Brenner and Rector's The Kidney, 8th ed.

CHAPTER 18. Risk Factors and Kidney Disease

Vandana Menon   Mark J. Sarnak   Andrew S. Levey

  

 

Framework for Natural History, Definition, and Classification of Chronic Kidney Disease, 633

  

 

Epidemiologic Methods for Risk Factor Identification, 633

  

 

Definition of a Risk Factor, 633

  

 

Sources of Evidence for Identification of Risk Factors, 635

  

 

Types of Risk Factors in Chronic Kidney Disease, 637

  

 

Cardiovascular Disease and Chronic Kidney Disease, 638

  

 

Cardiovascular Disease Risk Factors as Risk Factors for Chronic Kidney Disease, 642

  

 

Hypertension, 642

  

 

Diabetes, 642

  

 

Smoking, 643

  

 

Dyslipidemia, 643

  

 

Obesity, 644

  

 

Metabolic Syndrome, 644

  

 

Cardiovascular Disease as a Risk Factor for Chronic Kidney Disease, 644

  

 

Kidney Disease-Related Risk Factors, 644

  

 

Proteinuria/Microalbuminuria, 644

  

 

Renin-Angiotensin-Aldosterone System Activity, 646

  

 

Dietary Protein, 646

  

 

Low Serum Albumin, 646

  

 

Reduction in Kidney Mass, 646

  

 

Primary Hyperfiltration States, 647

  

 

Anemia, 647

  

 

Kidney Disease-Related Nontraditional Cardiovascular Disease Risk Factors, 647

  

 

Other Kidney Disease-Related Risk Factors, 648

  

 

Other Risk Factors for Chronic Kidney Disease, 648

  

 

Family History, 648

  

 

Low Birthweight, 648

  

 

Racial Factors, 649

  

 

Other Non-kidney Related Factors, 649

  

 

Conclusion, 649

Chronic kidney disease (CKD) is a public health problem with increasing prevalence, poor outcomes, and high costs. [1] [2] The major adverse outcomes of CKD include loss of kidney function sometimes leading to kidney failure, complications of decreased kidney function, and also development of cardiovascular disease and premature death.[3] Improving outcomes in CKD requires an integrated approach to prevention, detection, evaluation, and management, as exists for other chronic diseases, such as hypertension, diabetes, hypercholesterolemia, and obesity. A comprehensive analysis of risk factors for the development and progression of CKD is imperative to inform clinical practice and health policy.

FRAMEWORK FOR NATURAL HISTORY, DEFINITION, AND CLASSIFICATION OF CHRONIC KIDNEY DISEASE

Figure 18-1 shows the natural history of CKD and provides a framework for a public health approach to improving outcomes in kidney disease. [4] [5] [6] Shaded ellipses denote stages of kidney disease, kidney damage, decreased glomerular filtration rate (GFR), and kidney failure; unshaded ellipses represent antecedents or outcomes of CKD. Thick arrows between ellipses represent transitions between stages, and can be considered as risk factors for adverse outcomes: susceptibility factors (black), initiation factors (dark gray), progression factors (light gray), and end-stage factors (white). Complications refer to all complications of CKD and its treatment, including complications of decreased GFR (hypertension, anemia, malnutrition, bone disease, neuropathy, and decreased quality of life), and cardiovascular disease. Increasing thickness of arrows connecting later stages of kidney disease to complications represents the increased risk as kidney disease progresses. Below each ellipse are actions to improve outcomes specific for each stage.

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FIGURE 18-1  Stages in progression of CKD and therapeutic strategies.  (From Kidney Disease Outcome Quality Initiative: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classifi cation, and stratifi cation. Am J Kidney Dis 39:S1–246, 242 [Figure 1]; Levey AS, Eckardt KU, Tsukamoto Y, et al: Defi nition and classifi cation of chronic kidney disease: A position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 67:2089–2100, 2005; Coresh J, Astor BC, Greene T, et al: Prevalence of chronic kidney disease and decreased kidney function in the adult U.S. population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 41:1–12, 2003.)

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Chronic kidney disease is defined as functional or structural abnormalities of the kidneys for three or more months, irrespective of cause ( Table 18-1 ). Proteinuria is the most common marker of kidney damage. [4] [7] Glomerular filtration rate is estimated from serum creatinine and equations using age, sex, race, and body size.[8] Patients with CKD can be classified according to severity based on the level of GFR ( Table 18-2 ). Qualitatively, stages 1 and 2 represent kidney damage, stages 3 and 4 represent decreased kidney function, and stage 5 is kidney failure, usually with signs and symptoms of uremia requiring kidney replacement therapies such as dialysis or transplantation.


TABLE 18-1   -- Definition of Chronic Kidney Disease

Criteria

  

 

Kidney damage for ≥3 months, with or without decreased GFR

  

   

Pathological abnormalities

  

   

Markers of kidney damage

  

   

Urinary abnormalities (proteinuria)

  

   

Blood abnormalities (renal tubular syndromes)

  

   

Imaging abnormalities

  

   

Kidney transplantation

GFR <60 ml/min/1.73 m2 for ≥3 months, with or without kidney damage

Kidney Disease Outcome Quality Initiative: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39(2 Suppl 2):S1–246, 2002 [Table 2].

GFR, glomerular filtration rate.

 

 

 

 


TABLE 18-2   -- National Kidney Foundation Kidney Disease Outcomes Quality Initiative Classification, Prevalence, and Action Plan for Stages of Chronic Kidney Disease

Stage[*]

Description

GFR ml/min/1.73 m2

Prevalence, n (%)[†]

Actions[‡]

At increased risk

≥60 (with chronic kidney disease risk factors)

Screening; chronic kidney disease risk reduction

1

Kidney damage with normal or increased GFR

≥90

5,900,000 (3.3)

Diagnosis and treatment; treatment of comorbid conditions; slowing progression; cardiovascular disease risk reduction

2

Kidney damage with mild decreased GFR

60–89

5,300,000 (3.0)

Estimating progression

3

Moderately decreased GFR

30–59

7,600,000 (4.3)

Evaluating and treating complications

4

Severely decreased GFR

15–29

400,000 (0.2)

Preparation for kidney replacement therapy

5

Kidney failure

<15 or dialysis

300,000 (0.1)

Kidney replacement therapy (if uremia present)

Modified from National Kidney Foundation: K/DOQI clinical practice guidelines on hypertension and antihypertensive agents in chronic kidney disease. Am J Kidney Dis 43(5 Suppl 1):S1–290, 2004 [Table 2, Table 51].

GFR, glomerular filtration rate.

 

*

Stages 1 to 5 indicate patients with chronic kidney disease; the row without a stage number indicates persons at increased risk for developing chronic kidney disease. Chronic kidney disease is defined as either kidney damage or GFR less than 60 mL/min per 1.73 m2 for 3 or more months. Kidney damage is defined as pathologic abnormalities or markers of damage, including abnormalities in blood or urine tests or imaging studies.

Prevalence for stage 5 is from the U.S. Renal Data System (1998); it includes approximately 230,000 patients treated with dialysis and assumes 70,000 additional patients not receiving dialysis. Prevalence for stages 1 to 4 is from the Third National Health and Nutrition Survey Examination (1988 to 1994). Population of 177 million adults age 20 or more years. Glomerular filtration rate is estimated from serum creatinine measurements by using the Modification of Diet in Renal Disease study equation based on age, sex, race, and calibration for serum creatinine. For stages 1 and 2, kidney damage is estimated by using untimed urine samples to determine the albumin-creatinine ratios; greater than 17 mg/g in men or greater than 25 mg/g in women on two measurements indicates kidney damage. The proportion of persons at risk for chronic kidney disease has not been estimated accurately.

Includes actions from preceding stages.

 

 

This definition and classification enable identification and staging of the severity of kidney disease based on objective criteria, without the need for specialized laboratory studies or specialist evaluation of the cause of disease. In addition, the definition and classification facilitate study of risk factors in large clinical databases and populations based on commonly available clinical data. Indeed, there has been a large increase in the number of studies on risk factors for kidney disease in the past few years. In this chapter, we will use the term “risk factors” to include conditions that increase risk for the development of kidney disease, as well as those that increase risk of adverse outcomes associated with CKD. Accordingly, these can be defined as susceptibility and initiation factors that help to define persons at increased risk for developing CKD and progression, and end-stage factors that define persons at risk for increasing kidney damage, decline in GFR and development of associated complications ( Table 18-3 ). This chapter will briefly review basic concepts of epidemiologic investigation and provide an overview of the current evidence regarding the epidemiology of risk factors in CKD.


TABLE 18-3   -- Risk Factors for Chronic Kidney Disease and its Outcomes

Risk Factor

Definition

Examples

Susceptibility factors

Increase susceptibility to kidney damage

Older age, family history of chronic kidney disease, reduction in kidney mass, low birthweight, U.S. racial or ethnic minority status, low income or education

Initiation factors

Directly initiate kidney damage

Diabetes, high blood pressure, autoimmune diseases, systemic infections, urinary tract infections, urinary stones, lower urinary tract obstruction, drug toxicity

Progression factors

Cause worsening kidney damage and faster decline in kidney function after initiation of kidney damage

Higher level of proteinuria, systolic blood pressure, poor glycemic control in diabetes, smoking

End-stage factors

Increase morbidity and mortality in kidney failure

Lower dialysis dose (Kt/V), temporary vascular access, anemia, low serum albumin level, late referral

Modified and reprinted with permission from Levey AS, Coresh J, Balk E, et al: National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 139:137–147, 2003; Kidney Disease Outcome Quality Initiative: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39:S1–246, 2002.

Kt/V, dialyzer urea clearance multiplied by time divided by volume of distribution of urea.

 

 

 

 

EPIDEMIOLOGIC METHODS FOR RISK FACTOR IDENTIFICATION

In this section, we review epidemiologic methods that are used to identify and confirm relationships between putative risk factors and development of disease.

Definition of a Risk Factor

The purpose of epidemiologic investiga-tion is to identify a profile of variables that characterize the disease under study. The associations identified between the characteristics and disease may be due to chance, may represent a non-causal relationship, or may signify a true risk factor. The latter implies the presence of a cause and effect relationship between the variable and disease of interest. Identification of risk factors is a key step in understanding pathways leading to development of disease and therefore for the formulation of effective strategies to prevent development and retard progression.

Bradford-Hill criteria provide guidelines for inferring causation when an association is observed and specify the minimal conditions that must be met to establish a causal relationship between the putative risk factor (exposure) and disease (outcome) ( Table 18-4 ).[9] In a complex disease such as CKD with its multifactorial etiology, most risk factors studied may not meet all these criteria. However, they form a good framework to evaluate the adequacy of existing evidence for or against a causal association between risk factors under investigation and CKD.


TABLE 18-4   -- Bradford-Hill Criteria of Causality

Criteria

Explanation

Strength of association

Stronger the association the more likely the relationship is causal

Consistency

A causal association is consistent when replicated in different populations and studies

Specificity

A single putative cause produces a single effect

Temporality

Exposure precedes outcome (i.e., risk factor predates disease)

Biological gradient

Increasing exposure to risk factor increases risk of disease and reduction in exposure reduces risk

Plausibility

The observed association is consistent with biological mechanisms of disease processes

Coherence

The observed association is compatible with existing theory and knowledge within a given field

Experimental evidence

The factor under investigation is amenable to modification by an appropriate experimental approach

Analogy

An established cause and effect relationship exists for a similar exposure or disease

Modified from Hill AB: The environment and disease: Association or causation? Proc R Soc Med 58:295–300, 1965.

 

 

 

Sources of Evidence for Identification of Risk Factors

Analytical epidemiology studies examine associations be-tween putative risk factor exposures and health outcomes and can be broadly classified as observational and experimental. The three basic observational study designs include cross-sectional studies, case control studies, and prospective or cohort studies, and the main experimental study design is a randomized controlled trial ( Table 18-5 ). [10] [11]


TABLE 18-5   -- Comparison of Observational Study Designs

 

Cross-Sectional

Case-Control

Cohort

Study population

Cases (individuals with disease) and controls (individuals without disease) ascertained by single examination of population

Cases (individuals with disease) selected based on selection criteria formulated by investigator and controls (individuals without disease) selected to resemble cases

Defined population followed-up for pre defined time period, cases and controls ascertained during follow-up.

Exposure

Exposure ascertained by single examination of population

Past exposure predating development of disease, measured, or reconstructed

Exposure measured before development of disease

Statistical analysis

Odds Ratio provides estimate of relative risk of exposure

Odds Ratio provides estimate of relative risk of disease

Direct measures of incidence and relative risk

From Fletcher RH, Fletcher SW, Wagner EH: Clinical Epidemiology, The Essentials. Philadelphia: Lippincott Williams & Wilkins, 1996.

 

 

 

Cross-Sectional Studies

In this type of study the relationship between exposure and outcome of interest in a given study population is assessed at a single point in time. Cross-sectional studies are the simplest study design and offer a quick first look at associations. However, a major shortcoming of cross-sectional studies is that the relationships detected using this study design by definition cannot fulfill Hill's criteria of temporality. Because this study design involves a snap shot of the association being studied, with both disease and exposure being assessed simultaneously, it cannot establish the temporal sequence required to establish causality. In other words, cross-sectional studies do not determine whether the exposure pre-ceded outcome. Nevertheless, this study design is useful for the preliminary examination of plausible relationships and hypothesis generation.

Case-Control Studies

In this study design associations between exposure and disease are assessed by comparing rates of exposure in groups with and without disease. The measure of association between the risk factor and disease obtained from a case-control study is the odds ratio. In the simplest design, individuals with (cases) and without (controls) the disease are identified at a given time point from a study population. Rates of past exposure to the risk factor of interest are measured and compared between these groups. A major issue with case-control studies includes exposure identification bias or recall bias whereby because the exposure occurred in the past there may be imperfect ascertainment of the level of exposure.

Cohort Studies

In a cohort study, also termed prospective study, a study population consisting of individuals with and without exposure to the risk factor of interest is followed into the future and rates of disease occurrence are compared between the two groups. A major advantage of a cohort study is the ability to obtain direct measures of disease occurrence or incidence and of the risk of developing disease. The measure of association obtained from a cohort study is a relative risk. A cohort study is of benefit to confirm associations observed in cross-sectional or case-control studies. Table 18-6 , although by no means exhaustive, lists examples of important cohort studies that have provided key information regarding risk factor relationships in CKD. One potential problem with cohort studies is the issue of confounding. A confounder is a variable that is associated with both the exposure and the outcome under study ( Fig. 18-2 ). The presence of confounding can alter (i.e., strengthen, weaken, or mask) the association between the exposure of interest and outcome. One analytical approach for dealing with confounding is to adjust or control for potentially confounding variables in multivariable regression analyses. However, it must be emphasized that statistical adjustment may not completely mitigate the effects of confounding and imperfect adjustment may result in residual confounding.


TABLE 18-6   -- Examples of Epidemiologic Studies Involving Patients with Kidney Disease[*]

Study Design

Examples

Prospective cohorts

  

 

Population Based Cohorts

  

 

Atherosclerosis Risk in Communities Study (ARIC)

  

 

Framingham Heart Study

  

 

Cardiovascular Health Study (CHS)

  

 

Multi-Ethnic Study of Atherosclerosis (MESA)

  

 

Health, Aging and Body Composition (Health ABC)

  

 

Coronary Artery Risk Development in Young Adults (CARDIA)

  

 

Cohorts of Patients with Kidney Disease

  

 

Chronic Renal Insufficiency Cohort (CRIC)

  

 

Cardiovascular Risk in Birmingham (CRIB)

  

 

United States Renal Data System (USRDS)

  

 

Choices for Healthy Outcomes in Caring for End Stage Renal Disease (CHOICE)

Intervention trials

  

 

Trials in Patients with Kidney Disease

  

 

Modification of Diet in Renal Disease Study (MDRD)

  

 

African American Study of Kidney Disease (AASK)

  

 

Study of Heart and Renal Protection (SHARP)

  

 

Prevention of Renal and Vascular Endstage Disease Intervention Trial (PREVEND IT)

  

 

The Microalbuminuria Captopril Study

  

 

Gruppo Italiano di Studi Epidemiologici in Nefrologia (GISEN)

  

 

Deutsche Diabetes Dialyse Studie (4D)

  

 

Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL)

  

 

Irbesartan in Diabetic Nephropathy Trial (IDNT)

  

 

Hemodialysis Study (HEMO)

  

 

The Ramipril Efficacy In Nephropathy (REIN)

  

 

Post Hoc Analysis of Trials in Populations with CVD or CVD Risk Factors

  

 

Heart Outcomes Prevention Evaluation Trial (HOPE)

  

 

Cholesterol and Recurrent Events Trial (CARE)

  

 

Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT)

 

*

This is not an exhaustive list.

 

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FIGURE 18-2  The confounder (C) is causally associated with the outcome of interest (Y) and either causally or noncausally associated with exposure (E); these associations may distort the association of interest: whether E causes Y.  (From Szklo M, Nieto JF: Epidemiology Beyond the Basics. Gaithersburg: Aspen Publishers, Inc. [Figure 5-1, page 181], 2000.)

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Randomized Controlled Trials

In this experimental study design a defined study population is randomly assigned to different interventions. After a fixed follow-up period, rates of pre-defined outcomes are compared between the study arms. In variations of this theme, comparisons can be made between existing treatments and new ones, treated versus untreated, etc. In addition, certain study questions may require blinding or masking; in a single blind study, participants are unaware of their assignment to treatment or control arms, whereas in a double blind study neither participants nor data collectors are aware of study assignment. Blinding in drug therapy trials is often achieved by using a placebo. Table 18-6 lists some examples of important randomized controlled trials that have investigated interventions for patients with CKD. The randomized trial is considered the gold standard for evaluating interventions and associations as it minimizes many of the biases associated with observational study designs and is the only study design that fulfills the Bradford Hill criteria of experimental evidence. In particular, these studies have an advantage over observational study designs of minimizing the effects of confounding because successful randomization should ensure the uniform distribution of known and unknown confounders between the different study arms. However, it must be noted that although randomized trials provide a high level of evidence for evaluating therapeutic agents they are less definitive in terms of assessing risk factor associations. This is attributable to the fact that several interventions affect multiple risk factors, for example angiotensin converting enzyme (ACE) inhibitors reduce blood pressure and proteinuria and statins improve lipid profiles and reduce levels of C-reactive protein, and thus it is difficult to isolate the association between one particular risk factor and outcome.

Data from clinical trials are also used for subgroup and post hoc analyses. In subgroup analyses, a subset of the original participants is selected for study. Post hoc analyses refer to an unplanned exploration of data to try and find associations between variables of interest. Subgroup analyses may be determined a priori or may be post hoc. For example, the Heart Outcomes and Prevention Evaluation (HOPE) study was a randomized trial that investigated the effects of ramipril and vitamin E on major cardiovascular outcomes in 9297 high-risk patients.[12] The study had an upper limit for serum creatinine concentrations of 2.3 mg/dL and found a benefit of ramipril on CVD mortality with a hazard ratio of 0.74. In a post hoc subgroup analysis, the investigators examined the impact of ramipril on prevention of CVD outcomes in 980 patients with mild kidney dysfunction defined as serum creatinine >1.4 mg/dL[13]and found a benefit for ramipril with a hazard ratio of 0.59 for CVD mortality. Although this was an important analysis demonstrating benefit of a specific intervention in a high-risk group of patients, subgroups and post hoc analyses are problematic in many ways. They may lack statistical power and thus be vulnerable to type 2 errors where one incorrectly fails to reject a null hypothesis or conversely when multiple hypotheses are tested, especially in a large dataset, there is an increased chance of a type 1 error (where one incorrectly rejects a true null hypothesis) unless the conventional cut off of P < 0.05 is lowered. Pre-determined analyses can be planned to minimize the risk of type 1 and type 2 errors. For example, if the subgroup analysis had been planned in advance, the investigators may have stratified by kidney function or performed power analyses for this particular subgroup of interest. However, despite these caveats, subgroup and post hoc analyses of large clinical trials are valuable in hypothesis generation and for exploratory analyses. Finally, participants from the different arms of randomized clinical trials are often combined and analyzed as a cohort. Examples of randomized clinical trials that have yielded prospective cohort data include the Modification of Diet in Renal Disease (MDRD) Study and the Multiple Risk Factor Intervention Trial (MRFIT).

Types of Risk Factors in Chronic Kidney Disease

In this section, we define the different types of risk factor relationships involved in the development and progression of CKD. By definition, studies of risk factors for susceptibility and initiation of kidney disease require study in populations without kidney disease, whereas studies of risk factors for progression and end-stage factors are conducted in populations with CKD. In later sections of the chapter, we will discuss individual risk factors for CKD. The distinction as to the type of risk factor is inherently complicated by limitations of study designs; in particular, without appropriate ascertainment for the earlier stages of CKD, it is difficult to determine whether risk factors for later stages of CKD affect susceptibility, initiation, or progression.

Susceptibility Factors

As defined in Table 18-3 and depicted in Figure 18-1 , a susceptibility factor is one that increases susceptibility to kidney damage following exposure to an initiation factor. For example, susceptibility to urinary tract infections is in part determined by host factors that influence pathogen recognition and pathogen-induced signaling. Recently, Toll-like receptors have been identified in the uroepithilia that are important for pathogen recognition and activation of the immune response. Thus, genetic polymorphisms that down-regulate the activity of these receptors may make an individual more susceptible to urinary tract infections.[14] An ideal study design to detect susceptibility factors would in-volve identifying a large cohort of individuals who are free of kidney disease and are exposed to an initiation factor and following them for an extended period of time to determine risk factors associated with development of kidney damage ( Table 18-7 ). The large sample size and extended follow-up time entailed by this approach has the disadvantage of costs and logistic difficulties. Much of our current understanding regarding susceptibility factors is derived from case-control studies; unfortunately, this design usually cannot distinguish susceptibility from initiation factors.


TABLE 18-7   -- Ideal Study Design for Risk Factor Identification

Risk Factors

Study Design

Populations

Outcome

Indicator

Susceptibility

  

 

Prospective

  

 

Randomized controlled trial

Free of kidney disease and exposure to initiation factor

Kidney damage

  

 

Microalbuminuria

  

 

Proteinuria

Initiation

  

 

Prospective

  

 

Randomized controlled trial

Free of kidney disease and susceptible to kidney disease

Kidney damage

  

 

Microalbuminuria

  

 

Proteinuria

Progression

  

 

Prospective

  

 

Randomized controlled trial

Earlier stages of kidney disease

Worsening kidney disease

  

 

Microalbuminuria ➙ proteinuria

  

 

Microalbuminuria ➙ reduced GFR

  

 

Worsening GFR

  

 

Kidney failure

End-stage including development of cardiovascular disease

  

 

Prospective

  

 

Randomized controlled trial

  

 

Earlier stages of kidney disease

  

 

Kidney failure

  

 

Morbidity

  

 

Complications

  

 

Mortality

  

 

Cardiovascular disease

  

 

Biomarkers/surrogate markers

  

 

Comorbid illness

  

 

Hospitalization

  

 

Death

 

GFR, glomerular filtration rate.

 

 

 

Initiation Factors

An initiation factor is one that directly initiates kidney damage, such as diabetes, hypertension, urinary tract infection, or a toxic drug, in an individual who is susceptible to kidney damage. Given the lack of a “cure” or means to reverse kidney damage, the identification and amelioration of initiation factors is crucial to prevent the development of CKD and its associated adverse outcomes. While case-control studies are hypothesis generating, the ideal study design for identification of initiation factors is a prospective cohort study (see Table 18-7 ). This would entail identifying and following a cohort of individuals free of kidney disease at baseline, with known susceptibility factors, and with and without exposure to the putative initiation factor, for the development of incident kidney disease defined as development of microalbuminuria, proteinuria, or reduced GFR.

Progression Factors

Progression factors worsen the kidney damage caused by initiation factors and lead to further decline in kidney function. Progression factors may also be termed perpetuation factors and this term better reflects the self-perpetuating nature of progressive kidney disease. Prospective cohort studies as well as clinical trials help to establish risk factor relationships between putative progression factors and kidney disease (see Table 18-7 ). The identification of progression factors using a cohort study design involves identification and follow-up of a cohort of patients with early-stage CKD to estimate rates of progression of disease. Alternatively, a clinical trial can be used to provide experimental evidence of a risk factor relationship (i.e., that the modification of the putative progression factor in a randomized controlled trial results in prevention of progression of disease). This would entail identification of a group of individuals in the earlier stages of CKD. Participants are randomly assigned to an intervention arm that receives the therapy designed to modify the risk factor under investigation, and a control arm that does not receive the study intervention, and rates of progression are compared between the two arms. Indicators of progression may include progression of microalbuminuria to overt proteinuria or reduced GFR, rate of decrease of GFR, or development of kidney failure necessitating dialysis or transplantation.

End-Stage Factors

End-stage factors are those that exacerbate the morbidity and mortality associated with kidney failure. As with progression factors, ideal study designs for studying end-stage factors include prospective cohort studies and randomized controlled trials (see Table 18-7 ). In a prospective study, a cohort of patients with kidney failure is followed to determine factors associated with adverse outcomes including morbidity and mortality. Alternatively, patients with kidney failure are randomized to receive interventions targeted at modifying putative end-stage factors and improving mortality and morbidity. Examples of indicators of morbidity include hospitalizations, poor quality of life measures, and cardiovascular disease complications.

CARDIOVASCULAR DISEASE AND CHRONIC KIDNEY DISEASE (see Chapter 48 )

It is well established that patients with kidney failure are at high risk of cardiovascular mortality ( Fig. 18-3 ). [15] [16] [17] Patients with CKD experience a high rate of fatal and nonfatal cardiovascular disease events prior to reaching kidney failure. [18] [19] [20] Patients in all stages of CKD are therefore considered in the “highest risk group” for development of cardiovascular disease and CKD is recognized as a cardiovascular risk equivalent. [21] [22] [23]

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FIGURE 18-3  Cardiovascular mortality defined by death due to arrhythmias, cardiomyopathy, cardiac arrest, myocardial infarction, atherosclerotic heart disease, and pulmonary edema in the general population (GP) (NCHS multiple cause of mortality data files ICD 9 codes 402, 404, 410–414, and 425-429, 1993) compared with kidney failure treated by dialysis or kidney transplant (USRDS special data request HCFA form 2746 #s 23, 26–29, and 31, 1994–1996). Data are stratified by age, race, and gender. CVD mortality is underestimated in kidney transplant recipients due to incomplete ascertainment of cause of death.  (From Foley RN, Parfrey PS, Sarnak MJ: Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis 32(5 Suppl 3) :S112–119, 1998; Sarnak MJ, Levey AS, Schoolwerth AC, et al: Kidney disease as a risk factor for development of cardiovascular disease: A statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Circulation 108:2154–2169 [Figure 1, page 2155], 2003.)

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An investigation of the natural history of disease in a large cohort of patients with CKD stages 2 to 4 demonstrated that death was a more likely outcome than progression to kidney failure in every stage of CKD ( Table 18-8 ).[24]There was a higher baseline prevalence of cardiovascular disease in patients who died, compared with those who survived, suggesting that cardiovascular disease accounted for a large proportion of the deaths. Thus, most patients in the earlier stages of CKD do not progress to kidney failure because of mortality due to cardiovascular disease; consequently, in studies of patients with earlier stages of CKD, cardiovascular disease is a major “competing outcome or risk” with kidney failure.


TABLE 18-8   -- Competing Risks of Death and Kidney Failure in Chronic Kidney Disease

End Points

GFR 60–89 No Proteinuria (n = 14,202)

Stage 2 GFR 60–89, Proteinuria (n = 1741)

Stage 3 GFR 30–59 (n = 11,278)

Stage 4 GFR 15–29 (n = 777)

Dis-enrolled from plan

14.9

16.2

10.3

6.6

Died (prior to transplant/dialysis)

10.2

19.5

24.3

45.7

Received a transplant

0.01

0.2

0.2

2.3

Initiated dialysis

0.06

0.9

1.1

17.6

None of the above through June 30, 2001

74.8

63.3

64.2

27.8

From Keith DS, Nichols GA, Gullion CM, et al: Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization. Arch Intern Med 164:659–663 [Table 2], 2004.

 

 

 

The relationship between CKD and cardiovascular disease is complex; CKD is a risk factor for cardiovascular disease and cardiovascular disease may be a risk factor for CKD ( Fig. 18-4 ). Several cardiovascular risk factors promote the development and progression of both CKD and cardiovascular disease; declining kidney function, in turn, is associated with elevated levels of cardiovascular risk factors[25] ( Table 18-9 ). As noted in Table 18-10 , several potential mechanisms underlie this complex relationship.[26]

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FIGURE 18-4  Chronic kidney disease (CKD) is a risk factor for cardiovascular disease (CVD) and cardiovascular disease may be a risk factor for progression of chronic kidney disease. Traditional cardiovascular disease risk factors promote the development and progression of both chronic kidney disease and cardiovascular disease. Declining kidney function is associated with elevated levels of traditional and nontraditional cardiovascular disease risk factors. It remains unknown whether nontraditional cardiovascular disease risk factors (dotted arrow) are important risk factors for progression of kidney disease.  (From Menon V, Gul A, Sarnak MJ: Cardiovascular risk factors in chronic kidney disease. Kidney Int 68:1413–1418 [Figure 1], 2005.)

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TABLE 18-9   -- Manifestations of Cardiovascular Disease in Chronic Kidney Disease and Associated Putative Risk Factors

Pathology

Traditional Risk Factors

Non-traditional Risk Factors

Cardiomyopathy

Older age

Albuminuria

Hypertension

Reduced glomerular filtration rate

Valvular disease

Anemia

Dyslipidemia

Inflammation

Smoking

Arteriosclerosis

Diabetes

Extracellular fluid volume overload

 

Abnormal calcium/phosphate metabolism

Atherosclerosis

Older age

Albuminuria

Male gender

Reduced glomerular filtration rate

Hypertension

Anemia

Diabetes

Inflammation

Dyslipidemia

Oxidative stress

Smoking

Endothelial dysfunction

Physical inactivity

Homocysteine

LVH

Lipoprotein (a)

 

Malnutrition

 

Thrombogenic factors

 

Sympathetic activity

 

Insulin resistance/metabolic syndrome

Arteriosclerosis

Older age

Albuminuria

Male gender

Reduced glomerular filtration rate

Smoking

Endothelial dysfunction

Hypertension

Abnormal calcium/phosphate metabolism

Diabetes

Metabolic syndrome

Dyslipidemia

 

From Menon V, Gul A, Sarnak MJ: Cardiovascular risk factors in chronic kidney disease. Kidney Int 68:1413–1418, 2005.

 

 

 


TABLE 18-10   -- Potential Mechanisms for Increased Cardiovascular Disease Risk in Chronic Kidney Disease

  

1.   

Chronic kidney disease is associated with an increase in prevalence of cardiovascular disease risk factors and these cardiovascular disease risk factors promote development and progression of CKD.

  

2.   

Cardiovascular disease is a risk factor for CKD.

  

3.   

Chronic kidney disease is an independent risk factor for cardiovascular disease.

From Menon V, Sarnak MJ: The epidemiology of chronic kidney disease stages 1 to 4 and cardiovascular disease: A high-risk combination. Am J Kidney Dis 45:223–232 [p 225], 2005.

CKD, chronic kidney disease.

 

 

 

 

An abundance of evidence exists in support of an association between reduced kidney function and cardiovascular disease morbidity and mortality.[23] Data from several population-based epidemiologic studies, such as the Atherosclerosis Risk In Communities Study,[20] Cardiovascular Health Study, [18] [27] [28] and the Hoorn Study,[29] show an association between reduced kidney function and risk of all-cause and cardiovascular disease mortality that persists after adjustment for traditional cardiovascular disease risk factors. In the Second National Health And Nutrition Examination Survey Mortality Study, patients with GFR <70 ml/min had a 68% higher risk of cardiovascular disease mortality compared with subjects with normal GFR.[30] In a pooled analysis of community-based studies including Atherosclerosis Risk in Communities Study, Cooperative Health Study, Framingham Heart Study, and the Framingham Offspring Study, CKD, defined as GFR of 15 to 60 ml/min/1.73 m2, was an independent predictor of a composite outcome of all-cause mortality as well as fatal and nonfatal cardiovascular disease events.[31] Finally, a study of over 1 million members of a large healthcare system demonstrated an independent graded association between reduced GFR and fatal and nonfatal cardiovascular events[32] ( Fig. 18-5 ). Possible explanations for the observed independent association between reduced GFR and cardiovascular disease are presented in Table 18-11 .

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FIGURE 18-5  Age-standardized rates of death from any cause (Panel A), cardiovascular events (Panel B), and hospitalization (Panel C), according to the estimated GFR among 1,120,295 ambulatory adults. A cardiovascular event was defined as hospitalization for coronary heart disease, heart failure, ischemic stroke, and peripheral arterial disease. Error bars represent 95% confidence intervals (CI). The rate of events is listed above each bar.  (From Age-Standardized Rates of Death from Any Cause (Panel A), Cardiovascular Events (Panel B), and Hospitalization (Panel C), According to the Estimated GFR. From Go AS, Chertow GM, Fan D, et al: Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 351:1296–1305 [Figure 1], 2004.)

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TABLE 18-11   -- Possible Explanations for the Observed Independent Association between Kidney Dysfunction and Cardiovascular Disease

Reduced Glomerular Filtration Rate

Albuminuria

Reduced GFR is associated with an increased level of nontraditional risk factors that are frequently not adjusted for in analyses.[153]

Microalbuminuria may be a marker of generalized endothelial dysfunction and vascular permeability.[190] [191]

Reduced GFR may be a marker of the severity of diagnosed vascular disease or of undiagnosed vascular disease.

Microalbuminuria may be associated with other traditional and nontraditional cardiovascular disease risk factors. [190] [192]

Reduced GFR may be a measure of residual confounding from traditional risk factors.[25]

Microalbuminuria may be a precursor for the development of early or incipient kidney disease.[39]

Patients with reduced GFR may not receive the benefits of optimal therapies such as aspirin, beta blockers, angiotensin converting enzyme inhibitors.[191]

 

 

GFR, glomerular filtration rate.

 

 

 

Evidence from several studies has established urinary albumin excretion as an independent predictor of cardiovascular outcomes. [23] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] The association between albumin excretion and cardiovascular disease appears to extend well below current definitions and cut offs for microalbuminuria and is independent of traditional cardiovascular risk factors ( Fig. 18-6 ). Potential reasons for the observed relationship between microalbuminuria and cardiovascular disease are presented in Table 18-11 .

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FIGURE 18-6  Adjusted effect of UAC on hazard function. Solid line shows estimated relation when logarithmic hazard is modeled as linear function of log(UAC). Dotted lines are 95% confidence limits for more general functional relation, as estimated by P-splines. Hatched area represents upper and lower limit of current definition of microalbuminuria (20 mg/L to 200 mg/L).  (From Hillege HL, Fidler V, Diercks GFH, et al for the Prevention of Renal and Vascular End Stage Disease (PREVEND) Study Group: Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population. Circulation 106:1777–1782 [Figure 1], 2002.)

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Given the close correlation between cardiovascular disease and CKD, we have organized the following discussion to reflect the association between these chronic diseases. Consequently, we have categorized risk factors for CKD as cardiovascular disease risk factors, kidney-related risk factors, and non-kidney-related risk factors.

CARDIOVASCULAR DISEASE RISK FACTORS AS RISK FACTORS FOR CHRONIC KIDNEY DISEASE

In this section we review the evidence relating cardiovascular disease risk factors to CKD. Although many of the risk factors discussed in this section may also promote the development of cardiovascular disease in individuals with CKD this is discussed in detail in Chapter 48 . Therefore, we limit our focus to the role of cardiovascular disease risk factors in promoting the development and progression of CKD.

Hypertension

Hypertension is well recognized as a risk factor for the development and progression of kidney disease. Several large prospective studies, including the MRFIT and the Systolic Hypertension in the Elderly Program, have established a strong relationship between hypertension and rate of decline in kidney function and development of kidney failure. [43] [44] [45] [46] [47] [48] Degree of blood pressure control appears to be an important determinant of rate of progression of kidney disease among treated patients with hypertension.[49] Systolic and diastolic blood pressure were demonstrated to be significant predictors for the development of microalbuminuria in several prospective studies of diabetic and non-diabetic populations. [50] [51] [52]

Data from randomized controlled trials examining the effect of blood pressure control on progression of kidney disease is less consistent. In the Modification of Diet in Renal Disease (MDRD) Study, a randomized, controlled trial of 840 persons with predominantly nondiabetic kidney disease and a GFR of 13 to 55 mL/min per 1.73 m2, strict blood pressure control did not slow progression of kidney disease over the 2.2-year follow-up period of the trial; however, in long-term follow-up the low target blood pressure slowed the progression of kidney disease in patients irrespective of cause of kidney disease, baseline GFR, or degree of proteinuria. [53] [54] In contrast, in the African American Study of Kidney Disease (AASK), 1094 African Americans with hypertensive renal disease were randomly assigned to usual or lower mean arterial pressure goals and to initial treatment with a beta-blocker, an ACE inhibitor, or a dihydropyridine calcium channel blocker, and followed up for 3 to 6.4 years. The lower blood pressure goal did not appear to confer any additional benefit of slowing progression of hypertensive nephrosclerosis, although ACE inhibitors appeared to be more effective than beta-blockers or dihydropyridine calcium channel blockers in slowing GFR decline.[55] One hypothesis to explain these discrepant results is that higher blood pressure is a stronger risk factor in patients with higher levels of proteinuria[56] ( Fig. 18-7 ), as was seen in the MDRD Study compared with AASK.[57] Similarly, a randomized controlled trial studied the effect of adding calcium channel blocker to achieve a lower blood pressure goal in patients with non-diabetic proteinuric nephropathies receiving background ACE-inhibitor therapy. This study was unable to demonstrate any additional benefit from further blood pressure reduction on progression of kidney disease,[58] possibly because of a lower than anticipated difference in achieved blood pressure between the two groups.[57] Thus, although there is consensus that high blood pressure is deleterious and promotes kidney injury and progression of kidney disease, further research is required to establish the ideal goal for target blood pressure.[57]

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FIGURE 18-7  Relative risk for kidney disease progression based on current level of systolic blood pressure and current urine protein excretion. The relative risk for patients with a current urine protein excretion of 1.0 g/d or greater represents 9336 patients (223 events), and the relative risk for patients with a current urine protein excretion less than 1.0 g/d represents 13,274 visits (88 events). The reference group for each is defined at a systolic blood pressure of 110 mm Hg to 119 mm Hg. Confidence intervals are truncated, as shown. Results are from a single multivariable model including two levels for urine protein excretion, six levels for systolic blood pressure, and the interaction of current systolic blood pressure and current urine protein excretion. Covariates include assignment to angiotensin-converting enzyme inhibitor versus control group, sex, age, baseline systolic blood pressure, baseline diastolic blood pressure, baseline urine protein excretion, baseline serum creatinine concentration (<2.0 or ≥2.0 mg/dL [<177 or ≥177 mmol/L]), interaction of baseline serum creatinine and baseline urine protein excretion, interaction of baseline serum creatinine and current urine protein excretion, and study terms.  (From Jafar TH, Stark PC, Schmid CH, et al: Progression of chronic kidney disease: The role of blood pressure control, proteinuria, and angiotensin-converting enzyme inhibition: A patient-level meta-analysis. Ann Intern Med 139:244–252 [Figure 1], 2003.)

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Diabetes

Diabetic kidney disease accounts for almost half of all incident cases of kidney failure in the United States. [59] [60] Several studies have established the role of diabetes as a predominant contributory factor for the development of CKD. In a population-based case-control study of White and African American individuals with type 1 and type 2 diabetes, the overall population-attributable risk for kidney failure was 42%.[61] In the United Kingdom Prospective Diabetes Study (UKPDS), 10 years after diagnosis of diabetes, the prevalence of microalbuminuria was 25%, of macroalbuminuria was 5.3%, and of elevated plasma creatinine or kidney failure was 0.8%.[62] In the Framingham Heart Study offspring cohort, baseline dysglycemia was associated with future risk of developing CKD.[63]

Among patients with diabetes, there appears to be a strong relationship between poor metabolic control and the risk for development of diabetic kidney disease. A Danish prospective study examined the incidence of diabetic kidney disease in patients with onset of type 1 diabetes between 1965 and 1979 followed up until death or until 1991. The cumulative incidence of diabetic kidney disease was 17%, and 19% to 28% of the patients had persistent microalbuminuria.[64] The primary risk factor for the development of kidney complications was long-term glycemic control. A Swedish population-based cohort study demonstrated dramatic decreases in the cumulative incidence of diabetic kidney disease with improved metabolic control.[65] In a prospective study of type 1 diabetes, glycemic control was the major determinant for the development of microalbuminuria.[66]

Evidence from intervention trials supports the data from observational studies regarding the importance of glycemic control. In the Diabetes Control and Complications Trial (DCCT), 1441 patients with type 1 diabetes and with and without retinopathy at baseline were randomized to receive intensive or conventional therapy. After a mean follow-up of 6.5 years, intensive therapy reduced the occurrence of microalbuminuria by 39%, and albuminuria by 54%[67]( Fig. 18-8 ). Thus reducing the incidence of diabetes and improving metabolic control among patients with diabetes are key components of any strategy aimed at reducing the burden of CKD.

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FIGURE 18-8  Cumulative incidence of urinary albumin excretion in patients with IDDM receiving intensive or conventional therapy. In the primary-prevention cohort (Panel A), intensive therapy reduced the adjusted mean risk of microalbuminuria by 34% (P < 0.04). In the secondary-intervention cohort (Panel B), patients with urinary albumin excretion of ≥40 mg per 24 hours at baseline were excluded from the analysis of the development of microalbuminuria. Intensive therapy reduced the adjusted mean risk of albuminuria by 56% (P = 0.01) and the risk of microalbuminuria by 43% (P = 0.001), as compared with conventional therapy.  (From The Diabetes Control and Complications Trial Research Group: The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 329:977–986 [Figure 3], 1993.)

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However, only one third of patients with newly diagnosed diabetes develop diabetic kidney disease, strongly suggesting the possibility of a major contribution of susceptibility factors to the pathogenesis of this disease. In the Inception Cohort Study, a prospective observational study of an inception cohort of 286 patients newly diagnosed with type 1 diabetes, baseline factors independently associated with development of persistent microalbuminuria included baseline urinary albumin excretion rate, male gender, mean arterial blood pressure, and haemoglobin A1c concentration.[51] Furthermore, progression of diabetic kidney disease also appears to be influenced by factors other than the level of glycemic control. For example, in the Reduction of End Points in NIDDM with the Angiotensin II Receptor Antagonist Losartan (RENAAL) study, which included 1513 patients with type 2 diabetes and nephropathy proteinuria, serum creatinine, serum albumin, and hemoglobin level were associated with increased risk of doubling of serum creatinine, dialysis, or transplantation for patients in whom blood pressure was controlled.[68] Diabetic nephropathy is discussed in detail in Chapter 36 .

Smoking

Several observational studies have suggested a link between smoking and CKD. In cross-sectional analysis of a population sample of 28,409 individuals, former and current smoking was associated with an approximately threefold increased risk of proteinuria.[69] Similar results were seen in an Australian population-based sample where the investigators found a graded relationship between smoking and proteinuria.[70] A European, multi-center, case-control study of men on dialysis demonstrated an increased risk of kidney failure among smokers.[71] Smoking was also a risk factor for kidney function decline in diabetic kidney disease[72] and essential hypertension.[73] Prospective studies have reproduced these findings. The population-based Prevention of Renal and Vascular End Stage Disease Study (PREVEND) noted that smoking was an independent predictor for the development of microalbuminuria and reduced GFR among healthy individuals.[74] Similar results were obtained from the Framingham Offspring Study.[75] In a prospective study of patients with CKD, smoking cessation was associated with decreased rate of progression and postponement of kidney failure over a 2-year follow-up period.[76] These data collectively suggest that smoking not only induces direct kidney injury but also potentiates kidney damage in the presence of other susceptibility and initiation factors.

Dyslipidemia

Several, but admittedly not all, studies suggest that dyslipidemia may promote development and progression of kidney disease.[77] In the Physician's Health Study, over a 14-year follow-up period, dyslipidemia was associated with increased risk of developing decreased kidney function (defined as creatinine >1.5 mg/dl) in men with normal kidney function at baseline[78] ( Fig. 18-9 ). In the Atherosclerosis Risk In Communities (ARIC) Study, high triglycerides and low high-density lipoprotein cholesterol were associated with an increased risk of developing decreased kidney function.[79] A study evaluating risk factors for incident CKD (defined as GFR <60 ml/min/1.73 m2) in patients with essential hypertension and normal glomerular filtration at baseline, noted that higher mean total cholesterol during follow up was a significant risk factor for the development of CKD.[80] In a hospital-based cohort, hypercholesterolemia was associated with a twofold increase in the risk of developing CKD.[81] Finally, low high-density lipoprotein cholesterol was an independent risk factor for the development of incident CKD (GFR <60 ml/min/1.73 m2) in the Framingham Offspring Study.[75]

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FIGURE 18-9  Association between total cholesterol categories and increased serum creatinine (≥1.5 mg/dl), adjusted for age (P for trend = 0.01).  (From Schaeffner ES, Kurth T, Curhan GC, et al: Cholesterol and the risk of renal dysfunction in apparently healthy men. J Am Soc Nephrol 14:2084–2091 [Figure 1], 2003.)

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Few randomized controlled trials have evaluated the effect of cholesterol lowering on the progression of CKD. The Cholesterol and Recurrent Events (CARE) Study was a randomized double-blind placebo controlled trial of pravastatin versus placebo in participants with previous myocardial infarction and total plasma cholesterol <240 mg/dl. In a post hoc subgroup analysis of this trial, pravastatin appeared to slow the rate of loss of kidney function in a subset of 690 individuals with estimated GFR <60 ml/min/1.73 m2.[82] In contrast, post hoc subgroup analysis of the Veterans Affairs High-Density Lipoprotein Intervention (VA-HIT) Trial, a randomized double-blind trial of gemfibrozil versus placebo in men with coronary disease, failed to demonstrate any benefit of gemfibrozil on progression of kidney disease in 399 participants with GFR of 30 to 60 ml/min/1.73 m2.[83] A meta-analysis of 13 prospective controlled trials concluded that treatment for hyperlipidemia may be associated with lower rate of decline in GFR and may decrease proteinuria compared with controls.[84] There is a need for a large randomized controlled trial in patients with CKD to provide definitive answers regarding whether treatment of hyperlipidemia retards the development and progression of CKD, and to identify optimal agents and target lipid levels.

Obesity

The emergence of obesity as a growing public health problem has led to its investigation as a risk factor for kidney disease. In a retrospective cohort study from Japan, a higher baseline body mass index was associated with increased risk for development of kidney failure.[85] In a small prospective study of patients who underwent unilateral nephrectomy, baseline obesity defined as body mass index >30 kg/m2 was associated with higher risk for the development of proteinuria and reduced kidney function.[86] Similarly, in a cohort of incident patients with biopsy-proven immunoglobulin A nephropathy, body mass index ≥25 kg/m2 at baseline was associated with the development of hypertension and kidney dysfunction.[87] Obesity also appears to predispose to the development of focal segmental glomerulosclerosis.[88] In a large retrospective cohort study of over 300,000 adults, there was a strong and graded independent relationship between body mass index and risk for kidney failure.[89] This relationship was present in subgroups based on race, gender, age, and comorbid conditions such as diabetes and hypertension. Several studies have also suggested a benefit of weight loss on preserving kidney function in obese patients. [90] [91] Further studies are required to confirm a pathophysiologic role for obesity in CKD and to demonstrate the benefits of weight loss in preventing progression of CKD.

Metabolic Syndrome

The metabolic syndrome is a clustering of risk factors that include abdominal obesity, dyslipidemia, hypertension, insulin resistance, hyperfiltration, and prothrombotic and proinflammatory states. Abundant data exist from observational studies in support of metabolic syndrome as a risk factor for the development of CKD. The association between the metabolic syndrome and CKD (defined as either GFR <60 ml/min/1.73 m2 or microalbuminuria) was assessed in cross-sectional analyses of the Third National Health and Nutrition Examination Survey (NHANES III).[92] The prevalence of CKD or microalbuminuria was higher among participants with two or more components of the metabolic syndrome compared with those with zero or one component. There was a linear relationship between presence of CKD and number of components of metabolic syndrome. In prospective analysis of 10,096 nondiabetic participants from the ARIC Study with normal baseline kidney function, after 9 years of follow-up, participants with metabolic syndrome had a 43% increased risk of developing CKD after adjusting for potential confounders.[93]This increased risk persisted after adjustment for the subsequent development of diabetes and hypertension during follow-up suggesting that metabolic syndrome is an independent risk factor for the development of kidney disease. Although observational evidence points to an association, there are no intervention trials aimed at studying the effect of treating metabolic syndrome on the risk of developing incident CKD. Such a trial would entail a complicated study design with multiple risk factor interventions. Glomerular hyperfiltration has also been identified as a new market of metabolic risk.[93a]

Cardiovascular Disease as a Risk Factor for Chronic Kidney Disease

Few studies have evaluated whether the presence of cardiovascular disease is an independent risk factor for progression of CKD and development of kidney failure. Patients with heart failure have decreased kidney perfusion that at times may lead to kidney failure and patients with coronary disease have a higher prevalence of renovascular disease, which in turn may promote progression of kidney disease.[94] In a Canadian cohort of patients in different stages of CKD, the presence of cardiovascular disease at baseline increased the probability of progression to kidney failure by 50%[95] ( Fig. 18-10 ). The magnitude of this effect persisted after multivariable adjustment for other established risk factors. In Medicare beneficiaries hospitalized for heart failure or myocardial infarction, there was a high prevalence of CKD stage 3 to 4 with more than half the cohort having reduced GFR.[96] The presence of CKD was associated with increased readmission and mortality rates, and a high risk for developing kidney failure. In a large cohort of hypertensive men, new-onset myocardial infarction doubled the future risk of kidney failure and heart failure increased the risk fivefold.[97] Thus, as described earlier, there is a complex interrelationship between cardiovascular disease and CKD resulting in a high-risk combination.

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FIGURE 18-10  Kaplan-Meier curves of time to RRT by cardiovascular disease status at baseline.  (From Levin A, Djurdjev O, Barrett B, et al: Cardiovascular disease in patients with chronic kidney disease: Getting to the heart of the matter. Am J Kidney Dis 38:1398–1407, 2001.)

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KIDNEY DISEASE-RELATED RISK FACTORS

In this section, we review risk factors for progression that are related to the characteristics of kidney disease and its treatment.

Proteinuria/Microalbuminuria

The National Kidney Foundation Kidney Disease Outcomes Quality Initiative guidelines define microalbuminuria as albumin excretion in 24-hour urine excretion of 30 to 300 mg/ day, or a spot urine albumin-to-creatinine ratio of 30 to 300 mg/g (some consider sex-specific cut-off values of 17 to 250 mg/g in men and 25 to 355 mg/g in women), or albumin concentration of >3 mg/dl in a spot urine specimen using an albumin-specific dipstick.[4] Albuminuria, macroalbuminuria, or clinical proteinuria is defined as urinary albumin excretion in excess of 300 mg/day, spot urine albumin-to-creatinine ratio above the microalbuminuria range, or ≥1+ tested in a spot urine sample using a conventional dipstick.

As described in an earlier section, there is abundant evidence in support of a strong and independent associa-tion between microalbuminuria and cardiovascular disease. In addition, a growing body of work that suggests that microalbuminuria or elevated urinary albumin excretion may be the earliest pathological marker of early kidney damage and may be a risk factor for the progression of diabetic and non-diabetic CKD. Microalbuminuria was inversely correlated to level of GFR in a cross-sectional analysis of 7728 individuals without diabetes.[98] In a prospective study of 537 patients with type 1 diabetes, 25% progressed to persistent microalbuminuria or macroalbuminuria during a 10-year follow-up period.[52] Similarly, in 286 newly diagnosed patients with type 1 diabetes, baseline urinary albumin excretion rate was a strong predictor for the development of persistent microalbuminuria.[51] In post hoc subgroup analysis of 7674 participants of the HOPE trial with albuminuria data available at baseline and at follow-up, baseline microalbuminuria was associated with a 17.5-fold increased risk for clinical proteinuria in individuals without and with diabetes. [39] [100] A higher baseline level of proteinuria and an increase in proteinuria during follow-up appear to be risk factors for faster kidney disease progression. For example, the rate of GFR decline was related to reduction in proteinuria in both the MDRD Study and the AASK Study. [101] [102] Similarly in the Ramipril Efficacy In Nephropathy (REIN) study of 352 patients with proteinuric non-diabetic chronic nephropathies, proteinuria was a strong predictor for the development of kidney failure[102] ( Fig. 18-11 ). As described in Chapter 54 , the effectiveness of agents that reduce the activity of the renin-angiotensin-aldosterone system (RAAS) on the progression of kidney disease appears to be mediated in part by lowering urine protein excretion.[102a]

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FIGURE 18-11  Progression to end-stage renal failure per tertile of baseline urinary protein excretion rate. Symbols are: (&z.cirf;) lowest; (▴) middle; (○) highest tertile.  (From Ruggenenti P, Perna A, Mosconi L, et al., Gruppo Italiano di Studi Epidemiologici in N: Urinary protein excretion rate is the best independent predictor of ESRF in non-diabetic proteinuric chronic nephropathies. Kidney Int 53:1209–1216, 1998.)

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Renin-Angiotensin-Aldosterone System Activity

The RAAS is a key regulator of blood pressure and has been implicated in hypertensive end-organ damage via its role in fluid and electrolyte balance, vasoconstrictor properties, and hypertrophic effects on the cardiovascular system. These hemodynamic effects suggest a role for RAAS in mediating kidney damage and the progression of kidney disease.[103] Several guidelines recommend ACE inhibitors and angiotensin receptor blockers (ARB) as first-line anti-hypertensive agents for patients with diabetic and non-diabetic kidney disease. [21] [106] [107] In addition, nonhemodynamic properties of the RAAS including oxidative stress, inflammation, and endothelial dysfunction,[106] may contribute to kidney damage. These pleiotropic effects indicate a potential benefit of RAAS blockade beyond its antihypertensive and antiproteinuric actions.

Several clinical trials demonstrate a beneficial effect of ACE inhibitors on kidney outcomes that was independent of blood pressure reduction and partly accounted for by their anti-proteinuric effects. [109] [110] [111] In data from the Collaborative Study Group, a randomized, controlled trial comparing captopril with placebo in patients with type 1 diabetes and overt kidney disease, captopril treatment was associated with a 50% reduction in the risk of the composite outcome of death, dialysis, and transplantation. This effect appeared to be independent of blood pressure.[110] In the Irbesartan Diabetic Nephropathy Trial (IDNT), 1715 hypertensive patients with kidney disease due to type 2 diabetes were assigned to irbesartan, amlodipine, or placebo with a target blood pressure of 135/85 mm Hg or less in all groups. The irbesartan arm had a lower risk of doubling of serum creatinine and kidney failure endpoints. These differences appeared to be independent of the blood pressures that were achieved in each arm.[111] In the RENAAL Study, a clinical trial in patients with type 2 diabetic kidney disease, losartan, an angiotensin II receptor antagonist, reduced the incidence of doubling of the serum creatinine concentration, kidney failure, and decreased level of proteinuria by 35%. The benefit of losartan on kidney outcomes exceeded that attributable to changes in blood pressure.[112] Similarly, in the REIN study where 352 patients were stratified by baseline proteinuria and assigned to ramipril or placebo plus conventional antihypertensive therapy with target diastolic blood pressure of under 90 mm Hg, ramipril reduced proteinuria and GFR decline beyond that expected with blood pressure reductions.[108] In contrast, in post hoc analyses of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), where hypertensive participants with one other coronary heart disease risk factor were randomized to chlorthalidone, amlodipine, or lisinopril, there was no difference in kidney outcomes of halving of GFR or kidney failure between the groups.[113]

Two meta-analyses demonstrated a benefit with ACE-inhibitor use on progression of kidney disease. ACE-inhibitor use was associated with decreased progression to macroalbuminuria in a meta-analysis of individual patient level data from 698 normotensive patients with type 1 diabetes mellitus and microalbuminuria, independent of blood pressure lowering.[114] These results were reproduced and extended by the ACE Inhibition in Progressive Renal Disease (AIPRD) Study Group with a patient-level meta-analysis of 1860 subjects with non-diabetic kidney disease, which demonstrated a benefit of ACE inhibitors in slowing the progression of non-diabetic kidney disease, defined as doubling of creatinine or kidney failure, which appeared to be independent of their effects on blood pressure and proteinuria.[115]

It appears clear that ACE inhibitors are the anti-hypertensive agents of choice in CKD due to the additional benefits derived from their ability to decrease urinary albumin excretion and other potential pleiotropic effects resulting from RAAS blockade. Clinical trials with appropriate comparators, which are specifically designed to study the effects of this class of drugs on kidney outcomes are needed to better define the mechanisms underlying the protective effects of these agents.

Dietary Protein

Several studies support the premise that dietary protein restriction delays the progression of CKD. In a cross-sectional analysis of data from the NHANES III, there was a correlation between dietary protein intake assessed from 24-hour dietary recall and albuminuria.[116] In the Nurse's Health Study, lower protein intake was associated with preservation of kidney function in women with reduced kidney function at baseline.[117] However, the MDRD Study was unable to demonstrate definitively that dietary protein restriction retards the progression of kidney disease in patients with CKD stage 3 to 4.[53] The lack of an effect appeared to be due to a short-term effect of dietary protein restriction to lower GFR and inadequate follow-up after the short-term effect.[118] In two meta-analyses, Foque and coworkers demonstrated a benefit of low-protein diets on progression of kidney disease for patients with diabetic and non-diabetic kidney disease. [121] [122] In a meta-analysis of 13 randomized trials, low-protein diets were associated with reduced rate of GFR decline.[121] Low-protein diets also appeared to reduce risk of kidney failure and death in a meta-analysis of 1413 patients with non-diabetic kidney disease and 108 patients with diabetic kidney disease.[122] Furthermore this effect appeared to be independent of blood pressure in both groups and glycemic control in patients with diabetes. Although these studies appear to support a role for dietary protein restriction in delaying progression of kidney disease, as stated in the National Kidney Foundation guidelines, these data are by no means conclusive.[4]

Low Serum Albumin

Several observational studies suggest an association between low serum albumin and faster progression of kidney disease. In the Modification of Diet in Renal Disease Study, low serum albumin at baseline was associated with a higher rate of decline of GFR in multivariate analyses.[47] In post hoc analysis from the Collaborative Study Group, low serum albumin was a predictor of loss of kidney function for patients with established diabetic kidney disease.[123] Similar results were found in a Japanese cohort of patients with type 2 diabetes.[124] However, there are no clinical trials evaluating whether a high serum albumin is protective against loss of kidney function.

Reduction in Kidney Mass

Acquired or congenital oligonephropathy with a concomitant reduction in total glomerular surface area available for filtration may induce systemic and glomerular hypertension, which leads to glomerular sclerosis and kidney injury, and the development of CKD.[125] The pathophysiologic process hypothesized to increase susceptibility, to initiate kidney damage, or to promote progression in this condition is glomerular hyperfiltration caused by a disparity between the need for excretion of wastes and the number of nephrons. The predominant cause of congenital oligonephropathy is low birthweight and this is discussed in more detail in the next section. Acquired causes of oligonephropathy include accidents, surgery, malignancies, and other pathology. Evidence regarding associations between reduced kidney mass and the development of CKD comes from autopsy studies, animal studies, and a few case control and cohort studies.

In whole kidney autopsy studies, female gender, older age, certain racial groups, and lower birthweight were associated with lower glomerular number.[126] In a uninephrectomized rat model, neonatal reduction of nephron mass was associated with the development of salt-sensitive hypertension and reduced kidney function in adulthood.[127] In a case-control study comparing kidneys of adults with primary hypertension or left ventricular hypertrophy, and age, gender, height, and weight matched normotensive controls, hypertension was associated with significantly fewer glomeruli per kidney and higher glomerular volume.[128] Whereas many studies of kidney donors have noted higher blood pressure and urinary albumin following nephrectomy, one study found a higher risk of proteinuria and hypertension.[129] These data, al-though not conclusive, collectively support the hypothesis that reduced nephron number may lead to hypertension and kidney damage. A more detailed discussion of low nephron endowment as a risk factor for CKD is presented in Chapter 19 .

Primary Hyperfiltration States

In this category we include those conditions in which glomerular hyperfiltration results from alterations in metabolism rather than reduction in nephron number. Examples of physiologic states leading to hyperfiltration include pregnancy,[130] and high protein intake[131]; examples of pathologic states include type and type 2 diabetes,[132] obesity,[133] sickle cell disease,[134] and glycogen storage diseases.[135] As with congenital or acquired oligonephropathy, it is unclear whether the hyperfiltration associated with these conditions is a susceptibility factor, is directly involved in the initiation of kidney injury, or promotes faster progression.

Anemia

Several observational studies have established that anemia is prevalent in the earlier stages of CKD and pervasive in kidney failure. [24] [138] [139] [140] Other studies have demonstrated that anemia is associated with a faster progression of kidney failure; for example, the randomized cohort of the RENAAL study, each 1 g/dL decrease in hemoglobin concentration from baseline was associated with an 11% increase in the risk of developing kidney failure over a mean follow-up time of 3.4 years.[139] The severity of anemia is closely related to both the duration and stage of CKD. Given this close correlation, it is inherently difficult to establish causality and resolve whether anemia is a risk factor for progression or a marker for more severe kidney disease. A few clinical trials examining the effect of treatment of anemia on progression of kidney disease have demonstrated a benefit of anemia correction with erythropoietin [142] [143] or iron.[142] However in other trials designed to study safety of erythropoietin, where kidney endpoints were not the primary outcomes, there was no effect on rate of decline in kidney function. [145] [146] [147] [148] [149] [150] [151] Three ongoing trials of cardiovascular disease, the Trial to Reduce Cardiovascular Events with Aranesp Therapy (TREAT),[150] Correction of Hemoglobin and Outcomes in Renal Insufficiency (CHOIR),[151] and Cardiovascular Risk Reduction by Early Anemia Treatment with Epoetin Beta (CREATE),[152] may provide more data regarding the utility of anemia correction in slowing progression of kidney disease as a secondary outcome.

Kidney Disease-Related Nontraditional Cardiovascular Disease Risk Factors

Nontraditional or novel risk factors for CVD are those that were not described in the Framingham study. Several of these novel risk factors increase in prevalence as kidney function declines and thus may potentially contribute to the excess risk of cardiovascular disease seen in CKD 15[153] ( Table 18-12 ). A scientific statement from the American Heart Association defines four criteria for a nontraditional risk factor ( Table 18-13 ).[23] There are limited trial data evaluating these nontraditional factors as risk factors for the development and progression of CKD.


TABLE 18-12   -- Traditional and Nontraditional Cardiovascular Risk Factors in Chronic Kidney Disease

Traditional Risk Factors

Nontraditional Risk Factors

Older age

Albuminuria/Proteinuria

Male sex

Homocysteine

Hypertension

Lipoprotein (a) and apolipoprotein (a) isoforms

Higher LDL cholesterol

Lipoprotein remnants

Low HDL cholesterol

Anemia

Diabetes

Abnormal calcium/phosphate metabolism

Smoking

Extracellular fluid overload

Physical inactivity

Oxidative stress

Menopause

Inflammation (C-reactive protein)

Family history of cardiovascular disease

Malnutrition

Thrombogenic factors

LVH

Sleep disturbances

Altered nitric oxide/endothelin balance

From Sarnak MJ, Levey AS: Cardiovascular disease and chronic renal disease: A new paradigm. Am J Kidney Dis 35:S117–131 [Table 4], 2000.

HDL, high-density lipoprotein; LDL, low-density lipoprotein; LVH, left ventricular hypertrophy.

 

 

 

 


TABLE 18-13   -- Criteria for Nontraditional Risk Factors

  

1.   

A biologically plausible role for the factor in promoting cardiovascular risk

  

2.   

A dose response relationship between level of the risk factor and severity of kidney disease

  

3.   

An association between the factor and cardiovascular disease in CKD

  

4.   

Evidence from clinical trials that treatment of the risk factor decreases cardiovascular risk

From Sarnak MJ, Levey AS, Schoolwerth AC, et al: Kidney disease as a risk factor for development of cardiovascular disease: A statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Circulation 108:2154–2169 [Page 2158], 2003.

CKD, chronic kidney disease.

 

 

 

 

Several cross-sectional studies have suggested that many of these factors such as markers of inflammation, oxidative stress, and endothelial dysfunction, homocysteine, and lipoprotein (a) [155] [156] [157] [158] [159] [160] [161] are elevated in CKD; however, few prospective studies and no intervention trials have investigated their role in the progression of kidney disease. In cross-sectional analyses of NHANES III data, there was a direct correlation between prevalence of CKD and markers of insulin resistance such as levels of serum insulin, C-peptide, glycosylated hemoglobin, and Homeostasis Model Assessment-insulin resistance.[160] In long-term prospective follow-up of the randomized cohort of the MDRD Study, leptin, C-reactive protein, homocysteine, cysteine, and B vitamins were not associated with progression of kidney disease. [163] [164] In contrast, data from the Cardiovascular Health Study demonstrated an association between rate of GFR decline and level of inflammatory and prothrombotic markers including C-reactive protein, white blood cell count, factor VII, and fibrinogen.[163] In a cohort of 131 patients with incident kidney disease, asymmetric dimethyl arginine, a marker of endothelial function, was an independent predictor for the development of kidney failure.[164] At this point, there is insufficient evidence in support of or against a role for nontraditional risk factors in CKD. Further laboratory, observational, and experi-mental studies are necessary to investigate nontraditional risk factors both from a pathophysiologic and therapeutic perspective.

Other Kidney Disease-Related Risk Factors

Other kidney disease-related risk factors for CKD include autoimmune disorders, chronic infections, drug toxicity, especially anti-inflammatory drugs, endogenous nephrotoxins (e.g., paraproteins), exogenous nephrotoxins, nephrolithiasis, inherited disorders, and cystic diseases ( Table 18-14 ). These topics are covered in detail in other chapters.


TABLE 18-14   -- Percentage of Incident End-Stage Kidney Disease from 1990–2000 Due to Non-diabetic Kidney Disease by Race/Ethnicity

Non-diabetic Kidney Disease

Whites

Blacks

Asians

Native Americans

Hispanics

Hypertension

24.0%

32.9%

23.5%

11.0%

16.5%

Glomerulonephritis/vasculitis

12.0%

10.4%

17.3%

10.4%

11.2%

Interstitial nephritis

4.8%

2.0%

2.9%

1.8%

2.4%

Cystic disease/hereditary

3.8%

1.5%

2.2%

1.2%

2.5%

Cancers/tumors

2.4%

1.3%

0.8%

0.8%

1.0%

Miscellaneous

3.7%

4.7%

1.6%

1.7%

2.1%

Unknown

5.7%

5.1%

5.5%

3.9%

4.1%

Total

56.5%

57.95%

53.8%

30.8%

39.8%

Adapted from the U.S. Renal Data System, USRDS: 2002 Annual Data Report: Atlas of End-Stage Renal Disease in the United States. Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2002.

 

 

 

OTHER RISK FACTORS FOR CHRONIC KIDNEY DISEASE

In this section, we review other significant risk factors for development or progression of CKD.

Family History

There are several hereditary kidney diseases that follow specific inheritance patterns and are due to single gene mutations. Examples of these include autosomal dominant polycystic kidney disease types 1 and 2 involving polycystin the protein product of the PKD 1 and 2 genes [167] [168] and x-linked Fabry disease involving the human α-galactosidase A gene.[167] These genetic factors would appear to be initiation factors as all affected individuals acquire the disease. Although the majority of kidney diseases are not associated with identifiable genetic defects, the presence of familial aggregation of kidney disease suggests a multifactorial etiology involving a genetic component with regard to susceptibility. [75] [170] [171] [172]

Data in support of family history as a risk factor for the development of CKD come from case-control and prospective studies. In a population-based case-control study, prevalence of kidney disease among first-degree relatives was compared between 689 incident kidney failure patients with nonhereditary kidney disease, and 361 population-based controls.[171] After adjustment for other covariates including sociodemographic variables, and family history of diabetes and hypertension, having two or more affected first-degree relatives was associated with a 10-fold increase in the odds of kidney failure. Thus in this study, family history could potentially be a susceptibility factor (siblings of affected individuals are more susceptible to disease), an initiation factor (family history increases vulnerability to other insults or injury), or a progression factor (family history promotes progression to end-stage disease). Faronato and colleagues compared albumin excretion rate among siblings of probands with type 2 diabetes, with and without albuminuria.[172] Siblings of probands with albuminuria had an almost four times increased odds of abnormal albumin excretion rates compared with siblings of probands without albuminuria after adjustment for several confounding variables including age, history and duration of hypertension, glycated haemoglobin A1c, duration of diabetes, body mass index, smoking, and alcohol. In addition, non-diabetic siblings of probands with albuminuria had high normal albumin excretion rates compared with non-diabetic siblings of probands without albuminuria. In this example, family history of albuminuria appears to be a susceptibility factor that increases susceptibility to kidney injury secondary to diabetes and an initiation factor in non-diabetic siblings. Freedman and colleagues[173]demonstrated that in a cohort of 4365 incident dialysis patients, 20% of these individuals reported a family history of kidney failure among first or second-degree relatives. These data collectively suggest that inherent genetic factors may play a role in the initiation, susceptibility, and progression of kidney disease irrespective of the underlying cause of kidney disease.

Low Birthweight (see Chapter 19 )

Intrauterine growth retardation or low birthweight (or both) appears to be associated with reduced nephron number. In an autopsy study of 35 neonates who died within 2 weeks of birth and who were free of congenital abnormalities of the genito-urinary tract, low birthweight was associated with reduced glomerular number and increased glomerular volume.[174] In a study using serial ultrasounds to estimate kidney size at 0, 3, and 18 months, in infants who were small or appropriate for gestational age, low birthweight was associated with smaller kidneys at birth and impaired kidney growth.[175] As discussed in greater detail in Chapter 19 , these findings have led to the hypothesis that congenital retardation of kidney development may contribute to the pathogenesis of CKD.

The relationship between birthweight and kidney function has been assessed in several prospective studies. In a cohort of 422 young adults whose gestational age was <32 weeks at birth, there was a positive correlation between birth-weight and GFR, and a negative correlation of birthweight with serum creatinine concentration and albumin creatinine ratio.[176] In a cohort of African Americans and whites, higher birthweight was associated with an increase in the number of glomeruli.[177] Epidemiologic studies in Pima Indians and Australian Aboriginals, racial groups at high risk for kidney disease, demonstrated that low birthweight was associated with albuminuria and kidney damage. [180] [181] Thus the weight of existing evidence appears to support a relationship between low birthweight and reduced kidney size and therefore increased susceptibility to kidney disease. Putative mechanisms for impaired nephrogenesis in the setting of intra uterine growth retardation include malnutrition, protein and vitamin deficiencies, maternal hyperglycemia, smoking, alcohol ingestion, and iron deficiency.

Racial Factors

Rates of kidney failure are higher among African Americans compared with whites.[180] The basis of this racial difference is unclear and possibly reflects both genetic etiology, as well as lifestyle and environmental differences. Although this is an inherently difficult question to resolve, a few prospective studies have attempted to investigate race as an independent risk factor for kidney disease.

In prospective analysis of 9802 African American and White adults who participated in NHANES II, during 10 years of follow-up African Americans had an almost threefold increased risk for a composite outcome of kidney failure or dying from kidney disease ( Fig. 18-12 ).[181] Only half of this excess risk was explained by identifiable sociodemographic, lifestyle, and clinical factors. The results of this study indicated that race or factors associated with it could potentially be involved in susceptibility to kidney disease, and in the initiation and progression of kidney disease. The effect of race on the development of earlier stages of kidney disease, defined as serum creatinine ≥1.5 mg/dl in men and ≥1.2 mg/dl in women, was studied in a cohort of individuals aged 18 to 30 years.[182] In univariate analyses black race was associated with increased risk of developing kidney disease; however, in multivariable analysis this relationship was attenuated in women but remained significant in men. Similarly, data from the Atherosclerosis Risk in Communities Study, a population-based cohort, showed that while African American race was associated with increased odds of developing reduced kidney function (defined as increase in serum creatinine of 0.4 mg/dl), 80% of the excess risk was attributable to sociodemographic, environmental, and behavioral factors, and comorbid conditions.[183] In these examples, race and race-related factors may be susceptibility or initiation factors for the development of kidney disease.

000027

000519

FIGURE 18-12  Cumulative incidence of chronic kidney disease, according to race and attained age, in NHANES II, 1976 to 1992. Results are weighted to the general United States population. Solid line, African Americans; dashed line, whites. The cumulative incidence of CKD among African Americans was significantly higher than that among whites (log-rank test, P < 0.001).  (From Tarver-Carr ME, Powe NR, Eberhardt MS, et al: Excess risk of chronic kidney disease among African-American versus white subjects in the United States: A population-based study of potential explanatory factors. J Am Soc Nephrol 13:2363–2370 [Figure 1, p 2366], 2002.)

000519

 

 

There is a racial difference in the rate of progression of kidney disease and potentially also with regard to development of cardiovascular disease. In a birth cohort analysis using data from the NHANES III, Hsu and colleagues[184]noted that although the prevalence of CKD was similar among black and white adults, the incidence rate of kidney failure was much higher among the blacks. Thus, for 100 blacks with CKD in 1991, there were five incident cases of kidney failure in 1996, compared with 1 incident case per 100 whites. Kiberd and co-workers[185] modeled the cumulative lifetime risk of kidney failure and found the risk was higher for African American men and women compared with whites. These data suggest a role for race and race-related factors in the progression of kidney disease. In summary, although it appears that racial disparities beyond differences in other known potential risk factors exist in the development and progression of kidney disease, the exact mechanisms for this excess risk remain unresolved.

Other Non-Kidney Related Factors

Other non-kidney related risk factors for CKD that we have not discussed include male gender and older age. These topics are covered in detail in Chapters 20 and 21 .

CONCLUSION

Given our current state of knowledge regarding risk factors for CKD, it is estimated that a significant portion of the U.S. population is vulnerable to the development and progression of kidney disease ( Table 18-15 ). Despite progress in the management of kidney failure, gains in reducing the incidence, prevalence, morbidity, and mortality attributable to CKD have been inadequate. As summarized in this chapter, several modifiable risk factors appear to be involved in the development and progression of kidney disease. These data imply that early interventions targeting these risk factors can prevent the development of CKD and delay its progression, as well as reduce associated adverse outcomes. Therefore, a better understanding of these risk factor associations and the identification of as-yet unrecognized mechanisms of development and progression are crucial to reduce the risk of developing kidney disease and to improve outcomes in patients with kidney disease.


TABLE 18-15   -- Prevalence of Individuals at Risk for Chronic Kidney Disease

Risk Factor

Prevalence

 

Estimated %

Estimated N

Diabetes mellitus

Diagnosed: 5.1% of adults age ≥ 20

10.2 million

Undiagnosed: 2.7% of adults age ≥ 20

5.4 million

Hypertension

24.0% of adults age ≥18

43.1 million

Systemic lupus erythematosus

-0.05% definite or suspected

-239,000

Functioning kidney graft

-0.03%

88,311 as of 12/31/98

African American

12.3%

34.7 million

Hispanic or Latino (of any race)

12.5%

35.3 million

American Indian and Alaska Native

0.9%

2.5 million

Age 60–70

7.3%

20.3 million

Age ≥ 70

9.2%

25.5 million

Acute kidney failure

-0.14%

-363,000 non-federal hospital stays in 1997

Daily NSAID use

-5.2% with rheumatoid arthritis or osteoarthritis (assumed daily use)

-13 million assumed daily use

-30% yearly use

-75 million yearly use

From Kidney Disease Outcome Quality Initiative: 2002 K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39:S1–246 [Table 42, p S74], 2002.

 

 

 

References

1. United States Renal Data System: Excerpts from the 2000 U.S. Renal Data System Annual Report: Atlas of End Stage Renal Disease in the United States.  Am J Kidney Dis  2000; 36:S1-S279.

2. Hunsicker LG: The consequences and costs of chronic kidney disease before ESRD.  J Am Soc Nephrol  2004; 15(5):1363-1364.

3. Special report from the National Kidney Foundation Task Force on Cardiovascular Disease: Controlling the epidemic of cardiovascular disease in chronic renal disease: What do we know? What do we need to learn? Where do we go from here?.  Am J Kidney Dis  1998; 32(5):S1-S199.

4. Kidney Disease Outcome Quality Initiative: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification.  Am J Kidney Dis  2002; 39(2 Suppl 2):S1-S246.

5. Coresh J, Astor BC, Greene T, et al: Prevalence of chronic kidney disease and decreased kidney function in the adult U.S. population: Third National Health and Nutrition Examination Survey.  Am J Kidney Dis  2003; 41(1):1-12.

6. Levey AS, Eckardt KU, Tsukamoto Y, et al: Definition and classification of chronic kidney disease: A position statement from Kidney Disease: Improving Global Outcomes (KDIGO).  Kidney Int  2005; 67(6):2089-2100.

7. Keane WF, Eknoyan G: Proteinuria, albuminuria, risk, assessment, detection, elimination (PARADE): A position paper of the National Kidney Foundation.  Am J Kidney Dis  1999; 33(5):1004-1010.

8. Levey AS, Bosch JP, Lewis JB, et al: A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group.  Ann Intern Med  1999; 130(6):461-470.

9. Hill AB: The environment and disease: Association or causation?.  Proc R Soc Med  1965; 58:295-300.

10. Gordis L: Epidemiology,  2nd ed. Philadelphia, WB Saunders, 2000.

11. Szklo M, Nieto JF: Epidemiology Beyond the Basics,  Gaithersburg, Aspen Publishers, Inc., 2000.

12. The Heart Outcomes Prevention Evaluation Study, Investigators : Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients.  N Engl J Med  2000; 342(3):145-153.

13. Mann JF, Gerstein HC, Pogue J, et al: Renal insufficiency as a predictor of cardiovascular outcomes and the impact of ramipril: The HOPE randomized trial.  Ann Intern Med  2001; 134(8):629-636.

14. Anders H-J, Patole PS: Toll-like receptors recognize uropathogenic Escherichia coli and trigger inflammation in the urinary tract.  Nephrol Dial Transplant  2005; 20(8):1529-1532.

15. Coresh J, Astor B, Sarnak MJ: Evidence for increased cardiovascular disease risk in patients with chronic kidney disease.  Curr Opin Nephrol Hypertens  2004; 13(1):73-81.

16. Cheung AK, Sarnak MJ, Yan G, et al: Atherosclerotic cardiovascular disease risks in chronic hemodialysis patients.  Kidney Int  2000; 58(1):353-362.

17. Foley RN, Parfrey PS, Sarnak MJ: Clinical epidemiology of cardiovascular disease in chronic renal disease.  Am J Kidney Dis  1998; 32(5 Suppl 3):S112-S119.

18. Fried LF, Shlipak MG, Crump C, et al: Renal insufficiency as a predictor of cardiovascular outcomes and mortality in elderly individuals.  J Am Coll Cardiol  2003; 41(8):1364-1372.

19. Jungers P, Massy ZA, Khoa TN, et al: Incidence and risk factors of atherosclerotic cardiovascular accidents in predialysis chronic renal failure patients: A prospective study.  Nephrol Dial Transplant  1997; 12(12):2597-2602.

20. Manjunath G, Tighiouart H, Ibrahim H, et al: Level of kidney function as a risk factor for atherosclerotic cardiovascular outcomes in the community.  J Am Coll Cardiol  2003; 41(1):47-55.

21. Chobanian AV, Bakris GL, Black HR, et al: The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: The JNC 7 report.  JAMA  2003; 289(19):2560-2572.

22. Mosca L, Appel LJ, Benjamin EJ, et al: Evidence-based guidelines for cardiovascular disease prevention in women.  Circulation  2004; 109(5):672-693.

23. Sarnak MJ, Levey AS, Schoolwerth AC, et al: Kidney disease as a risk factor for development of cardiovascular disease: A statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention.  Circulation  2003; 108(17):2154-2169.

24. Keith DS, Nichols GA, Gullion CM, et al: Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization.  Arch Intern Med  2004; 164(6):659-663.

25. Foley RN, Wang C, Collins AJ: Cardiovascular risk factor profiles and kidney function stage in the US general population: The NHANES III study.  Mayo Clin Proc  2005; 80(10):1270-1277.

26. Menon V, Gul A, Sarnak MJ: Cardiovascular risk factors in chronic kidney disease.  Kidney Int  2005; 68(4):1413-1418.

27. Manjunath G, Tighiouart H, Coresh J, et al: Level of kidney function as a risk factor for cardiovascular outcomes in the elderly.  Kidney Int  2003; 63(3):1121-1129.

28. Shlipak MG, Fried LF, Stehman-Breen C, et al: Chronic renal insufficiency and cardiovascular events in the elderly: Findings from the Cardiovascular Health Study.  Am J Geriatr Cardiol  2004; 13(2):81-90.

29. Henry RM, Kostense PJ, Bos G, et al: Mild renal insufficiency is associated with increased cardiovascular mortality: The Hoorn Study.  Kidney Int  2002; 62(4):1402-1407.

30. Muntner P, He J, Hamm L, et al: Renal insufficiency and subsequent death resulting from cardiovascular disease in the United States.  J Am Soc Nephrol  2002; 13(3):745-753.

31. Weiner DE, Tighiouart H, Amin MG, et al: Chronic kidney disease as a risk factor for cardiovascular disease and all-cause mortality: A pooled analysis of community-based studies.  J Am Soc Nephrol  2004; 15(5):1307-1315.

32. Go AS, Chertow GM, Fan D, et al: Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization.  N Engl J Med  2004; 351(13):1296-1305.

33. Arnlov J, Evans JC, Meigs JB, et al: Low-grade albuminuria and incidence of cardiovascular disease events in nonhypertensive and nondiabetic individuals: The Framingham Heart Study.  Circulation  2005; 112(7):969-975.

34. Borch-Johnsen K, Feldt-Rasmussen B, Strandgaard S, et al: Urinary albumin excretion. An independent predictor of ischemic heart disease.  Arterioscler Thromb Vasc Biol  1999; 19(8):1992-1997.

35. Dinneen SF, Gerstein HC: The association of microalbuminuria and mortality in non-insulin-dependent diabetes mellitus. A systematic overview of the literature.  Arch Intern Med  1997; 157(13):1413-1418.

36. Freedman BI, Langefeld CD, Lohman KK, et al: Relationship between albuminuria and cardiovascular disease in type 2 diabetes.  J Am Soc Nephrol  2005; 16:2156-2161.

37. Hillege HL, Fidler V, Diercks GFH, et al: Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population.  Circulation  2002; 106(14):1777-1782.

38. Klausen K, Borch-Johnsen K, Feldt-Rasmussen B, et al: Very low levels of microalbuminuria are associated with increased risk of coronary heart disease and death independently of renal function, hypertension, and diabetes.  Circulation  2004; 110(1):32-35.

39. Mann JF, Yi QL, Gerstein HC: Albuminuria as a predictor of cardiovascular and renal outcomes in people with known atherosclerotic cardiovascular disease.  Kidney Int  2004; 66(92):S59-S62.

40. Nakamura S, Kawano Y, Inenaga T, et al: Microalbuminuria and cardiovascular events in elderly hypertensive patients without previous cardiovascular complications.  Hypertens Res  2003; 26(8):603-608.

41. Wachtell K, Ibsen H, Olsen MH, et al: Albuminuria and cardiovascular risk in hypertensive patients with left ventricular hypertrophy: The LIFE study.  Ann Intern Med  2003; 139(11):901-906.

42. Gerstein HC, Mann JF, Yi Q, et al: Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals.  JAMA  2001; 286(4):421-426.

43. Pascual JM, Rodilla E, Gonzalez C, et al: Long-term impact of systolic blood pressure and glycemia on the development of microalbuminuria in essential hypertension.  Hypertension  2005; 45:1125-1130.

44. Klag MJ, Whelton PK, Randall BL, et al: Blood pressure and end-stage renal disease in men.  N Engl J Med  1996; 334(1):13-18.

45. Haroun MK, Jaar BG, Hoffman SC, et al: Risk factors for chronic kidney disease: A prospective study of 23,534 men and women in Washington County, Maryland.  J Am Soc Nephrol  2003; 14(11):2934-2941.

46. Hsu C-y, McCulloch CE, Darbinian J, et al: Elevated blood pressure and risk of end-stage renal disease in subjects without baseline kidney disease.  Arch Intern Med  2005; 165(8):923-928.

47. Hunsicker LG, Adler S, Caggiula A, et al: Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study.  Kidney Int  1997; 51(6):1908-1919.

48. Young JH, Klag MJ, Muntner P, et al: Blood pressure and decline in kidney function: Findings from the Systolic Hypertension in the Elderly Program (SHEP).  J Am Soc Nephrol  2002; 13(11):2776-2782.

49. Vupputuri S, Batuman V, Muntner P, et al: Effect of blood pressure on early decline in kidney function among hypertensive men.  Hypertension  2003; 42(6):1144-1149.

50. Ramirez SP, McClellan W, Port FK, Hsu SI: Risk factors for proteinuria in a large, multiracial, southeast Asian population.  J Am Soc Nephrol  2002; 13(7):1907-1917.

51. Hovind P, Tarnow L, Rossing P, et al: Predictors for the development of microalbuminuria and macroalbuminuria in patients with type 1 diabetes: Inception Cohort Study.  BMJ  2004; 328(7448):1100-1105.

52. Rossing P, Hougaard P, Parving H-H: Risk factors for development of incipient and overt diabetic nephropathy in type 1 diabetic patients: A 10-year prospective observational study.  Diabetes Care  2002; 25(5):859-864.

53. Klahr S, Levey AS, Beck GJ, et al: The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. Modification of Diet in Renal Disease Study Group.  N Engl J Med  1994; 330(13):877-884.

54. Sarnak MJ, Greene T, Wang X, et al: The effect of a lower target blood pressure on the progression of kidney disease: Long-term follow-up of the modification of diet in renal disease study.  Ann Intern Med  2005; 142(5):342-351.

55. Wright Jr JT, Bakris G, Greene T, et al: Effect of blood pressure lowering and antihypertensive drug class on progression of hypertensive kidney disease: Results from the AASK trial.  JAMA  2002; 288(19):2421-2431.

56. Jafar TH, Stark PC, Schmid CH, et al: Progression of chronic kidney disease: The role of blood pressure control, proteinuria, and angiotensin-converting enzyme inhibition: A patient-level meta-analysis.  Ann Intern Med  2003; 139(4):244-252.

57. Levey AS, Mulrow CD: An editorial update: What level of blood pressure control in chronic kidney disease?.  Ann Intern Med  2005; 143(1):79-81.

58. Ruggenenti P, Perna A, Loriga G, et al: Blood-pressure control for renoprotection in patients with non-diabetic chronic renal disease (REIN-2): multicentre, randomised controlled trial.  Lancet  2005; 365:939-946.

59.   American Diabetes Association. Diabetic Nephropathy, 2002.

60. US Renal Data Systems: USRDS 2003 Annual Data Report: Atlas of End Stage Renal Diseases in the United States,  Bethesda, MD, National Institutes of Health. The National Institute of Diabetes and Digestive and Kidney Disease. Division of Kidney, Urologic, and Hematologic Diseases, 2003.

61. Perneger TV, Brancati FL, Whelton PK, Klag MJ: End-stage renal disease attributable to diabetes mellitus.  Ann Intern Med  1994; 121(12):912-918.

62. Adler AI, Stevens RJ, Manley SE, et al: Development and progression of nephropathy in type 2 diabetes: The United Kingdom Prospective Diabetes Study (UKPDS 64).  Kidney Int  2003; 63(1):225-232.

63. Fox CS, Larson MG, Leip EP, et al: Glycemic status and development of kidney disease: The Framingham Heart Study.  Diabetes Care  2005; 28(10):2436-2440.

64. Rossing P, Rossing K, Jacobsen P, Parving HH: Unchanged incidence of diabetic nephropathy in IDDM patients.  Diabetes  1995; 44(7):739-743.

65. Bojestig M, Arnqvist HJ, Hermansson G, et al: Declining incidence of nephropathy in insulin-dependent diabetes mellitus.  N Engl J Med  1994; 330(1):15-18.

66. Powrie JK, Watts GF, Ingham JN, et al: Role of glycaemic control in development of microalbuminuria in patients with insulin dependent diabetes.  BMJ  1994; 309(6969):1608-1612.

67. The Diabetes Control and Complications Trial Research Group : The effect of inten-sive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus.  N Engl J Med  1993; 329(14):977-986.

68. Keane WF, Brenner BM, de Zeeuw D, et al: The risk of developing end-stage renal disease in patients with type 2 diabetes and nephropathy: The RENAAL study.  Kidney Int  2003; 63(4):1499-1507.

69. Halimi JM, Giraudeau B, Vol S, et al: Effects of current smoking and smoking discontinuation on renal function and proteinuria in the general population.  Kidney Int  2000; 58(3):1285-1292.

70. Briganti EM, Branley P, Chadban SJ, et al: Smoking is associated with renal impairment and proteinuria in the normal population: The AusDiab kidney study. Australian Diabetes, Obesity and Lifestyle Study.  Am J Kidney Dis  2002; 40(4):704-712.

71. Orth SR, Stockmann A, Conradt C, et al: Smoking as a risk factor for end-stage renal failure in men with primary renal disease.  Kidney Int  1998; 54(3):926-931.

72. Chuahirun T, Wesson DE: Cigarette smoking predicts faster progression of type 2 established diabetic nephropathy despite ACE inhibition.  Am J Kidney Dis  2002; 39(2):376-382.

73. Regalado M, Yang S, Wesson DE: Cigarette smoking is associated with augmented progression of renal insufficiency in severe essential hypertension.  Am J Kidney Dis  2000; 35(4):687-694.

74. Pinto-Sietsma SJ, Mulder J, Janssen WM, et al: Smoking is related to albuminuria and abnormal renal function in nondiabetic persons.  Ann Intern Med  2000; 133(8):585-591.

75. Fox CS, Larson MG, Leip EP, et al: Predictors of new-onset kidney disease in a community-based population.  JAMA  2004; 291(7):844-850.

76. Schiffl H, Lang SM, Fischer R: Stopping smoking slows accelerated progression of renal failure in primary renal disease.  J Nephrol  2002; 15(3):270-274.

77. Cases A, Coll E: Dyslipidemia and the progression of renal disease in chronic renal failure patients.  Kidney Int Suppl  2005; 99:S87-S93.

78. Schaeffner ES, Kurth T, Curhan GC, et al: Cholesterol and the risk of renal dysfunction in apparently healthy men.  J Am Soc Nephrol  2003; 14(8):2084-2091.

79. Muntner P, Coresh J, Smith JC, et al: Plasma lipids and risk of developing renal dysfunction: The atherosclerosis risk in communities study.  Kidney Int  2000; 58(1):293-301.

80. Segura J, Campo C, Gil P, et al: Development of chronic kidney disease and cardiovascular prognosis in essential hypertensive patients.  J Am Soc Nephrol  2004; 15(6):1616-1622.

81. Hsu CY, Bates DW, Kuperman GJ, Curhan GC: Diabetes, hemoglobin A(1c), cholesterol, and the risk of moderate chronic renal insufficiency in an ambulatory population.  Am J Kidney Dis  2000; 36(2):272-281.

82. Tonelli M, Moye L, Sacks FM, et al: Effect of pravastatin on loss of renal function in people with moderate chronic renal insufficiency and cardiovascular disease.  J Am Soc Nephrol  2003; 14(6):1605-1613.

83. Tonelli M, Collins D, Robins S, et al: Effect of gemfibrozil on change in renal function in men with moderate chronic renal insufficiency and coronary disease.  Am J Kidney Dis  2004; 44(5):832-839.

84. Fried LF, Orchard TJ, Kasiske BL: Effect of lipid reduction on the progression of renal disease: A meta-analysis.  Kidney Int  2001; 59(1):260-269.

85. Iseki K, Ikemiya Y, Kinjo K, et al: Body mass index and the risk of development of end-stage renal disease in a screened cohort.  Kidney Int  2004; 65(5):1870-1876.

86. Praga M, Hernandez E, Herrero JC, et al: Influence of obesity on the appearance of proteinuria and renal insufficiency after unilateral nephrectomy.  Kidney Int  2000; 58(5):2111-2118.

87. Bonnet F, Deprele C, Sassolas A, et al: Excessive body weight as a new independent risk factor for clinical and pathological progression in primary IgA nephritis.  Am J Kidney Dis  2001; 37(4):720-727.

88. Kambham N, Markowitz GS, Valeri AM, et al: Obesity-related glomerulopathy: an emerging epidemic.  Kidney Int  2001; 59(4):1498-1509.

89. Hsu C-y, McCulloch CE, Iribarren C, et al: Body mass index and risk for end-stage renal disease.  Ann Intern Med  2006; 144(1):21-28.

90. Chagnac A, Weinstein T, Herman M, et al: The effects of weight loss on renal function in patients with severe obesity.  J Am Soc Nephrol  2003; 14(6):1480-1486.

91. Morales E, Valero MA, Leon M, et al: Beneficial effects of weight loss in overweight patients with chronic proteinuric nephropathies.  Am J Kidney Dis  2003; 41(2):319-327.

92. Chen J, Muntner P, Hamm LL, et al: The metabolic syndrome and chronic kidney disease in U.S. adults.  Ann Intern Med  2004; 140(3):167-174.

93. Kurella M, Lo JC, Chertow GM: Metabolic syndrome and the risk for chronic kidney disease among nondiabetic adults.  J Am Soc Nephrol  2005; 16(7):2134-2140.

93a. Tomaszewski M, Charchor FJ, Maric C, et al: Glomerular hyperfiltration: a new marker of metabolic risk.  Kidney Int  2007; 71:816-821.

94. Buller CE, Nogareda JG, Ramanathan K, et al: The profile of cardiac patients with renal artery stenosis.  J Am Coll Cardiol  2004; 43(9):1606-1613.

95. Levin A, Djurdjev O, Barrett B, et al: Cardiovascular disease in patients with chronic kidney disease: Getting to the heart of the matter.  Am J Kidney Dis  2001; 38(6):1398-1407.

96. McClellan WM, Langston RD, Presley R: Medicare patients with cardiovascular disease have a high prevalence of chronic kidney disease and a high rate of progression to end-stage renal disease.  J Am Soc Nephrol  2004; 15(7):1912-1919.

97. Perry Jr HM, Miller JP, Fornoff JR, et al: Early predictors of 15-year end-stage renal disease in hypertensive patients.  Hypertension  1995; 25(4 Pt 1):587-594.

98. Pinto-Sietsma SJ, Janssen WM, Hillege HL, et al: Urinary albumin excretion is associated with renal functional abnormalities in a nondiabetic population.  J Am Soc Nephrol  2000; 11(10):1882-1888.

99. Mann JFE, Gerstein HC, Yi Q-L, et al: Development of renal disease in people at high cardiovascular risk: Results of the HOPE Randomized Study.  J Am Soc Nephrol  2003; 14(3):641-647.

100. Peterson JC, Adler S, Burkart JM, et al: Blood pressure control, proteinuria, and the progression of renal disease. The Modification of Diet in Renal Disease Study.  Ann Intern Med  1995; 123(10):754-762.

101. Lea J, Greene T, Hebert L, et al: The relationship between magnitude of proteinuria reduction and risk of end-stage renal disease: Results of the African American Study of Kidney Disease and Hypertension.  Arch Intern Med  2005; 165(8):947-953.

102. Ruggenenti P, Perna A, Mosconi L, Gruppo Italiano di Studi Epidemiologici in N : Urinary protein excretion rate is the best independent predictor of ESRF in non-diabetic proteinuric chronic nephropathies.  Kidney Int  1998; 53(5):1209-1216.

102a. Eijkelkamp WB, Zhang Z, Remuzzi G, et al: Albuminuria is a target for renoprotective therapy independent from blood pressure in patients with type 2 diabetic nephropathy.  J Am Soc Nephrol  2007; 18:1540-1546.

103. Remuzzi G, Bertani T: Pathophysiology of progressive nephropathies.  N Engl J Med  1998; 339(20):1448-1456.

104. Standards of medical care in diabetes.  Diabetes Care  2005; 28(Suppl 1):S4-S36.

105. National Kidney Foundation: K/DOQI clinical practice guidelines on hypertension and antihypertensive agents in chronic kidney disease.  Am J Kidney Dis  2004; 43(5 Suppl 1):S1-S290.

106. Schmidt-Ott KM, Kagiyama S, Phillips MI: The multiple actions of angiotensin II in atherosclerosis.  Regul Pept  2000; 93(1-3):65-77.

107. Agodoa LY, Appel L, Bakris GL, et al: Effect of ramipril vs amlodipine on renal outcomes in hypertensive nephrosclerosis: A randomized controlled trial.  JAMA  2001; 285(21):2719-2728.

108. The GISEN Group (Gruppo Italiano di Studi Epidemiologici in Nefrologia) : Randomised placebo-controlled trial of effect of ramipril on decline in glomerular filtration rate and risk of terminal renal failure in proteinuric, non-diabetic nephropathy.  Lancet  1997; 349(9069):1857-1863.

109. Ruggenenti P, Perna A, Gherardi G, et al: Renal function and requirement for dialysis in chronic nephropathy patients on long-term ramipril: REIN follow-up trial. Gruppo Italiano di Studi Epidemiologici in Nefrologia (GISEN). Ramipril Efficacy in Nephropathy.  Lancet  1998; 352(9136):1252-1256.

110. Lewis EJ, Hunsicker LG, Bain RP, Rohde RD: The effect of angiotensin-converting-enzyme inhibition on diabetic nephropathy. The Collaborative Study Group.  N Engl J Med  1993; 329(20):1456-1462.

111. Lewis EJ, Hunsicker LG, Clarke WR, et al: Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes.  N Engl J Med  2001; 345(12):851-860.

112. Brenner BM, Cooper ME, de Zeeuw D, et al: Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy.  N Engl J Med  2001; 345(12):861-869.

113. Rahman M, Pressel S, Davis BR, et al: Renal outcomes in high-risk hypertensive patients treated with an angiotensin-converting enzyme inhibitor or a calcium channel blocker vs a diuretic: A report from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT).  Arch Intern Med  2005; 165(8):936-946.

114. ACE Inhibitors in Diabetic Nephropathy Trialist Group : Should all patients with type 1 diabetes mellitus and microalbuminuria receive angiotensin-converting enzyme inhibitors? A meta-analysis of individual patient data.  Ann Intern Med  2001; 134(5):370-379.

115. Jafar TH, Schmid CH, Landa M, et al: Angiotensin-converting enzyme inhibitors and progression of nondiabetic renal disease. A meta-analysis of patient-level data.  Ann Intern Med  2001; 135(2):73-87.

116. Wrone EM, Carnethon MR, Palaniappan L, Fortmann SP: Association of dietary protein intake and microalbuminuria in healthy adults: Third National Health and Nutrition Examination Survey.  Am J Kidney Dis  2003; 41(3):580-587.

117. Knight EL, Stampfer MJ, Hankinson SE, et al: The impact of protein intake on renal function decline in women with normal renal function or mild renal insufficiency.  Ann Intern Med  2003; 138(6):460-467.

118. Levey AS, Greene T, Beck GJ, et al: Dietary protein restriction and the progression of chronic renal disease: What have all of the results of the MDRD study shown? Modification of Diet in Renal Disease Study group.  J Am Soc Nephrol  1999; 10(11):2426-2439.

119. Fouque D, Laville M, Boissel JP, et al: Controlled low protein diets in chronic renal insufficiency: Meta-analysis.  BMJ  1992; 304(6821):216-220.

120. Fouque D, Wang P, Laville M, Boissel JP: Low protein diets delay end-stage renal disease in non-diabetic adults with chronic renal failure.  Nephrol Dial Transplant  2000; 15(12):1986-1992.

121. Kasiske BL, Lakatua JD, Ma JZ, Louis TA: A meta-analysis of the effects of dietary protein restriction on the rate of decline in renal function.  Am J Kidney Dis  1998; 31(6):954-961.

122. Pedrini MT, Levey AS, Lau J, et al: The effect of dietary protein restriction on the progression of diabetic and nondiabetic renal diseases: A meta-analysis.  Ann Intern Med  1996; 124(7):627-632.

123. Breyer JA, Bain RP, Evans JK, et al: Predictors of the progression of renal insufficiency in patients with insulin-dependent diabetes and overt diabetic nephropathy. The Collaborative Study Group.  Kidney Int  1996; 50(5):1651-1658.

124. Yokoyama H, Tomonaga O, Hirayama M, et al: Predictors of the progression of diabetic nephropathy and the beneficial effect of angiotensin-converting enzyme inhibitors in NIDDM patients.  Diabetologia  1997; 40(4):405-411.

125. Brenner BM, Chertow GM: Congenital oligonephropathy and the etiology of adult hypertension and progressive renal injury.  Am J Kidney Dis  1994; 23(2):171-175.

126. Hoy WE, Hughson MD, Bertram JF, et al: Nephron number, hypertension, renal disease, and renal failure.  J Am Soc Nephrol  2005; 16:2557-2564.

127. Woods LL, Weeks DA, Rasch R: Hypertension after neonatal uninephrectomy in rats precedes glomerular damage.  Hypertension  2001; 38(3):337-342.

128. Keller G, Zimmer G, Mall G, et al: Nephron number in patients with primary hypertension.  N Engl J Med  2003; 348(2):101-108.

129. Hakim RM, Goldszer RC, Brenner BM: Hypertension and proteinuria: Long-term sequelae of uninephrectomy in humans.  Kidney Int  1984; 25(6):930-936.

130. Conrad KP, Novak J, Danielson LA, et al: Mechanisms of renal vasodilation and hyperfiltration during pregnancy: Current perspectives and potential implications for preeclampsia.  Endothelium  2005; 12(1-2):57-62.

131. Skov AR, Toubro S, Bulow J, et al: Changes in renal function during weight loss induced by high vs low-protein low-fat diets in overweight subjects.  Int J Obes Relat Metab Disord  1999; 23(11):1170-1177.

132. Parving H-H, Mauer M, Ritz E: Diabetic nephropathy.   In: Brenner BM, ed. Brenner and Rector's The Kidney,  7th ed. Philadelphia: Elsevier; 2004:1177-1818.

133. Chagnac A, Weinstein T, Herman M, et al: The effects of weight loss on renal function in patients with severe obesity.  J Am Soc Nephrol  2003; 14(6):1480-1486.

134. Kenneth I, Ataga EPO: Renal abnormalities in sickle cell disease.  Am J Hematol  2000; 63(4):205-211.

135. Lee PJ, Dalton RN, Shah V, et al: Glomerular and tubular function in glycogen storage disease.  Pediatr Nephrol  1995; 9(6):705-710.

136. Wheeler DC, Townend JN, Landray MJ: Cardiovascular risk factors in predialysis patients: Baseline data from the Chronic Renal Impairment in Birmingham (CRIB) study.  Kidney Int  2003;S201-S203.

137. Muntner P, He J, Astor BC, et al: Traditional and Nontraditional Risk Factors Predict Coronary Heart Disease in Chronic Kidney Disease: Results from the Atherosclerosis Risk in Communities Study.  J Am Soc Nephrol  2005; 16(2):529-538.

138. Levin A, Thompson CR, Ethier J, et al: Left ventricular mass index increase in early renal disease: Impact of decline in hemoglobin.  Am J Kidney Dis  1999; 34(1):125-134.

139. Mohanram A, Zhang Z, Shahinfar S, et al: Anemia and end-stage renal disease in patients with type 2 diabetes and nephropathy.  Kidney Int  2004; 66(3):1131-1138.

140. Kuriyama S, Tomonari H, Yoshida H, et al: Reversal of anemia by erythropoietin therapy retards the progression of chronic renal failure, especially in nondiabetic patients.  Nephron  1997; 77(2):176-185.

141. Jungers P, Choukroun G, Oualim Z, et al: Beneficial influence of recombinant human erythropoietin therapy on the rate of progression of chronic renal failure in predialysis patients.  Nephrol Dial Transplant  2001; 16(2):307-312.

142. Silverberg DS, Iaina A, Peer G, et al: Intravenous iron supplementation for the treatment of the anemia of moderate to severe chronic renal failure patients not receiving dialysis.  Am J Kidney Dis  1996; 27(2):234-238.

143. Albertazzi A, Di Liberato L, Daniele F, et al: Efficacy and tolerability of recombinant human erythropoietin treatment in pre-dialysis patients: Results of a multicenter study.  Int J Artif Organs  1998; 21(1):12-18.

144. Hayashi T, Suzuki A, Shoji T, et al: Cardiovascular effect of normalizing the hematocrit level during erythropoietin therapy in predialysis patients with chronic renal failure.  Am J Kidney Dis  2000; 35(2):250-256.

145. Roth D, Smith RD, Schulman G, et al: Effects of recombinant human erythropoietin on renal function in chronic renal failure predialysis patients.  Am J Kidney Dis  1994; 24(5):777-784.

146. Portoles J, Torralbo A, Martin P, et al: Cardiovascular effects of recombinant human erythropoietin in predialysis patients.  Am J Kidney Dis  1997; 29(4):541-548.

147. The US Recombinant Human Erythropoietin Predialysis Study Group : Double-blind, placebo-controlled study of the therapeutic use of recombinant human erythropoietin for anemia associated with chronic renal failure in predialysis patients.  Am J Kidney Dis  1991; 18(1):50-59.

148. Austrian Multicenter Study Group of r-HuEPO in Predialysis Patients : Effectiveness and safety of recombinant human erythropoietin in predialysis patients.  Nephron  1992; 61(4):399-403.

149. Abraham PA, Opsahl JA, Rachael KM, et al: Renal function during erythropoietin therapy for anemia in predialysis chronic renal failure patients.  Am J Nephrol  1990; 10(2):128-136.

150. Rao M, Pereira BJ: Prospective trials on anemia of chronic disease: The Trial to Reduce Cardiovascular Events with Aranesp Therapy (TREAT).  Kidney Int  2003;S12-S19.

151.   Reddan DN, Singh AK, Group tCS: Can risk factor modification provide meaningful benefit? The Correction of Hemoglobin and Outcomes in Renal Insufficiency (CHOIR) Study. Paper presented at: The American Society of Nephrology Renal Week; 2003; San Diego, CA.

152. Macdougall IC: CREATE: New strategies for early anaemia management in renal insufficiency.  Nephrol Dial Transplant  2003; 18(Suppl 2):ii13-ii16.

153. Muntner P, Hamm LL, Kusek JW, et al: The prevalence of nontraditional risk factors for coronary heart disease in patients with chronic kidney disease.  Ann Intern Med  2004; 140(1):9-17.

154. Knight EL, Rimm EB, Pai JK, et al: Kidney dysfunction, inflammation, and coronary events: A prospective study.  J Am Soc Nephrol  2004; 15(7):1897-1903.

155. Annuk M, Zilmer M, Lind L, et al: Oxidative stress and endothelial function in chronic renal failure.  J Am Soc Nephrol  2001; 12(12):2747-2752.

156. Oberg BP, McMenamin E, Lucas FL, et al: Increased prevalence of oxidant stress and inflammation in patients with moderate to severe chronic kidney disease.  Kidney Int  2004; 65(3):1009-1016.

157. Stuveling EM, Bakker SJL, Hillege HL, et al: Biochemical risk markers: A novel area for better prediction of renal risk?.  Nephrol Dial Transplant  2005; 20(3):497-508.

158. Menon V, Wang X, Greene T, et al: Homocysteine in chronic kidney disease: Effect of low protein diet and repletion with B vitamins.  Kidney Int  2005; 67(4):1539-1546.

159. Kronenberg F, Kuen E, Ritz E, et al: Lipoprotein(a) serum concentrations and apolipoprotein(a) phenotypes in mild and moderate renal failure.  J Am Soc Nephrol  2000; 11(1):105-115.

160. Chen J, Muntner P, Hamm LL, et al: Insulin resistance and risk of chronic kidney disease in nondiabetic U.S. adults.  J Am Soc Nephrol  2003; 14(2):469-477.

161. Sarnak MJ, Poindexter A, Wang SR, et al: Serum C-reactive protein and leptin as predictors of kidney disease progression in the Modification of Diet in Renal Disease Study.  Kidney Int  2002; 62(6):2208-2215.

162. Sarnak MJ, Wang SR, Beck GJ, et al: Homocysteine, cysteine, and B vitamins as predictors of kidney disease progression.  Am J Kidney Dis  2002; 40(5):932-939.

163. Fried L, Solomon C, Shlipak M, et al: Inflammatory and prothrombotic markers and the progression of renal disease in elderly individuals.  J Am Soc Nephrol  2004; 15(12):3184-3191.

164. Ravani P, Tripepi G, Malberti F, et al: Asymmetrical dimethylarginine predicts progression to dialysis and death in patients with chronic kidney disease: A competing risks modeling approach.  J Am Soc Nephrol  2005; 16(8):2449-2455.

165. The European Polycystic Kidney Disease Consortium: The polycystic kidney disease 1 gene encodes a 14 kb transcript and lies within a duplicated region on chromosome 16.  Cell  1994; 77(6):881-894.

166. Peters DJ, Spruit L, Saris JJ, et al: Chromosome 4 localization of a second gene for autosomal dominant polycystic kidney disease.  Nat Genet  1993; 5(4):359-362.

167. Eng CM, Desnick RJ: Molecular basis of Fabry disease: Mutations and polymorphisms in the human alpha-galactosidase A gene.  Hum Mutat  1994; 3(2):103-111.

168. Jurkovitz C, Franch H, Shoham D, et al: Family members of patients treated for ESRD have high rates of undetected kidney disease.  Am J Kidney Dis  2002; 40(6):1173-1178.

169. Paterson AD, Magistroni R, He N, et al: Progressive loss of renal function is an age-dependent heritable trait in type 1 autosomal dominant polycystic kidney disease.  J Am Soc Nephrol  2005; 16(3):755-762.

170. Spray BJ, Atassi NG, Tuttle AB, Freedman BI: Familial risk, age at onset, and cause of end-stage renal disease in white Americans.  J Am Soc Nephrol  1995; 5(10):1806-1810.

171. Lei HH, Perneger TV, Klag MJ, et al: Familial aggregation of renal disease in a population-based case-control study.  J Am Soc Nephrol  1998; 9(7):1270-1276.

172. Faronato PP, Maioli M, Tonolo G, et al: Clustering of albumin excretion rate abnormalities in Caucasian patients with NIDDM. The Italian NIDDM Nephropathy Study Group.  Diabetologia  1997; 40(7):816-823.

173. Freedman BI, Soucie JM, McClellan WM: Family history of end-stage renal disease among incident dialysis patients.  J Am Soc Nephrol  1997; 8(12):1942-1945.

174. Manalich R, Reyes L, Herrera M, et al: Relationship between weight at birth and the number and size of renal glomeruli in humans: A histomorphometric study.  Kidney Int  2000; 58(2):770-773.

175. Schmidt IM, Chellakooty M, Boisen KA, et al: Impaired kidney growth in low-birth-weight children: Distinct effects of maturity and weight for gestational age.  Kidney Int  2005; 68(2):731-740.

176. Keijzer-Veen MG, Schrevel M, Finken MJJ, et al: Microalbuminuria and lower glomerular filtration rate at young adult age in subjects born very premature and after intrauterine growth retardation.  J Am Soc Nephrol  2005; 16(9):2762-2768.

177. Hughson M, Farris 3rd AB, Douglas-Denton R, et al: Glomerular number and size in autopsy kidneys: The relationship to birthweight.  Kidney Int  2003; 63(6):2113-2122.

178. Hoy WE, Rees M, Kile E, et al: Low birthweight and renal disease in Australian aborigines.  Lancet  1998; 352(9143):1826-1827.

179. Nelson RG, Morgenstern H, Bennett PH: Birthweight and renal disease in Pima Indians with type 2 diabetes mellitus.  Am J Epidemiol  1998; 148(7):650-656.

180. Klag MJ, Whelton PK, Randall BL, et al: End-stage renal disease in African-American and white men. 16-year MRFIT findings.  JAMA  1997; 277(16):1293-1298.

181. Tarver-Carr ME, Powe NR, Eberhardt MS, et al: Excess risk of chronic kidney disease among African-American versus white subjects in the United States: A population-based study of potential explanatory factors.  J Am Soc Nephrol  2002; 13(9):2363-2370.

182. Stehman-Breen CO, Gillen D, Steffes M, et al: Racial differences in early-onset renal disease among young adults: The coronary artery risk development in young adults (CARDIA) study.  J Am Soc Nephrol  2003; 14(9):2352-2357.

183. Krop JS, Coresh J, Chambless LE, et al: A community-based study of explanatory factors for the excess risk for early renal function decline in blacks vs whites with diabetes: The Atherosclerosis Risk in Communities study.  Arch Intern Med  1999; 159(15):1777-1783.

184. Hsu CY, Lin F, Vittinghoff E, Shlipak MG: Racial differences in the progression from chronic renal insufficiency to end-stage renal disease in the United States.  J Am Soc Nephrol  2003; 14(11):2902-2907.

185. Kiberd BA, Clase CM: Cumulative risk for developing end-stage renal disease in the US population.  J Am Soc Nephrol  2002; 13(6):1635-1644.

186. Fletcher RH, Fletcher SW, Wagner EH: Clinical Epidemiology, The Essentials,  Philadelphia, Lippincott Williams & Wilkins, 1996.

187. Menon V, Sarnak MJ: The epidemiology of chronic kidney disease stages 1 to 4 and cardiovascular disease: A high-risk combination.  Am J Kidney Dis  2005; 45(1):223-232.

188. Stehouwer CD, Gall MA, Twisk JW, et al: Increased urinary albumin excretion, endothelial dysfunction, and chronic low-grade inflammation in type 2 diabetes: Progressive, interrelated, and independently associated with risk of death.  Diabetes  2002; 51(4):1157-1165.

189. Paisley KE, Beaman M, Tooke JE, et al: Endothelial dysfunction and inflammation in asymptomatic proteinuria.  Kidney Int  2003; 63(2):624-633.

190. Jensen JS, Borch-Johnsen K, Jensen G, Feldt-Rasmussen B: Atherosclerotic risk factors are increased in clinically healthy subjects with microalbuminuria.  Atherosclerosis  1995; 112(2):245-252.

191. McCullough PA, Sandberg KR, Borzak S, et al: Benefits of aspirin and beta-blockade after myocardial infarction in patients with chronic kidney disease.  Am Heart J  2002; 144(2):226-232.

192. Sarnak MJ, Levey AS: Cardiovascular disease and chronic renal disease: A new paradigm.  Am J Kidney Dis  2000; 35(4 Suppl 1):S117-S131.

193. U.S. Renal Data Systems : USRDS 2002 Annual Data Report: Atlas of End Stage Renal Diseases in the United States,  Bethesda, MD, National Institutes of Health. The National Institute of Diabetes and Digestive and Kidney Disease. Division of Kidney, Urologic, and Hematologic Diseases, 2002.