Predictors of all-cause mortality within and beyond 1 year after an acute coronary syndrome

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

Predictive role of platelet indices on hospital admission and discharge in the long-term prognosis of acute coronary syndrome: Platelets do count

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