Paul Muntner

Global burden of hypertension: analysis of worldwide data

BACKGROUND Reliable information about the prevalence of hypertension in different world regions is essential to the development of national and international health policies for prevention and control of this condition. We aimed to pool data from different regions of the world to estimate the overall prevalence and absolute burden of hypertension in 2000, and to estimate the global burden in 2025. METHODS We searched the published literature from Jan 1, 1980, to Dec 31, 2002, using MEDLINE, supplemented by a manual search of bibliographies of retrieved articles. We included studies that reported sex-specific and age-specific prevalence of hypertension in representative population samples. All data were obtained independently by two investigators with a standardised protocol and data-collection form. RESULTS Overall, 26.4% (95% CI 26.0-26.8%) of the adult population in 2000 had hypertension (26.6% of men [26.0-27.2%] and 26.1% of women [25.5-26.6%]), and 29.2% (28.8-29.7%) were projected to have this condition by 2025 (29.0% of men [28.6-29.4%] and 29.5% of women [29.1-29.9%]). The estimated total number of adults with hypertension in 2000 was 972 million (957-987 million); 333 million (329-336 million) in economically developed countries and 639 million (625-654 million) in economically developing countries. The number of adults with hypertension in 2025 was predicted to increase by about 60% to a total of 1.56 billion (1.54-1.58 billion). INTERPRETATION Hypertension is an important public-health challenge worldwide. Prevention, detection, treatment, and control of this condition should receive high priority.

Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association

Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2015 Update A Report From the American Heart Association

STRIDE (Stanford Translational Research Integrated Database Environment) is a research and development project at Stanford University to create a standards-based informatics platform supporting clinical and translational research. STRIDE consists of three integrated components: a clinical data warehouse, based on the HL7 Reference Information Model (RIM), containing clinical information on over 1.3 million pediatric and adult patients cared for at Stanford University Medical Center since 1995; an application development framework for building research data management applications on the STRIDE platform and a biospecimen data management system. STRIDEs semantic model uses standardized terminologies, such as SNOMED, RxNorm, ICD and CPT, to represent important biomedical concepts and their relationships. The system is in daily use at Stanford and is an important component of Stanford Universitys CTSA (Clinical and Translational Science Award) Informatics Program.on behalf of the American Heart Association Statistics Committee and Stroke Statistics Nathan D. Wong, Daniel Woo and Melanie B. Turner Elsayed Z. Soliman, Paul D. Sorlie, Nona Sotoodehnia, Tanya N. Turan, Salim S. Virani, Claudia S. Moy, Dariush Mozaffarian, Michael E. Mussolino, Graham Nichol, Nina P. Paynter, Lynda D. Lisabeth, Diane M. Makuc, Gregory M. Marcus, Ariane Marelli, David B. Matchar, Lichtman, Virginia J. Howard, Brett M. Kissela, Steven J. Kittner, Daniel T. Lackland, Judith H. Caroline S. Fox, Heather J. Fullerton, Cathleen Gillespie, Susan M. Hailpern, John A. Heit, Benjamin, Jarett D. Berry, William B. Borden, Dawn M. Bravata, Shifan Dai, Earl S. Ford, Writing Group Members, Véronique L. Roger, Alan S. Go, Donald M. Lloyd-Jones, Emelia J. Association 2012 Update : A Report From the American Heart −− Heart Disease and Stroke StatisticsHeart Disease, Stroke and other Cardiovascular Diseases • Cardiovascular disease is the leading global cause of death, accounting for 17.3 million deaths per year, a number that is expected to grow to more than 23.6 million by 2030. • In 2008, cardiovascular deaths represented 30 percent of all global deaths, with 80 percent of those deaths taking place in lowand middle-income countries. • Nearly 787,000 people in the U.S. died from heart disease, stroke and other cardiovascular diseases in 2011. That’s about one of every three deaths in America. • About 2,150 Americans die each day from these diseases, one every 40 seconds. • Cardiovascular diseases claim more lives than all forms of cancer combined. • About 85.6 million Americans are living with some form of cardiovascular disease or the after-effects of stroke. • Direct and indirect costs of cardiovascular diseases and stroke total more than

Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis.

320.1 billion. That includes health expenditures and lost productivity. • Nearly half of all African-American adults have some form of cardiovascular disease, 48 percent of women and 46 percent of men. • Heart disease is the No. 1 cause of death in the world and the leading cause of death in the United States, killing over 375,000 Americans a year. • Heart disease accounts for 1 in 7 deaths in the U.S. • Someone in the U.S. dies from heart disease about once every 90 seconds.Author(s): Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Judd, Suzanne E; Kissela, Brett M; Lackland, Daniel T; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Matchar, David B; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Willey, Joshua Z; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics'2017 Update: A Report from the American Heart Association

BACKGROUND Substantial controversy surrounds the use of estimated glomerular filtration rate (eGFR) and albuminuria to define chronic kidney disease and assign its stages. We undertook a meta-analysis to assess the independent and combined associations of eGFR and albuminuria with mortality. METHODS In this collaborative meta-analysis of general population cohorts, we pooled standardised data for all-cause and cardiovascular mortality from studies containing at least 1000 participants and baseline information about eGFR and urine albumin concentrations. Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause and cardiovascular mortality associated with eGFR and albuminuria, adjusted for potential confounders. FINDINGS The analysis included 105,872 participants (730,577 person-years) from 14 studies with urine albumin-to-creatinine ratio (ACR) measurements and 1,128,310 participants (4,732,110 person-years) from seven studies with urine protein dipstick measurements. In studies with ACR measurements, risk of mortality was unrelated to eGFR between 75 mL/min/1.73 m(2) and 105 mL/min/1.73 m(2) and increased at lower eGFRs. Compared with eGFR 95 mL/min/1.73 m(2), adjusted HRs for all-cause mortality were 1.18 (95% CI 1.05-1.32) for eGFR 60 mL/min/1.73 m(2), 1.57 (1.39-1.78) for 45 mL/min/1.73 m(2), and 3.14 (2.39-4.13) for 15 mL/min/1.73 m(2). ACR was associated with risk of mortality linearly on the log-log scale without threshold effects. Compared with ACR 0.6 mg/mmol, adjusted HRs for all-cause mortality were 1.20 (1.15-1.26) for ACR 1.1 mg/mmol, 1.63 (1.50-1.77) for 3.4 mg/mmol, and 2.22 (1.97-2.51) for 33.9 mg/mmol. eGFR and ACR were multiplicatively associated with risk of mortality without evidence of interaction. Similar findings were recorded for cardiovascular mortality and in studies with dipstick measurements. INTERPRETATION eGFR less than 60 mL/min/1.73 m(2) and ACR 1.1 mg/mmol (10 mg/g) or more are independent predictors of mortality risk in the general population. This study provides quantitative data for use of both kidney measures for risk assessment and definition and staging of chronic kidney disease. FUNDING Kidney Disease: Improving Global Outcomes (KDIGO), US National Kidney Foundation, and Dutch Kidney Foundation.Background A comprehensive evaluation of the independent and combined associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality is required for assessment of the impact of kidney function on risk in the general population, with implications for improving the definition and staging of chronic kidney disease (CKD).

Mortality Prediction with a Single General Self-Rated Health Question: A Meta-Analysis

WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

The metabolic syndrome and chronic kidney disease in U.S. adults.

AbstractOBJECTIVE: Health planners and policy makers are increasingly asking for a feasible method to identify vulnerable persons with the greatest health needs. We conducted a systematic review of the association between a single item assessing general self-rated health (GSRH) and mortality. DATA SOURCES: Systematic MEDLINE and EMBASE database searches for studies published from January 1966 to September 2003. REVIEW METHODS: Two investigators independently searched English language prospective, community-based cohort studies that reported (1) all-cause mortality, (2) a question assessing GSRH; and (3) an adjusted relative risk or equivalent. The investigators searched the citations to determine inclusion eligibility and abstracted data by following a standarized protocol. Of the 163 relevant studies identified, 22 cohorts met the inclusion criteria. Using a random effects model, compared with persons reporting “excellent” health status, the relative risk (95% confidence interval) for all-cause mortality was 1.23 [1.09, 1.39], 1.44 [1.21, 1.71], and 1.92 [1.64, 2.25] for those reporting “good,” “fair,” and “poor” health status, respectively. This relationship was robust in sensitivity analyses, limited to studies that adjusted for comorbid illness, functional status, cognitive status, and depression, and across subgroups defined by gender and country of origin. CONCLUSIONS: Persons with “poor” self-rated health had a 2-fold higher mortality risk compared with persons with “excellent” self-rated health. Subjects’ responses to a simple, single-item GSRH question maintained a strong association with mortality even after adjustment for key covariates such as functional status, depression, and co-morbidity.

Prevalence, Awareness, Treatment, and Control of Hypertension in China

Context People with the metabolic syndrome (hypertension, low high-density lipoprotein cholesterol level, high triglyceride level, high glucose level, and obesity) are at high risk for cardiovascular disease, and cardiovascular disease is associated with chronic kidney disease. However, it is unknown whether the metabolic syndrome is independently associated with chronic kidney disease. Contribution In this population-based study of more than 6000 adults, the risks for chronic kidney disease and microalbuminuria both increased progressively as the number of components of the metabolic syndrome increased from 0 or 1 to 5. Cautions It is difficult to disentangle the effects of the metabolic syndrome from those of hypertension and abnormal glucose metabolism. It is unclear whether treating the metabolic syndrome will prevent chronic kidney disease. The Editors Chronic kidney disease has become an important public health challenge in the United States. According to data from the third National Health and Nutrition Examination Survey (NHANES III), 8.3 million (4.6%) U.S. adults 20 years of age or older have chronic kidney disease (1). Chronic kidney disease is a major risk factor for end-stage renal disease, cardiovascular disease, and premature death (1-7). Identifying and treating risk factors for early chronic kidney disease may be the best approach to prevent and delay adverse outcomes (1). The metabolic syndrome, characterized by abdominal obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol level, high blood pressure, and high fasting glucose level, is a common disorder in the United States (8). For example, 47 million (23.7%) U.S. residents 20 years of age or older have the metabolic syndrome, according to data from NHANES III (9). With the continuous increase in the prevalence of obesity in the United States, the metabolic syndrome is expected to be even more common in the future (10). The metabolic syndrome has been associated with an increased risk for diabetes mellitus and cardiovascular disease, as well as increased mortality from cardiovascular disease and all causes (11-13). However, there are sparse data on the relationship between the metabolic syndrome and risk for chronic kidney disease (14). We examined the association between the metabolic syndrome and risk for chronic kidney disease and microalbuminuria in a large representative sample of U.S. adults who participated in the NHANES III. Methods Study Participants The NHANES III was conducted by the National Center for Health Statistics between 1988 and 1994. A detailed description of the study participants and methods has been published elsewhere (15, 16). In brief, a stratified, multistage probability design was used to obtain a representative sample of the civilian noninstitutionalized U.S. general population (15, 16). A subsample of 7832 NHANES III participants who were 20 years of age and older was randomly selected to participate in morning visits at which fasting blood specimens were obtained. Persons without a fasting blood sample (n = 503), women who were pregnant (n = 120) or menstruating (n = 275), and 1 person with kidney failure (estimated glomerular filtration rate <15 mL/min per 1.73 m2) were excluded from the current analysis. Furthermore, persons who were missing measurements for any component of the metabolic syndrome (plasma glucose level, HDL cholesterol level, serum triglyceride level, waist circumference, or blood pressure measurements) were excluded (n = 621). In addition, 95 persons with missing creatinine measurements were excluded from the chronic kidney disease analyses and 94 persons with missing data on urinary albumin and 93 persons with clinical proteinuria (urinary albumincreatinine ratio >300 mg/g) were excluded from the microalbuminuria analyses. After these exclusions, 6217 persons were included in the chronic kidney disease analyses and 6125 persons were included in the microalbuminuria analyses. Exposure Measurements Data from NHANES III were collected during a home interview followed by a detailed physical examination at a mobile examination center or at the participants home. Information on age; race or ethnicity; sex; years of education completed; history of smoking and hypertension; use of antihypertensive medication, diabetes medication, insulin, and nonsteroidal anti-inflammatory drugs (NSAIDs); alcohol consumption; and physical activity were obtained during the home interview (15, 16). Blood pressure was measured 3 times during the home interview and 3 times during the subsequent evaluation at the mobile examination center by trained observers using a standard protocol (15, 16). Blood pressure for an individual participant was calculated as the average of all available systolic and diastolic readings. Waist circumference was measured according to a standard protocol by a trained NHANES III staff member. For NHANES III participants who were assigned to a physical examination during a morning session, a blood sample was collected after an overnight fast of 8 hours or more. Plasma glucose level was measured with a hexokinase enzymatic reference method (COBAS MIRA, Roche Diagnostics Corp., Indianapolis, Indiana) (15, 16). Serum HDL cholesterol and triglyceride levels were measured enzymatically by using a commercially available reagent mixture (Cholesterol/HP, Boehringer Mannheim, Indianapolis, Indiana), and creatinine was analyzed by the modified kinetic Jaffe reaction method using a Hitachi 737 analyzer (Boehringer Mannheim) (15, 16). The metabolic syndrome was defined by using criteria recommended in the National Cholesterol Education Program Adult Treatment Panel III (ATP III) guidelines (8). Specifically, elevated blood pressure was defined as an average systolic or diastolic blood pressure of 130/85 mm Hg or higher. Low HDL cholesterol level was defined as less than 1.036 mmol/L (40 mg/dL) in men or less than 1.295 mmol/L (50 mg/dL) in women. High serum triglyceride level was defined as 1.695 mmol/L (150 mg/dL) or more. Elevated fasting plasma glucose level was defined as 6.10 mmol/L (110 mg/dL) or more. Finally, abdominal obesity was defined as a waist circumference of 102 cm or more in men or 88 cm or more in women. Participants who reported current use of antihypertensive or antidiabetic medication (insulin or oral agents) were classified as having elevated blood pressure or elevated fasting plasma glucose level, respectively. The metabolic syndrome was defined as the presence of 3 or more of these components (8). Diabetes was defined as a self-reported history of a previous diagnosis of diabetes or a fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or more. Outcome Measures Two outcomes, chronic kidney disease and microalbuminuria, were used in this analysis. Glomerular filtration rate was calculated by using the abbreviated equation developed by the Modification of Diet in Renal Disease (MDRD) study (17): Estimated glomular filtration rate = 186.3 (serum creatinine level) 1.154 age 0.203 (0.742 if female) (1.21 if black). Serum creatinine level was calibrated for measurement variance between NHANES III and MDRD clinical laboratories (18). Chronic kidney disease was defined as a glomerular filtration rate less than 60 mL/min per 1.73 m2. In addition, we conducted a sensitivity analysis by using serum creatinine level to define chronic kidney disease ( 132.6 mol/L [ 1.5 mg/dL] for men and 114.9 mol/L [ 1.3 mg/dL] for women). During the physical examination, a random untimed urine sample was obtained from all adults. Urinary albumin concentration was measured by solid-phase fluorescent immunoassay on thawed urine specimens (15, 16). Urinary albumin level was not measured on visibly hematuric specimens or those testing positive for hemoglobin by using qualitative test strips. Urinary creatinine level was analyzed by the modified kinetic Jaffe reaction method by using SYNCHRON AS/ASTRA analyzer (Beckman Instruments, Inc., Brea, California). Microalbuminuria was defined as a urinary albumincreatinine ratio of 30 to 300 mg/g, and clinical proteinuria was defined as a urinary albumincreatinine ratio greater than 300 mg/g. Statistical Analyses The prevalence of the metabolic syndrome and its individual components (elevated blood pressure level, high plasma glucose level, high triglyceride level, low HDL cholesterol level, and abdominal obesity) as well as the number of the metabolic syndrome components present (0, 1, 2, 3, 4, or 5) was determined for the overall study sample. Mean values of continuous variables and percentages of categorical variables for exposures, covariates, and outcomes were calculated by metabolic syndrome status. The statistical significance of differences in these characteristics across those with and without the metabolic syndrome was examined by using the Z test (continuous variables) and the Wald chi-square test (categorical variables) in multivariate regression models after adjustment for age, sex, and race or ethnicity. The prevalence of chronic kidney disease and microalbuminuria was determined for participants with and without each of the 5 components of the metabolic syndrome. The prevalence of chronic kidney disease and microalbuminuria was also calculated by the number of metabolic syndrome components present. Logistic regression analysis, adjusted for age, sex, and race or ethnicity, was used to determine the statistical significance of the differences in prevalence. The crude; age-, sex-, and race- or ethnicity-adjusted; and multivariate-adjusted odds ratios of chronic kidney disease and microalbuminuria, separately, were calculated by using logistic regression models with each component of the metabolic syndrome as an exposure of interest. The crude and adjusted odds ratios of chronic kidney disease and microalbuminuria were also determined by clustering the components of the metabolic syndrome. In these analyses, the odds ratios of chr

Traditional and Nontraditional Risk Factors Predict Coronary Heart Disease in Chronic Kidney Disease: Results from the Atherosclerosis Risk in Communities Study

Abstract—The objective of this study was to estimate the prevalence and distribution of hypertension and to determine the status of hypertension awareness, treatment, and control in the general adult population in China. The International Collaborative Study of Cardiovascular Disease in ASIA (InterASIA), conducted in 2000–2001, used a multistage cluster sampling method to select a nationally representative sample. A total of 15 540 adults, age 35 to 74 years, were examined. Three blood pressure measurements were obtained by trained observers by use of a standardized mercury sphygmomanometer after a 5-minute sitting rest. Information on history of hypertension and use of antihypertensive medications was obtained by use of a standard questionnaire. Hypertension was defined as a mean systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, and/or use of antihypertensive medications. Overall, 27.2% of the Chinese adult population age 35 to 74 years, representing 129 824 000 persons, had hypertension. The age-specific prevalence of hypertension was 17.4%, 28.2%, 40.7%, and 47.3% in men and 10.7%, 26.8%, 38.9%, and 50.2% in women age 35 to 44 years, 45 to 54 years, 55 to 64 years, and 65 to 74 years, respectively. Among hypertensive patients, only 44.7% were aware of their high blood pressure, 28.2% were taking antihypertensive medication, and 8.1% achieved blood pressure control (<140/90 mm Hg). Our results indicate that hypertension is highly prevalent in China. The percentages of those with hypertension who are aware, treated, and controlled are unacceptably low. These results underscore the urgent need to develop national strategies to improve prevention, detection, and treatment of hypertension in China.

The Chronic Renal Insufficiency Cohort (CRIC) Study: Design and Methods

Some risk factors for coronary heart disease (CHD) incidence in the general population are not associated with CHD incidence among patients with ESRD but have not been well characterized in chronic kidney disease (CKD). The association of several risk factors with CHD incidence was studied among participants with CKD in the population-based Atherosclerosis Risk in Communities (ARIC) Study. CHD risk factors and estimated GFR using serum creatinine were measured among 807 ARIC participants with CKD (estimated GFR between 15 and 59 ml/min per 1.73 m(2)). The incidence of CHD during 10.5 yr of follow-up was 6.3, 8.5, and 14.4 per 1000 person-years among ARIC participants with an estimated GFR of >/=90, 60 to 89, and 15 to 59 ml/min per 1.73 m(2), respectively. After adjustment for age, race, gender, and ARIC field center, among those with CKD, the relative risk (95% confidence interval) of CHD was 1.65 (1.01 to 2.67) for current smoking, 2.02 (1.27 to 3.22) for hypertension, 3.06 (2.01 to 4.67) for diabetes, and 1.96 (1.14 to 3.36) for anemia. The comparably adjusted relative risks of CHD for each standard deviation higher total and HDL cholesterol were 1.50 (1.25 to 1.71) and 0.79 (0.62 to 1.01), respectively, and 1.38 (1.13 to 1.69), 1.24 (1.06 to 1.46), 0.65 (0.54 to 0.79), and 1.38 (1.19 to 1.59) for waist circumference, leukocyte count, serum albumin, and fibrinogen, respectively. CHD risk factors in the general population remain predictive among patients with CKD. Given the high risk for CHD among patients with CKD, control of these risk factors may have a substantial impact on their excess burden of CHD.