Meta-Analysis of Bleeding Risk Prediction Scores in Patients After Percutaneous Coronary Intervention on Dual Antiplatelet Therapy

Risk Scores of Bleeding Complications in Patients on Dual Antiplatelet Therapy: How to Optimize Identification of Patients at Risk of Bleeding after Percutaneous Coronary Intervention

Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 receptor inhibitor in patients undergoing percutaneous coronary intervention (PCI) reduces the risk of ischemic events but reduces the risk of ischemic events but increases the risk of bleeding, which in turn is associated with increased morbidity and mortality. With the aim to offer personalized treatment regimens to patients undergoing PCI, much effort has been devoted in the last decade to improve the identification of patients at increased risk of bleeding complications. Several clinical scores have been developed and validated in large populations of patients with coronary artery disease (CAD) and are currently recommended by guidelines to evaluate bleeding risk and individualize the type and duration of antithrombotic therapy after PCI. In clinical practice, these risk scores are conventionally computed at the time of PCI using baseline features and risk factors. Yet, bleeding risk is dynamic and can change over time after PCI, since patients can worsen or improve their clinical status and accumulate comorbidities. Indeed, evidence now exists that the estimated risk of bleeding after PCI can change over time. This concept is relevant, as the inappropriate estimation of bleeding risk, either at the time of revascularization or subsequent follow-up visits, might lead to erroneous therapeutic management. Serial evaluation and recalculation of bleeding risk scores during follow-up can be important in clinical practice to improve the identification of patients at higher risk of bleeding while on DAPT after PCI.

Validation of the academic research consortium high bleeding risk criteria in patients undergoing percutaneous coronary intervention: A systematic review and meta-analysis of 10 studies and 67,862 patients

BACKGROUND

To assess the performance of the Academic Research Consortium High Bleeding Risk (ARC-HBR) criteria in stratifying the risk of bleeding and ischaemic events after percutaneous coronary intervention (PCI).

METHODS

MEDLINE, COCHRANE, Web of Sciences, and SCOPUS were searched for studies aimed at validating the ARC-HBR criteria in patients treated with PCI. The primary outcome measure of this meta-analysis was major bleeding.

RESULTS

The analysis included 10 studies encompassing 67,862 patients undergoing PCI; the HBR definition was fulfilled in 44.7% of the cases. The risk of major bleeding was significantly higher in HBR vs. Non-HBR group (RR, 2.56, 95% CI 2.28-2.89). The average C-statistic was 0.64 (95% CI 0.60-0.68), indicating modest discrimination. The risk of intracranial hemorrhage, gastrointestinal bleeding, fatal bleeding, ischaemic stroke, cardiac death and all-cause death was higher in HBR vs. Non-HBR group. Despite a higher incidence of myocardial infarction and stent thrombosis in patients deemed at HBR, the rate of target lesion revascularization was comparable between groups (RR, 1.01, 95% CI 0.88-1.16). The mean effect size for the cumulative incidence of major bleeding exceeded the HBR cut-off value of 4% for all major criteria except one, and for two out of six minor criteria, namely age ≥ 75 years and moderate CKD.

CONCLUSION

The ARC-HBR definition identifies patients at higher risk of major bleeding and other adverse cardiovascular events after PCI. Almost all major criteria, but also two of the minor criteria, were individually associated with rates of major bleeding above 4% thus fulfilling the definition of major HBR criteria.

Risk Assessment Using Risk Scores in Patients with Acute Coronary Syndrome

Risk scores are widely used in patients with acute coronary syndrome (ACS) prior to treatment decision-making at different points in time. At initial hospital presentation, risk scores are used to assess the risk for developing major adverse cardiac events (MACE) and can guide clinicians in either discharging the patients at low risk or swiftly admitting and treating the patients at high risk for MACE. During hospital admission, risk assessment is performed to estimate mortality, residual ischemic and bleeding risk to guide further in-hospital management (e.g., timing of coronary angiography) and post-discharge management (e.g., duration of dual antiplatelet therapy). In the months and years following ACS, long term risk can also be assessed to evaluate current treatment strategies (e.g., intensify or reduce pharmaceutical treatment options). As multiple risk scores have been developed over the last decades, this review summarizes the most relevant risk scores used in ACS patients.

Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation

Background

Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences.

Objective

The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding.

Methods

We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA).

Results

In-hospital bleeding occurred in 112 of 4262 participants (2.6%) in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital bleeding in age (odds ratio [OR] 1.047, 95% CI 1.029-1.066; P<.001), Killip III (OR 3.265, 95% CI 2.008-5.31; P<.001), and Killip IV (OR 5.133, 95% CI 3.196-8.242; P<.001). We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was 0.777 (SD 0.021, 95% CI 0.73576-0.81823). We constructed a nomogram based on age and Killip classification. In-hospital bleeding occurred in 117 of 6015 participants (1.9%) in the validation data set. The AUC was 0.7234 (SD 0.0252, 95% CI 0.67392-0.77289).

Conclusions

We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory.

Trial Registration

ChiCTR.org ChiCTR1900027578; http://www.chictr.org.cn/showprojen.aspx?proj=45926

Utility of the HAS-BLED score for risk stratification of patients with acute coronary syndrome

HAS-BLED score was developed for bleeding prediction in patients with atrial fibrillation (AF). Recently, it was also used in patients undergoing percutaneous coronary interventions (PCI). This study analyzes the HAS-BLED predictivity for bleedings and mortality in patients with acute coronary syndromes (ACS) without AF, and evaluates the utilization of alternative criteria for renal dysfunction. The study population was composed of 704 patients with ACS. Six-hundred and eleven patients completed the follow-up. The HAS-BLED score was calculated both using the original definition of renal dysfunction, both using three alternative eGFR thresholds (< 30, < 60 and ≤ 90 ml/min/1.73 mq). In-hospital and post-discharge bleedings and mortality were recorded, and calibration and discrimination of the various risk models were evaluated using the Hosmer-Lemeshow test and the C-statistic. In-hospital bleedings were 4.7% and mortality was 2.7%. Post-discharge bleedings were 3.1% and mortality was 4.4%. Regarding bleeding events and in-hospital mortality, the HAS-BLED original risk model demonstrated a moderate-to-good discriminative performance (C-statistics from 0.65 to 0.76). No significant differences were found in predictive accuracy when applying alternative definitions of renal dysfunction based on eGFR, with the exception of post-discharge mortality, for which HAS-BLED model assuming an eGFR value < 60 ml/min/1.73 mq showed a discriminative performance significantly higher in comparison to the other risk models (C-statistic 0.71 versus 0.64-0.66). In conclusion, in our ACS population, the HAS-BLED risk score showed a fairly good predictive accuracy regarding in-hospital and follow-up bleeding events and in-hospital mortality. The use of renal dysfunction alternative criteria based on eGFR values resulted in out-of hospital mortality predictive accuracy enhancement.

Ticagrelor Versus Prasugrel for the Treatment of Patients with Type 2 Diabetes Mellitus Following Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis

INTRODUCTION

Antiplatelet therapy is very important following percutaneous coronary intervention (PCI). New generation P2Y₁₂ inhibitors (ticagrelor and prasugrel) might potentially replace clopidogrel for the treatment of post-interventional acute coronary syndrome (ACS). In this analysis, we aimed to systematically compare the post-interventional clinical outcomes and bleeding events observed with ticagrelor versus prasugrel in patients with type 2 diabetes mellitus (T2DM).

METHODS

EMBASE, MEDLINE, the Cochrane Central Register of Controlled Trials, and www.ClinicalTrials.gov were carefully searched for publications comparing the post-coronary interventional outcomes following ticagrelor versus prasugrel use in patients with T2DM. Adverse clinical outcomes and bleeding events were considered as the endpoints. Statistical analysis was carried out by the Revman software (version 5.3). Odds ratios (OR) and 95% confidence intervals (CI) were used to represent the data during subgroup analysis.

RESULTS

A total of 2004 participants with T2DM were included in this analysis. Following PCI, mortality (OR 1.00, 95% CI 0.57-1.76; P = 0.99, I² = 19%), myocardial infarction (OR 0.86, 95% CI 0.42-1.75; P = 0.67, I² = 0%), major adverse cardiac events (OR 0.73, 95% CI 0.42-1.27; P = 0.27, I² = 0%), and stroke (OR 0.72, 95% CI 0.20-2.59; P = 0.61, I² = 0%) were not significantly different between ticagrelor and prasugrel. In addition, total bleeding events (OR 0.87, 95% CI 0.55-1.40; P = 0.58, I² = 6%), Thrombolysis in Myocardial Infarction (TIMI) defined minor bleeding (OR 2.39, 95% CI 0.58-9.91; P = 0.23, I² = 0%), TIMI defined major bleeding (OR 1.42, 95% CI 0.27-7.45; P = 0.68, I² = 0%), bleeding defined according to the Bleeding Academic Research Consortium (BARC) major bleeding (OR 0.55, 95% CI 0.22-1.36; P = 0.20, I² = 0%), BARC minor bleeding (OR 1.44, 95% CI 0.52-3.99; P = 0.48, I² = 0%), and total minimal bleeding (OR 3.12, 95% CI 0.55-17.59; P = 0.20, I² = 0%) were also not significantly different.

CONCLUSION

Ticagrelor and prasugrel were not associated with significantly different adverse clinical outcomes and bleeding events in these patients with T2DM. Therefore, both antiplatelet agents might safely be used in patients with T2DM following coronary intervention. However, this head-to-head comparison still remains a major challenge which should be resolved in larger clinical trials.