Comparison of ACUITY, CRUSADE, and GRACE Risk Scales for Predicting Clinical Outcomes in Patients Treated with Dual-Antiplatelet Therapy

Predictive Model of Internal Bleeding in Elderly Aspirin Users Using XGBoost Machine Learning

Objective

This study aimed to develop a predictive model for assessing internal bleeding risk in elderly aspirin users using machine learning.

Methods

A total of 26,030 elderly aspirin users (aged over 65) were retrospective included in the study. Data on patient demographics, clinical features, underlying diseases, medical history, and laboratory examinations were collected from Affiliated Dongyang Hospital of Wenzhou Medical University. Patients were randomly divided into two groups, with a 7:3 ratio, for model development and internal validation, respectively. Least absolute shrinkage and selection operator (LASSO) regression, extreme gradient boosting (XGBoost), and multivariate logistic regression were employed to develop prediction models. Model performance was evaluated using area under the curve (AUC), calibration curves, decision curve analysis (DCA), clinical impact curve (CIC), and net reduction curve (NRC).

Results

The XGBoost model exhibited the highest AUC among all models. It consisted of six clinical variables: HGB, PLT, previous bleeding, gastric ulcer, cerebral infarction, and tumor. A visual nomogram was developed based on these six variables. In the training dataset, the model achieved an AUC of 0.842 (95% CI: 0.829-0.855), while in the test dataset, it achieved an AUC of 0.820 (95% CI: 0.800-0.840), demonstrating good discriminatory performance. The calibration curve analysis revealed that the nomogram model closely approximated the ideal curve. Additionally, the DCA curve, CIC, and NRC demonstrated favorable clinical net benefit for the nomogram model.

Conclusion

This study successfully developed a predictive model to estimate the risk of bleeding in elderly aspirin users. This model can serve as a potential useful tool for clinicians to estimate the risk of bleeding in elderly aspirin users and make informed decisions regarding their treatment and management.

LASSO-derived model for the prediction of bleeding in aspirin users

Aspirin is widely used for both primary and secondary prevention of panvascular diseases, such as stroke and coronary heart disease (CHD). The optimal balance between reducing panvascular disease events and the potential increase in bleeding risk remains unclear. This study aimed to develop a predictive model specifically designed to assess bleeding risk in individuals using aspirin. A total of 58,415 individuals treated with aspirin were included in this study. Detailed data regarding patient demographics, clinical characteristics, comorbidities, medical history, and laboratory test results were collected from the Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups at a ratio of 7:3. The larger group was used for model development, while the smaller group was used for internal validation. To develop the prediction model, we employed least absolute shrinkage and selection operator (LASSO) regression followed by multivariate logistic regression. The performance of the model was assessed through metrics such as the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The LASSO-derived model employed in this study incorporated six variables, namely, sex, operation, previous bleeding, hemoglobin, platelet count, and cerebral infarction. It demonstrated excellent performance at predicting bleeding risk among aspirin users, with a high AUC of 0.866 (95% CI 0.857-0.874) in the training dataset and 0.861 (95% CI 0.848-0.875) in the test dataset. At a cutoff value of 0.047, the model achieved moderate sensitivity (83.0%) and specificity (73.9%). The calibration curve analysis revealed that the nomogram closely approximated the ideal curve, indicating good calibration. The DCA curve demonstrated a favorable clinical net benefit associated with the nomogram model. Our developed LASSO-derived predictive model has potential as an alternative tool for predicting bleeding in clinical settings.

Short- and long-term performance of risk calculation tools for mortality in patients with acute coronary syndrome

Background

The mortality rate of acute coronary syndrome (ACS) remains high. Therefore, patients with ACS should undergo early risk stratification, for which various risk calculation tools are available. However, it remains uncertain whether the predictive performance varies over time between risk calculation tools for different target periods. This study aimed to compare the predictive performance of risk calculation tools in estimating short- and long-term mortality risks in patients with ACS, while considering different observation periods using time-dependent receiver operating characteristic (ROC) analysis.

Methods

This study included 404 consecutive patients with ACS who underwent coronary angiography at our hospital from March 2017 to January 2021. The ACTION and GRACE scores for short-term risk stratification purposes and CRUSADE scores for long-term risk stratification purposes were calculated for all participants. The participants were followed up for 36 months to assess mortality. Using time-dependent ROC analysis, we evaluated the area under the curve (AUC) of the ACTION, CRUSADE, and GRACE scores at 1, 6, 12, 24, and 36 months.

Results

Sixty-six patients died during the observation periods. The AUCs at 1, 6, 12, 24, and 36 months of the ACTION score were 0.942, 0.925, 0.889, 0.856, and 0.832; those of the CRUSADE score were 0.881, 0.883, 0.862, 0.876, and 0.862; and those of the GRACE score 0.949, 0.928, 0.888, 0.875, and 0.860, respectively.

Conclusions

The ACTION and GRACE scores were excellent risk stratification tools for mortality in the short term. The prognostic performance of each risk score was almost similar in the long term, but the CRUSADE score might be a superior risk stratification tool in the longer term than 3 years.

Influences of different dose of tirofiban for acute ST elevation myocardial infarction patients underwent percutaneous coronary intervention

Tirofiban is widely used in patients with acute ST elevation myocardial infarction (STEMI) underwent percutaneous coronary intervention (PCI). This drug can efficiently improve myocardial perfusion and cardiac function, but its dose still remains controversial. We here investigated the effects of different dose of tirofiban on myocardial reperfusion and heart function in patients with STEMI. A total of 312 STEMI patients who underwent PCI in our hospital from March 2017 to March 2018 were enrolled and randomly divided into control group (75 cases, 0 μg/kg), low-dose group (79 cases, 5 μg/kg), medium-dose group (81 cases, 10 μg/kg) and high-dose group (77 cases, 20 μg/kg). The infarction-targeted artery flow grade evaluated by thrombolysis in myocardial infarction (TIMI), corrected TIMI frame count (CTFC) and sum-ST-segment resolution were recorded. At Day 7 and Day 30 after PCI, the left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter, left ventricular end systolic diameter, major adverse cardiovascular events and the hemorrhage and thrombocytopenia were also evaluated. After PCI, the rate of TIMI grade 3, CTFC and incidence of sum-ST-segment resolution > 50% of high-dose group were significantly higher than those of control group, low-dose group and medium-dose group (P < .05), and the CTFC of medium -dose group were significantly higher than that of control group, low-dose group (P < .05). Moreover, the LVEF, left ventricular end diastolic diameter and left ventricular end systolic diameter of high-dose group were significantly improved than those of other groups, and the LVEF of medium-dose group was significantly superior to that of low-dose group (P < .05). However, the incidence of major adverse cardiac events in high-dose group was significantly decreased, while the hemorrhage and incidence of thrombocytopenia of high-dose group were significantly higher than those of other 3 groups (P < .05). The tirofiban can effectively alleviate the myocardial ischemia-reperfusion injury and promote the recovery of cardiac function in STEMI patients underwent PCI. Although the high-dose can enhance the clinical effects, it also increased the hemorrhagic risk. Therefore, the rational dosage application of tirofiban become much indispensable in view of patient's conditions and hemorrhagic risk, and a medium dose of 10 μg/kg may be appropriate for patients without high hemorrhagic risk.

Cardiovascular Risk Factors and Secondary Events Among Acute and Chronic Stable Myocardial Infarction Patients: Findings from a Managed Care Database

INTRODUCTION

Long-term risk for recurrent cardiovascular events among myocardial infarction (MI) patients in the acute versus chronic stable phase is not well characterized. This study was conducted to evaluate risk factors associated with all-cause mortality and cardiovascular (CVD) morbidity and to determine the transition period from the acute to chronic stable phase of disease.

METHODS

Administrative claims data from a managed care database (2007-2012) were linked to the Social Security Death Index. Kaplan-Meier curves were generated over a 3-year period. The association between risk factors and clinical endpoints was assessed using Cox proportional hazard models. Poisson models estimated the 'transition time' from acute to chronic phase of disease.

RESULTS

On average, recurrent cardiovascular event rates were higher among acute MI patients in comparison to the chronic MI patients during the first 3 months of follow-up. Over the 3-year follow-up period, survival curves became parallel and for some outcomes (i.e., acute myocardial infarction and bleeding events), were not statistically significantly different between the two groups. In both the acute and chronic MI cohorts, diabetes, heart failure, and renal disease were consistently statistically significant and positively associated with greater risk of death and ischemic events. PAD was consistently associated with increased risk among the chronic cohort and composite endpoints among the acute patients.

CONCLUSIONS

Greater understanding of differences in the CVD risk profiles and the transition from acute to chronic stable phase may help identify high-risk patients and inform clinical risk stratification and long-term disease management in MI patients.

FUNDING

Merck & Co., Inc., Kenilworth, NJ, USA.