Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural classes of images with m pixels need only n=O(m1/4log5/2(m)) nonadaptive nonpixel samples for faithful recovery, as opposed to the usual m pixel samples. More specifically, suppose x has a sparse representation in some orthonormal basis (e.g., wavelet, Fourier) or tight frame (e.g., curvelet, Gabor)-so the coefficients belong to an lscrp ball for 0<ples1. The N most important coefficients in that expansion allow reconstruction with lscr2 error O(N1/2-1p/). It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients. Moreover, a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing. The nonadaptive measurements have the character of "random" linear combinations of basis/frame elements. Our results use the notions of optimal recovery, of n-widths, and information-based complexity. We estimate the Gel'fand n-widths of lscrp balls in high-dimensional Euclidean space in the case 0<ples1, and give a criterion identifying near- optimal subspaces for Gel'fand n-widths. We show that "most" subspaces are near-optimal, and show that convex optimization (Basis Pursuit) is a near-optimal way to extract information derived from these near-optimal subspaces

Compressed sensing

Global strategy for asthma management and prevention

Background—The objective of this study was to examine the association of Joint National Committee (JNC-V) blood pressure and National Cholesterol Education Program (NCEP) cholesterol categories with coronary heart disease (CHD) risk, to incorporate them into coronary prediction algorithms, and to compare the discrimination properties of this approach with other noncategorical prediction functions. Methods and Results—This work was designed as a prospective, single-center study in the setting of a community-based cohort. The patients were 2489 men and 2856 women 30 to 74 years old at baseline with 12 years of follow-up. During the 12 years of follow-up, a total of 383 men and 227 women developed CHD, which was significantly associated with categories of blood pressure, total cholesterol, LDL cholesterol, and HDL cholesterol (all P,.001). Sex-specific prediction equations were formulated to predict CHD risk according to age, diabetes, smoking, JNC-V blood pressure categories, and NCEP total cholesterol and LDL cholesterol categories. The accuracy of this categorical approach was found to be comparable to CHD prediction when the continuous variables themselves were used. After adjustment for other factors, ’28% of CHD events in men and 29% in women were attributable to blood pressure levels that exceeded high normal ($130/85). The corresponding multivariable-adjusted attributable risk percent associated with elevated total cholesterol ($200 mg/dL) was 27% in men and 34% in women. Conclusions—Recommended guidelines of blood pressure, total cholesterol, and LDL cholesterol effectively predict CHD risk in a middle-aged white population sample. A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD. (Circulation. 1998;97:1837-1847.)

/pdf/prediction-of-coronary-heart-disease-using-risk-factor-2poljzi903.pdf

Prediction of Coronary Heart Disease Using Risk Factor Categories

Background—Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. Methods and Results—We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions (“general CVD” algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non–laboratory-based predictors. Conclusions—A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care. (Circulation. 2008;117: 743-753.)

/pdf/general-cardiovascular-risk-profile-for-use-in-primary-care-3o2jjgr182.pdf

General Cardiovascular Risk Profile for Use in Primary Care The Framingham Heart Study

Author(s): Go, Alan S; Mozaffarian, Dariush; Roger, Veronique L; Benjamin, Emelia J; Berry, Jarett D; Borden, William B; Bravata, Dawn M; Dai, Shifan; Ford, Earl S; Fox, Caroline S; Franco, Sheila; Fullerton, Heather J; Gillespie, Cathleen; Hailpern, Susan M; Heit, John A; Howard, Virginia J; Huffman, Mark D; Kissela, Brett M; Kittner, Steven J; Lackland, Daniel T; Lichtman, Judith H; Lisabeth, Lynda D; Magid, David; Marcus, Gregory M; Marelli, Ariane; Matchar, David B; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Mussolino, Michael E; Nichol, Graham; Paynter, Nina P; Schreiner, Pamela J; Sorlie, Paul D; Stein, Joel; Turan, Tanya N; Virani, Salim S; Wong, Nathan D; Woo, Daniel; Turner, Melanie B; American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2013 Update A Report From the American Heart Association

National Center for Health Statistics (NCHS)

The Framingham Heart Study (FHS) was started in 1948 as a prospective investigation of cardiovascular disease in a cohort of adult men and women. Continuous surveillance of this sample of 5209 subjects has been maintained through biennial physical examinations. In 1971 examinations were begun on the children of the FHS cohort. This study, called the Framingham Offspring Study (FOS), was undertaken to expand upon knowledge of cardiovascular disease, particularly in the area of familial clustering of the disease and its risk factors. This report reviews the sampling design of the FHS and describes the nature of the FOS sample. The FOS families appear to be of typical size and age structure for families with parents born in the late 19th or early 20th century. In addition, there is little evidence that coronary heart disease (CHD) experience and CHD risk factors differ in parents of those who volunteered for this study and the parents of those who did not volunteer.

An investigation of coronary heart disease in families the framingham offspring study

An extensive psychosocial questionnaire was administered to 1674 coronary free individuals participating in the Framingham Heart Study between 1965 and 1967. The respondents were followed for the development of coronary heart disease (CHD) over an eight-year period. Women (aged 45-64 years) who developed CHD scored significantly higher on the Framingham Type A behavior, suppressed hostility (not showing or discussing anger), tension, and anxiety symptoms scales than women remaining free of CHD. Type A women developed twice as much CHD and three times as much angina as Type B women. In a multivariate analysis, Framingham Type A behavior and not discussing anger were independent predictors of CHD incidence when controlled for the standard coronary risk factors and other psychosocial scales. Men exhibiting Framingham Type A behavior, work overload, suppressed hostility (not showing anger), and frequent job promotions were at increased risk of developing CHD (especially in the age group 55-64 years). Among men aged 45-64 years, Type A behavior was associated with a twofold risk of angina, myocardial infarction, and CHD in general, as compared to Type B behavior. The association was found only among white-collar workers and was also independent of the standard coronary risk factors and other psychosocial scales. This prospective study suggests that Type A behavior and suppressed hostility may be involved in the pathogenesis of CHD in both men and women.

The relationship of psychosocial factors to coronary heart disease in the framingham study. iii. eight-year incidence of coronary heart disease

Questionnaires administered to 1822 members of the Framingham Heart Study from 1965 to 1967 provided measures of personality type, sociocultural mobility, situational stress and somatic strain. Clusters of questions selected by a panel of experts, and verified by item and factor analysis, formed scales of Type A behavior and other psychosocial states. The Framingham Type A behavior scale was significantly correlated with daily stress (.47), emotional lability (.43), tension (.42), anger symptoms (.34), and ambitiousness (.31). Women were less likely than men to be ambitious and to exhibit the Framingham Type A behavior, and were more likely than men to be emotionally labile, tense, and to suppress hostility. Few consistent associations were found between psychosocial stress measures and levels of blood pressure or cholesterol. Social status and marital conflicts were significantly associated with patterns of smoking. The Framingham Type A behavior pattern and other psychosocial measures were not related to the level of CHD risk, as determined by the Framingham logistic equations.

The relationship of psychosocial factors to coronary heart disease in the Framingham study. I. Methods and risk factors.

A representative population sample of 5192 men and women was followed for 16 years, during which overt congestive heart failure (CHF) developed in 142. In the age range from 30 to 62 years the dominant etiologic precursor was hypertension, which preceded CHF in 75 per cent of the cases. Six times more CHF developed in hypertensive than in normotensive persons. Examination of the association of myocardial hypertrophy on x-ray or electrocardiographic study with systolic versus diastolic pressure revealed little to suggest a greater role for diastolic pressure. Systolic and diastolic pressure together, mean arterial pressure, pulse pressure, and tension-time index discriminated potential hypertrophy and CHF no better than systolic pressure alone. Examination of the correlation of heart weight and left ventricular thickness at autopsy with premorbid systolic versus diastolic pressure revealed a better correlation with systolic than with diastolic pressure. CHF was a lethal phenomenon, with only 50 pe...

https://www.nejm.org/doi/pdf/10.1056/NEJM197210192871601?listPDF=true

Manning Feinleib

Papers

National Center for Health Statistics (NCHS)

An investigation of coronary heart disease in families the framingham offspring study

The relationship of psychosocial factors to coronary heart disease in the framingham study. iii. eight-year incidence of coronary heart disease

The relationship of psychosocial factors to coronary heart disease in the Framingham study. I. Methods and risk factors.

Role of blood pressure in the development of congestive heart failure. The Framingham study.