The relative impact of scar and viable tissue in predicting global left ventricular remodeling in medically treated patients

We sought to determine the relative impact of myocardial scar and viability on post-infarct left ventricular (LV) remodeling in medically-treated patients with LV dysfunction. Forty patients with chronic ischemic heart disease (age 64±9, EF 40±11%) underwent rest-redistribution Tl201 SPECT (scar = 50% transmural extent), A global index of scarring for each patient (CMR scar score) was calculated as the sum of transmural extent scores in all segts. LV end diastolic volumes (LVEDV) and LV end systolic volumes (LVESV) were measured by real-time threedimensional echo at baseline and median of 12 months follow-up. There was a significant positive correlation between change in LVEDV with number of scar segts by all three imaging techniques (LVEDV: SPECT scar, r = 0.62, p < 0.001; DbE scar, r = 0.57, p < 0.001; CMR scar, r = 0.52, p < 0.001) but change in LV volumes did not the correlate with number of viable segments. ROC curve analysis showed that remodeling (LVEDV> 15%) was predicted bySPECTscars(AUC= 0.79),DbEscars(AUC= 0.76),CMR scars (AUC= 0.70), and CMR scar score (AUC 0.72). There were no significant differences between any of the ROC curves (Z score

Reduction in scar thickness post myocardial infarction is secondary to increase in regional left ventricular volumes

We sought to determine the relative impact of myocardial scar and viability on post-infarct left ventricular (LV) remodeling in medically-treated patients with LV dysfunction. Forty patients with chronic ischemic heart disease (age 64±9, EF 40±11%) underwent rest-redistribution Tl201 SPECT (scar = 50% transmural extent), A global index of scarring for each patient (CMR scar score) was calculated as the sum of transmural extent scores in all segts. LV end diastolic volumes (LVEDV) and LV end systolic volumes (LVESV) were measured by real-time threedimensional echo at baseline and median of 12 months follow-up. There was a significant positive correlation between change in LVEDV with number of scar segts by all three imaging techniques (LVEDV: SPECT scar, r = 0.62, p < 0.001; DbE scar, r = 0.57, p < 0.001; CMR scar, r = 0.52, p < 0.001) but change in LV volumes did not the correlate with number of viable segments. ROC curve analysis showed that remodeling (LVEDV> 15%) was predicted bySPECTscars(AUC= 0.79),DbEscars(AUC= 0.76),CMR scars (AUC= 0.70), and CMR scar score (AUC 0.72). There were no significant differences between any of the ROC curves (Z score

Long-term risk stratification for survivors of acute coronary syndromes - Results from the long-term intervention with pravastatin in ischemic disease (LIPID) study

OBJECTIVES We developed a prognostic strategy for quantifying the long-term risk of coronary heart disease (CHD) events in survivors of acute coronary syndromes (ACS). BACKGROUND Strategies for quantifying long-term risk of CHD events have generally been confined to primary prevention settings. The Long-term Intervention with Pravastatin in Ischemic Disease (LIPID) study, which demonstrated that pravastatin reduces CHD events in ACS survivors with a broad range of cholesterol levels, enabled assessment of long-term prognosis in a secondary prevention setting. METHODS Based on outcomes in 8,557 patients in the LIPID study, a multivariate risk factor model was developed for prediction of CHD death or nonfatal myocardial infarction. Prognostic indexes were developed based on the model, and low-, medium-, high- and very high-risk groups were defined by categorizing the prognostic indexes. RESULTS In addition to pravastatin treatment, the independently significant risk factors included: total and high density lipoprotein cholesterol, age, gender, smoking status, qualifying ACS, prior coronary revascularization, diabetes mellitus, hypertension and prior stroke. Pravastatin reduced coronary event rates in each risk level, and the relative risk reduction did not vary significantly between risk levels. The predicted five-year coronary event rates ranged from 5% to 19% for those assigned pravastatin and from 6.4% to 23.6% fur those assigned placebo. CONCLUSIONS Long-term prognosis of ACS survivors varied substantially according to conventional risk factor profile. Pravastatin reduced coronary risk within all risk levels; however, absolute risk remained high in treated patients with unfavorable profiles. Our risk stratification strategy enables identification of ACS survivors who remain at very high risk despite statin therapy. CT Am Coil Cardiol 2001;38:56-63) (C) 2001 by the American College of Cardiology.

Death and readmission in the year after hospital admission with cardiovascular disease: the Hunter Area Heart and Stroke Register

Objectives: To compare outcomes one year after hospital admission for patients initially discharged with a diagnosis of acute myocardial infarction (AMI), other ischaemic heart disease (other IHD), congestive heart failure (CHF) or stroke. Design: Cohort study. Setting: Hunter Area Heart and Stroke Register, which registers all patients admitted with heart disease or stroke to any of the 22 hospitals in the Hunter Area Health Service in New South Wales. Patients: 4981 patients with AMI, other IHD, CHF or stroke admitted to hospital as an emergency between 1 July 1995 and 30 June 1997 and followed for at least one year. Main outcome measures: Death from any cause or emergency hospital readmission for cardiovascular disease. Results: In-hospital mortality varied from 1% of those with other IHD to 22% of those with stroke. Almost a third of all patients discharged alive (and 38% of those aged 70 or more) had died or been readmitted within one year. This varied from 22% of those with stroke to 49% of those with CHF. The causes of death and readmission were from a spectrum of cardiovascular disease, regardless of the cause of the original hospital admission. Conclusions: Data from this population register show the poor outcome, especially with increasing age, among patients admitted to hospital with cardiovascular disease. This should alert us to determine whether optimal secondary prevention strategies are being adopted among such patients.

The prediction of disease risk in genomic medicine

In recent years, the phrase 'genomic medicine' has increasingly been used to describe a new development in medicine that holds great promise for human health. This new approach to health care uses the knowledge of an individual's genetic make-up to identify those that are at a higher risk of developing certain diseases and to intervene at an earlier stage to prevent these diseases. Identifying genes that are involved in disease aetiology will provide researchers with tools to develop better treatments and cures. A major role within this field is attributed to 'predictive genomic medicine', which proposes screening healthy individuals to identify those who carry alleles that increase their susceptibility to common diseases, such as cancers and heart disease. Physicians could then intervene even before the disease manifests and advise individuals with a higher genetic risk to change their behaviour - for instance, to exercise or to eat a healthier diet - or offer drugs or other medical treatment to reduce their chances of developing these diseases. These promises have fallen on fertile ground among politicians, health-care providers and the general public, particularly in light of the increasing costs of health care in developed societies. Various countries have established databases on the DNA and health information of whole populations as a first step towards genomic medicine. Biomedical research has also identified a large number of genes that could be used to predict someone's risk of developing a certain disorder. But it would be premature to assume that genomic medicine will soon become reality, as many problems remain to be solved. Our knowledge about most disease genes and their roles is far from sufficient to make reliable predictions about a patient’s risk of actually developing a disease. In addition, genomic medicine will create new political, social, ethical and economic challenges that will have to be addressed in the near future.

The Australian Burden of Disease Study: measuring the loss of health from diseases, injuries and risk factors

This is an overview of the first burden of disease and injury studies carried out in Australia. Methods developed for the World Bank and World Health Organization Global Burden of Disease Study were adapted and applied to Australian population health data. Depression was found to be the top-ranking cause of non-fatal disease burden in Australia, causing 8% of the total years lost due to disability in 1996. Mental disorders overall were responsible for nearly 30% of the non-fatal disease burden. The leading causes of total disease burden (disability-adjusted life years [DALYs]) were ischaemic heart disease and stroke, together causing nearly 18% of the total disease burden. Depression was the fourth leading cause of disease burden, accounting for 3.7% of the total burden. Of the 10 major risk factors to which the disease burden can be attributed, tobacco smoking causes an estimated 10% of the total disease burden in Australia, followed by physical inactivity (7%).

The burden of disease and injury in Australia

An overview of the results of the Australian Burden of Disease (ABD) study is presented. The ABD study was the first to use methodology developed for the Global Burden of Disease study to measure the burden of disease and injury in a developed country. In 1996, mental disorders were the main causes of disability burden, responsible for nearly 30% of total years of life lost to disability (YLD), with depression accounting for 8% of the total YLD. Ischaemic heart disease and stroke were the main contributors to the disease burden disability-adjusted life years (DALYs), together causing nearly 18% of the total disease burden. Risk factors such as smoking, alcohol consumption, physical inactivity, hypertension, high blood cholesterol, obesity and inadequate fruit and vegetable consumption were responsible for much of the overall disease burden in Australia. The lessons learnt from the ABD study are discussed, together with methodological issues that require further attention.

Identification of novel "pathologs" (human disease-related gene candidates) from the RIKEN full-length mouse cDNA data set

The majority of common diseases such as cancer, allergy, diabetes, or heart disease are characterized by complex genetic traits, in which genetic and environmental components contribute to disease susceptibility. Our knowledge of the genetic factors underlying most of such diseases is limited. A major goal in the post-genomic era is to identify and characterize disease susceptibility genes and to use this knowledge for disease treatment and prevention. More than 500 genes are conserved across the invertebrate and vertebrate genomes. Because of gene conservation, various organisms including yeast, fruitfly, zebrafish, rat, and mouse have been used as genetic models.

Prevalence of peripheral arterial disease: persistence of excess risk in former smokers

Objective: To determine the age-standardised prevalence of peripheral arterial disease (PAD) and associated risk factors, particularly smoking. Method: Design: Cross-sectional survey of a randomly selected population. Setting: Metropolitan area of Perth, Western Australia. Participants: Men aged between 65-83 years. Results: The adjusted response fraction was 77.2%. Of 4,470 men assessed, 744 were identified as having PAD by the Edinburgh Claudication Questionnaire and/or the ankle-brachial index of systolic blood pressure, yielding an age-standardised prevalence of PAD of 15.6% (95% confidence intervals (CI): 14.5%, 16.6%). The main risk factors identified in univariate analyses were increasing age, smoking current (OR=3.9, 95% CI 2.9-5.1) or former (OR=2.0, 95% CI 1.6-2.4), physical inactivity (OR=1.4, 95% CI 1.2-1.7), a history of angina (OR=2.2, 95% CI 1.8-2.7) and diabetes mellitus (OR=2.1, 95% CI 1.7-2.6). The multivariate analysis showed that the highest relative risk associated with PAD was current smoking of 25 or more cigarettes daily (OR=7.3, 95% CI 4.2-12.8). In this population, 32% of PAD was attributable to current smoking and a further 40% was attributable to past smoking by men who did not smoke currently. Conclusions: This large observational study shows that PAD is relatively common in older, urban Australian men. In contrast with its relationship to coronary disease and stroke, previous smoking appears to have a long legacy of increased risk of PAD. Implications: This research emphasises the importance of smoking as a preventable cause of PAD.

A comparison of lipid variables as predictors of cardiovascular disease in the Asia Pacific Region

PURPOSE: Many guidelines advocate measurement of total or low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides (TG) to determine treatment recommendations for preventing coronary heart disease (CHD) and cardiovascular disease (CVD). This analysis is a comparison of lipid variables as predictors of cardiovascular disease. METHODS: Hazard ratios for coronary and cardiovascular deaths by fourths of total cholesterol (TC), LDL, HDL, TG, non-HDL, TC/HDL, and TG/HDL values, and for a one standard deviation change in these variables, were derived in an individual participant data meta-analysis of 32 cohort studies conducted in the Asia-Pacific region. The predictive value of each lipid variable was assessed using the likelihood ratio statistic. RESULTS: Adjusting for confounders and regression dilution, each lipid variable had a positive (negative for HDL) log-linear association with fatal CHD and CVD. Individuals in the highest fourth of each lipid variable had approximately twice the risk of CHD compared with those with lowest levels. TG and HDL were each better predictors of CHD and CVD risk compared with TC alone, with test statistics similar to TC/HDL and TG/HDL ratios. Calculated LDL was a relatively poor predictor. CONCLUSIONS: While LDL reduction remains the main target of intervention for lipid-lowering, these data support the potential use of TG or lipid ratios for CHD risk prediction. (c) 2005 Elsevier Inc. All rights reserved.

Telehealth and the diagnosis and management of cardiac disease

The financial and personal burden of chronic cardiac disease is high. Costs are likely to increase over the next few decades. Promising applications of telehealth have appeared in the diagnosis and management of cardiac disease and there are indications that telehealth services can improve the management of chronic cardiac disease as well as extend services to remote and rural populations. Telehealth has been applied to the capture of symptoms of cardiac disease with electrocardiography and echocardiography, to the management and rehabilitation of recently discharged patients, and in peer-to-peer consultation where remote expertise can facilitate diagnosis. Telehealth promises cost reductions in service delivery, although there is a need for properly controlled cost-effectiveness trials to underpin telehealth with a firm evidence base.

Use of stress echocardiography to predict mortality in patients with diabetes and known or suspected coronary artery disease

OBJECTIVE - This study sought to determine whether stress echocardiography using exercise (when feasible) or dobutamine echo could be used to predict mortality in patients with diabetes. RESEARCH DESIGN AND METHODS - Stress echo was performed in 937 patients with diabetes (aged 59 +/- 13 years, 529 men) for symptom evaluation (42%) and follow-up of known coronary artery disease (CAD) (58%). Stress echocardiography using exercise was performed in 333 patients able to exercise maximally, and dobutamine echo using a standard dobutamine stress was used in 604 patients. Patients were followed for less than or equal to9 years (mean 3.9 +/- 2.3) for all-cause mortality. RESULTS - Normal studies were obtained in 567 (60%) patients; 29% had resting left ventricular (LV) dysfunction, and 25% had ischemia. Abnormalities were confined to one territory in 183 (20%) patients and to multiple territories in 187 (20%) patients. Death (in 275 [29%] patients) was predicted by referral for pharmacologic stress (hazard ratio [HR] 3.94, P < 0.0001), ischemia (1.77, P <0.0001), age (1.02, P = 0.002), and heart failure (1.54, P = 0.01). The risk of death in patients With a normal scan was 4% per year, and this was associated with age and selection for pharmacologic stress testing. In stepwise models replicating the sequence of clinical evaluation, the predictive power of independent clinical predictors (age, selection for pharmacologic stress, previous infarction, and heart failure; model chi(2) = 104.8) was significantly enhanced by addition of stress echo data (model chi(2) = 122.9). CONCLUSIONS - The results of stress echo are independent predictors of death in diabetic patients with known or suspected CAD.. Ischemia adds risk that is incremental to clinical risks and LV dysfunction.