Background: Superiority of potent P2Y12 inhibitors over clopidogrel after an acute coronary syndrome (ACS) has been well established, however potent P2Y12 inhibition is responsible for more adverse events, which may influence patient adherence to treatment. Aim of the present study is to investigate the adherence to the prescribed P2Y12 inhibitor (P2Y12i) in patients on dual antiplatelet therapy (DAPT) after an ACS. Methods: In an IDEAL-LDL trial substudy, we included 344 patients after ACS discharged on DAPT. The primary outcome was the difference between potent P2Y12i and clopidogrel in terms of adherence, as well as other predictors of adherence to the antiplatelet regimen. Secondary outcomes included the prevalence of DAPT continuation and its predictors and the antiplatelet regimen selection after DAPT. Results: Adherence to the potent P2Y12i and to clopidogrel was observed in 140/178 (78.7%) and 111/166 (66.9%) patients (p = 0.016), respectively. In the multivariate model, after adjustment for P2Y12i switching during the first year of therapy, there was no difference observed in adherence between potent P2Y12i and clopidogrel (odds ratio [OR] = 0.98, 95% confidence interval [CI] = 0.55-1.74). Significant predictors included history of cardiovascular disease (CVD) (OR = 0.51, 95% CI = 0.31-0.86) and percutaneous coronary intervention (PCI) index event treatment (OR = 2.58, 95% CI = 1.38-4.82). Of patients, 72% continued DAPT >12 months and female gender was a negative predictor of DAPT prolongation (adjusted OR = 0.43, 95% CI = 0.21-0.90). DAPT was continued until the end of follow-up in 42.7%, while 54.6% resumed with single antiplatelet regimen. Conclusions: Adherence to DAPT was not affected by the P2Y12i potency, whereas history of CVD and PCI treatment were associated with reduced and increased adherence, respectively. Clinical Trial Registration: NCT02927808, https://clinicaltrials.gov/ct2/show/NCT02927808.

Our study aimed to investigate the association between platelet indices and their in-hospital change and long-term prognosis in acute coronary syndrome (ACS). Data from a randomized controlled trial (NCT02927808) recruiting ACS patients were analyzed (survival analysis). The examined variables were platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) on admission and discharge, as well as their alteration during hospitalization. The primary endpoint was major adverse cardiac events (MACE) (cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke or hospitalization for unstable angina) and all-cause mortality, while secondary endpoints were all-cause hospitalization and bleeding events. The study included 252 patients with a follow-up of 39 (28–45) months. In the univariate analysis, MACE was associated with discharge PC [hazard ratio (HR) 2.20, 95% confidence interval (CI) 1.10–4.40], discharge MPV (HR 0.48, 95% CI 0.25–0.94), and in-hospital PC difference (HR 0.25, 95% CI 0.13–0.51). In the multivariable analysis, only in-hospital PC decrease correlated with lower MACE incidence (adjusted HR .27, 95% CI 0.14–0.54) and lower all-cause hospitalization risk (adjusted HR 0.36, 95% CI 0.19–0.68). PC reduction during hospitalization for ACS is an independent predictor of better prognosis.

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Funding Acknowledgements Type of funding sources: None. Background/Introduction: Previous clinical studies have underlined the prognostic role of platelet indices in acute coronary syndrome (ACS). However, the effect of their dynamic change during hospitalization has not thoroughly been examined. Purpose: We aimed to investigate the association between platelet indices on admission, on discharge and their change during hospitalization and the long-term prognosis of patients with ACS. Methods: Data from a randomized controlled trial recruiting ACS patients were analyzed in a survival analysis. Platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (PCT) on admission and on discharge dichotomized at the median value, as well as the change between admission and discharge of each variable dichotomized at the zero value. Primary endpoints were major adverse cardiac events (MACE), defined as occurrence of cardiovascular death, non-fatal myocardial infarction, non-fatal stroke or hospitalization for unstable angina, while secondary endpoints were all-cause mortality, all-cause hospitalization and major or minor bleeding events. Results: The study included 252 individuals who were followed-up for a median of 39 months. In the univariate Cox regression analysis, only PC at discharge (HR 2.20, 95% CI 1.10-4.40), MPV at discharge (HR 0.48, 95% CI 0.25-0.94) and PC reduction during the hospitalization (HR 0.25, 95% CI 0.13-0.51) predicted MACE. PC reduction correlated with a lower MACE occurrence (adjusted HR 0.27, 95%CI 0.14-0.54) and lower risk of all-cause hospitalization (adjusted HR 0.36, 95%CI 0.19-0.68) in the multivariable Cox-regression analysis. Conclusion: PC change during hospitalization can be a substantial independent predictor of long-term prognosis of ACS patients. Baseline and admission characteristics Characteristic Statistic Overall, N = 252 Negative Platelet Difference, N = 98 Postive Platelet Difference, N = 154 p-value Age, years median (IQR) 60 (53, 72) 62 (55, 74) 60 (53, 72) 0.2 Hypertension n(%) 147(58.3%) 58(59.2%) 89(57.8%) >0.9 Diabetes n(%) 71(28.2%) 27(27.6%) 44(28.6%) >0.9 Cardiovascualr Disease (CVD) n(%) 100(39.7%) 43(43.9%) 57(37.0%) 0.3 Primary Coronary Intervention (PCI) treatment n(%) 200(79.4%) 71(72.4%) 129(83.8%) 0.045 Number of vessels n 0.6 1 n(%) 107(59.1%) 38(59.4%) 69(59.0%) ≥2 n(%) 68(37.6%) 25(39.1%) 43(36.8%) Platelets at admission, K/μL mean(SD) 257179(71031) 237020(62555) 270006(73282) 0.001 Platelets at dischage, K/μL mean(SD) 250952(70263) 279153(75159) 233006(60698) <0.001 Abstract Figure. MACE univariate / multivariate analysis

Funding Acknowledgements Type of funding sources: None. Background Patients discharged after an acute coronary syndrome (ACS) have substantial mortality risk, especially during the first year. Purpose To determine differences between first year and long-term all-cause mortality of patients after an ACS and identify its risk predictors. Methods This is a post-hoc analysis of the baseline data from 360 patients after ACS with a median follow up 3.2 years (IQR: 2.5-3.8) that enrolled in a prospective randomized controlled trial. Mortality rates with 95% confidence intervals (CIs) were estimated by Kaplan–Meier method. Multivariate Cox proportional hazards regression analyses of clinical parameters and cardiac biomarkers were performed to identify predictors for all-cause mortality within first year and thereafter. Results In our cohort, all-cause mortality incidence per 100 person-years at risk within and after first year was 4.9 and 2.1, respectively (RR = 2.3, p < 0.001). Notably, 83% of the deaths during the first year were attributed to any cardiovascular cause, dropped to 50% after the first year. Baseline NT-proBNP value and prior myocardial infarction were the main independent predictors of all-cause mortality for both first year and beyond time periods (Table 1). Οn the contrary, severe chronic kidney disease lost predictive power after 1 year. Conclusion We observed higher all-cause mortality rate during the first year, mainly driven by cardiovascular death. History of myocardial infarction and baseline NT-proBNP levels outperformed any other clinical variable or biomarker for long-term all-cause mortality in  post-ACS patients. Predictors of long-term all-cause death Variables Univariate analysis Multivariate analysis HR (95% CI) P-value HR (95% CI) P-value Age per 1-year increase 1.06 (1.03 - 1.10) <0.001 1.02 (0.99 - 1.06) 0.11 Female 1.07 (0.79 - 3.71) 0.17 HTN 2.52 (1.14 - 5.63) 0.02 Diabetes 2.06 (1.03 - 4.15) 0.04 CKD IV or V 9.01 (3.89 - 20.86) <0.001 0.88 (0.26 - 2.95) 0.83 History of MI 0.55 (0.26 - 1.17) 0.001 3.28 (1.05 - 7.17) 0.002 HFrEF 1.25 (0.51 - 3.04) 0.62 Family history of CAD 0.55 (0.26 - 1.17) 0.12 NT-proBNP* 1.92 (1.46 - 2.51) <0.001 1.70 (1.22 - 2.36) 0.001 hs-cTnT* 1.15 (0.91 - 1.44) 0.27 LDL-C 0.99 (0.98 - 1.00) 0.22 *Natural logarithms Abstract Figure. Kaplan-Meier for all-cause mortality