Background Long‐term antithrombotic strategies for patients with chronic coronary syndrome with high‐risk factors represent an important treatment dilemma in clinical practice. Our aim was to conduct a network meta‐analysis to evaluate the efficacy and safety of long‐term antithrombotic strategies in patients with chronic coronary syndrome. Methods and Results Four randomized studies were included (n=75167; THEMIS [Ticagrelor on Health Outcomes in Diabetes Mellitus Patients Intervention Study], COMPASS [Cardiovascular Outcomes for People Using Anticoagulation Strategies], PEGASUS‐TIMI 54 [Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin–Thrombolysis in Myocardial Infarction 54], and DAPT [Dual Anti‐platelet Therapy]). The odds ratios (ORs) and 95% CIs) were calculated as the measure of effect size. The results of the network meta‐analysis showed that, compared with aspirin monotherapy, the ORs for trial‐defined major adverse cardiovascular and cerebrovascular events were 0.86; (95% CI, 0.80–0.93) for ticagrelor plus aspirin, 0.89 (95% CI, 0.78–1.02) for rivaroxaban monotherapy, 0.74 (95% CI, 0.64–0.85) for rivaroxaban plus aspirin, and 0.72 (95% CI, 0.60,–0.86) for thienopyridine plus aspirin. Compared with aspirin monotherapy, the ORs for trial‐defined major bleeding were 2.15 (95% CI, 1.78–2.59]) for ticagrelor plus aspirin, 1.51 (95% CI, 1.23–1.85) for rivaroxaban monotherapy, and 1.68 (95% CI, 1.37–2.05) for rivaroxaban plus aspirin. For death from any cause, the improvement effect of rivaroxaban plus aspirin was detected versus aspirin monotherapy (OR, 0.76; 95% CI, 0.65–0.90), ticagrelor plus aspirin (OR, 0.79; 95% CI, 0.66–0.95), rivaroxaban monotherapy (OR, 0.82; 95% CI, 0.69–0.97), and thienopyridine plus aspirin (OR, 0.58; 95% CI, 0.41–0.82) regimens. Conclusions All antithrombotic strategies combined with aspirin significantly reduced the incidence of major adverse cardiovascular and cerebrovascular events and increased the risk of major bleeding compared with aspirin monotherapy. Considering the outcomes of all ischemic and bleeding events and all‐cause mortality, rivaroxaban plus aspirin appears to be the preferred long‐term antithrombotic regimen for patients with chronic coronary syndrome and high‐risk factors.

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Purpose: The goal of this study was to evaluate the predictive ability of the inflammation-based Glasgow Prognostic Score (GPS), platelet-lymphocyte ratio (PLR), Global Registry of Acute Coronary Events (GRACE) score and combined diagnostic models for the occurrence of major adverse cardiovascular and cerebrovascular events (MACEs) in patients with acute myocardial infarction (AMI). Methods: In this retrospective cohort study, eligible patients were required to meet the third global definition of myocardial infarction. The primary outcome of this study was the occurrence of MACEs during hospitalization. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive ability of the GPS, PLR, GRACE scores, and joint diagnostic models for primary outcomes; univariate and multivariate logistic regression analyses were performed. Findings: A total of 175 patients were enrolled. The results of the univariate ROC curve analysis for the incidence of MACEs during hospitalization showed that the area under the curve (AUC) was 0.780 (95% confidence interval (CI) 0.696-0.864) for the GPS, 0.766 (95% CI 0.682-0.850) for the redefined GPS (RGPS), 0.561 (95% CI 0.458-0.664) for the PLR score (PLRS), and 0.793 (95% CI 0.706-0.880) for GRACE. Multivariate ROC curve analysis showed that the AUC value was 0.809 (95% CI 0.726-0.893) for the GPS combined with GRACE, 0.783 (95% CI 0.701-0.864) for the GPS combined with the PLRS, 0.794 (95% CI 0.707-0.880) for GRACE combined with the PLRS, and 0.841 (95% CI 0.761-0.921) for the GPS combined with GRACE and the PLRS. The combined diagnostic model including the GPS plus GRACE and the PLRS had a higher AUC value than the GPS, RGPS and GRACE models (P = 0.014, P = 0.004, and P = 0.038, respectively). The multivariate logistic regression model showed that the odds ratio for hospitalized MACEs was 5.573 (95% CI 1.588-19.554) for GPS scores of 2 versus 0, and the GRACE score was also an independent risk factor for MACEs, with an odds ratio of 1.023 (95% CI 1.009-1.036). Implications: The diagnostic model combining the GPS plus GRACE and the PLRS has better predictive ability for the occurrence of MACEs during hospitalization than each single score. Thus, the use of a combined GPS plus GRACE and PLRS model will be of clinical benefit in a broad group of individuals with AMI.

Aim Inflammation-based Glasgow Prognostic Scores (GPS) have been reported to predict the prognosis of patients with acute ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). The goal of this study was to investigate whether three kinds of GPSs can effectively predict major cardiovascular adverse events (MACEs) in STEMI or non-ST-segment elevation myocardial infarction (NSTEMI) patients undergoing PPCI, elective PCI (EPCI) or conservative drug therapy during hospitalization. Methods In this retrospective cohort study, patients with acute myocardial infarction (AMI) were divided into 0, 1 or 2 score according to the GPSs. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of GPSs for MACE and all-cause mortality during hospitalization. Three kinds of GPSs, Inflammation-based Glasgow Prognostic Score (GPS), modified GPS (MGPS) and high-sensitivity CRP-modified GPS (HS-MGPS) and Global Registry of Acute Coronary Events (GRACE) score were applied in this study. Results A total of 188 patients were enrolled. The ROC curve with MACE showed that the AUC of GPS (0.820 (95% confidence interval (CI) [0.754–0.885]), P < 0.001) was larger than that of MGPS (0.789 (95% CI [0.715–0.863]), P < 0.001), HS-MGPS (0.787 (95% CI [0.717–0.856]), P < 0.001) and GRACE score (0.743 (95% CI [0.672–0.814]), P < 0.001). The ROC curve with all-cause mortality showed that the AUC of GPS (0.696 (95% CI [0.561–0.831]), P = 0.005) was similar to the HS-MGPS (0.698 (95% CI [0.569–0.826]), P = 0.005) and higher than the MGPS (0.668 (95% CI [0.525–0.812]), P = 0.016), but lower than the GRACE score (0.812 (95% CI [0.734–0.889]), P < 0.001). Multivariate logistic regression analysis showed that the GPS was an independent risk factor for the incidence of MACE during hospitalization. Compared with the odds ratio (OR) value for a GPS of 0, the OR for a GPS of 1 was 7.173 (95% CI [2.425–21.216]), P < 0.001), and that for a GPS of 2 was 18.636 (95% CI [5.813–59.746]), P < 0.001), but not an independent risk factor for all-cause mortality (P = 0.302). GRACE score was an independent risk factor for MACE (1.019 (95% CI [1.004–1.035]), P = 0.015) and all-cause mortality (1.040 (95% CI [1.017–1.064]), P = 0.001). In the subgroups classified according to the type of AMI, the presence of disease interference GPSs and the type of PCI, the ability of GPS to predict the occurrence of MACE seemed to be greater than that of MGPS and HS-MGPS. Conclusion The GPS has a good predictive value for the occurrence of MACE during hospitalization in patients with AMI, regardless of STEMI or NSTEMI, the choice of PCI mode and the presence or absence of diseases that interfere with GPS. However, GPS is less predictive of all-cause mortality during hospitalization than GRACE score, which may be due to the interference of patients with other diseases.

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