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

XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

Background and Purpose—The authors present an overview of the current evidence and management recommendations for evaluation and treatment of adults with acute ischemic stroke. The intended audienc...

/pdf/guidelines-for-the-early-management-of-patients-with-acute-19udbft6e7.pdf

Guidelines for the Early Management of Patients With Acute Ischemic Stroke A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association

Objective. —To identify and quantify the major external (nongenetic) factors that contribute to death in the United States. Data Sources. —Articles published between 1977 and 1993 were identified through MEDLINE searches, reference citations, and expert consultation. Government reports and compilations of vital statistics and surveillance data were also obtained. Study Selection. —Sources selected were those that were often cited and those that indicated a quantitative assessment of the relative contributions of various factors to mortality and morbidity. Data Extraction. —Data used were those for which specific methodological assumptions were stated. A table quantifying the contributions of leading factors was constructed using actual counts, generally accepted estimates, and calculated estimates that were developed by summing various individual estimates and correcting to avoid double counting. For the factors of greatest complexity and uncertainty (diet and activity patterns and toxic agents), a conservative approach was taken by choosing the lower boundaries of the various estimates. Data Synthesis. —The most prominent contributors to mortality in the United States in 1990 were tobacco (an estimated 400000 deaths), diet and activity patterns (300 000), alcohol (100 000), microbial agents (90 000), toxic agents (60 000), firearms (35 000), sexual behavior (30 000), motor vehicles (25 000), and illicit use of drugs (20 000). Socioeconomic status and access to medical care are also important contributors, but difficult to quantify independent of the other factors cited. Because the studies reviewed used different approaches to derive estimates, the stated numbers should be viewed as first approximations. Conclusions. —Approximately half of all deaths that occurred in 1990 could be attributed to the factors identified. Although no attempt was made to further quantify the impact of these factors on morbidity and quality of life, the public health burden they impose is considerable and offers guidance for shaping health policy priorities. (JAMA. 1993;270:2207-2212)

https://jamanetwork.com/journals/JAMA/articlepdf/409171/jama_270_18_038.pdf

Actual causes of death in the United States.

▪ Abstract Socioeconomic status (SES) is one of the most widely studied constructs in the social sciences. Several ways of measuring SES have been proposed, but most include some quantification of family income, parental education, and occupational status. Research shows that SES is associated with a wide array of health, cognitive, and socioemotional outcomes in children, with effects beginning prior to birth and continuing into adulthood. A variety of mechanisms linking SES to child well-being have been proposed, with most involving differences in access to material and social resources or reactions to stress-inducing conditions by both the children themselves and their parents. For children, SES impacts well-being at multiple levels, including both family and neighborhood. Its effects are moderated by children's own characteristics, family characteristics, and external support systems.

Socioeconomic status and child development.

Background: Numerous reports show that a centralized distribution of adiposity is a more dangerous risk factor for cardiovascular disease and diabetes than total body obesity. No studies have evaluated whether the same pattern exists with dementia. The objective was to evaluate the association between midlife central obesity and risk of dementia three decades later. Methods: A longitudinal analysis was conducted of 6,583 members of Kaiser Permanente of Northern California who had their sagittal abdominal diameter (SAD) measured in 1964 to 1973. Diagnoses of dementia were from medical records an average of 36 years later, January 1, 1994, to June 16, 2006. Cox proportional hazard models adjusted for age, sex, race, education, marital status, diabetes, hypertension, hyperlipidemia, stroke, heart disease, and medical utilization were conducted. Results: A total of 1,049 participants (15.9%) were diagnosed with dementia. Compared with those in the lowest quintile of SAD, those in the highest had nearly a threefold increased risk of dementia (hazard ratio, 2.72; 95% CI, 2.33–3.33), and this was only mildly attenuated after adding body mass index (BMI) to the model (hazard ratio, 1.92; 95% CI, 1.58 –2.35). Those with high SAD (25 cm) and normal BMI had an increased risk (hazard ratio, 1.89; 95% CI, 0.98 – 3.81) vs those with low SAD (25 cm) and normal BMI (18.5–24.9 kg/m 2 ), whereas those both obese (BMI 30 kg/m 2 ) and with high SAD had the highest risk of dementia (HR, 3.60; 95% CI,

http://www.onespiritmedicine.com/wp-content/uploads/documents/studies/central_obesity_and_increased_risk_of_dementia_more_than_three_decades_later.pdf

Central obesity and increased risk of dementia more than three decades later

To examine the reasons for the association between socioeconomic status and poor health, the authors examined the nine-year mortality experience of a random sample of residents aged 35 and over in Oakland, California. Residents of a federally designated poverty area experienced higher age-, race-, and sex-adjusted mortality over the follow-up period compared with residents of nonpoverty areas (relative risk = 1.71, 95 per cent confidence interval 1.20-2.44). This increased risk of death persisted when there was multivariate adjustment for baseline health status, race, income, employment status, access to medical care, health insurance coverage, smoking, alcohol consumption, physical activity, body mass index, sleep patterns, social isolation, marital status, depression, and personal uncertainty. These results support the hypothesis that properties of the sociophysical environment may be important contributors to the association between low socioeconomic status and excess mortality, and that this contribution is independent of individual behaviors.

/pdf/poverty-and-health-prospective-evidence-from-the-alameda-1dthqhdtfh.pdf

Poverty and health prospective evidence from the alameda county study

Poverty and Health. A prospective evidence from the Alameda County Study

Background—Several epidemiological studies have associated depressive symptoms with cardiovascular disease. We investigated whether depressive symptoms constituted a risk for coronary heart disease (CHD) and total mortality among an apparently healthy elderly cohort. Methods and Results—In a prospective cohort of 5888 elderly Americans (≥65 years) who were enrolled in the Cardiovascular Health Study, 4493 participants who were free of cardiovascular disease at baseline provided annual information on their depressive status, which was assessed using the Depression Scale of the Center for Epidemiological Studies. These 4493 subjects were followed for 6 years for the development of CHD and mortality. The cumulative mean depression score was assessed for each participant up to the time of event (maximum 6-year follow-up). Using time-dependent, proportional-hazards models, the unadjusted hazard ratio associated with every 5-unit increase in mean depression score for the development of CHD was 1.15 (P=0.006); t...

Depressive Symptoms and Risks of Coronary Heart Disease and Mortality in Elderly Americans

ContextCognitive decline in elderly persons is often an early predictor of
dementia. Subclinical cardiovascular disease (CVD) and diabetes mellitus may
contribute to substantial decline in cognitive function in the elderly. These
risks may be modified by gene-environment interactions between apolipoprotein
E (APOE) genotype and CVD risk factors or subclinical
CVD.ObjectivesTo examine the association between subclinical CVD and decline in cognitive
functioning in the elderly and to examine effect modification by the APOE genotype of the association between subclinical disease
and cognitive decline.DesignThe Cardiovascular Health Study, a population-based, prospective cohort
study.Setting and PopulationA total of 5888 randomly selected Medicare-eligible participants from
Sacramento County, California; Forsyth County, North Carolina; Washington
County, Maryland; and Pittsburgh, Pa, aged 65 years or older, who were recruited
in 1989-1990 (n = 5201) and in 1992-1993 (n = 687) and who were followed up
for 7 and 5 years, respectively.Main Outcome MeasuresChange over time in scores on the Modified Mini-Mental State Examination
and the Digit Symbol Substitution Test as a function of APOE genotype, subclinical CVD, and diabetes mellitus.ResultsSeventy percent of participants had no significant decline on the Modified
Mini-Mental State Examination. Systolic blood pressure, the ankle-arm brachial
index, atherosclerosis of the internal carotid artery, diabetes mellitus,
and several diagnoses of prevalent CVD were significantly associated with
declines in scores on the Modified Mini-Mental State Examination and the Digit
Symbol Substitution Test. The rate of cognitive decline associated with peripheral
vascular disease, atherosclerosis of the common and internal carotid arteries,
or diabetes mellitus was increased by the presence of any APOE ∊4 allele.ConclusionsMost healthy elderly people did not experience cognitive decline. Measures
of subclinical CVD were modest predictors of cognitive decline. Those with
any APOE ∊4 allele in combination with atherosclerosis,
peripheral vascular disease, or diabetes mellitus were at substantially higher
risk of cognitive decline than those without the APOE ∊4
allele or subclinical CVD. High levels of atherosclerosis increased cognitive
decline independently of APOE genotype.

https://idealab.ucdavis.edu/pubs/papers/haan_shemanski_etal_JAMA1999.pdf

Mary N. Haan

Papers

Central obesity and increased risk of dementia more than three decades later

Poverty and health prospective evidence from the alameda county study

Poverty and Health. A prospective evidence from the Alameda County Study

Depressive Symptoms and Risks of Coronary Heart Disease and Mortality in Elderly Americans

The Role of APOE ∊4 in Modulating Effects of Other Risk Factors for Cognitive Decline in Elderly Persons