Association Between Major Bleeding and In-Hospital Major Adverse Cardiovascular Events After Percutaneous Coronary Intervention in Acute Coronary Syndromes

Abstract

Background

Major bleeding (MB) is a serious complication in patients with acute coronary syndromes (ACS) undergoing percutaneous coronary intervention (PCI). Although its association with long-term adverse outcomes is well documented, the impact of in-hospital MB on early cardiovascular prognosis remains incompletely characterized.

Objective

To investigate the association between in-hospital MB and major adverse cardiovascular events (MACE) in patients with ACS treated with PCI.

Methods

We conducted a retrospective cohort study on 829 consecutive ACS patients who underwent successful PCI between January 2021 and December 2023. MB was defined as Bleeding Academic Research Consortium (BARC) type 3 or 5 bleeding events. MACE was defined as a composite of all-cause mortality, recurrent myocardial infarction, ischemic stroke, urgent target vessel revascularization, or new-onset/decompensated heart failure with left ventricular ejection fraction (LVEF) <30%. Clinical data and outcomes were extracted from hospital records and independently adjudicated.

Results

MB occurred in 4.5% of patients (n = 37). The incidence of in-hospital MACE was significantly higher among patients with MB compared to those without (40.5% vs. 8.1%, p < 0.001). In multivariate logistic regression, MB was the strongest independent predictor of in-hospital MACE (OR: 12.43, 95% CI: 3.43–44.98, p < 0.001), followed by reduced LVEF (OR per % increase: 0.794, 95% CI: 0.747–0.843, p < 0.001), age, and white blood cell count.

Conclusions

In-hospital MB is a potent and independent predictor of early MACE in patients with ACS undergoing PCI. These findings emphasize the need for careful risk stratification, bleeding prevention strategies, and individualized antithrombotic management in this high-risk population.

 

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Keywords

acute coronary syndrome - percutaneous coronary ıntervention - major bleeding - major adverse cardiovascular events - dual antiplatelet therapy - BARC bleeding criteria - in-hospital outcomes

Introduction

Acute coronary syndrome (ACS) is a major global health burden and among the leading causes of cardiovascular morbidity and mortality. Percutaneous coronary intervention (PCI), in conjunction with dual antiplatelet therapy (DAPT), has significantly improved outcomes in patients with ACS by reducing ischemic complications.[1]

However, the benefits of PCI come at the cost of increased risk of bleeding, particularly in the context of aggressive antithrombotic therapy. Major bleeding (MB), commonly defined by the Bleeding Academic Research Consortium (BARC) criteria as type 3 or above, has been consistently associated with worse clinical outcomes.[2] These include not only increased short-term mortality but also adverse cardiovascular events such as myocardial infarction, stroke, and unplanned revascularization.[3] [4] [5] Several pathophysiological mechanisms have been proposed, including hemodynamic compromise, withdrawal of antiplatelet agents, and inflammatory responses following bleeding events.[6] [7]

Although the link between MB and poor prognosis is well established, it remains unclear whether bleeding is an independent predictor of adverse cardiovascular events or merely a surrogate marker for patient's frailty and comorbidities.[8] [9] Furthermore, much of the current evidence focuses on long-term outcomes, whereas the impact of in-hospital bleeding events on early post-PCI prognosis in patients with ACS is less well-characterized.[10]

This study aims to investigate the association between MB and major adverse cardiovascular events (MACE) in patients with ACS undergoing PCI, thereby providing further insight into the prognostic importance of bleeding during the acute phase of treatment.

 

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Materials and Methods

Study Design and Setting

This retrospective observational cohort study was conducted in the cardiology department of a tertiary care hospital. This study adhered to the principles of the Declaration of Helsinki and was approved by the local institutional ethics committee. Due to the retrospective design of the study, the requirement for informed consent was waived.

 

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Study Population

A total of 829 patients aged ≥18 years who were hospitalized with ACS and underwent PCI between January 2021 and December 2023 were included. Patients with incomplete clinical outcome data, active malignancy, end-stage renal disease requiring dialysis, or advanced hepatic dysfunction were excluded from the study. A detailed flowchart of the inclusion and exclusion process is presented in [Fig. 1].

Fig. 1 Flowchart presenting the inclusion and exclusion process. MB, major bleeding; PCI, percutaneous coronary intervention.

Although patient care during the study period was guided by prior European Society of Cardiology (ESC) recommendations for consistency and clarity, ACS diagnoses in this analysis were retrospectively reviewed and classified according to the 2023 ESC guidelines.[11] The diagnosis of ACS was based on the presence of ischemic chest pain; electrocardiographic changes such as ST-segment elevation, depression, or new left bundle branch block; and/or a dynamic elevation in high-sensitivity cardiac troponin levels. ACS was further classified into ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), or unstable angina, according to the combination of electrocardiographic and biochemical findings. All patients underwent successful PCI during the same index hospitalization, defined as a continuous hospital stay during which the ACS diagnosis was made and treated without inter-hospital transfer or staged procedures beyond the initial admission.

 

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Definitions and Outcomes

MB was defined according to the BARC criteria as type 3 or 5 bleeding events that occurred during the in-hospital period.[2] [12] MACE were defined as a composite of clinically significant outcomes, including all-cause mortality, recurrent myocardial infarction, ischemic stroke, urgent target vessel revascularization, and new-onset or decompensated heart failure with a left ventricular ejection fraction (LVEF) of <30%. Although not included in all MACE definitions across clinical trials, we incorporated new-onset or decompensated heart failure with LVEF <30% to better reflect early post-PCI clinical deterioration in ACS patients. Prior evidence suggests that severe systolic dysfunction is a key prognostic marker in this population, justifying its inclusion in our composite outcome. All clinical events were verified through a detailed review of hospital medical records and independently adjudicated by two experienced cardiologists who were blinded to patient group assignments.

 

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Data Collection

Demographic characteristics, clinical history, vital signs on admission, medication use, and laboratory parameters were extracted from the hospital's electronic medical record system. Echocardiographic data, particularly LVEF, were recorded from the initial transthoracic echocardiography performed during hospitalization. All data were collected and entered into an anonymized database by two independent research assistants.

 

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Statistical Analysis

Statistical analyses were performed using the SPSS version 21.0 software (SPSS Inc., Chicago, IL, USA). Continuous variables were reported as mean ± standard deviation (SD) or median with interquartile range (IQR), depending on the normality of distribution assessed using the Kolmogorov–Smirnov test. Categorical variables are expressed as frequencies and percentages.

Group comparisons were performed using the independent-samples t-test or Mann–Whitney U test for continuous variables and the chi-square or Fisher's exact test for categorical variables. Variables with a p-value <0.05 in univariate analysis were included in a multivariate logistic regression model to identify independent predictors of in-hospital MACE. Results are reported as odds ratios (OR) with 95% confidence intervals (CI). For continuous variables, OR represent the change in the likelihood of the outcome per one-unit increase in the respective predictor variable (e.g., per 1 year increase in age, or per 1% change in LVEF). Statistical significance was set at a two-tailed p-value <0.05.

 

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Results

In total, 829 patients who underwent PCI for ACS were included in this study. The mean age of the study population was 62.0 ± 12.1 years, and 74.9% were male. MB, defined as BARC type ≥3, was observed in 37 patients (4.5%), whereas in-hospital MACE occurred in 79 patients (9.5%).

Comparison According to Major Bleeding Status

Patients who experienced MB were significantly older than those without bleeding (65.8 ± 12.3 vs. 61.7 ± 12.1 years, p = 0.041). Admission heart rate was also higher in the MB(+) group (92.5 ± 18.4 vs. 80.8 ± 13.2 bpm, p < 0.001). C-reactive protein (CRP) levels were higher in the MB(+) group (21.9 [7.2–45] vs. 9.0 [3.3–26.2] mg/L); the difference was statistically significant (p = 0.034). There were no significant differences in sex, blood pressure, hemoglobin level, creatinine level, lipid profile, or ejection fraction between patients with and without bleeding. Notably, the incidence of in-hospital MACE was markedly higher in the MB(+) group (40.5% vs. 8.1%, p < 0.001) ([Table 1]).

Table 1 Comparison of baseline clinical, demographic, and laboratory characteristics according to major bleeding status^a

	MB(+) patients (n = 37)	MB(−) patients (n = 792)	p
Age (years)	65.84 ± 12.27	61.68 ± 12.06	0.041
Gender (Male, %)	24 (64.9)	597 (75.4)	0.149
Systolic blood pressure (mmHg)	126.71 ± 16.62	127.98 ± 18.01	0.733
Diastolic blood pressure (mmHg)	79.71 ± 13.11	76.76 ± 11.98	0.24
Heart rate (bpm)	92.46 ± 18.4	80.81 ± 13.2	< 0.001
Hypertension (n, %)	19 (51.4)	462 (58.3)	0.4
Diabetes mellitus (n, %)	18 (48.6)	352 (44.4)	0.615
Hyperlipidemia (n, %)	5 (13.5)	178 (22.5)	0.199
Active smoking (n, %)	15 (40.5)	354 (44.7)	0.619
Family history of CAD (n, %)	6 (16.2)	115 (14.5)	0.775
Stroke (n, %)	1 (2.7)	16 (2)	0.775
Left ventricular ejection fraction (%)	44.05 ± 7.58	46.42 ± 7.77	0.07
Hemoglobin (g/dL)	13.54 ± 2.29	13.63 ± 2.08	0.793
White blood cell count (g/dL)	11.61 ± 2.36	11.04 ± 3.69	0.382
Platelet count (109/L)	260 (224–329)	251 (208–301)	0.113
Baseline creatinine (mg/dL)	0.89 (0.74–1.06)	0.87 (0.72–1.16)	0.905
Total cholesterol (mg/dL)	168.95 ± 46.91	177.73 ± 46.24	0.279
LDL cholesterol (mg/dL)	105.76 ± 38.52	109.02 ± 37.26	0.629
HDL cholesterol (mg/dL)	38.47 ± 7.3	39.57 ± 10.61	0.563
Triglyceride (mg/dL)	136 (94–189)	145 (104–201)	0.319
Glucose (mg/dL)	129 (115–220)	130 (105–193)	0.609
C reactive protein (mg/L)	21.90 (7.18–45)	9.01 (3.31–26.20)	0.034
Body mass index (kg/m2)	26.8 ± 2.88	27.04 ± 3.36	0.715
MACE	15 (40.5)	64 (8.1)	<0.001

Abbreviations: CAD, coronary artery diseases; CRP, C-reactive protein; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MACE, major adverse cardiovascular events.

Note: ^aContinuous variables are expressed as mean ± standard deviation and compared using the independent-samples t-test or Mann–Whitney U test, as appropriate. Categorical variables were compared using the chi-square or Fisher's exact test.

 

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Comparison According to MACE Status

Compared to patients without MACE, those who experienced MACE were significantly older (68.3 ± 12.6 vs. 61.2 ± 11.8 years, p < 0.001), had higher heart rates at admission (86.0 ± 17.5 vs. 80.9 ± 13.2 bpm, p = 0.016), and higher white blood cell (WBC) counts (12.6 ± 4.9 vs. 10.9 ± 3.6 × 10⁹/L, p < 0.001). Patients in the MACE(+) group also had significantly lower left ventricular ejection fraction (35.3 ± 11.0% vs. 47.5 ± 6.3%, p < 0.001), and elevated serum glucose (149 [114–228] vs. 128 [105–189] mg/dL, p = 0.015) and creatinine levels (1.00 [0.80–1.34] vs. 0.88 [0.74–1.05] mg/dL, p = 0.001). A history of stroke was significantly more frequent in the MACE(+) group (7.6% vs. 1.5%, p < 0.001). The occurrence of MB was substantially higher in patients who developed MACE (19.0% vs. 2.9%, p < 0.001) ([Table 2]).

Table 2 Comparison of clinical, demographic, and laboratory characteristics according to in-hospital MACE status^a

	MACE(+) patients (n = 79)	MACE(−) patients (n = 750)	p
Age (years)	68.3 ± 12.57	61.19 ± 11.84	< 0.001
Gender (Male, %)	60 (75.9)	561 (74.8)	0.823
Systolic blood pressure (mmHg)	123.11 ± 22.09	128.35 ± 17.49	0.054
Diastolic blood pressure (mmHg)	75.3 ± 14.76	77.02 ± 11.76	0.347
Heart rate (bpm)	85.96 ± 17.5	80.89 ± 13.19	0.016
Hypertension (n, %)	44 (55.7)	437 (58.3)	0.66
Diabetes mellitus (n, %)	34 (43)	336 (44.8)	0.764
Hyperlipidemia (n, %)	13 (16.5)	170 (22.7)	0.206
Active smoking (n, %)	28 (35.4)	341 (45.5)	0.088
Family history of CAD (n, %)	6 (7.6)	115 (15.3)	0.064
Stroke (n, %)	6 (7.6)	11 (1.5)	< 0.001
Left ventricular ejection fraction (%)	35.25 ± 10.99	47.48 ± 6.32	< 0.001
Hemoglobin (g/dL)	13.71 ± 2.17	13.62 ± 2.07	0.722
White blood cell count (g/dL)	12.58 ± 4.85	10.91 ± 3.55	< 0.001
Platelet count (109/L)	238 (199–317)	253 (210–301)	0.531
Baseline creatinine (mg/dL)	1.0 (0.8–1.34)	0.88 (0.74–1.05)	0.001
Total cholesterol (mg/dL)	168.32 ± 44.89	178.24 ± 46.34	0.085
LDL cholesterol (mg/dL)	102.64 ± 31.29	109.47 ± 37.77	0.152
HDL cholesterol (mg/dL)	39.67 ± 11.65	39.51 ± 10.38	0.907
Triglyceride (mg/dL)	137 (105–186)	145 (102–203)	0.663
Glucose (mg/dL)	149 (114–228)	128 (105–189)	0.015
C reactive protein (mg/L)	11.90 (3.85–42)	9.19 (3.31–27.40)	0.091
Body mass index (kg/m2)	26.45 ± 4.23	27.09 ± 3.23	0.138
Major bleeding	15 (19)	22 (2,9)	<0.001

Abbreviations: CAD, coronary artery diseases; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MACE, major adverse cardiovascular events.

Note: ^aContinuous variables are presented as mean ± standard deviation and were compared using the independent-samples t-test or the Mann–Whitney U test, depending on data distribution. Categorical variables were compared using the chi-square test or Fisher's exact test, as appropriate.

 

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Multivariate Predictors of In-Hospital MACE

In multivariate logistic regression analysis, MB emerged as the most powerful independent predictor of in-hospital MACE (adjusted OR: 12.43; 95% CI: 3.43–44.98; p < 0.001). In addition, a lower LVEF was independently associated with an increased risk of MACE (OR: 0.794; 95% CI: 0.747–0.843; p < 0.001), indicating a protective effect of preserved cardiac function. Advanced age (OR, 1.054; 95% CI, 1.013–1.096; p = 0.009) and elevated WBC count (OR, 1.125; 95% CI, 1.022–1.239; p = 0.016) were also significantly associated with MACE. Other variables, including serum creatinine level, glucose level, heart rate, and history of stroke, were not statistically significant in the final model ([Table 3]).

Table 3 Multivariate logistic regression analysis to determine the independent predictors of MACE^a

Variable	OR	95% CI		p
		Lower	Upper
Major bleeding	12.426	3.433	44.983	<0.001
Left ventricular ejection fraction	0.794	0.747	0.843	<0.001
Age	1.054	1.013	1.096	0.009
White blood cell count	1.125	1.022	1.239	0.016
Creatinine	1.343	0.618	2.922	0.457
Glucose	1.002	0.997	1.007	0.478
Heart rate (bpm)	1.002	0.973	1.032	0.913
Stroke	1.108	0.109	11.267	0.931

Abbreviation: MACE, major adverse cardiovascular events.

Note: ^aOdds ratios (OR) with 95% confidence intervals (CI) were calculated using multivariate logistic regression analysis.

 

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Discussion

MB has emerged as a critical determinant of outcomes in ACS patients undergoing PCI. In this retrospective cohort study, we demonstrated that MB was significantly associated with an increased risk of in-hospital MACE. These findings reinforce the growing body of evidence that MB is not a benign complication, but rather a marker of heightened vulnerability to a broad range of adverse cardiovascular outcomes—including not only ischemic events such as myocardial infarction and stroke, but also non-ischemic complications like acute decompensated heart failure associated with severely reduced LVEF.[13]

Importantly, we included heart failure with LVEF <30% as part of the MACE definition. This approach was selected based on evidence that impaired left ventricular systolic function particularly below this threshold is strongly associated with in-hospital mortality and early adverse events following PCI. Supporting this, recent studies have highlighted the prognostic value of low LVEF in ACS patients both for ischemic and bleeding complications.[14] Therefore, inclusion of this endpoint enhances the clinical relevance of our composite outcome.

Our study revealed that the incidence of MB was 4.5%, and that these patients exhibited a significantly higher rate of in-hospital MACE than those without bleeding. Although MB was the strongest independent predictor of in-hospital MACE in our study, the wide confidence interval (OR: 12.43, 95% CI: 3.43–44.98) reflects the relatively low number of bleeding events (n = 37, 4.5%), which may have reduced the precision of our effect estimate. This limitation has also been reported in other registries, such as PARIS and TRACER, where MB events were infrequent but highly prognostic. These results are consistent with previous large-scale studies and registries, such as the PARIS registry and the TRACER trial, which reported that bleeding complications independently predicted subsequent myocardial infarction, stroke, and death.[15] [16] The observed association suggests that bleeding exerts pathophysiological effects that extend far beyond simple hemodynamic compromise.[17] [18]

Several interrelated biological mechanisms likely underlie the association between MB and cardiovascular events. First, MB results in acute hypovolemia, which leads to a reduced preload, decreased cardiac output, and hypotension. These hemodynamic changes compromise coronary perfusion, particularly in territories already jeopardized by ACS, potentially triggering myocardial ischemia, infarct extension, or arrhythmic events. Compensatory tachycardia, while attempting to preserve perfusion pressure, paradoxically increases myocardial oxygen demand, thus exacerbating the supply–demand mismatch. In patients with impaired systolic function, even modest drops in perfusion may precipitate decompensated heart failure or cardiogenic shock.[19] [20] [21] [22]

Second, MB often necessitates premature discontinuation of DAPT, particularly P2Y12 inhibitors. This withdrawal removes critical pharmacological protection against platelet aggregation during the early phase post-PCI when the endothelial healing of stents is incomplete. Studies have shown that early cessation of DAPT, particularly within the first 30 days, significantly increases the incidence of stent thrombosis and recurrent myocardial infarction.[23] [24] [25] [26] Although the interruption of DAPT is widely recognized as a mechanism contributing to adverse cardiovascular events following MB, our study did not capture data on antiplatelet therapy discontinuation. Therefore, this proposed pathway should be interpreted cautiously in our context.

Third, MB initiates a systemic inflammatory response characterized by the release of proinflammatory cytokines such as interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and CRP. These mediators promote leukocyte adhesion, endothelial activation, and increased oxidative stress, all of which contribute to plaque destabilization and a prothrombotic vascular environment.[27] [28] In our study, a trend toward elevated CRP levels in patients with MB supported the role of inflammation as a bridge between bleeding and adverse ischemic outcomes.

Furthermore, hemorrhage induces a hypercoagulable state. Physiological responses aimed at halting bleeding, such as platelet activation and thrombin generation, may inadvertently trigger arterial thrombosis.[29] The vascular endothelium, which normally maintains an antithrombotic balance through nitric oxide (NO) and prostacyclin release, is dysfunctional in the setting of systemic inflammation and hemodynamic stress. Reduced endothelial nitric oxide synthase (eNOS) activity impairs vasodilation and enhances platelet adhesion.[30] Circulating microparticles released in response to vascular injury further amplify coagulation cascades. This pathophysiological milieu creates a window of vulnerability wherein both bleeding and thrombosis can coexist and reinforce one another.

Recent studies, such as that by Yoshii et al, have highlighted the prognostic significance of endothelial dysfunction in patients with ACS and its association with both bleeding risk and cardiovascular death.[31] These data support the hypothesis that bleeding is not merely a complication but also a systemic event that destabilizes vascular integrity and precipitates further cardiovascular deterioration.

When comparing our findings with those in the literature, several similarities and differences emerge. Consistent with previous studies, we found that older age, elevated heart rate at admission, lower LVEF, and higher WBC count were associated with worse outcomes.[5] [32] [33] [34] [35] Elderly patients are particularly vulnerable owing to increased vascular fragility, comorbidities, and diminished compensatory mechanisms. Elevated WBC counts and inflammatory markers not only may reflect systemic stress or occult infection but also likely contribute directly to plaque instability and thrombotic potential.[6]

Our study contributes to the growing recognition of the “risk paradox” phenomenon where patients at high bleeding risk simultaneously harbor high ischemic risk.[36] This dual vulnerability complicates therapeutic decision-making, as intensifying antithrombotic therapy reduces ischemic events but increases bleeding, whereas de-escalation strategies may prevent bleeding, but leave patients exposed to thrombosis. Recent trials, such as MASTER DAPT, have suggested that shorter durations of DAPT may offer a safer balance in select high-risk populations, although careful patient selection remains crucial.[37] [38]

In recent years, platelet function testing (PFT) and biomarker-guided strategies have emerged as valuable tools in tailoring antiplatelet therapy, particularly for patients at increased risk of bleeding.[39] [40] Trials such as TROPICAL-ACS and ARCTIC demonstrated that PFT-guided de-escalation starting with a potent P2Y12 inhibitor like prasugrel or ticagrelor, followed by a switch to clopidogrel based on platelet reactivity can safely reduce bleeding events without increasing ischemic risk.[41] [42] Capranzano and Angiolillo further emphasized that such de-escalation approaches may be particularly beneficial in subgroups such as diabetics, who often exhibit enhanced platelet reactivity.[43] Moreover, current guidelines support individualized DAPT strategies, especially in high bleeding risk populations, highlighting the clinical relevance of incorporating PFT or biomarkers into antithrombotic decision-making. These tools allow clinicians to better balance ischemic and hemorrhagic risks and may improve outcomes in ACS patients following PCI. Future studies may further refine patient selection for PFT-guided strategies and validate their impact on long-term cardiovascular outcomes.

These findings emphasize the need for early identification of bleeding-prone individuals and implementation of individualized treatment strategies. Practical measures include the preferential use of radial arterial access during PCI to minimize access-site bleeding, cautious dosing of antithrombotic agents based on body weight and renal function, and consideration of abbreviated DAPT courses in patients deemed to be at high bleeding risk. In addition, the use of validated bleeding risk scores and endothelial function markers may provide further refinement for clinical risk stratification.

 

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Study Limitations

Our study has some limitations. First, given the observational nature of our study, the associations identified—while statistically significant—do not establish causality and should be interpreted as correlational findings rather than definitive cause–effect relationships. Second, although all bleeding events were classified using the BARC definitions, adjudication was not centralized, which may have led to some degree of misclassification. Third, the lack of post-discharge follow-up data limits our understanding of the long-term implications. Moreover, we did not collect data on DAPT discontinuation following bleeding events, which limits our ability to directly assess this mechanism as a mediator of in-hospital MACE. Additionally, the dual role of LVEF <30% both as a MACE component and an independent predictor could introduce collinearity. However, multicollinearity diagnostics using variance inflation factor (VIF) revealed acceptable levels (VIF <2). Still, the possibility of statistical overlap cannot be fully excluded and warrants further exploration in future prospective cohorts.

 

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Conclusion

In conclusion, MB was strongly and independently associated with an increased risk of in-hospital MACE in patients with ACS undergoing PCI. Multiple interconnected biological mechanisms, including hemodynamic instability, interruption of antithrombotic therapy, systemic inflammation, platelet activation, endothelial dysfunction, and impaired cardiac reserve contribute to this relationship. Recognizing bleeding as a sentinel prognostic event and adopting individualized physiology-informed management strategies are essential steps toward improving early and long-term outcomes in this vulnerable population.

 

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Conflict of Interest

The authors declare that they have no conflict of interest.

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Publikationsverlauf

Eingereicht: 01. Juni 2025

Angenommen: 22. Juli 2025

Artikel online veröffentlicht:
14. August 2025