Independent Components of Chronic Kidney Disease as a Cardiovascular Risk State: Results From the Kidney Early Evaluation Program (KEEP)

Background  The relationships of anemia, microalbuminuria, and estimated glomerular filtration rate (eGFR) with cardiovascular disease (CVD) and subsequent death are not fully understood. We hypothesized that each of these chronic kidney disease–related measures would have an independent relationship with CVD.

Methods  A cohort of 37 153 persons screened in the National Kidney Foundation's Kidney Early Evaluation Program were followed up for a median of 16.0 months (range, 0.2-47.5 months). Participants were volunteers who completed surveys regarding past medical events and who underwent blood pressure and laboratory testing. Estimated glomerular filtration rate was computed using a 4-variable equation. Mortality was ascertained by linkage to national data systems.

Results  Of 37 153 persons, the mean ± SD age was 52.9 ± 15.9 years, and 68.7% were female. A total of 1835 (4.9%) had a self-reported history of myocardial infarction, 1336 (3.6%) had a history of stroke, and 2897 (7.8%) had a history of myocardial infarction or stroke. Multivariate analysis controlling for age demonstrated that the following were independently associated with CVD: male sex (odds ratio [OR], 1.64; P<.001), smoking (OR, 1.73; P<.001), body mass index (OR, 1.01; P = .03), diabetes mellitus (OR, 1.66; P<.001), hypertension (OR, 1.77; P<.001), eGFR of 30 to 59 mL/min per 173 m³ (OR, 1.37; P = .001), hemoglobin level of 12.8 g/dL or less (OR, 1.45; P<.001), and microalbuminuria of greater than 30 mg/L (OR, 1.28; P = .01). Survival analysis found CVD (OR, 3.02; P = .003), chronic kidney disease (OR, 1.98; P = .05), and the combination (OR, 3.80; P<.001) to be independent predictors of mortality. Persons with a combination of all 3 chronic kidney disease measures (anemia, microalbuminuria, and eGFR of <60 mL/min per 1.73 m²) had the lowest survival of about 93% by the end of 30 months.

Conclusion  Anemia, eGFR, and microalbuminuria were independently associated with CVD, and when all 3 were present, CVD was common and survival was reduced.

Kidney disease is a common progressive health problem that is becoming a global public health problem.^1,2 Chronic kidney disease (CKD) has been linked to a plethora of adverse systemic complications, including anemia, neuropathy, bone disease, all-cause mortality, and fatal and nonfatal cardiovascular disease (CVD).^3,4 Most persons with CKD do not die of kidney failure but rather of CVD complications, which are often worsened by diabetes mellitus (DM).^4-15

Persons with CKD are at risk for CVD because of traditional factors (eg, smoking, DM, dyslipidemia, and hypertension) and CKD-related factors (eg, anemia, oxidative stress, microalbuminuria, hyperparathyroidism, and reduced estimated glomerular filtration rate [eGFR]). Chronic kidney disease (defined as a urine albumin–creatinine ratio of >30 mg/g or an eGFR of <60 mL/min per 173 m²) is widely recognized as an independent CVD risk factor.¹⁶ Overall, there is support for the notion that the CKD state independently contributes to de novo and accelerated atherosclerotic disease in the coronary, cerebral, and peripheral circulations.¹⁷ Chronic kidney disease is one of the most important independent risk factors for complications after revascularization procedures.^18,19 In addition, the development of systolic and diastolic dysfunction is affected by levels of kidney function, and CKD has been found to be an independent risk factor for atrial and ventricular arrhythmias and sudden death.^20-22 The relationships of eGFR, anemia, and microalbuminuria with CVD and subsequent death are not fully understood. Therefore, our aim was to evaluate these relationships in a large population that had been screened for CKD. We hypothesized that each CKD-related measure (eGFR, anemia, and microalbuminuria) would have an independent relationship with CVD.

The National Kidney Foundation's Kidney Early Evaluation Program is a free, on-going, community-based screening program designed to identify individuals at increased risk for kidney disease and to encourage them to seek follow-up care.²³ From August 1, 2000, through December 31, 2003, participants from 42 National Kidney Foundation affiliates representing 49 states and 560 screening events were recruited. Eligible participants were men or women at least 18 years old with DM or hypertension or with a family history of DM, hypertension, or kidney disease.

Screening data were collected on participant demographic characteristics and medical history, including self-reported personal and family history of CVD. One-time systolic and diastolic blood pressure measurements were obtained, and blood and urine specimens were collected and processed for determination of blood glucose, creatinine, and hemoglobin (Hb) levels and urine albumin levels. Screening methods were previously described.²³

Participants who reported use of medications for hypertension and those with systolic blood pressure of 140 mm Hg or higher or with diastolic blood pressure of 90 mm Hg or higher were categorized as having hypertension. Participants who reported having DM and those with blood glucose values exceeding 125 mg/dL (>6.9 mmol/L) if reported as fasting or exceeding 200 mg/dL (>11.1 mmol/L) otherwise were categorized as having DM. Estimated glomerular filtration rates were calculated using the Levey modified Modification of Diet in Renal Disease formula (186.3 × [serum creatinine level^−1.154] × [age^−0.203]); calculated values were multiplied by 0.742 for women and by 1.21 for persons of African American race/ethnicity.⁴ Calculated eGFR values were categorized as less than 30 mL/min per 1.73 m², 30 to 59 mL/min per 1.73 m², 60 to 89 mL/min per 1.73 m², and at least 90 mL/min per 1.73 m² based on the Kidney Disease Outcomes Quality Initiative classification of kidney function; eGFR values less than 60 mL/min per 1.73 m² were considered abnormal and indicative of moderately reduced kidney function and prevalent CKD.⁴ Urinary dipstick albumin values of at least 20 mg/L were categorized as microalbuminuria. Participants were categorized as having anemia based on the Kidney Disease Outcomes Quality Initiative definition for anemia (Hb values of <12.0 g/dL for men and women >50 years and <11.0 g/dL for women <51 years). Cardiovascular disease represented a composite of self-reported “heart attack” or stroke (Kidney Early Evaluation Program 2.0 data form elements 18a and 18b). All-cause mortality was determined using a previously validated multilevel tracking system by the Nephrology Analytical Services Division at Minneapolis Medical Research Foundation, Hennepin County Medical Center, Minneapolis, Minn. These methods are analogous to the ones used by the United States Renal Data System Coordinating Center by 2 of us (A.J.C. and S.-C.C.). This system is capable of using name and Social Security number data and incident end-stage renal disease records, with cross-checks against the US Medicare Database and the Social Security Administration Death Files.

Univariate statistics were reported as mean ± SD or as counts with proportions as appropriate. Stratified analyses were carried out across the quartiles of Hb, quartiles of microalbuminuria, and National Kidney Foundation stages of CKD (based on eGFR). Quartile analyses were performed to evaluate Hb and microalbuminuria in an exploratory manner with respect to the outcome. Binary accepted definitions for anemia and microalbuminuria were also used in the analysis. χ² for proportions was used to determine the P value for trend across these groups. Multiple logistic regression analysis was used to determine the independent relationships between the composite CVD variable and the predictor variables, including eGFR, anemia, microalbuminuria, and demographics (age, sex, race/ethnicity, education, smoking status, health insurance coverage, and family history of DM, hypertension, and kidney disease). The Cox proportional hazards regression model was used to analyze the time to all-cause death from the screening event adjusted for baseline demographics. The independent effect of the 3 factors (anemia, reduced eGFR, and microalbuminuria) was evaluated using the Cox proportional hazards regression model. Exploratory analyses were performed by strata of eGFR, Hb level, and microalbuminuria on the outcome of CVD to understand the marginal increase in risk when additional CKD-related factors were added to the model. Exploratory analyses were performed in a similar manner for the individual components of the CVD outcome. P<.05 was considered statistically significant.

Demographic characteristics of the screening population are given in Table 1. Men were significantly more likely than women to be smokers; however, women were more commonly of African American race/ethnicity and had a high school education or higher, health insurance coverage, and a family history of DM, CKD, or hypertension.

Health screening results are given in Table 2. Only 2237 participants (6.0%) had abnormal serum creatinine values of greater than 1.4 mg/dL (>123.8 μmol/L) in men and greater than 1.3 mg/dL (>114.9 μmol/L) in women. The overall mean eGFR was 82.2 ± 23.5 mL/min per 1.73 m². A total of 5504 participants (14.8%) had calculated eGFR values of less than 60 mL/min per 1.73 m², 15 959 (49.5%) of 32 240 participants had microalbuminuria (>20 mg/L), and 4588 (13.1%) of 34 983 participants had anemia by the Kidney Disease Outcomes Quality Initiative definition.

Men were more likely to have DM, hypertension, and an elevated creatinine level, while the eGFR was similar among men and women (mean, 82.2 ± 23.5 mL/min per 1.73 m²). Women were significantly more likely than men to have anemia (3923/24 002 [16.3%] vs 665/10 981 [6.1%], P<.001).

A total of 1835 participants (4.9%) had a self-reported history of myocardial infarction, 1336 (3.6%) had a history of stroke, and 2897 (7.8%) had a history of myocardial infarction or stroke. A stratified analysis using eGFR group and microalbuminuria as independent variables found a steeper gradient for eGFR than for microalbuminuria (eGFR χ² = 508.21 and microalbuminuria χ² = 71.35, P<. 001 for both) for CVD defined as myocardial infarction or stroke (Figure 1). Likewise, a similar analysis using eGFR and Hb group again found a steeper gradient for eGFR (eGFR χ² = 614.95, P<.001; Hb χ² = 15.67, P = .001) (Figure 2). Last, the stratified analysis using microalbuminuria and Hb group as the independent predictors found the least incremental increase in CVD across both variables; however, microalbuminuria was the more influential factor (microalbuminuria χ² = 117.49 and Hb χ² = 22.68, P<.001 for both) (Figure 3). Among those with anemia and microalbuminuria, there was a graded increase in the prevalence of CVD from the highest to the lowest eGFR group (6.5%, 13.0%, 22.2%, and 25.9% for eGFR of ≥90 mL/min per 1.73 m², 60-89 mL/min per 1.73 m², 30-59 mL/min per 1.73 m², and <30 mL/min per 1.73 m², respectively; P<.001) (Figure 4). There was an approximate 5-fold increased prevalence of CVD from the highest to the lowest eGFR group.

Multiple logistic regression analysis results for the outcome of CVD are given in Table 3. The conventional CVD risk factors of male sex, smoking, obesity, DM, and hypertension were associated with CVD prevalence. However, African American race/ethnicity (odds ratio [OR], 0.79; 95% confidence interval [CI], 0.71-0.89; P<.001) and a high school education or higher (OR, 0.74; 95% CI, 0.66-0.83; P<.001) were associated with the absence of CVD. At a level of greater than 30 mg/L, microalbuminuria was found to be an independent risk marker (OR, 1.28; 95% CI, 1.06-1.55; P = .01). Likewise, an eGFR of less than 60 mL/min per 1.73 m² was independently associated with CVD (OR, 1.37; 95% CI, 1.13-1.67; P = .001). Anemia as a binary variable according to the National Kidney Foundation Kidney Disease Outcomes Quality Initiative definition was not associated with CVD (P = .40), likely because of the instability of the point estimate (n = 4588) and the wide CI (0.77-1.11). However, both lower 2 quartiles of Hb, capturing more individuals (n = 17 587 combined), had significant associations with CVD prevalence (Table 3).

There were 191 deaths during the follow-up period. The mean, median, and range of follow-up months from the screening date to December 31, 2004, for the 37 153 participants were 17.0, 16.0, and 0.2 to 47.5 months, respectively. Compared with CVD as an outcome, all-cause mortality had fewer significant predictors, which included male sex, DM, microalbuminuria at 2 levels, prevalent CKD, prevalent CVD, and combined CKD and CVD (greatest association hazard ratio, 3.80; 95% CI, 1.83-7.91; P<.001) (Table 4). Figure 5 shows the survival according to CKD and CVD status during 30 months. Those without CKD or CVD had more than 98% survival. Conversely, those with both CKD and CVD had about 93% survival by the end of 30 months. Figure 6shows the survival according to the number of CKD risk components (including anemia, microalbuminuria, and eGFR of <60 mL/min per 1.73 m²). Those with a combination of all 3 factors had the lowest survival of approximately 93% at 30 months.

Among individuals who volunteered for this screening program, CVD was common. At a mean age of 52 years, individuals in our program were only slightly more obese than the general US population (the World Health Organization reports a mean body mass index [calculated as weight in kilograms divided by height in meters squared] of approximately 27).²⁵ Anemia, eGFR, and microalbuminuria were associated with the reported CVD prevalence, and when all 3 were present, approximately one quarter of these individuals had known CVD. Chronic kidney disease and self-reported CVD were related to mortality. In terms of mortality as an outcome, neither DM nor CKD had an hazard ratio as high as that of CVD, and they were not considered CVD risk equivalents. However, prevalent combined CKD and CVD was the highest risk state, with a 3-fold increased risk of death during the short follow-up period. Finally, CKD risk factors (anemia, reduced eGFR, microalbuminuria) in combination were associated with incrementally higher mortality during the follow-up period.

There are several important implications of this study. The first is that confounding by excess rates of conventional risk factors cannot explain the association between CKD risk markers and CVD prevalence as demonstrated in our multivariate analysis that controlled for sex, DM, smoking, body mass index, and hypertension.¹⁸ These data are consistent with the observations by Go et al,²⁶ who found a similar steep gradient between eGFR and CVD mortality. Our data extend the observations by Go and colleagues in that we reported on the individual components of CKD as a CVD risk state and not the eGFR alone. The second implication is that there is a high (>25%) prevalence of CVD among those with anemia, microalbuminuria, and an eGFR of less than 30 mL/min per 1.73 m² among these patients who volunteered and were eligible based on a personal or family history of DM, CKD, or hypertension. These data suggest that screening for CVD would be of high yield among patients with these risk markers but who do not report any history of CVD symptoms. The third implication is that there is no dominant CKD risk component. Each measurable marker contributed independently to the prevalence of CVD in the multivariate analysis. The fourth and final implication deals with the notion that DM alone (OR, 1.67; P = .001) and CKD alone (OR, 1.98; P = .05) were associated with all-cause mortality. These findings are consistent with those of Howard et al,²⁷ who found wide ranges in cardiac risk in populations with DM. In general, DM plus an additional cardiac risk factor is needed to increase the mortality risk to the same level as the risk associated with CVD.²⁷ Hence, the term risk equivalent should be used with caution until more data are available on this concept. It is clear that the presence of multiple risk markers in an individual confers the highest mortality during a short (median, 16 months) follow-up period. It is also possible that prior investigations that evaluated each CKD factor in isolation may have exaggerated the association with CVD given the overlap and individual contributions of each factor.

The potential explanations for how the CKD state can cause, accelerate, or worsen atherosclerosis and myocardial disease have been of considerable interest in clinical and research communities. The 4 basic explanations are (1) uncontrolled confounding, or the effect of comorbidities that occur in patients with CKD, especially older age; (2) therapeutic nihilism, meaning that patients with CKD receive lesser degrees of cardioprotective therapies; (3) excess treatment toxicities, intolerances, or risks, such that therapy cannot be used or offers a less favorable benefit-to-risk ratio; and (4) a unique vascular pathobiology that occurs in the CKD state.^18,19,28 Although this screening program cannot address each of these explanations individually, we can speculate that a reduction in eGFR is a surrogate for a complex set of biologic processes that occur even in the best-treated patient. A reduction in renal clearance of different nitrogenous products could be injurious to the vascular system in many ways.¹⁷ This could be in part due to activation of various neurohormonal, inflammatory, and oxidative pathways that work to accelerate the atherosclerosis process, causing vascular injury throughout the body.²⁹ For example, it is well recognized that coronary artery calcification, as a reflection of the burden of atherosclerosis, is accelerated when the eGFR falls below 60 mL/min per 1.73 m².¹⁷ Hence, microalbuminuria represents to some degree this ongoing process at the level of the glomerulus.³⁰ Neurohormonal activation is clearly implicated in myocardial injury and in the development of heart failure as a form of CVD in those with CKD.³¹ An alternative line of thinking would suggest that a reduction in eGFR is a surrogate for a reduction in renal parenchymal mass.³² With this reduction in renal tissue, there is a relative deficiency in renally produced protective substances, including erythropoietin and perhaps other proteins.²² Therefore, the anemia and its related risks reflect to some extent this axis of cardiorenal function, with unclear treatment implications at this time. Therefore, it is important to realize that eGFR, anemia, and microalbuminuria represent important measurable components of CVD risk in patients undergoing screening for CKD.³²

Our program has the limitations common to population screening studies. Subjects were volunteers who were likely motivated by their recognized risk of CKD. However, the screening process does not recruit individuals using the terms heart or cardiovascular disease. So, we believe that participants enrolled based on concern about CKD and that CVD represents a measured variable disclosed by the individual. We acknowledge that self-reported CVD has inherent variance related to overreporting and underreporting. Measurements were taken once; therefore, misclassification bias according to groupings by measure biased hypothesis testing to the null. The eGFR variable may have worked to underestimate actual GFR and misclassified patients with higher levels into those with an eGFR of less than 60 mL/min per 1.73 m² and diluted the biologic effect of CKD on CVD. There were limited numbers of individuals with an eGFR of less than 30 mL/min per 1.73 m², leading to some unstable point estimates in that group. Small numbers and random variation statistically explain some inconsistencies seen in the tables. In addition, there were few deaths, leading to instability in the point estimates of some predictor variable categories such as microalbuminuria for the outcome of death. Lipid values were not checked and could be a source of uncontrolled confounding. We did not have electrocardiographic, echocardiographic, or clinical record confirmation of myocardial infarction or stroke. However, the surveys were completed in an assisted manner by health care professionals trained in eliciting the most accurate and complete medical information possible. Another shortcoming is the use of dipstick urine for microalbuminuria detection. In future Kidney Early Evaluation Program protocols, this has been changed to the urine albumin-creatinine ratio. Last, we had only short-term follow-up and few deaths. This resulted in creating less stable point estimates for the association of variables with mortality.

In conclusion, among individuals who volunteered for this screening program, CVD was common. Anemia, microalbuminuria, and eGFR of less than 30 mL/min per 1.73 m² were associated with the prevalence of self-reported CVD, and when all 3 were present, more than one quarter of these individuals had known CVD. Chronic kidney disease and CVD were independently related to mortality. All CKD components in combination were associated with mortality after the health screening event.

Correspondence: Peter A. McCullough, MD, MPH, Divisions of Cardiology, Nutrition, and Preventive Medicine, William Beaumont Hospital, 4949 Coolidge Hwy, Royal Oak, MI 48073 (pmc975@yahoo.com).

Accepted for Publication: January 5, 2007.

Author Contributions:Study concept and design: McCullough, McGill, Collins, Singh, Norris, and Bakris. Acquisition of data: McCullough, Pergola, Collins, and Chen. Analysis and interpretation of data: McCullough, Jurkovitz, Brown, Collins, Chen, Li, Norris, and Klag. Drafting of the manuscript: Pergola, Norris, and Bakris. Critical revision of the manuscript for important intellectual content: Jurkovitz, Pergola, McGill, Brown, Collins, Chen, Li, Singh, Norris, and Klag. Statistical analysis: Collins, Chen, and Li. Obtained funding: Collins and Bakris. Administrative, technical, and material support: McCullough, Pergola, Collins, Singh, Norris, and Klag. Study supervision: McCullough and Collins.

Financial Disclosure: None reported.

Group Information: A complete list of the KEEP Investigators was published in KEEP 2005 Annual Data Report, New York, NY: National Kidney Foundation; 2005:s8.

Previous Presentation: This study was presented in part at the American College of Cardiology Annual Scientific Session 2005; March 7, 2005; Orlando, Fla.