Current smoking and the risk of non-fatal myocardial infarction in the WHO MONICA Project populations

Background: Cohort studies have shown that smoking has a substantial influence on coronary heart disease mortality in young people. Population based data on non-fatal events have been sparse, however. Objective: To study the impact of smoking on the risk of non-fatal acute myocardial infarction (MI) in young middle age people. Methods: From 1985 to 1994 all non-fatal MI events in the age group 35 - 64 were registered in men and women in the WHO MONICA ( multinational monitoring of trends and determinants in cardiovascular disease) project populations ( 18 762 events in men and 4047 in women from 32 populations from 21 countries). In the same populations and age groups 65 741 men and 66 717 women participated in the surveys of risk factors ( overall response rate 72%). The relative risk of non-fatal MI for current smokers was compared with non-smokers, by sex and five year age group. Results: The prevalence of smoking in people aged 35 - 39 years who experienced non-fatal MI events was 81% in men and 77% in women. It declined with increasing age to 45% in men aged 60 - 64 years and 36% in women, respectively. In the 35 - 39 years age group the relative risk of non-fatal MI for smokers was 4.9 (95% confidence interval (CI) 3.9 to 6.1) in men and 5.3 ( 95% CI 3.2 to 8.7) in women, and the population attributable fractions were 65% and 55%, respectively. Conclusions: During the study period more than half of the non-fatal MIs occurring in young middle age people can be attributed to smoking.

The Australian Universities Teaching Committee project in 'Learning Outcomes and Curriculum Development in Psychology'

The Australian Universities Teaching Committee (AUTC) funds projects intended to improve the quality of teaching and learning in specific disciplinary areas. The project brief for 'Learning Outcomes and Curriculum Development in Psychology' for 2004/2005 was to 'produce an evaluative overview of courses ... with a focus on the specification and assessment of learning outcomes and ... identify strategic directions for universities to enhance teaching and learning'. This project was awarded to a consortium from The University of Queensland, University of Tasmania, and Southern Cross University. The starting point for this project is an analysis of the scientist-practitioner model and its role in curriculum design, a review of current challenges at a conceptual level, and consideration of the implications of recent changes to universities relating to such things as intemationalisation of programs and technological advances. The project will seek to bring together stakeholders from around the country in order to survey the widest possible range of perspectives on the project brief requirements. It is hoped also to establish mechanisms for fiiture scholarly discussion of these issues, including the establishment of an Australian Society for the Teaching of Psychology and an annual conference.

A study of the interaction between operator style and machine capability for a hydraulic mining excavator

This paper presents a case study that explores how operator digging style juxtaposes with mechanical capability for a class of hydraulic mining excavators. The relationships between actuator and digging forces are developed and these are used to identify the excavator's capability to apply forces in various directions. Two distinct modes of operation are examined to see how they relate to the mechanical capabilities of the linkage and to establish if one has merit over the other. It is found that one of these styles results in lower loading of the machine.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Low- and high-density lipoprotein cholesterol goal attainment in dyslipidemic women: The Lipid Treatment Assessment Project (L-TAP) 2

Background Differences between women and men have been documented for both diagnostic testing and treatment in cardiology. This analysis evaluates whether low-density lipoprotein cholesterol (LDL-C) success rates according to current guidelines and high-density lipoprotein cholesterol (HDL-C) levels differ by gender in the L-TAP 2 population. Methods Patients aged >= 20 years with dyslipidemia on stable lipid-lowering therapy were assessed in 9 countries between September 2006 and April 2007. Low-density lipoprotein cholesterol goal attainment by cardiovascular risk level and region and determinants of low HDL-C were compared between genders. Results Of 9,955 patients (45.3% women) evaluated, women had a significantly lower overall LDL-C success rate than men (71.5% vs 73.7%, P = .014), due entirely to the difference in the high-risk/coronary heart disease (CHD) group (LDL-C goal <100 mg/dL, 62.6% vs 70.6%, P < .0001) Among CHD patients with >= 2 additional risk factors, only 26.7% of women and 31.5% of men (P = .021) attained the optional LDL-C goal of <70 mg/dL. High-density lipoprotein cholesterol was <50 mg/dL in 32.2% of women and <40 mg/dL in 26.8% of men (P < .0001), including 38.2% of women and 29.8% of men in the high risk/CHD group (P < .0001). Predictors of low HDL-C in women included diabetes, smoking, waist circumference, and hypertension. Conclusions Cholesterol treatment has, improved substantially since the original L-TAP a decade ago, when only 39% of women attained their LDL-C goal. However, high-risk women are undertreated compared to men, and a substantial opportunity remains to reduce their cardiovascular risk. (Am Heart J 2009; 158:860-6.)

Lipid Treatment Assessment Project 2 A Multinational Survey to Evaluate the Proportion of Patients Achieving Low-Density Lipoprotein Cholesterol Goals

Background-Information about physicians` adherence to cholesterol management guidelines remains scant. The present survey updates our knowledge of lipid management worldwide. Methods and Results-Lipid levels were determined at enrollment in dyslipidemic adult patients on stable lipid-lowering therapy in 9 countries. The primary end point was the success rate, defined as the proportion of patients achieving appropriate low-density lipoprotein cholesterol (LDL-C) goals for their given risk. The mean age of the 9955 evaluable patients was 62 +/- 12 years; 54% were male. Coronary disease and diabetes mellitus had been diagnosed in 30% and 31%, respectively, and 14% were current smokers. Current treatment consisted of a statin in 75%. The proportion of patients achieving LDL-C goals according to relevant national guidelines ranged from 47% to 84% across countries. In low-, moderate-, and high-risk groups, mean LDL-C was 119, 109, and 91 mg/dL and mean high-density lipoprotein cholesterol was 62, 49, and 50 mg/dL, respectively. The success rate for LDL-C goal achievement was 86% in low-, 74% in moderate-, and 67% in high-risk patients (73% overall). However, among coronary heart disease patients with >= 2 risk factors, only 30% attained the optional LDL-C goal of < 70 mg/dL. In the entire cohort, high-density lipoprotein cholesterol was < 40 mg/dL in 19%, 40 to 60 mg/dL in 55%, and > 60 mg/dL in 26% of patients. Conclusions-Although there is room for improvement, particularly in very-high-risk patients, these results indicate that lipid-lowering therapy is being applied much more successfully than it was a decade ago. (Circulation. 2009; 120: 28-34.)

Reaching C-Reactive Protein and Low-Density Lipoprotein Cholesterol Goals in Dyslipidemic Patients (from the Lipid Treatment Assessment Project [L-TAP] 2)

The purpose of the present substudy of the Lipid Treatment Assessment Project 2 was to assess dual C-reactive protein (CRP) and low-density lipoprotein (LDL) cholesterol goal attainment across a spectrum of low-, moderate-, and high-risk patients with dyslipidemia in 8 countries in North America, Latin America, Europe, and Asia. Of the 9,518 patients studied overall, 45% were women, 64% had hypertension, 31% had diabetes, 14% were current smokers, 60% were high risk, and 79% were taking a statin. The median CRP level was 1.5 mg/L (interquartile range 0.2 to 2.8). On multivariate analysis, higher CRP levels were associated with older age, female gender, hypertension, current smoking, greater body mass index, larger waist circumference, LDL cholesterol level, and triglyceride/high-density lipoprotein cholesterol ratio. In contrast, being from Asia or taking a statin was associated with lower levels. Across all risk groups, 59% of patients attained the CRP target of <2 mg/L, and 33% had <1 mg/L. Overall, 44% of patients attained both their National Cholesterol Education Program Adult Treatment Panel III LDL cholesterol target and a CRP level of <2 mg/L, but only 26% attained their LDL cholesterol target and a CRP level of <1 mg/L. In the very high-risk group with coronary heart disease and >= 2 risk factors, only 19% attained both their LDL cholesterol goal and a CRP level of <2 mg/L and 12% their LDL cholesterol goal and a CRP level of <1 mg/L. In conclusion, with current treatment, most dyslipidemic patients do not reach the dual CRP and LDL cholesterol goals. Smoking cessation, weight reduction, and the greater use of more potent statins at higher doses might be able to improve these outcomes. (C) 2011 Elsevier Inc. All rights reserved. (Am J Cardiol 2011;107:1639-1643)

Lipid goals among patients with diabetes or metabolic syndrome: Lipid Treatment Assessment Project (L-TAP) 2

Objective: This analysis of the Lipid Treatment Assessment Project 2 population compared lipid goal attainment by diabetes and metabolic syndrome status. Research design and methods: Dyslipidaemic patients aged >= 20 years on stable lipid lowering therapy had their lipid levels determined once during enrolment at investigation sites in nine countries between September 2006 and April 2007. Achievement of low-density lipoprotein (LDL) cholesterol success, triglycerides < 150 mg/dl (1.7 mmol/l), and high-density lipoprotein (HDL) cholesterol success (> 40 mg/dl [1.0 mmol/l] in men or > 50 mg/dl [1.3 mmol/l] in women) was compared using logistic regression. Results: A total of 9955 patients were evaluated. Patients with diabetes, compared with those without diabetes, had lower achievement of LDL cholesterol goals (according to National Cholesterol Education Program Adult Treatment Panel [NCEP ATP] III guidelines; 67% vs. 75%), triglycerides < 150 mg/dl (55% vs. 64%), and HDL cholesterol success (61% vs. 74%; p < 0.0001 for all comparisons). The significantly lower lipid goal attainment in patients with diabetes was consistent across participating world regions. Patients with metabolic syndrome, compared with those without metabolic syndrome, had lower achievement of NCEP ATP III LDL cholesterol goals (69% vs. 76%), triglycerides < 150 mg/dl (36% vs. 83%), and HDL cholesterol success (49% vs. 89%; p < 0.0001 for all comparisons). As the number of metabolic syndrome components increased, lipid success rates progressively decreased (p < 0.0001 for LDL cholesterol success, triglycerides < 150 mg/dl, and HDL cholesterol success). Conclusions: This analysis indicates that despite their increased cardiovascular risk, patients with diabetes or metabolic syndrome remain undertreated.

Smoking and relative body weight: An international perspective from the WHO MONICA project

Study objective-To investigate the magnitude and consistency of the associations between smoking and body mass index (BMI) in different populations. Design-A cross sectional study. Setting and participants-About 69000 men and women aged 35-64 years from 42 populations participating in the first WHO MONICA survey in the early and mid 1980s. Main restults-Compared to never smokers, regular smokers had significantly (p < 0.05) lower median BMI in 20 (men) and 30 (women) out of 42 populations (range -2.9 to 0.5kg/m(2)). There was no population in which smokers had a significantly higher BMI than never smokers. Among men, the association between leanness and smoking was less apparent in populations with relatively low proportions of regular smokers and high proportions of ex-smokers. Ex-smokers had significantly higher BMI than never smokers in 10 of the male populations but in women no consistent pattern was observed. Adjustment for socioeconomic status did not affect these results. Conclusions-Although in most populations the association between smoking and BMI is similar, the magnitude of this association may be affected by the proportions of smokers and ex-smokers in these populations.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Population versus clinical view of case fatality from acute coronary heart disease - Results from the WHO MONICA Project 1985-1990

Background The clinical view of case fatality (CF) from acute myocardial infarction (AMI) in those reaching the hospital alive is different from the population view. Registration of both hospitalized AMI cases and out-of-hospital coronary heart disease (CHD) deaths in the WHO MONICA Project allows both views to be reconciled. The WHO MONICA Project provides the largest data set worldwide to explore the relationship between CHD CF and age, sex, coronary event rate, and first versus recurrent event. Methods and Results All 79 669 events of definite AMI or possible coronary death, occurring from 1985 to 90 among 5 725 762 people, 35 to 64 years of age, in 29 MONICA populations are the basis for CF calculations. Age-adjusted CF (percentage of CHD events that were fatal) was calculated across populations, stratified for different time periods, and related to age, sex, and CHD event rate. Median 28-day population CF was 49% (range, 35% to 60%) in men and 51% (range, 34% to 70%) in women and was particularly higher in women than men in populations in which CHD event rates were low. Median 28-day CF for hospitalized events was much lower: in men 22% (range, 15% to 36%) and in women 27% (range, 19% to 46%). Among hospitalized events CF was twice as high for recurrent as for first events. Conclusions Overall 28-day CF is halved for hospitalized events compared with all events and again nearly halved for hospitalized 24-hour survivors. Because approximately two thirds of 28-day CHD deaths in men and women occurred before reaching the hospital, opportunities for reducing CF through improved care in the acute event are limited. Major emphasis should be on primary and secondary prevention.

International study of temperature, heat and urban mortality: the `ISOTHURM` project

Background This study describes heat- and cold-related mortality in 12 urban populations in low- and middle-income countries, thereby extending knowledge of how diverse populations, in non-OECD countries, respond to temperature extremes. Methods The cities were: Delhi, Monterrey, Mexico City, Chiang Mai, Bangkok, Salvador, So Paulo, Santiago, Cape Town, Ljubljana, Bucharest and Sofia. For each city, daily mortality was examined in relation to ambient temperature using autoregressive Poisson models (2- to 5-year series) adjusted for season, relative humidity, air pollution, day of week and public holidays. Results Most cities showed a U-shaped temperature-mortality relationship, with clear evidence of increasing death rates at colder temperatures in all cities except Ljubljana, Salvador and Delhi and with increasing heat in all cities except Chiang Mai and Cape Town. Estimates of the temperature threshold below which cold-related mortality began to increase ranged from 15 degrees C to 29 degrees C; the threshold for heat-related deaths ranged from 16 degrees C to 31C. Heat thresholds were generally higher in cities with warmer climates, while cold thresholds were unrelated to climate. Conclusions Urban populations, in diverse geographic settings, experience increases in mortality due to both high and low temperatures. The effects of heat and cold vary depending on climate and non-climate factors such as the population disease profile and age structure. Although such populations will undergo some adaptation to increasing temperatures, many are likely to have substantial vulnerability to climate change. Additional research is needed to elucidate vulnerability within populations.