correlation between a modest decrease in pre-PCI hemoglobin level and an increased risk of all-cause mortality at 6 months after adjustment for possible confounders. The rates of clinical outcomes for 6-month all-cause mortality, including cardiac death, cerebrovascular events, and myocardial infarction, were significantly higher in the lower hemoglobin level group than in the higher hemoglobin level group. In addition, a nonlinear relationship between pre-PCI hemoglobin and 6-month all-cause mortality was found. The linear decrease between hemoglobin and 6-month all-cause mortality reached a valley at a hemoglobin level of 10.3 g/dL (saturation value). With a hemoglobin level <10.3 g/dL, the relationship between pre-PCI hemoglobin and 6-month all-cause mortality was not significant. On the right side of the inflection point, mortality reduced with increasing hemoglobin level. The OR, 95% CI, and P values were 0.7, 0.6–0.8, and P<0.001, respectively.

Reviewing previous studies, we discerned that whether hemoglobin level can predict prognosis of AMI after PCI is controversial (10,18-23). By studying 16,318 patients with ACS, Brener et al. found that baseline hemoglobin and anemia could independently predict major bleeding and death. They found a nonlinear relationship between post-PCI hemoglobin level, a continuous variable, 30-day major bleeding, and adverse ischemic outcomes at 1 year, with an increased event rate at low hemoglobin levels and an inflection point of approximately 14 g/dL (18). In the study by Pei et al., 21,374 patients recruited in the ACS-QUIK trial revealed that baseline hemoglobin level could independently predict prognosis of South Asian patients with AMI. There was a nonlinear correlation between hemoglobin level and major bleeding, CVD death, and major adverse cardiovascular events (MACEs) (P<0.05 for nonlinearity). The threshold value for major bleeding, MACEs and CVD death were 13, 14.8, and 14.3 g/dL, respectively (24). Studies conducted by Sabatine et al. reported that there was a significant independent association between low hemoglobin levels and adverse cardiovascular outcomes. More importantly, in patients with STEMI, cardiovascular mortality and heart failure progressively increased when the baseline hemoglobin level was below 14 g/dL. In patients with NSTEMI ACS, a baseline hemoglobin level <11 g/dL significantly increased the odds of cardiovascular death, myocardial infarction, and recurrent ischemia (10). Thomas et al. reviewed 2,418 patients with STEMI who underwent primary PCI (PPCI) and found an increased risk of adverse events in anemia patients undergoing PPCI (9). In contrast, Vis et al. observed that in patients with STEMI undergoing PCI, the hemoglobin level was not predictive of 12-month mortality (25). However, none of these studies reported the nonlinear association of pre-PCI hemoglobin level and 6-month all-cause mortality in Korean patients with AMI undergoing PCI; we did examine this association and found that the threshold value was 10.3 g/dL for 6-month all-cause mortality.

Our research has several advantages. Firstly, we found trends in the effect size of pre-PCI hemoglobin level as a continuous and categorical variable and tested P for trends when hemoglobin was used as a category variable. Second, we used GAM to describe nonlinear relationships. This model can deal with nonparametric smoothing and fit regression splines into the data to better characterize the true correlation between exposure and clinical outcomes (26). Third, to minimize the effect of possible confounders, we used strict statistical adjustment.

However, our study had some limitations. We enrolled patients with from the KAMIR-NIH database, a population composed only of Koreans, so its versatility is limited. Moreover, this study only adjusted for the variables contained in the original database for a secondary analysis. Additionally, we only controlled for measurable factors but not for unmeasured confounding factors. Finally, pre-PCI hemoglobin levels were generally high in the population, and the correlation between hemoglobin level and adverse events in patients with severe anemia could not be better analyzed.

Conclusions

The study examined the clinical implications of pre-PCI hemoglobin levels in patients with AMI undergoing PCI. Patients with higher pre-PCI hemoglobin levels had better clinical laboratory risk profiles and outcomes. Pre-PCI hemoglobin levels were inversely associated with postoperative mortality when hemoglobin levels were ≥10.3 g/dL. More studies are needed to determine the optimal cutoff values in Asian populations, as well as long-term effects in patients with AMI.

Acknowledgments

The authors express our gratitude to the department that provided the funding to this study and the medical personnel of The Affiliated Hospital of Guizhou Medical University.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-665/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-665/prf

Funding: This work was finally funded by the National Natural Science Foundation of China (Nos. 82360990, 81904319, 82260987, and 82060855), the China Postdoctoral Science Foundation (No. 2022MD723769), the Science and Technology Fund of Guizhou Provincial Health Department (No. qiankehejichu-ZK[2022]zhongdian043), and the Fund of the Affiliated Hospital of Guizhou Medical University (Nos. gyfybsky-2021-33, 2021-GNHCT-020, gyfyxkyc-2023-10, GYFYBSKY-2021-49).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-665/coif). The authors have no conflicts of interest to declare.

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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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