The presence of coexisting conditions has a substantial effect on the outcome of acute myocardial infarction. Renal failure is associated with one of the highest risks, but the influence of milder ...degrees of renal impairment is less well defined.
As part of the Valsartan in Acute Myocardial Infarction Trial (VALIANT), we identified 14,527 patients with acute myocardial infarction complicated by clinical or radiologic signs of heart failure, left ventricular dysfunction, or both, and a documented serum creatinine measurement. Patients were randomly assigned to receive captopril, valsartan, or both. The glomerular filtration rate (GFR) was estimated by means of the four-component Modification of Diet in Renal Disease equation, and the patients were grouped according to their estimated GFR. We used a 70-candidate variable model to adjust and compare overall mortality and composite cardiovascular events among four GFR groups.
The distribution of estimated GFR was wide and normally shaped, with a mean (+/-SD) value of 70+/-21 ml per minute per 1.73 m2 of body-surface area. The prevalence of coexisting risk factors, prior cardiovascular disease, and a Killip class of more than I was greatest among patients with a reduced estimated GFR (less than 45.0 ml per minute per 1.73 m2), and the use of aspirin, beta-blockers, statins, or coronary-revascularization procedures was lowest in this group. The risk of death or the composite end point of death from cardiovascular causes, reinfarction, congestive heart failure, stroke, or resuscitation after cardiac arrest increased with declining estimated GFRs. Although the rate of renal events increased with declining estimated GFRs, the adverse outcomes were predominantly cardiovascular. Below 81.0 ml per minute per 1.73 m2, each reduction of the estimated GFR by 10 units was associated with a hazard ratio for death and nonfatal cardiovascular outcomes of 1.10 (95 percent confidence interval, 1.08 to 1.12), which was independent of the treatment assignment.
Even mild renal disease, as assessed by the estimated GFR, should be considered a major risk factor for cardiovascular complications after a myocardial infarction.
Aims
Acute heart failure (AHF) has a poor prognosis. We evaluated 3- and 12-month mortality in different clinical classes of AHF patients from 30 European countries who were included in the EuroHeart ...Failure Survey (EHFS) II.
Methods and results
Follow-up data were available for 2981 AHF patients, of these 62% had a history of chronic HF. One-year mortality after discharge was lower in patients with de novo AHF when compared with acutely decompensated chronic HF (ADCHF), 16.4 vs. 23.2% (P < 0.001). Cardiogenic shock conferred the highest cumulative 1-year mortality (52.9%) as a result of in-hospital mortality of 39.3%. Long-term prognosis in decompensated AHF was also dismal. Hypertensive HF was associated with the lowest mortality (13.7% at 1 year). Age, prior myocardial infarction, creatinine level, and low plasma sodium were independently associated with mortality during the whole follow-up period. Diabetes, anaemia, and history of chronic HF were associated with worse and hypertension with better long-term survival. History of cerebrovascular disease was associated with worse short-term outcome.
Conclusion
Early and late mortality differ between de novo AHF and ADCHF and between clinical classes of AHF. EHFS II identifies clinical risk markers and demonstrates the importance of a thorough characterization of AHF populations according to history and clinical presentation.
Aims
Several studies have shown that older patients with heart failure with reduced ejection fraction (HFrEF) are undertreated. The aim of this study was to evaluate the association of up‐titration ...of angiotensin‐converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB) and beta‐blockers on outcome across the age spectrum in HFrEF patients.
Methods and results
We analysed HFrEF patients on sub‐optimal doses of ACEI/ARB and/or beta‐blockers from the BIOSTAT‐CHF study stratified by age. Patients underwent a 3‐month up‐titration period. We used inverse probability weighting to adjust for the likelihood of successful up‐titration to determine the association of achieved dose with mortality and/or heart failure hospitalisation, testing for an interaction with age. Over a median follow‐up of 21 months in 1720 HFrEF patients (76.5% male, mean age 67 years), the primary outcome occurred in 558 patients. Increased percentage of target dose of ACEI/ARB and beta‐blocker achieved at 3 months were both significantly associated with reduced incidence of the primary outcome, ACEI‐ARB: hazard ratio (HR) per 12.5% increase in dose: 0.92, 95% confidence interval (CI) 0.91–0.94, P < 0.001; beta‐blocker: HR 0.98, 95% CI 0.95–1.00, P = 0.046, with a significant interaction with age seen for beta‐blockers but not ACEI/ARB (P = 0.034 and P = 0.22, respectively).
Conclusions
Achieving higher doses of ACEI/ARB was associated with improved outcome regardless of age. However, achieving higher doses of beta‐blockers was only associated with improved outcome in younger, but not in older patients.
Identifying risk factors for specific modes of death in patients with heart failure (HF) or left ventricular (LV) dysfunction after acute myocardial infarction (MI) may help to avert events. We ...sought to evaluate LV ejection fraction (LVEF) as a prognosticator of specific death modes.
In an individual patient data meta-analysis of four merged trials (CAPRICORN, EPHESUS, OPTIMAAL, and VALIANT), Cox modelling was performed to study the association between baseline LVEF from 19,740 patients and types of death during follow-up. Over a median follow-up of 707 days 3419 deaths occurred. The distribution pattern for mode of death was similar across categories (LVEF < 25%, LVEF 25–35%, and LVEF > 35%). In multivariable models, the risk of all types of death increased with decreasing LVEF. If compared to LVEF > 35%, LVEF < 25% was associated with a 113% increased risk of sudden death (hazard ratio (HR) 2.13, 95% confidence interval (CI) 1.53–2.98), a 170% increased risk of HF death (HR 2.70, 95% CI 1.83–3.98), a 66% increased risk of other cardiovascular (CV) death (HR 1.66, 95% CI 1.14–2.42), and a 90% increased risk of non CV death (HR 1.90, 95% CI 1.15–3.14).
In patients with HF or LV dysfunction after acute MI, low LVEF is a ubiquitous risk marker associated with death regardless of type. The different modes of death are fairly equally represented throughout the categories of LVEF and sudden death remains a significant mode of death also in patients with LVEF > 35%.
•LVEF as a prognosticator of specific death modes is evaluated.•The risk of all types of death increased with decreasing LVEF.•Different modes of death are fairly equally represented throughout LVEF categories.•Sudden death remains a significant mode of death also in patients with LVEF > 35%.
Abstract Objective To investigate the impact on the apparent incidence and classification of acute myocardial infarction (AMI) after employing the ESC–ACC–AHA–WHF 2007 Universal definition of ...myocardial infarction (the 2007 definition). Setting Retrospective cohort study in a single hospital serving a geographically well-defined population. Methods and results Retrospectively, the medical records for all patients hospitalized with suspected AMI during 2004 were reviewed (915 with AMI discharge diagnosis, 1037 with elevated troponin T > 0.03 µg/L without AMI diagnosis, 948 undergoing revascularisation and 34 with sudden death possible due to AMI). After correcting for misclassification (49 overdiagnosed and 236 underdiagnosed AMI) the number of AMI according to the 2000 definition was 1102 (20.5% overall underdiagnosed). After reclassification to the 2007 definition the total number of AMI cases decreased with 9 patients mainly due to increase of the troponin decision limit for PCI related AMI (reducing the number of PCI related AMI from 111 to 69). The percentages of patients of each type according to the 2007 subclassification were spontaneous AMI (type 1) 88.5%; AMI due to myocardial oxygen deficit (type 2) 1.6%; sudden death without troponin elevation (type 3) 2.6%; PCI related AMI (type 4) 6.8%; and AMI after coronary artery bypass (type 5) 0.5%. Conclusions Employing the 2007 revision of the Universal definition of AMI did not substantially alter the apparent incidence of acute AMI substantially in our population. The level of misclassification of acute coronary syndromes after introduction of the 2007 definition may depend on the clinical acceptance of AMI subgrouping.
Abstract Accessibility to the available traditional forms of cardiac rehabilitation programmes in heart failure patients is not adequate and adherence to the programmes remains unsatisfactory. The ...home-based telerehabilitation model has been proposed as a promising new option to improve this situation. This paper's aims are to discuss the tools available for telemonitoring, and describing their characteristics, applicability, and effectiveness in providing optimal long term management for heart failure patients who are unable to attend traditional cardiac rehabilitation programmes. The critical issues of psychological support and adherence to the telerehabilitation programmes are outlined. The advantages and limitations of this long term management modality are presented and compared with alternatives. Finally, the importance of further research, multicentre studies of telerehabilitation for heart failure patients and the technological development needs are outlined, in particular interactive remotely controlled intelligent telemedicine systems with increased inter-device compatibility.
Aims
Heart failure (HF) patients are at high‐risk of cardiovascular (CV) events, including CV death. Nonetheless, a substantial proportion of these patients die from non‐CV causes. Identifying ...patients at higher risk for each individual event may help selecting patients for clinical trials and tailoring cardiovascular therapies. The aims of the present study are to: (i) characterize patients according to CV vs. non‐CV death; (ii) develop models for the prediction of the respective events; (iii) assess the models' performance to differentiate CV from non‐CV death.
Methods and results
This study included 2309 patients with HF from the BIOSTAT‐CHF (a systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure) study. Competing‐risk models were used to assess the best combination of variables associated with each cause‐specific death. Results were validated in an independent cohort of 1738 HF patients. The best model to predict CV death included low blood pressure, estimated glomerular filtration rate ≤ 60 mL/min, peripheral oedema, previous HF hospitalization, ischaemic HF, chronic obstructive pulmonary disease, elevated N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP), and troponin (c‐index = 0.73). The non‐CV death model incorporated age > 75 years, anaemia and elevated NT‐proBNP (c‐index = 0.71). Both CV and non‐CV death rose by quintiles of the risk scores; yet these models allowed the identification of patients in whom absolute CV death rates clearly outweigh non‐CV death ones. These findings were externally replicated, but performed worse in a less severely diseased population.
Conclusions
Risk models for predicting CV and non‐CV death allowed the identification of patients at higher absolute risk of dying from CV causes (vs. non‐CV ones). Troponin helped in predicting CV death only, whereas NT‐proBNP helped in the prediction of both CV and non‐CV death. These findings can be useful both for tailoring therapies and for patient selection in HF trials in order to attain CV event enrichment.
Aims
To develop a risk model for sudden cardiac death (SCD) in high‐risk acute myocardial infarction (AMI) survivors.
Methods and results
Data from the Effect of Carvedilol on Outcome After ...Myocardial Infarction in Patients With Left Ventricular Dysfunction trial (CAPRICORN) and the Valsartan in Acute Myocardial Infarction Trial (VALIANT) were used to create a SCD risk model (with non‐SCD as a competing risk) in 13 202 patients. The risk model was validated in the Eplerenone Post‐AMI Heart Failure Efficacy and Survival Study (EPHESUS). The rate of SCD was 3.3 (95% confidence interval 3.0–3.5) per 100 person‐years over a median follow‐up of 2.0 years. Independent predictors of SCD included age > 70 years; heart rate ≥ 70 bpm; smoking; Killip class III/IV; left ventricular ejection fraction ≤30%; atrial fibrillation; history of prior myocardial infarction, heart failure or diabetes; estimated glomerular filtration rate < 60 mL/min/1.73 m2; and no coronary reperfusion or revascularisation therapy for index AMI. The model was well calibrated and showed good discrimination (C‐statistic = 0.72), including in the early period after AMI. The observed 2‐year event rates increased steeply with each quintile of risk score (1.9%, 3.6%, 6.2%, 9.0%, 13.4%, respectively).
Conclusion
An easy to use SCD risk score developed from routinely collected clinical variables in patients with heart failure, left ventricular systolic dysfunction or both, early after AMI was superior to left ventricular ejection fraction. This score might be useful in identifying patients for future trials testing treatments to prevent SCD early after AMI.
Aims
Heart failure (HF) is frequently caused by an ischaemic event (e.g. myocardial infarction) but might also be caused by a primary disease of the myocardium (cardiomyopathy). In order to identify ...targeted therapies specific for either ischaemic or non‐ischaemic HF, it is important to better understand differences in underlying molecular mechanisms.
Methods and results
We performed a biological physical protein–protein interaction network analysis to identify pathophysiological pathways distinguishing ischaemic from non‐ischaemic HF. First, differentially expressed plasma protein biomarkers were identified in 1160 patients enrolled in the BIOSTAT‐CHF study, 715 of whom had ischaemic HF and 445 had non‐ischaemic HF. Second, we constructed an enriched physical protein–protein interaction network, followed by a pathway over‐representation analysis. Finally, we identified key network proteins. Data were validated in an independent HF cohort comprised of 765 ischaemic and 100 non‐ischaemic HF patients. We found 21/92 proteins to be up‐regulated and 2/92 down‐regulated in ischaemic relative to non‐ischaemic HF patients. An enriched network of 18 proteins that were specific for ischaemic heart disease yielded six pathways, which are related to inflammation, endothelial dysfunction superoxide production, coagulation, and atherosclerosis. We identified five key network proteins: acid phosphatase 5, epidermal growth factor receptor, insulin‐like growth factor binding protein‐1, plasminogen activator urokinase receptor, and secreted phosphoprotein 1. Similar results were observed in the independent validation cohort.
Conclusions
Pathophysiological pathways distinguishing patients with ischaemic HF from those with non‐ischaemic HF were related to inflammation, endothelial dysfunction superoxide production, coagulation, and atherosclerosis. The five key pathway proteins identified are potential treatment targets specifically for patients with ischaemic
HF.
Therapy has improved the survival of heart failure (HF) patients. However, many patients progress to advanced chronic HF (ACHF). We propose a practical clinical definition and describe the ...characteristics of this condition.
Patients that are generally recognised as ACHF often exhibit the following characteristics: 1) severe symptoms (NYHA class III to IV); 2) episodes with clinical signs of fluid retention and/or peripheral hypoperfusion; 3) objective evidence of severe cardiac dysfunction, shown by at least one of the following: left ventricular ejection fraction<30%, pseudonormal or restrictive mitral inflow pattern at Doppler-echocardiography; high left and/or right ventricular filling pressures; elevated B-type natriuretic peptides; 4) severe impairment of functional capacity demonstrated by either inability to exercise, a 6-minute walk test distance<300 m or a peak oxygen uptake<12-14 ml/kg/min; 5) history of >1 HF hospitalisation in the past 6 months; 6) presence of all the previous features despite optimal therapy. This definition identifies a group of patients with compromised quality of life, poor prognosis, and a high risk of clinical events. These patients deserve effective therapeutic options and should be potential targets for future clinical research initiatives.
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