Prognostic Impact of Nutritional Status After Transcatheter Edge-to-Edge Mitral Valve Repair: The MIVNUT Registry

Background Malnutrition is associated with poor prognosis in several cardiovascular diseases. However, its prognostic impact in patients undergoing transcatheter edge-to-edge mitral valve repair (TEER) is not well known. This study sought to assess the prevalence, clinical associations, and prognostic consequences of malnutrition in patients undergoing TEER. Methods and Results A total of 892 patients undergoing TEER from the international MIVNUT (Mitral Valve Repair and Nutritional Status) registry were studied. Malnutrition status was assessed with the Controlling Nutritional Status score. The association of nutritional status with mortality was analyzed with multivariable Cox regression models, whereas the association with heart failure admission was assessed by Fine-Gray models, with death as a competing risk. According to the Controlling Nutritional Status score, 74.4% of patients with TEER had any degree of malnutrition at the time of TEER (75.1% in patients with body mass index <25?kg/m2, 72.1% in those with body mass index ?25?kg/m2). However, only 20% had moderate-severe malnutrition. TEER was successful in most of patients (94.2%). During a median follow-up of 1.6?years (interquartile range, 0.6-3.0), 267 (29.9%) patients died and 256 patients (28.7%) were admitted for heart failure after TEER. Compared with normal nutritional status moderate-severe malnutrition resulted a strong predictor of mortality (adjusted hazard ratio [HR], 2.1 [95% CI, 1.1-2.4]; P<0.001) and heart failure admission (adjusted subdistribution HR, 1.6 [95% CI, 1.1-2.4]; P=0.015). Conclusions Malnutrition is common among patients submitted to TEER, and moderate-severe malnutrition is strongly associated with increased mortality and heart failure readmission. Assessment of nutritional status in these patients may help to improve risk stratification

Management and outcomes of patients with left atrial appendage thrombus prior to percutaneous closure

Altres ajuts: Fundación Interhospitalaria para la Investigación Cardiovascular (FIC Foundation); Abbott.Objective: Left atrial appendage (LAA) thrombus has heretofore been considered a contraindication to percutaneous LAA closure (LAAC). Data regarding its management are very limited. The aim of this study was to analyse the medical and invasive treatment of patients referred for LAAC in the presence of LAA thrombus. Methods: This multicentre observational registry included 126 consecutive patients referred for LAAC with LAA thrombus on preprocedural imaging. Treatment strategies included intensification of antithrombotic therapy (IAT) or direct LAAC. The primary and secondary endpoints were a composite of bleeding, stroke and death at 18 months, and procedural success, respectively. Results: IAT was the preferred strategy in 57.9% of patients, with total thrombus resolution observed in 60.3% and 75.3% after initial and subsequent IAT, respectively. Bleeding complications and stroke during IAT occurred in 9.6% and 2.9%, respectively, compared with 3.8% bleeding and no embolic events in the direct LAAC group before the procedure. Procedural success was 90.5% (96.2% vs 86.3% in direct LAAC and IAT group, respectively, p=0.072), without cases of in-hospital thromboembolic complications. The primary endpoint occurred in 29.3% and device-related thrombosis was found in 12.8%, without significant difference according to treatment strategy. Bleeding complications at 18 months occurred in 22.5% vs 10.5% in the IAT and direct LAAC group, respectively (p=0.102). Conclusion: In the presence of LAA thrombus, IAT was the initial management strategy in half of our cohort, with initial thrombus resolution in 60% of these, but with a relatively high bleeding rate (∼10%). Direct LAAC was feasible, with high procedural success and absence of periprocedural embolic complications. However, a high rate of device-related thrombosis was detected during follow-up

Management and outcomes of patients with left atrial appendage thrombus prior to percutaneous closure.

Left atrial appendage (LAA) thrombus has heretofore been considered a contraindication to percutaneous LAA closure (LAAC). Data regarding its management are very limited. The aim of this study was to analyse the medical and invasive treatment of patients referred for LAAC in the presence of LAA thrombus. This multicentre observational registry included 126 consecutive patients referred for LAAC with LAA thrombus on preprocedural imaging. Treatment strategies included intensification of antithrombotic therapy (IAT) or direct LAAC. The primary and secondary endpoints were a composite of bleeding, stroke and death at 18 months, and procedural success, respectively. IAT was the preferred strategy in 57.9% of patients, with total thrombus resolution observed in 60.3% and 75.3% after initial and subsequent IAT, respectively. Bleeding complications and stroke during IAT occurred in 9.6% and 2.9%, respectively, compared with 3.8% bleeding and no embolic events in the direct LAAC group before the procedure. Procedural success was 90.5% (96.2% vs 86.3% in direct LAAC and IAT group, respectively, p=0.072), without cases of in-hospital thromboembolic complications. The primary endpoint occurred in 29.3% and device-related thrombosis was found in 12.8%, without significant difference according to treatment strategy. Bleeding complications at 18 months occurred in 22.5% vs 10.5% in the IAT and direct LAAC group, respectively (p=0.102). In the presence of LAA thrombus, IAT was the initial management strategy in half of our cohort, with initial thrombus resolution in 60% of these, but with a relatively high bleeding rate (~10%). Direct LAAC was feasible, with high procedural success and absence of periprocedural embolic complications. However, a high rate of device-related thrombosis was detected during follow-up

Impacto del bloqueo del sistema renina-angiotensina en el pronóstico del síndrome coronario agudo en función de la fracción de eyección

Introduction and objectives: For patients with acute coronary syndrome (ACS) treated with percutaneous coronary intervention (PCI), it is unclear whether angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB) are associated with reduced mortality, particularly with preserved left ventricular ejection fraction (LVEF). The goal of this study was to determine the association between ACEI/ARB and mortality in ACS patients undergoing PCI, with and without reduced LVEF. Methods: Data from the BleeMACS registry were used. The endpoint was 1-year all-cause mortality. The prognostic value of ACEI/ARB was tested after weighting by survival-time inverse probability and after adjustment by Cox regression, propensity score, and instrumental variable analysis. Results: Among 15 401 ACS patients who underwent PCI, ACEI/ARB were prescribed in 75.2%. There were 569 deaths (3.7%) during the first year after hospital discharge. After multivariable adjustment, ACEI/ARB were associated with lower 1-year mortality, ≤ 40% (HR, 0.62; 95%CI, 0.43-0.90; P =.012). The relative risk reduction of ACEI/ARB in mortality was 46.1% in patients with LVEF ≤ 40%, and 15.7% in patients with LVEF > 40% (P value for treatment-by-LVEF interaction =.008). For patients with LVEF > 40%, ACEI/ARB was associated with lower mortality only in ST-segment elevation myocardial infarction (HR, 0.44; 95%CI, 0.21-0.93; P =.031). Conclusion: The benefit of ACEI/ARB in decreasing mortality after an ACS in patients undergoing PCI is concentrated in patients with LVEF ≤ 40%, and in those with LVEF > 40% and ST-segment elevation myocardial infarction. In non–ST-segment elevation-ACS patients with LVEF > 40%, further studies are needed to assess the prognostic impact of ACEI/ARB

P2Y12 inhibitors in acute coronary syndrome patients with renal dysfunction: an analysis from the RENAMI and BleeMACS projects

AIMS: The aim of the present study was to establish the safety and efficacy profile of prasugrel and ticagrelor in real-life acute coronary syndrome (ACS) patients with renal dysfunction. METHODS AND RESULTS: All consecutive patients from RENAMI (REgistry of New Antiplatelets in patients with Myocardial Infarction) and BLEEMACS (Bleeding complications in a Multicenter registry of patients discharged with diagnosis of Acute Coronary Syndrome) registries were stratified according to estimated glomerular filtration rate (eGFR) lower or greater than 60 mL/min/1.73 m2. Death and myocardial infarction (MI) were the primary efficacy endpoints. Major bleedings (MBs), defined as Bleeding Academic Research Consortium bleeding types 3 to 5, constituted the safety endpoint. A total of 19 255 patients were enrolled. Mean age was 63 ± 12; 14 892 (77.3%) were males. A total of 2490 (12.9%) patients had chronic kidney disease (CKD), defined as eGFR <60 mL/min/1.73 m2. Mean follow-up was 13 ± 5 months. Mortality was significantly higher in CKD patients (9.4% vs. 2.6%, P < 0.0001), as well as the incidence of reinfarction (5.8% vs. 2.9%, P < 0.0001) and MB (5.7% vs. 3%, P < 0.0001). At Cox multivariable analysis, potent P2Y12 inhibitors significantly reduced the mortality rate [hazard ratio (HR) 0.82, 95% confidence interval (CI) 0.54-0.96; P = 0.006] and the risk of reinfarction (HR 0.53, 95% CI 0.30-0.95; P = 0.033) in CKD patients as compared to clopidogrel. The reduction of risk of reinfarction was confirmed in patients with preserved renal function. Potent P2Y12 inhibitors did not increase the risk of MB in CKD patients (HR 1.00, 95% CI 0.59-1.68; P = 0.985). CONCLUSION: In ACS patients with CKD, prasugrel and ticagrelor are associated with lower risk of death and recurrent MI without increasing the risk of MB

Impact of renin-angiotensin system blockade on the prognosis of acute coronary syndrome based on left ventricular ejection fraction

INTRODUCTION AND OBJECTIVES: For patients with acute coronary syndrome (ACS) treated with percutaneous coronary intervention (PCI), it is unclear whether angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB) are associated with reduced mortality, particularly with preserved left ventricular ejection fraction (LVEF). The goal of this study was to determine the association between ACEI/ARB and mortality in ACS patients undergoing PCI, with and without reduced LVEF. METHODS: Data from the BleeMACS registry were used. The endpoint was 1-year all-cause mortality. The prognostic value of ACEI/ARB was tested after weighting by survival-time inverse probability and after adjustment by Cox regression, propensity score, and instrumental variable analysis. RESULTS: Among 15 401 ACS patients who underwent PCI, ACEI/ARB were prescribed in 75.2%. There were 569 deaths (3.7%) during the first year after hospital discharge. After multivariable adjustment, ACEI/ARB were associated with lower 1-year mortality, ≤ 40% (HR, 0.62; 95%CI, 0.43-0.90; P=.012). The relative risk reduction of ACEI/ARB in mortality was 46.1% in patients with LVEF ≤ 40%, and 15.7% in patients with LVEF> 40% (P value for treatment-by-LVEF interaction=.008). For patients with LVEF> 40%, ACEI/ARB was associated with lower mortality only in ST-segment elevation myocardial infarction (HR, 0.44; 95%CI, 0.21-0.93; P=.031). CONCLUSION: The benefit of ACEI/ARB in decreasing mortality after an ACS in patients undergoing PCI is concentrated in patients with LVEF ≤ 40%, and in those with LVEF> 40% and ST-segment elevation myocardial infarction. In non-ST-segment elevation-ACS patients with LVEF> 40%, further studies are needed to assess the prognostic impact of ACEI/ARB

Efficacy and Safety of Clopidogrel, Prasugrel and Ticagrelor in ACS Patients Treated with PCI: A Propensity Score Analysis of the RENAMI and BleeMACS Registries

Introduction: Real-life data comparing clopidogrel, prasugrel, and ticagrelor for unselected patients undergoing percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS) are lacking, as are data for the temporal distribution of ischemic and bleeding risks. Methods: A total of 19,825 patients were enrolled from the RENAMI and BleeMACS registries. Both were multicenter, retrospective, observational registries including the data and outcomes of consecutive patients with ACS who underwent primary PCI and were discharged with dual antiplatelet therapy (DAPT). We evaluated the long-term outcome stratified by the different antiplatelet agents. Results: A total of 14,105 patients (71.2%) were treated with clopidogrel, 2364 patients (11.9%) with prasugrel and 3356 patients (16.9%) with ticagrelor. After propensity score matching, at 1 year, prasugrel reduced the incidence of net adverse clinical events (NACE; a composite endpoint of all-cause death, myocardial infarction [MI] and Bleeding Academic Research Consortium [BARC] 3–5 bleeding) (4.2% vs.7.6%, p = 0.002) and of major adverse cardiovascular events (MACE; a composite endpoint of death and MI) compared with clopidogrel (2.6% vs. 5.2%, p = 0.007). Ticagrelor decreased rates of MACE compared with clopidogrel (2.7% vs. 6.2%, p < 0.001), but not of NACE (6.6% vs. 8.7%, p = 0.07). Ticagrelor presented similar performance in terms of MACE compared with prasugrel (2.8% vs. 2.4%, p = 0.56), with a trend towards a reduction in MI (0.2% vs. 0.4%, p = 0.56), but with higher risk of BARC 3–5 bleedings (3.8% vs. 1.7%, p = 0.04). In the daily risk analysis, clopidogrel presented a binomial distribution with a peak of ischemic risk at 3 months, which decreased towards bleedings; prasugrel had a constant equivalence between opposite risks; and ticagrelor constantly reduced recurrent MIs despite higher risk of BARC 3–5 events. Conclusion: In real life, ticagrelor is more effective in reducing ischemic events during the first year after ACS, despite an increased risk of major bleedings, while prasugrel assures a better balance between ischemic and bleeding recurrent events

Development and external validation of a post-discharge bleeding risk score in patients with acute coronary syndrome: The BleeMACS score

Background: Accurate 1-year bleeding risk estimation after hospital discharge for acute coronary syndrome(ACS) may help clinicians guide the type and duration of antithrombotic therapy. Currently there are no predictive models for this purpose. The aim of this study was to derive and validate a simple clinical tool for bedside risk estimation of 1-year post-discharge serious bleeding in ACS patients. Methods: The risk score was derived and internally validated in the BleeMACS (Bleeding complications in a Multicenter registry of patients discharged with diagnosis of Acute Coronary Syndrome) registry, an observational international registry involving 15,401 patients surviving admission for ACS and undergoing percutaneous coronary intervention (PCI) from 2003 to 2014, engaging 15 hospitals from 10 countries located in America, Europe and Asia. External validation was conducted in the SWEDEHEART population, with 96,239 ACS patients underwent PCI and 93,150 without PCI. Results: Seven independent predictors of bleeding were identified and included in the BleeMACS score: age, hypertension, vascular disease, history of bleeding, malignancy, creatinine and hemoglobin. The BleeMACS risk score exhibited a C-statistic value of 0.71 (95% CI 0.68-0.74) in the derivation cohort and 0.72 (95% CI 0.67-0.76) in the internal validation sample. In the SWEDEHEART external validation cohort, the C-statistic was 0.65 (95% CI 0.64-0.66) for PCI patients and 0.63 (95% CI 0.62-0.64) for non-PCI patients. The calibration was excellent in the derivation and validation cohorts. Conclusions: The BleeMACS bleeding risk score is a simple tool useful for identifying those ACS patients at higher risk of serious 1-year post-discharge bleeding. (c) 2017 Elsevier B.V. All rights reserve

Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets

Background: The accuracy of current prediction tools for ischaemic and bleeding events after an acute coronary syndrome (ACS) remains insufficient for individualised patient management strategies. We developed a machine learning-based risk stratification model to predict all-cause death, recurrent acute myocardial infarction, and major bleeding after ACS. Methods: Different machine learning models for the prediction of 1-year post-discharge all-cause death, myocardial infarction, and major bleeding (defined as Bleeding Academic Research Consortium type 3 or 5) were trained on a cohort of 19 826 adult patients with ACS (split into a training cohort [80%] and internal validation cohort [20%]) from the BleeMACS and RENAMI registries, which included patients across several continents. 25 clinical features routinely assessed at discharge were used to inform the models. The best-performing model for each study outcome (the PRAISE score) was tested in an external validation cohort of 3444 patients with ACS pooled from a randomised controlled trial and three prospective registries. Model performance was assessed according to a range of learning metrics including area under the receiver operating characteristic curve (AUC). Findings: The PRAISE score showed an AUC of 0\ub782 (95% CI 0\ub778\u20130\ub785) in the internal validation cohort and 0\ub792 (0\ub790\u20130\ub793) in the external validation cohort for 1-year all-cause death; an AUC of 0\ub774 (0\ub770\u20130\ub778) in the internal validation cohort and 0\ub781 (0\ub776\u20130\ub785) in the external validation cohort for 1-year myocardial infarction; and an AUC of 0\ub770 (0\ub766\u20130\ub775) in the internal validation cohort and 0\ub786 (0\ub782\u20130\ub789) in the external validation cohort for 1-year major bleeding. Interpretation: A machine learning-based approach for the identification of predictors of events after an ACS is feasible and effective. The PRAISE score showed accurate discriminative capabilities for the prediction of all-cause death, myocardial infarction, and major bleeding, and might be useful to guide clinical decision making. Funding: None

Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets

Background The accuracy of current prediction tools for ischaemic and bleeding events after an acute coronary syndrome (ACS) remains insufficient for individualised patient management strategies. We developed a machine learning-based risk stratification model to predict all-cause death, recurrent acute myocardial infarction, and major bleeding after ACS.Methods Different machine learning models for the prediction of 1-year post-discharge all-cause death, myocardial infarction, and major bleeding (defined as Bleeding Academic Research Consortium type 3 or 5) were trained on a cohort of 19 826 adult patients with ACS (split into a training cohort [80%] and internal validation cohort [20%]) from the BleeMACS and RENAMI registries, which included patients across several continents. 25 clinical features routinely assessed at discharge were used to inform the models. The best-performing model for each study outcome (the PRAISE score) was tested in an external validation cohort of 3444 patients with ACS pooled from a randomised controlled trial and three prospective registries. Model performance was assessed according to a range of learning metrics including area under the receiver operating characteristic curve (AUC).Findings The PRAISE score showed an AUC of 0.82 (95% CI 0.78-0.85) in the internal validation cohort and 0.92 (0.90-0.93) in the external validation cohort for 1-year all-cause death; an AUC of 0.74 (0.70-0.78) in the internal validation cohort and 0.81 (0.76-0.85) in the external validation cohort for 1-year myocardial infarction; and an AUC of 0.70 (0.66-0.75) in the internal validation cohort and 0.86 (0.82-0.89) in the external validation cohort for 1-year major bleeding.Interpretation A machine learning-based approach for the identification of predictors of events after an ACS is feasible and effective. The PRAISE score showed accurate discriminative capabilities for the prediction of all-cause death, myocardial infarction, and major bleeding, and might be useful to guide clinical decision making. Copyright (C) 2021 Elsevier Ltd. All rights reserved