0
Original Investigation |

Association of Kidney Function and Albuminuria With Cardiovascular Mortality in Older vs Younger Individuals:  The HUNT II Study FREE

Stein Hallan, MD, PhD; Brad Astor, MPH, PhD; Solfrid Romundstad, MD, PhD; Knut Aasarød, MD, PhD; Kurt Kvenild, MD; Josef Coresh, MD, PhD
[+] Author Affiliations

Author Affiliations: Departments of Cancer Research and Molecular Medicine (Drs Hallan, Romundstad, and Aasarød) and Community Medicine (Dr Kvenild), Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway; Department of Medicine, Division of Nephrology, St Olav University Hospital, Trondheim (Drs Hallan, Romundstad, and Aasarød); and Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Bloomberg School of Public Health, and Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland (Drs Astor and Coresh).


Arch Intern Med. 2007;167(22):2490-2496. doi:10.1001/archinte.167.22.2490.
Text Size: A A A
Published online

Background  The cardiovascular risk implications of a combined assessment of reduced kidney function and microalbuminuria are unknown. In elderly persons, traditional cardiovascular risk factors are less predictive, and measures of end organ damage, such as kidney disease, may be needed for improved cardiovascular mortality risk stratification.

Methods  The glomerular filtration rate was estimated from calibrated serum creatinine, and the urine albumin-creatinine ratio (ACR) was measured in 3 urine samples in 9709 participants of the second Nord-Trøndelag Health Study (HUNT II), a Norwegian community-based health study, followed for 8.3 years with a 71% participation rate.

Results  An estimated glomerular filtration rate (EGFR) at levels of less than 75 mL/min/1.73 m2 was associated with higher cardiovascular mortality risk, whereas a higher ACR was associated with higher risk with no lower limit. Low EGFR and albuminuria were synergistic cardiovascular mortality risk factors. Compared with subjects with an EGFR greater than 75 mL/min/1.73 m2 and ACR below the sex-specific median who were at the lowest risk, subjects with an EGFR of less than 45 mL/min/1.73 m2 and microalbuminuria had an adjusted incidence rate ratio of 6.7 (95% confidence interval, 3.0-15.1; P < .001). The addition of ACR and EGFR improved traditional risk models: 39% of subjects with intermediate risk were reclassified to low- or high-risk categories with corresponding observed risks that were 3-fold different than the original category. Age-stratified analyses showed that EGFR and ACR were particularly strong risk factors for persons 70 years or older.

Conclusions  Reduced kidney function and microalbuminuria are risk factors for cardiovascular death, independent of each other and traditional risk factors. The combined variable improved cardiovascular risk stratification at all age levels, but particularly in elderly persons where the predictive power of traditional risk factors is attenuated.

Figures in this Article

Primary prevention of cardiovascular disease (CVD) in people 70 years or older is debated.1,2 Despite the fact that most of the cardiovascular morbidity, mortality, and costs occur at older ages, there are few data on the benefits and risks of the treatment, and we lack tools for accurate prediction of cardiovascular risk. Reduced kidney function and urinary excretion of albumin are used for defining and staging chronic kidney disease,3 a common condition with a high risk of CVD in addition to the risk of progression to end-stage renal disease.47 The interaction between the kidney and the heart increasingly emerges as an important factor for CVD,8 and kidney function and urinary excretion of albumin are now suggested as risk factors to be measured in assessing risk of cardiovascular death, in addition to hypertension, diabetes mellitus (DM), hypercholesterolemia, and smoking.9,10 However, these new, potentially related risk factors have seldom been evaluated together in population-based studies.

Many of the studies that found decreased kidney function increases mortality are analyses of cardiovascular intervention trials with limited measures of kidney disease.11 Early population-based studies did not find reduced kidney function to be an independent risk factor for cardiovascular death,12,13 but most recent studies7,10,14 find that a reduced estimated glomerular filtration rate (EGFR) (an EGFR <60 mL/min/1.73 m2) is a major risk factor for cardiovascular mortality and morbidity. Albumin leakage in the urine, despite its large day-to-day variation, has emerged as an important risk factor for atherosclerotic CVD.10,15 International guidelines16,17 recommend screening for microalbuminuria in subjects with DM or hypertension. However, most studies have examined either EGFR or albuminuria, but not both. So far, to our knowledge, there are only 2 reports on the combined effect of kidney function and albuminuria.18,19 These studies used a semiquantitative dipstick analysis for measuring albuminuria in a single urine sample and were able to evaluate only subjects with macroalbuminuria.

Hence, more information on the combined effect of reduced kidney function and quantitatively measured microalbuminuria is needed. Both can be considered as measures of end organ damage, and inclusion of such variables could improve risk stratification in general, and in particular among elderly persons, for whom traditional risk factors have reduced predictive power.2022 This could be important in screening programs and targeting preventive treatment for subjects with increased cardiovascular risk. We analyzed data from the second Nord-Trøndelag Health Study (HUNT II), a large prospective cohort study with an albumin-creatinine ratio (ACR) measured in 3 urine samples. First, we explored the association among abnormal EGFR, albuminuria, and cardiovascular mortality, with special emphasis on the near-normal levels in a general population. Second, to address the potential clinical usefulness of such measurements, we compared cardiovascular risk models with and without a combined EGFR-ACR variable in subjects younger than 70 years and those 70 years or older.

The HUNT II study is a large-scale Norwegian general health survey. From 1995 to 1997, every individual residing in the county who was at least 20 years old (n = 92 939) was invited to participate, and 70.6% of the total adult population participated. We evaluated a subpopulation that was asked to deliver urine samples in addition to the standard testing: all subjects with DM or treated hypertension (prevalence rates, 3.4% and 11.1%, respectively), plus a 5% random sample.

Nord-Trøndelag County is located in the middle of Norway and is fairly representative in terms of geography, economy, industry, age distribution, and morbidity and mortality.23 The population is ethnically homogeneous (> 97% white). A more detailed description of the objectives, contents, methods, and participation in the HUNT II study has been given elsewhere.24 The participants gave an informed consent, which included linkage to central national registries, and the study was approved by the regional committee for medical research ethics, the Norwegian Data Inspectorate, and the Ministry of Health.

The participants reported on several aspects of their current and former health, on illness in the family, socioeconomic status, and risk factors, such as physical activity and smoking. The clinical examination included measurement of height, weight, and waist and hip circumference. Three consecutive standardized blood pressure measurements were recorded in the sitting position at 1-minute intervals using an automatic oscillometric method (Dinamap 845XT; Criticon, Tampa, Florida). Fresh serum and urine samples were analyzed on a Hitachi 911 autoanalyzer (Hitachi, Mito, Japan) within 2 days. The GFR was estimated with the reexpressed 4-variable Modification of Diet in Renal Disease study formula for isotope dilution mass spectrometry traceable serum creatinine values in all subjects25:

EGFR = 175 × (Serum Creatinine in Milligrams per Deciliter)-1.154 × Age -0.203 (× 0.742 for Women) (× 1.21 for Black Persons).

Our original Jaffé-based creatinine values were recalibrated to the Roche enzymatic method to provide isotope dilution mass spectrometry traceable values, and the EGFR values have been shown to be unbiased in a general population.26 Participants were asked to deliver urine samples on 3 consecutive mornings, and those reporting urine infection during the previous week or menstruation at the time of collection were excluded. Urine albumin was measured by an immunoturbidimetric method (Dako A/S, Glostrup, Denmark), and urine ACR was used as an expression for albumin excretion.

Vital status as of January 1, 2005, was provided by the Statistics Norway database23 for all participants, and the cause of death was available in 99.7% of cases. We defined cardiovascular death as death certificates with the following International Statistical Classification of Diseases, 10th Revision (ICD-10),27 codes as underlying cause of death28: hypertensive disease (I10-I15), ischemic heart disease (I20-I25), arhythmia (I44-I49), heart failure (I50), cerebrovascular disease (I60-I69), and diseases of the arteries (I70-I77). We defined coronary heart death as caused by ischemic heart disease (I20-I25).

Statistical analyses were generated using Stata software (version 9; Stata Corp, College Station, Texas). Six subjects with an EGFR below 15 mL/min/1.73 m2 were excluded, and 7 with EGFR greater than 200 mL/min/1.73 m2, which is physiological unlikely, were given a value of 200 mL/min/1.73 m2. Associations of EGFR and ACR with mortality were examined using multivariate Poisson regression models, which express relative risk as an incidence rate ratio (IRR), and this yielded similar results to Cox proportional hazard regression analyses. Analyses addressing the general population accounted for the urinary testing sampling scheme using appropriate sample weights. We explored the continuous relationship of mortality risk associated with lower EGFR or higher ACR using restricted cubic spline models adjusted for age, sex, EGFR, and ACR. Interaction on an additive scale was used to evaluate whether EGFR and ACR are more useful for risk stratification when used together vs separately.29 A composite variable with 16 categories (combining 4 EGFR categories and 4 ACR categories) was used to evaluate the combined effect of these 2 variables. Microalbuminuria was defined as an ACR of 20 to 200 mg/g in men and 30 to 300 mg/g in women,30 but because previous studies indicate that the risk extends below this level, we also categorized ACR as “optimal” values below the sex-specific median (<5 mg/g in men and <7 mg/g in women) and as “high normal” values (5-19 mg/g in men and 7-29 mg/g in women). Age- and sex-adjusted IRRs, as well as multivariate-adjusted IRRs, were calculated (age, sex, prevalent CVD, DM, systolic blood pressure, antihypertensive medication, current smoking, cholesterol, high-density lipoprotein cholesterol, and EGFR-ACR categories). We also calculated excess risk, an absolute measure of risk increase, by categories of EGFR and ACR, using the coefficients from the multivariate-adjusted models and the observed risk in the reference group (optimal ACR and EGFR ≥75).

We assessed the risk for cardiovascular death associated with traditional risk factors and with EGFR-ACR in subjects younger than 70 years and those 70 years or older. This age stratification was chosen a priori because current risk models are based on study populations below this threshold.31,32 All-cause and coronary heart disease mortality were used as outcomes in secondary analyses. Risk models with and without EGFR-ACR were assessed with the Akaike Information Criterion,33 which is a likelihood-based measure that adds a penalty for model complexity, and with the C statistic (area under the receiver operating characteristic [ROC] curve) based on logistic regression analyses. We also compared risk estimates from Poisson regression models with the observed risk during follow-up. European guidelines recommend primary preventive treatment in subjects younger than 65 years if the 10-year absolute cardiovascular mortality risk is more than 5%,28 but higher thresholds for absolute risks may be more useful in elderly persons.34,35 We therefore classified people into low-, intermediate-, or high-risk categories when cardiovascular mortality rates were less than 5, 5 to 10, and more than 10 per 1000 person-years, respectively.

Baseline data for the study population are given in Table 1. A total of 9709 participants returned 3 urine samples, giving an overall response rate of 86.4%. The 2294 subjects without hypertension and DM selected at random had cardiovascular mortality rates similar to those not selected for urine testing (3.19 vs 3.29 per 1000 person-years; log rank test, P = .80). When adjusting for a slightly higher age, none of the baseline characteristics and cardiovascular risk factors of our study subjects were substantially different from the general Norwegian population. During a median follow-up period of 8.3 years, 1981 subjects in our study group died, and 1018 of those deaths were caused by CVD.

Table Graphic Jump LocationTable 1. Baseline Data in the Study Populationa

The continuous relationships of cardiovascular mortality risk associated with lower EGFR and higher ACR adjusted for each other and for age and sex are shown in Figure 1. The adjusted IRR started to increase as the EGFR decreased below 75 mL/min/1.73 m2. In the EGFR range of 75 to 135, the IRR was very close to 1. At EGFRs above 135, where precision is poor and estimates may reflect low muscle mass as much as higher GFR, the risk of cardiovascular mortality was higher than in the EGFR range of 75 to 135 (IRR, 1.48; 95% CI, 1.10-1.99). In contrast, the IRR increased continuously with increasing ACR. An interaction between EGFR and ACR, defined as a departure from the additivity of their absolute effects, was observed. Subjects with EGFR lower than 60 mL/min/1.73 m2 and microalbuminuria had an excess age- and sex-adjusted risk: relative excess risk owing to interaction was 1.98 (95% CI, 0.02-3.94).

Place holder to copy figure label and caption
Figure 1.

Incidence rate ratio (IRR) (95% confidence interval) for cardiovascular death. The IRR associated with (A) decreasing kidney function (estimated glomerular filtration rate [EGFR]) and (B) increasing urine albumin-creatinine ratio (ACR). The restricted cubic spline models were adjusted for age, sex, EGFR, and ACR, and the reference (IRR = 1) was set to the median ACR or median EGFR. The distributions of EGFR and ACR in the general population are also shown (bars).

Graphic Jump Location

The association of a combined kidney function and albuminuria variable with cardiovascular mortality using categories emphasizing the near-normal levels is illustrated in Figure 2. In the general population, age- and sex-adjusted Poisson regression analysis showed that lower EGFR categories were associated with increased relative risk within every ACR category. Likewise, increasing ACR categories were associated with increased mortality within every EGFR category. Subjects with microalbuminuria and an EGFR lower than 45 mL/min/1.73 m2 had 12 times higher cardiovascular mortality risk compared with the reference category of subjects with an EGFR higher than 75 mL/min/1.73 m2 and “optimal” ACR. However, if subjects had a low EGFR but an optimal ACR, or if they had microalbuminuria and a normal EGFR, they had only a moderately increased risk (IRR, 2.3 and 3.0).

Place holder to copy figure label and caption
Figure 2.

Cardiovascular mortality risk in the general population by categories of estimated glomerular filtration rate (EGFR) and urine albumin-creatinine ratio (ACR). The incidence rate ratios (IRRs) were adjusted for age and sex. The ACR is the mean of 3 samples, and optimal ACR is below sex-specific median (< 5 mg/g in men and < 7 mg/g in women), and high normal is 5 to 19 mg/g in men and 7 to 29 mg/g in women. Microalbuminuria is 20 to 199 mg/g in men and 30 to 299 mg/g in women.30 Subjects with an optimal ACR and an EGFR of 75 mL/min/1.73 m2 or higher comprised the reference group. *P < .05. †P < .01. ‡P < .001.

Graphic Jump Location

Adjusting for age, sex, prevalent CVD, DM, systolic blood pressure, antihypertensive medication, current smoking, cholesterol, and high-density lipoprotein cholesterol attenuated the IRRs, as shown in Table 2. There was a strong trend for higher risk at lower GFR in subjects with microalbuminuria (P = .02 at age <70 years, P = .002 at age ≥70 years). At lower ACR levels, there was no significant trend for increased cardiovascular risk with decreasing EGFR ( = .91 and  = .98 at optimal ACR, and  = .31 and  = .78 at high normal ACR for both age ranges, respectively). The association of reduced kidney function and increased albumin excretion with cardiovascular mortality tended to be even stronger in participants 70 years or older compared with those younger than 70 years. Given the higher baseline risk among older participants, this translates into large differences in absolute excess risk by EGFR-ACR category. Table 2 shows that there were 4.1 more cardiovascular deaths per 1000 person-years when the EGFR was lower than 45 mL/min/1.73 m2 and microalbuminuria was present in an average person younger than 70 years, compared with those with EGFR higher than 75 mL/min/1.73 m2 and optimal ACR. The corresponding mortality risk difference for persons older than 70 years was 63.6 per 1000 person-years. The associations between EGFR-ACR and all-cause mortality, as well as coronary heart disease mortality, were assessed in secondary analyses, and the associations were similar to those for cardiovascular mortality.

Table Graphic Jump LocationTable 2. Adjusted CV Mortality Risk in Younger and Older People From the General Population by Categories of EGFR and Mean ACR in 3 Samplesa

The relative contribution of different risk factors to global cardiovascular risk is displayed in Table 3. Their ranking was nearly identical based on the change in the Akaike Criterion Information index or the area under the ROC curve. Adding EGFR-ACR or information on prevalent CVD to the risk model made the greatest additional improvement to the model in subjects younger than 70 years as well as in those 70 years or older. Diabetes mellitus had the next highest contribution, whereas current smoking changed from a moderately important variable in young and middle-aged persons to not being associated with cardiovascular risk in elderly individuals. Adding EGFR-ACR to a model already including all of the traditional risk factors substantially improved the model for both younger and older participants. Both ROC and Akaike Information Criterion analyses showed that the combined EGFR-ACR variable was especially important among older participants.

Table Graphic Jump LocationTable 3. Relative Contribution of Traditional Risk Factors and a Combined EGFR-ACR Variable to Global Cardiovascular Mortality Risk by Agea

Reclassification of subjects, that is, the percentage of subjects initially classified as having a low (<5%), intermediate (5%-10%), or high (>10%) 10-year cardiovascular mortality risk based on a traditional model who would be reclassified to higher- or lower-risk categories by a model also including GFR-ACR, is presented in Table 4. A traditional model (age, sex, prevalent CVD, hypertension treated with drugs, systolic blood pressure, current smoking, and total and high-density lipoprotein cholesterol) and a model also including EGFR-ACR agreed that 76.6% of the general population was at low risk. However, 6.6% of the general population would be classified differently by adding EGFR-ACR to the traditional model, and the most dramatic impact was on the intermediate-risk category, which constitutes 7.7% of the general population. One-quarter of the intermediate-risk subjects were reclassified to low risk, and these individuals had a 2.9-fold lower observed risk than those classified as having an intermediate risk in both models. One-tenth of the intermediate-risk subjects were reclassified to high risk, and these individuals had a 5.67-fold higher observed risk than those classified as intermediate risk in both risk models.

Table Graphic Jump LocationTable 4. Reclassification of Cardiovascular Mortality Risk (MR) in the General Population by Adding Kidney Function and Albuminuria to a Traditional Risk Modela

In this large, population-based study, we documented that impaired kidney function and urinary albumin excretion were strongly associated with cardiovascular mortality. Both were independent risk factors with higher risk at lower EGFR below a threshold of 75 mL/min/1.73 m2 and at higher ACR with no lower threshold apparent. They were synergistic on the additive scale, suggesting better risk stratification when both EGFR and ACR are used together. The improvement of global fit of cardiovascular risk models was comparable with that obtained by adding traditional risk factors like DM, hypertension, smoking, or cholesterol, and model improvement was most dramatic in subjects who were at least 70 years old.

Until now, the combined effect of reduced kidney function and albuminuria has been uncertain. Previous data showing that patients with macroalbuminuria and EGFR levels lower than 60 mL/min/1.73 m2 have 2 to 4 times higher mortality risk than subjects without these risk factors18,19 are useful, but the impact of the much higher prevalence of lower levels of albuminuria needed to be quantified. Dipstick testing for albuminuria is a relatively insensitive method not able to detect microalbuminuria. Our study extends these previous results from Japan and from patients who have had a myocardial infarction to a white general population. Future risk in subjects with moderately to severely reduced kidney function (EGFR <60 mL/min/1.73 m2) varied dramatically by level of albuminuria. The risk remained rather low, even in elderly persons, if urinary albumin excretion was “optimal” (ACR <6 mg/g). If these data prove to be generalizable, they suggest that combined assessment with both EGFR and albuminuria will be a useful way to stratify risk among the large group of subjects with chronic kidney disease. The prevalence of chronic kidney disease is high (10%) in the United States as well as in Europe,4,5 and further risk stratification will be useful.

Current cardiovascular risk models are intended for use in subjects younger than 70 years,31,32 and all attach importance to age as a major risk factor. However, age itself is not directly causally related to CVDs but rather reflects the progressive accumulation of atherosclerosis and end organ damage. The mean risk scores for age fail to account for individual variability. Preventive treatment is increasingly offered to people older than 70 years, but applying current guidelines for primary prevention to the elderly population is problematic because it tends to indicate treatment for nearly everyone.36,37 At the same time, elderly persons are susceptible to higher risks of polypharmacy and adverse effects. Thus, more accurate risk models are needed for the elderly population, and new cardiovascular risk models should consider including information on kidney function and urinary albumin excretion.

Our study has some methodological aspects that need discussion. First, urine samples were not collected from all participants. However, ACR determinations in 3 fresh urine samples for 9709 subjects based on a stratified random sample provide a solid base for inference to the population. Second, GFR estimation based on serum creatinine level has limitations. Although we used calibrated serum creatinine values to avoid systematic bias, the GFR estimation has only moderate accuracy, especially when the GFR is greater than 60 mL/min/1.73 m2.25 This could veil a possible association to mortality and create a threshold effect. Studies of cystatin C in elderly individuals suggest that the risk associated with decreased kidney function may be strongly underestimated when one relies on creatinine.38 Third, our primary end point (cardiovascular death) was based on death certificates. Even though the Nordic cause-of-death registers have been found to be reasonably valid indicators for cardiovascular death,39,40 there might have been some misclassification. However, the unique identification number given to all Norwegian citizens at birth enabled us to determine vital status of all participants with certainty at the end of the observation period, and the effect of EGFR-ACR on all-cause mortality was similar to that observed for cardiovascular mortality. Fourth, only baseline data were available, so we could not take into account the potential effect of changing risk factors and treatments that could affect the outcomes of interest. Finally, the generalizability of our results to other races and ethnic groups may be limited.

In conclusion, decreased kidney function and increased albumin excretion, even at near-normal levels, were associated with increased cardiovascular mortality independently of each other and of established risk factors. A variable based on the combination of EGFR and ACR was especially helpful for refining risk estimates in subjects older than 70 years, and its relative contribution to global risk was comparable with that provided by individual traditional cardiovascular risk factors such as DM, hypertension, lipids, or smoking.

Correspondence: Stein Hallan, MD, PhD, Department of Cancer Research and Molecular Medicine, Faculty of Medicine, NTNU St Olav University Hospital, Olav Kyrres gt 17, Trondheim N-70006, Norway (stein.hallan@ntnu.no).

Accepted for Publication: July 1, 2007.

Author Contributions:Study concept and design: Hallan, Kvenild, and Coresh. Acquisition of data: Hallan and Kvenild. Analysis and interpretation of data: Hallan, Astor, Romundstad, Aasarød, and Coresh. Drafting of the manuscript: Hallan. Critical revision of the manuscript for important intellectual content: Astor, Romundstad, Aasarød, Kvenild, and Coresh. Statistical analysis: Hallan, Astor, and Coresh. Obtained funding: Kvenild. Administrative, technical, and material support: Romundstad, Aasarød, and Kvenild.

Financial Disclosure: None reported.

Additional Information: The HUNT Study is a collaboration between the HUNT Research Center, Faculty of Medicine, Norwegian University of Science and Technology, Verdal; the Norwegian Institute of Public Health, Oslo; Nord-Trøndelag County Council; and the Central Norway Regional Health Authority.

Additional Contributions: We thank the health service and people of Nord-Trøndelag for their endurance and participation.

Abramson  JWright  JM Are lipid-lowering guidelines evidence-based? Lancet 2007;369 (9557) 168- 169
PubMed
Robinson  JGMBakris  GMTorner  JPStone  NJMWallace  RM Is it time for a cardiovascular primary prevention trial in the elderly? Stroke 2007;38 (2) 441- 450
PubMed
National Kidney Foundation, K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002;39 (2) ((suppl 1)) S1- S246
PubMed
Coresh  JAstor  BCGreene  TEknoyan  GLevey  AS Prevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 2003;41 (1) 1- 12
PubMed
Hallan  SICoresh  JAstor  B  et al.  International comparison of the relationship of chronic kidney disease prevalence and end-stage renal disease risk. J Am Soc Nephrol 2006;17 (8) 2275- 2284
PubMed
Coresh  JAstor  BSarnak  MJ Evidence for increased cardiovascular disease risk in patients with chronic kidney disease. Curr Opin Nephrol Hypertens 2004;13 (1) 73- 81
PubMed
Go  ASChertow  GMFan  DMcCulloch  CEHsu  CY Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351 (13) 1296- 1305
PubMed
Amann  KWanner  CRitz  E Cross-talk between the kidney and the cardiovascular system. J Am Soc Nephrol 2006;17 (8) 2112- 2119
PubMed
de Zeeuw  DHillege  HLde Jong  PE The kidney, a cardiovascular risk marker, and a new target for therapy. Kidney Int Suppl 2005; (98) S25- S29
PubMed
Sarnak  MJLevey  ASSchoolwerth  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
PubMed
Tonelli  MWiebe  NCulleton  B  et al.  Chronic kidney disease and mortality risk: a systematic review. J Am Soc Nephrol 2006;17 (7) 2034- 2047
PubMed
Culleton  BFLarson  MGWilson  PW  et al.  Cardiovascular disease and mortality in a community-based cohort with mild renal insufficiency. Kidney Int 1999;56 (6) 2214- 2219
PubMed
Garg  AXClark  WFHaynes  RBHouse  AA Moderate renal insufficiency and the risk of cardiovascular mortality: results from the NHANES I. Kidney Int 2002;61 (4) 1486- 1494
PubMed
Henry  RMKostense  PJBos  G  et al.  Mild renal insufficiency is associated with increased cardiovascular mortality: the Hoorn Study. Kidney Int 2002;62 (4) 1402- 1407
PubMed
Pedrinelli  RDell'Omo  GPenno  GMariani  M Non-diabetic microalbuminuria, endothelial dysfunction and cardiovascular disease. Vasc Med 2001;6 (4) 257- 264
PubMed
Bakris  G Inclusion of albuminuria in hypertension and heart guidelines. Kidney Int Suppl 2004; (92) S124- S125
PubMed
Cifkova  RErdine  SFagard  R  et al.  Practice guidelines for primary care physicians: 2003 ESH/ESC hypertension guidelines. J Hypertens 2003;21 (10) 1779- 1786
PubMed
Tonelli  MJose  PCurhan  G  et al.  Proteinuria, impaired kidney function, and adverse outcomes in people with coronary disease: analysis of a previously conducted randomised trial. BMJ 2006;332 (7555) 1426- 1432
PubMed
Irie  FIso  HSairenchi  T  et al.  The relationships of proteinuria, serum creatinine, glomerular filtration rate with cardiovascular disease mortality in Japanese general population. Kidney Int 2006;69 (7) 1264- 1271
PubMed
Grundy  SMBazzarre  TCleeman  J  et al. Writing Group I, Prevention Conference V: beyond secondary prevention: identifying the high-risk patient for primary prevention: medical office assessment. Circulation 2000;101 (1) E3- E11
PubMed
Abbott  RDCurb  JDRodriguez  BL  et al.  Age-related changes in risk factor effects on the incidence of coronary heart disease. Ann Epidemiol 2002;12 (3) 173- 181
PubMed
Störk  SFeelders  RAvan den Beld  AW  et al.  Prediction of mortality risk in the elderly. Am J Med 2006;119 (6) 519- 525
PubMed
 Statistics Norway http://www.ssb.no/english/subjects/. Accessed December 4, 2005
Holmen  JMidthjell  KKruger  O  et al.  The Nord-Trondelag Health Study 1995-97 (HUNT 2): objectives, contents, methods and participation. Norsk Epidemiologi 2003;1319- 32
Levey  ASCoresh  JGreene  T  et al.  Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006;145 (4) 247- 254
PubMed
Hallan  SAstor  BCLydersen  S Estimating glomerular filtration rate in the general population: the second Health Survey of Nord Trondelag (HUNT II). Nephrol Dial Transplant 2006;21 (6) 1525- 1533
PubMed
World Health Organization, International Statistical Classification of Diseases, 10th Revision (ICD-10).  Geneva, Switzerland World Health Organization1992;
De Backer  GAmbrosioni  EBorch-Johnsen  K  et al.  European guidelines on cardiovascular disease prevention in clinical practice: Third Joint Task Force of European and other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of eight societies and by invited experts). Eur Heart J 2003;24 (17) 1601- 1610
PubMed
Rothman  KJGreenland  S Modern Epidemiology. 2nd ed. Philadelphia, PA Lippincott Williams & Wilkins2002;
de Jong  PECurhan  GC Screening, monitoring, and treatment of albuminuria: public health perspectives. J Am Soc Nephrol 2006;17 (8) 2120- 2126
PubMed
Anderson  KMOdell  PMWilson  PWKannel  KM Cardiovascular disease risk profiles. Am Heart J 1991;121 (1, pt 2) 293- 298
PubMed
Conroy  RMPyorala  KFitzgerald  AP  et al.  Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;24 (11) 987- 1003
PubMed
Burnham  KPAnderson  DR Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. 2nd ed. New York, NY Springer Verlag2002;
Grundy  SMPasternak  RGreenland  PSmith  S  JrFuster  V Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation 1999;100 (13) 1481- 1492
PubMed
van Venrooij  FVStolk  RPBanga  JDErkelens  DWGrobbee  DE Primary and secondary prevention in cardiovascular disease: an old-fashioned concept? J Intern Med 2002;251 (4) 301- 306
PubMed
Getz  LKirkengen  ALHetlevik  IRomundstad  SSigurdsson  JA Ethical dilemmas arising from implementation of the European guidelines on cardiovascular disease prevention in clinical practice: a descriptive epidemiological study. Scand J Prim Health Care 2004;22 (4) 202- 208
PubMed
Hartz  INjolstad  IEggen  AE Does implementation of the European guidelines based on the SCORE model double the number of Norwegian adults who need cardiovascular drugs for primary prevention? the Tromso study 2001. Eur Heart J 2005;26 (24) 2673- 2680
PubMed
Coresh  JAstor  B Decreased kidney function in the elderly: clinical and preclinical, neither benign. Ann Intern Med 2006;145 (4) 299- 301
PubMed
Pajunen  PKoukkunen  HKetonen  M  et al.  The validity of the Finnish Hospital Discharge Register and Causes of Death Register data on coronary heart disease. Eur J Cardiovasc Prev Rehabil 2005;12 (2) 132- 137
PubMed
Sundman  LJakobsson  SNystrom  LRosen  M A validation of cause of death certification for ischaemic heart disease in two Swedish municipalities. Scand J Prim Health Care 1988;6 (4) 205- 211
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Incidence rate ratio (IRR) (95% confidence interval) for cardiovascular death. The IRR associated with (A) decreasing kidney function (estimated glomerular filtration rate [EGFR]) and (B) increasing urine albumin-creatinine ratio (ACR). The restricted cubic spline models were adjusted for age, sex, EGFR, and ACR, and the reference (IRR = 1) was set to the median ACR or median EGFR. The distributions of EGFR and ACR in the general population are also shown (bars).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Cardiovascular mortality risk in the general population by categories of estimated glomerular filtration rate (EGFR) and urine albumin-creatinine ratio (ACR). The incidence rate ratios (IRRs) were adjusted for age and sex. The ACR is the mean of 3 samples, and optimal ACR is below sex-specific median (< 5 mg/g in men and < 7 mg/g in women), and high normal is 5 to 19 mg/g in men and 7 to 29 mg/g in women. Microalbuminuria is 20 to 199 mg/g in men and 30 to 299 mg/g in women.30 Subjects with an optimal ACR and an EGFR of 75 mL/min/1.73 m2 or higher comprised the reference group. *P < .05. †P < .01. ‡P < .001.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Baseline Data in the Study Populationa
Table Graphic Jump LocationTable 2. Adjusted CV Mortality Risk in Younger and Older People From the General Population by Categories of EGFR and Mean ACR in 3 Samplesa
Table Graphic Jump LocationTable 3. Relative Contribution of Traditional Risk Factors and a Combined EGFR-ACR Variable to Global Cardiovascular Mortality Risk by Agea
Table Graphic Jump LocationTable 4. Reclassification of Cardiovascular Mortality Risk (MR) in the General Population by Adding Kidney Function and Albuminuria to a Traditional Risk Modela

References

Abramson  JWright  JM Are lipid-lowering guidelines evidence-based? Lancet 2007;369 (9557) 168- 169
PubMed
Robinson  JGMBakris  GMTorner  JPStone  NJMWallace  RM Is it time for a cardiovascular primary prevention trial in the elderly? Stroke 2007;38 (2) 441- 450
PubMed
National Kidney Foundation, K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002;39 (2) ((suppl 1)) S1- S246
PubMed
Coresh  JAstor  BCGreene  TEknoyan  GLevey  AS Prevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 2003;41 (1) 1- 12
PubMed
Hallan  SICoresh  JAstor  B  et al.  International comparison of the relationship of chronic kidney disease prevalence and end-stage renal disease risk. J Am Soc Nephrol 2006;17 (8) 2275- 2284
PubMed
Coresh  JAstor  BSarnak  MJ Evidence for increased cardiovascular disease risk in patients with chronic kidney disease. Curr Opin Nephrol Hypertens 2004;13 (1) 73- 81
PubMed
Go  ASChertow  GMFan  DMcCulloch  CEHsu  CY Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351 (13) 1296- 1305
PubMed
Amann  KWanner  CRitz  E Cross-talk between the kidney and the cardiovascular system. J Am Soc Nephrol 2006;17 (8) 2112- 2119
PubMed
de Zeeuw  DHillege  HLde Jong  PE The kidney, a cardiovascular risk marker, and a new target for therapy. Kidney Int Suppl 2005; (98) S25- S29
PubMed
Sarnak  MJLevey  ASSchoolwerth  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
PubMed
Tonelli  MWiebe  NCulleton  B  et al.  Chronic kidney disease and mortality risk: a systematic review. J Am Soc Nephrol 2006;17 (7) 2034- 2047
PubMed
Culleton  BFLarson  MGWilson  PW  et al.  Cardiovascular disease and mortality in a community-based cohort with mild renal insufficiency. Kidney Int 1999;56 (6) 2214- 2219
PubMed
Garg  AXClark  WFHaynes  RBHouse  AA Moderate renal insufficiency and the risk of cardiovascular mortality: results from the NHANES I. Kidney Int 2002;61 (4) 1486- 1494
PubMed
Henry  RMKostense  PJBos  G  et al.  Mild renal insufficiency is associated with increased cardiovascular mortality: the Hoorn Study. Kidney Int 2002;62 (4) 1402- 1407
PubMed
Pedrinelli  RDell'Omo  GPenno  GMariani  M Non-diabetic microalbuminuria, endothelial dysfunction and cardiovascular disease. Vasc Med 2001;6 (4) 257- 264
PubMed
Bakris  G Inclusion of albuminuria in hypertension and heart guidelines. Kidney Int Suppl 2004; (92) S124- S125
PubMed
Cifkova  RErdine  SFagard  R  et al.  Practice guidelines for primary care physicians: 2003 ESH/ESC hypertension guidelines. J Hypertens 2003;21 (10) 1779- 1786
PubMed
Tonelli  MJose  PCurhan  G  et al.  Proteinuria, impaired kidney function, and adverse outcomes in people with coronary disease: analysis of a previously conducted randomised trial. BMJ 2006;332 (7555) 1426- 1432
PubMed
Irie  FIso  HSairenchi  T  et al.  The relationships of proteinuria, serum creatinine, glomerular filtration rate with cardiovascular disease mortality in Japanese general population. Kidney Int 2006;69 (7) 1264- 1271
PubMed
Grundy  SMBazzarre  TCleeman  J  et al. Writing Group I, Prevention Conference V: beyond secondary prevention: identifying the high-risk patient for primary prevention: medical office assessment. Circulation 2000;101 (1) E3- E11
PubMed
Abbott  RDCurb  JDRodriguez  BL  et al.  Age-related changes in risk factor effects on the incidence of coronary heart disease. Ann Epidemiol 2002;12 (3) 173- 181
PubMed
Störk  SFeelders  RAvan den Beld  AW  et al.  Prediction of mortality risk in the elderly. Am J Med 2006;119 (6) 519- 525
PubMed
 Statistics Norway http://www.ssb.no/english/subjects/. Accessed December 4, 2005
Holmen  JMidthjell  KKruger  O  et al.  The Nord-Trondelag Health Study 1995-97 (HUNT 2): objectives, contents, methods and participation. Norsk Epidemiologi 2003;1319- 32
Levey  ASCoresh  JGreene  T  et al.  Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006;145 (4) 247- 254
PubMed
Hallan  SAstor  BCLydersen  S Estimating glomerular filtration rate in the general population: the second Health Survey of Nord Trondelag (HUNT II). Nephrol Dial Transplant 2006;21 (6) 1525- 1533
PubMed
World Health Organization, International Statistical Classification of Diseases, 10th Revision (ICD-10).  Geneva, Switzerland World Health Organization1992;
De Backer  GAmbrosioni  EBorch-Johnsen  K  et al.  European guidelines on cardiovascular disease prevention in clinical practice: Third Joint Task Force of European and other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of eight societies and by invited experts). Eur Heart J 2003;24 (17) 1601- 1610
PubMed
Rothman  KJGreenland  S Modern Epidemiology. 2nd ed. Philadelphia, PA Lippincott Williams & Wilkins2002;
de Jong  PECurhan  GC Screening, monitoring, and treatment of albuminuria: public health perspectives. J Am Soc Nephrol 2006;17 (8) 2120- 2126
PubMed
Anderson  KMOdell  PMWilson  PWKannel  KM Cardiovascular disease risk profiles. Am Heart J 1991;121 (1, pt 2) 293- 298
PubMed
Conroy  RMPyorala  KFitzgerald  AP  et al.  Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;24 (11) 987- 1003
PubMed
Burnham  KPAnderson  DR Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. 2nd ed. New York, NY Springer Verlag2002;
Grundy  SMPasternak  RGreenland  PSmith  S  JrFuster  V Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation 1999;100 (13) 1481- 1492
PubMed
van Venrooij  FVStolk  RPBanga  JDErkelens  DWGrobbee  DE Primary and secondary prevention in cardiovascular disease: an old-fashioned concept? J Intern Med 2002;251 (4) 301- 306
PubMed
Getz  LKirkengen  ALHetlevik  IRomundstad  SSigurdsson  JA Ethical dilemmas arising from implementation of the European guidelines on cardiovascular disease prevention in clinical practice: a descriptive epidemiological study. Scand J Prim Health Care 2004;22 (4) 202- 208
PubMed
Hartz  INjolstad  IEggen  AE Does implementation of the European guidelines based on the SCORE model double the number of Norwegian adults who need cardiovascular drugs for primary prevention? the Tromso study 2001. Eur Heart J 2005;26 (24) 2673- 2680
PubMed
Coresh  JAstor  B Decreased kidney function in the elderly: clinical and preclinical, neither benign. Ann Intern Med 2006;145 (4) 299- 301
PubMed
Pajunen  PKoukkunen  HKetonen  M  et al.  The validity of the Finnish Hospital Discharge Register and Causes of Death Register data on coronary heart disease. Eur J Cardiovasc Prev Rehabil 2005;12 (2) 132- 137
PubMed
Sundman  LJakobsson  SNystrom  LRosen  M A validation of cause of death certification for ischaemic heart disease in two Swedish municipalities. Scand J Prim Health Care 1988;6 (4) 205- 211
PubMed

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 130

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Topics
JAMAevidence.com

Users' Guides to the Medical Literature
Table 9.2-1 Refuted Evidence From Nonhuman Studiesa