Research Article |
Sarah Nurdiana‡, Neng Fisheri Kurniati‡, Triwedya Indra Dewi§, Zulfan Zazuli‡
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Corresponding author: Zulfan Zazuli ( zulfan@itb.ac.id ) Academic editor: Borislav Georgiev
© 2025 Sarah Nurdiana, Neng Fisheri Kurniati, Triwedya Indra Dewi, Zulfan Zazuli.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Nurdiana S, Kurniati NF, Dewi TI, Zazuli Z (2025) Interactions among antithrombotic agents in acute coronary syndrome: association with bleeding and hospital length of stay. Pharmacia 72: 1-8. https://doi.org/10.3897/pharmacia.72.e163748
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Abstract
Acute coronary syndrome management requires antiplatelets and anticoagulants to prevent thrombus formation. However, concurrent use may lead to drug interactions and harmful effects – such as bleeding – that can impact the patient’s treatment process, including the length of stay (LOS). This study aimed to analyze potential and actual drug interactions among antithrombotic agents and their association with LOS. This retrospective study was conducted using electronic medical records and laboratory results from patients during the period October 2024–March 2025. The inclusion criteria were hospitalized patients receiving antithrombotic agents. A total of 176 patients were included using a consecutive sampling method. Drug interactions were analyzed using Micromedex. Bleeding was evaluated using hemoglobin levels and clinical signs based on BARC criteria. Bleeding was observed in 14 patients, of whom 57.14% received three or more antithrombotic agents. The most common potential pharmacodynamic interaction occurred between aspirin and clopidogrel. The median LOS was 4 days (IQR 4), and the median number of potential pharmacodynamic interactions was 3 (IQR 3). The number of drugs and LOS were significantly higher in the bleeding group (p < 0.05). The number of drugs and the type of ACS were significant factors influencing LOS.
Keywords
antithrombotic, bleeding, drug interaction, length of stay
Introduction
Acute coronary syndrome (ACS) is one of the clinical manifestations of coronary heart disease resulting from a sudden decrease in blood flow to the heart. This decrease is caused by an occlusion following the rupture of an unstable atherosclerotic plaque. Atherosclerosis arises from endothelial dysfunction and the accumulation of oxidized low-density lipoprotein (LDL), triggering a series of inflammatory processes and plaque formation. Plaques with a thin fibrous cap and a large necrotic core may be unstable and rupture, causing a cascade of coagulation and thrombus formation (
Management of ACS aims to rapidly restore coronary blood flow and prevent recurrent ischemic events. Antiplatelet therapy is a fundamental component in the management of ACS. Dual antiplatelet therapy (DAPT), which combines aspirin with a P2Y12 inhibitor such as clopidogrel, is used for both short-term and long-term therapy, particularly in patients undergoing interventions such as stenting via percutaneous coronary intervention (PCI). In addition to antiplatelet agents, patients with ACS often use anticoagulants – particularly those with atrial fibrillation or a history of venous thromboembolism and those undergoing PCI – to prevent stent thrombosis (
A drug interaction is defined as a change in the effect of a drug caused by the presence of another chemical compound in the body at the same time. These compounds may include drugs, food, herbal medicines, or other substances that affect the drug’s efficacy (Baxter 2010). The occurrence of drug interactions can result in adverse effects, such as bleeding. Such effects may lead to hospitalization, rehospitalization, and increased length of stay. The length of stay refers to the duration a patient spends in a hospital or healthcare facility, from admission to discharge (
Materials and methods
The study was conducted retrospectively using secondary patient data obtained through electronic medical records and laboratory results.
Participants
This research obtained ethical approval from the Padjadjaran University Research Ethics Commission (No. 266/UN6.KEP/EC/2025). The study was conducted at Hasan Sadikin Hospital, Bandung. Samples were selected using a consecutive sampling method based on inclusion criteria. Inclusion criteria in this study were patients diagnosed with acute coronary syndrome (STEMI or NSTEMI), hospitalized between October 2024 and March 2025, and who received at least two antithrombotic agents during admission. Exclusion criteria were patients whose medical records were incomplete or inaccessible, who received only one antithrombotic agent, or who passed away within the initial 24-hour period following admission.
Data collection
Hemoglobin values and clinical events were used to assess bleeding events, based on the Bleeding Academic Research Consortium (BARC) classification. Clinical signs were obtained from narrative notes in the physician’s documentation. Medicines used during hospitalization were examined through drug use records and analyzed using Micromedex to identify potential drug interactions.
Statistical analysis
The number of samples was determined using the bivariate normal model formula, with an alpha value of 0.05, a beta value of 0.2, and a correlation coefficient value from previous research of 0.22. Therefore, the minimum number of participants was 160. In this study, 176 medical records met the inclusion criteria and were included as research samples.
Based on normality testing using the Kolmogorov–Smirnov test, it was found that the data distribution was not normal; therefore, non-parametric tests were used. Data are shown as median (interquartile range, IQR). Continuous variables – such as age, length of stay, number of comorbidities, number of drugs, number of antithrombotic agents, and number of potential pharmacodynamic interactions – were analyzed using the Mann–Whitney U test. Categorical variables – such as gender and type of ACS – were analyzed using Fisher’s exact test and the Chi-square test. A correlation test between variables was performed using the Spearman rank test. Logistic regression was performed to assess which variables influenced the incidence of bleeding. Multiple linear regression was performed to evaluate the variables that influenced the length of stay. Variables included in the multivariate regression analysis were those with a p-value < 0.2 in the bivariate analysis. Statistical analysis was performed using Minitab Statistical Software 22. The results of the analysis were considered statistically significant if the p-value < 0.05.
Results
During the study period, there were 198 patients whose medical records could be accessed. However, 22 patients did not meet the inclusion criteria because their data were incomplete, they received only one antithrombotic drug, they died, or they had multiple admissions. Thus, the total number of patients who met the inclusion criteria was 176.
A total of 148 patients were male, and 28 patients were female. Their ages ranged from 25 to 90 years, with a median of 56 years (IQR 15). The length of stay had a median value of 4 days (IQR 4). ST-elevation myocardial infarction (STEMI) was the predominant diagnosis (69.32%). The number of comorbidities per patient had a median value of 2. Hypertension, diabetes mellitus, and acute kidney injury were the most common comorbidities in this study.
| Variables | Category | Frequency | Percentage |
|---|---|---|---|
| Gender | Male | 148 | 84.09% |
| Female | 28 | 15.91% | |
| Age (years) | <45 | 18 | 10.23% |
| 45–60 | 106 | 60.23% | |
| 61–76 | 43 | 24.43% | |
| >76 | 9 | 5.11% | |
| Type of ACS | STEMI | 122 | 69.32% |
| NSTEMI | 54 | 30.86% | |
| Length of stay (days) | ≤ 4 | 117 | 66.47% |
| > 4 | 59 | 33.53% | |
| Number of drugs per patient | < 10 | 13 | 7.38% |
| 10–20 | 101 | 57.38% | |
| > 20 | 62 | 35.24% | |
| Number of antithrombotic agents | ≤ 3 drugs | 94 | 53.4% |
| > 3 drugs | 82 | 46.6% | |
| Number of potential pharmacodynamic interaction | ≤ 3 | 96 | 54.55% |
| > 3 | 80 | 45.45% | |
| Number of comorbidity | ≤ 2 | 90 | 51.13% |
| > 2 | 86 | 48.87% | |
| Types of comorbidity | Hypertension | 85 | 48.3% |
| DM | 62 | 35.23% | |
| AKI | 37 | 21.02% | |
| CHF | 27 | 15.34% | |
| Ischemic cardiomyopathy | 12 | 6.8% | |
| COPD | 9 | 5.1% | |
| Atrioventricular block | 8 | 4.5% |
The number of drugs prescribed per patient during hospitalization ranged from 8 to 61 (median = 17). The median number of antithrombotic agents per patient was 3 (IQR 1). In this study, 14 patients (7.95%) showed signs of bleeding – both clinically and based on laboratory results. The most common clinical signs of bleeding observed were hematuria and gastrointestinal (GI) bleeding.
A total of 742 potential pharmacodynamic interactions were identified. Table
| No | Potential drug interaction | n | % |
|---|---|---|---|
| 1 | Aspirin–clopidogrel | 106 | 14.29% |
| 2 | Aspirin–ticagrelor | 100 | 13.48% |
| 3 | Aspirin–heparin | 91 | 12.26% |
| 4 | Aspirin–enoxaparin | 68 | 9.16% |
| 5 | Clopidogrel–heparin | 59 | 7.95% |
| 6 | Heparin–ticagrelor | 44 | 5.93% |
| 7 | Aspirin–fondaparinux | 39 | 5.26% |
| 8 | Clopidogrel–enoxaparin | 36 | 4.85% |
| 9 | Clopidogrel–ticagrelor | 33 | 4.45% |
| 10 | Heparin–enoxaparin | 31 | 4.18% |
Comparative analysis in Table
| Variable | Category | Bleeding group (n = 14) | Non-bleeding group (n = 162) | p-value |
|---|---|---|---|---|
| Gender, n (%) | Male | 13 (92.85%) | 135 (83.3%) | 0.701 |
| Female | 1 (7.15%) | 27 (16.7%) | ||
| Type of ACS, n (%) | STEMI | 10 (71.42%) | 112 (69.14%) | 1 |
| NSTEMI | 4 (28.58%) | 50 (30.86%) | ||
| Age (years) | Median (IQR) | 56.5 (16) | 55.5 (16) | 0.648 |
| LOS (days) | Median (IQR) | 5 (3.5) | 3 (3) | 0.031* |
| Number of drugs per patient | Median (IQR) | 23 (15.25) | 16 (10) | 0.001* |
| Number of antithrombotic agents | Median (IQR) | 4 (2) | 3 (1) | 0.148 |
| >3 drugs | 8 (57.14%) | 74 (45.68%) | 0.409 | |
| ≤3 drugs | 6 (42.86%) | 88 (54.32%) | ||
| Number of potential drug interactions | Median (IQR) | 5.5 (6.25) | 3 (3) | 0.275 |
| Number of comorbidities | Median (IQR) | 3 (3.5) | 2 (3) | 0.527 |
| Hemoglobin (g/dL) | Initial | 13.55 | 14 | 0.812 |
| Final | 14.5 | 13.7 | 0.785 | |
| ΔHb | -1.2 | -0.5 | 0.099 |
| Variable | OR | 95% CI | p-value |
|---|---|---|---|
| Length of stay | 1.1188 | 0.9205; 1.3599 | 0.259 |
| Number of drugs | 1.0295 | 0.9481; 1.1178 | 0.489 |
| Number of antithrombotic agents | 1.2312 | 0.6576; 2.3050 | 0.516 |
Table
| Variable | LOS, days (Median (IQR)) | Bivariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|---|---|
| ρ | Interpretation | p-value | B | 95% CI | p-value | ||
| Gender | 0.550 | ||||||
| Male | 4 (4) | ||||||
| Female | 3.5 (3) | ||||||
| Type of ACS | 0.002* | (-0.1462:-0.0266) | 0.005* | ||||
| NSTEMI | 5 (4) | Ref | |||||
| STEMI | 3 (3) | -0.0864 | |||||
| Bleeding | 0.031* | (-0.0634:0.1421) | 0.451 | ||||
| No | 3 (3) | Ref | |||||
| Yes | 5 (3.5) | 0.0394 | |||||
| Age | 0.189 | Very weak | 0.012* | 0.00039 | (-0.00211:0.0029) | 0.757 | |
| Number of Comorbid | 0.413 | Moderate | 0.000* | 0.01781 | (-0.00084:0.03645) | 0.061 | |
| Number of drugs | 0.657 | Strong | 0.000* | 0.01765 | (0.01336:0.02194) | 0.000* | |
| Number of potential pharmacodynamic interactions | 0.248 | Weak | 0.001* | 0.00386 | (-0.00648:0.01457) | 0.477 | |
| Number of antithrombotic drugs | 0.267 | Weak | 0.000* | ||||
Discussion
This study examined the association between pharmacodynamic interactions among antithrombotic agents and clinical outcomes – especially bleeding occurrence and length of hospital stay – in patients with acute coronary syndrome (ACS). The findings highlight the high prevalence of potential pharmacodynamic interactions involving commonly used antiplatelet and anticoagulant combinations.
In this study, the number of male patients was higher than the number of female patients. These results are consistent with those from the acute coronary syndrome registries in Indonesia and Malaysia (
A total of 48.3% of patients in this study were diagnosed with hypertension as an additional condition. This is consistent with another study showing that more than 50% of ACS patients have hypertension (
The most common potential drug interactions in this study were those between antiplatelet agents, such as aspirin, and P2Y12 inhibitors, including clopidogrel and ticagrelor. These combinations are consistent with dual antiplatelet therapy (DAPT), which is commonly recommended for managing acute coronary syndrome. This aligns with previous research on cardiothoracic ICU patients in China (
The interaction between antithrombotic drugs is a pharmacodynamic interaction – an interaction that occurs at the receptor or drug target level when drugs with similar or opposing pharmacological effects are administered simultaneously (
The analysis of gender and age variables revealed no significant differences between the groups that experienced bleeding and those that did not. These results suggest that bleeding is not associated with gender or age. However, previous research showed a significant difference in age between patients who experienced bleeding and those who did not (
The median length of stay was significantly greater in the bleeding group than in the non-bleeding group (5 days vs 3 days, p < 0.05). These results suggest that bleeding is associated with longer hospital stays. A previous study showed similar results, reporting that the length of stay was longer for patients who experienced major bleeding than for those who did not (12 days vs 9 days) (
Analysis of the primary diagnosis revealed no significant correlation between ACS type and bleeding incidence. Median hemoglobin values at baseline and at the end of hospitalization showed no significant differences between the two groups. Other parameters – such as INR, aPTT, and PT – were not analyzed because they were not routinely measured.
In this study, patients received an average of 17 drugs, three of which were antithrombotic agents. According to the guidelines, ACS patients typically receive two types of antiplatelet medications (DAPT) and one anticoagulant during hospitalization – particularly those undergoing invasive procedures such as PCI (
The number of potential pharmacodynamic interactions was greater in the bleeding group than in the non-bleeding group. However, the statistical results did not show a significant difference. Previous studies have demonstrated an association between the number of potential drug interactions – especially those related to anticoagulant use – and bleeding events (
Bivariate analysis revealed a significant difference in length of hospitalization between patients diagnosed with STEMI and those with NSTEMI. Multivariate analysis showed consistent results. Patients with a primary diagnosis of NSTEMI had a longer length of stay. Previous studies have reported similar findings – NSTEMI patients tend to be older, have more extensive coronary artery disease, and have more comorbidities than STEMI patients (
Analysis of the age variable showed a weak association with length of stay. Previous studies have suggested that older age is associated with increased length of stay in patients with ACS. As age increases, physiological function declines – causing greater complexity in disease management that requires evaluation and prolonged hospitalization (
The number of drugs was strongly associated with length of hospitalization. Patients with more complex disease states requiring more drugs usually undergo longer hospitalizations. However, receiving multiple medications also increases the risk of adverse events and drug interactions, which may further prolong hospitalization. This analysis cannot infer causality – it only examines the relationship between variables.
Analysis of length of stay in the bleeding and non-bleeding groups showed a significant difference (p = 0.031). However, after correcting for age, number of drugs, type of ACS diagnosis, number of comorbidities, and number of bleeding-related drugs, bleeding was no longer an independent predictor of length of stay.
This study has the advantage of not only relying on potential drug interactions based on literature or databases but also analyzing actual drug interactions occurring in patients during treatment. The limitation of this study is that it was conducted retrospectively – so there is a possibility of incomplete information regarding bleeding events, as no direct observation was made. Nevertheless, the results of this study still provide insight into the incidence of bleeding as an actual drug interaction occurring in patients with ACS. Future studies are expected to be conducted prospectively to observe the effects of drug interactions directly.
Conclusion
Potential pharmacodynamic interactions between antithrombotic medications were shown to be highly prevalent in hospitalized acute coronary syndrome (ACS) patients. Bleeding can result from these interactions, and in this study, it occurred in 14 patients (7.8% of the total sample). The median length of stay for those patients was significantly longer than for those who did not experience bleeding, and 57% of them received three or more antithrombotic agents. Medication regimens must be closely monitored in order to reduce the risk of bleeding and prolonged hospital stays.
Acknowledgments
The authors would like to express their gratitude to the Pharmacy and Medical Records Departments of Hasan Sadikin Hospital (RSHS) Bandung for their assistance in providing access to the patient data utilized in this study.
Additional information
Conflict of interest
The authors have declared that no competing interests exist.
Ethical statements
The authors declared that no clinical trials were used in the present study.
The authors declared that no experiments on humans or human tissues were performed for the present study.
The authors declared that no informed consent was obtained from the humans, donors, or donors’ representatives participating in the study.
The authors declared that no experiments on animals were performed for the present study.
The authors declared that no commercially available immortalized human or animal cell lines were used in the present study.
Use of AI
No use of AI was reported.
Funding
This study was funded by the 2025 Research, Community Service, and Innovation (PPMI 2025) Program, School of Pharmacy, Institut Teknologi Bandung (grant number 26D/IT1.C10/SK-KU/2025).
Author contributions
All authors have contributed equally.
Author ORCIDs
Neng Fisheri Kurniati https://orcid.org/0000-0002-3313-6612
Zulfan Zazuli https://orcid.org/0000-0002-1264-9558
Data availability
All of the data that support the findings of this study are available in the main text or Supplementary Information.
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Supplementary material
List of drug interactions
Data type: xlsx