Document Detail

Clinical correlates of renal dysfunction in hypertensive patients without cardiovascular complications: the REDHY study.
Jump to Full Text
MedLine Citation:
PMID:  19440210     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Our study was aimed to assess the clinical correlates of different degrees of renal dysfunction in a wide group of non-diabetic hypertensive patients, free from cardiovascular (CV) complications and known renal diseases, participating to the REDHY (REnal Dysfunction in HYpertension) study. A total of 1856 hypertensive subjects (mean age: 47+/-14 years), attending our hypertension centre, were evaluated. The glomerular filtration rate (GFR) was estimated by the simplified Modification of Diet in Renal Disease Study prediction equation. A 24-h urine sample was collected to determine albumin excretion rate (AER). Albuminuria was defined as an AER greater than 20 microg min(-1). We used the classification proposed by the US National Kidney Foundation's guidelines for chronic kidney disease (CKD) to define the stages of renal function impairment. In multiple logistic regression analysis, the probability of having stage 1 and stage 2 CKD was significantly higher in subjects with greater values of systolic blood pressure (SBP) and with larger waist circumference. SBP was also positively related to stage 3 CKD. Stage 3 and stages 4-5 CKD were inversely associated with waist circumference and directly associated with serum uric acid. Age was inversely related to stage 1 CKD and directly related to stage 3 CKD. The factors associated with milder forms of kidney dysfunction are, in part, different from those associated with more advanced stages of renal function impairment.
Authors:
G Cerasola; G Mulè; E Nardi; P Cusimano; A Palermo; R Arsena; M Guarneri; C Geraci; S Cottone
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of human hypertension     Volume:  24     ISSN:  1476-5527     ISO Abbreviation:  J Hum Hypertens     Publication Date:  2010 Jan 
Date Detail:
Created Date:  2009-12-16     Completed Date:  2010-02-19     Revised Date:  2011-07-25    
Medline Journal Info:
Nlm Unique ID:  8811625     Medline TA:  J Hum Hypertens     Country:  England    
Other Details:
Languages:  eng     Pagination:  44-50     Citation Subset:  IM    
Affiliation:
Cattedra di Medicina Interna, Dipartimento di Medicina Interna, Malattie Cardiovascolari e Nefrourologiche, European Society of Hypertension Excellence Centre, Università di Palermo, Palermo 90146, Italy.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Albuminuria / etiology*
Cardiovascular Diseases / etiology*
Chronic Disease
Female
Glomerular Filtration Rate
Humans
Hypertension / complications*,  drug therapy,  physiopathology
Kidney Diseases / etiology*
Logistic Models
Male
Middle Aged
Risk Factors
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): J Hum Hypertens
ISSN: 0950-9240
ISSN: 1476-5527
Publisher: Nature Publishing Group
Article Information
Download PDF
Copyright © 2010 Macmillan Publishers Limited
open-access:
Received Day: 01 Month: 01 Year: 2009
Revision Received Day: 16 Month: 04 Year: 2009
Accepted Day: 16 Month: 04 Year: 2009
Print publication date: Month: 01 Year: 2010
Electronic publication date: Day: 14 Month: 05 Year: 2009
Volume: 24 Issue: 1
First Page: 44 Last Page: 50
ID: 3017309
PubMed Id: 19440210
Publisher Item Identifier: jhh200941
DOI: 10.1038/jhh.2009.41

Clinical correlates of renal dysfunction in hypertensive patients without cardiovascular complications: the REDHY study Alternate Title:Renal dysfunction and arterial hypertension
G Cerasola1
G Mulè1*
E Nardi1
P Cusimano1
A Palermo1
R Arsena1
M Guarneri1
C Geraci1
S Cottone2
1Cattedra di Medicina Interna, Dipartimento di Medicina Interna, Malattie Cardiovascolari e Nefrourologiche, European Society of Hypertension Excellence Centre, Università di Palermo, Palermo, Italy
2Cattedra di Nefrologia, Dipartimento di Medicina Interna, Malattie Cardiovascolari e Nefrourologiche, European Society of Hypertension Excellence Centre, Università di Palermo, Palermo, Italy
*Cattedra di Medicina Interna, Dipartimento di Medicina Interna, Malattie Cardiovascolari e Nefrourologiche, European Society of Hypertension Excellence Centre, Università di Palermo, Via Monte San Calogero, 29, Palermo 90146, Italy. E-mail: giusemme@unipa.it

Introduction

Recent guidelines for the management of hypertension have recognized the relevance of albuminuria and an estimated glomerular filtration rate (eGFR) value <60 ml min−1 per 1.73 m2 on cardiovascular (CV) prognosis of hypertensive patients.1, 2, 3 The presence or absence of albumin in urine and the level of eGFR allow patients to be allocated to one of the five stages of chronic kidney disease (CKD), described by the US National Kidney Foundation's (NKF) Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines,4 which is the accepted classification of any renal disease.

The available information about the prevalence of renal dysfunction in arterial hypertension arises chiefly from clinical trials enrolling elderly hypertensive subjects or patients with high or very high CV risk.5, 6, 7, 8 Little is known about the clinical correlates of the various stages of kidney disease in arterial hypertension, especially in patients without diabetes and free from CV complications.

We recently found that renal dysfunction is highly prevalent among non-diabetic middle-aged subjects with non-malignant arterial hypertension and without CV complications, participating to the REDHY (REnal Dysfunction in HYpertension) study.9

The aim of this study was to analyse, in the same wide group of hypertensive subjects, the clinical correlates of different degrees of renal dysfunction.


Methods

The study population was selected from 2258 Caucasian hypertensive patients consecutively attending our hypertension centre. Most of them had been referred to our institution by their general practitioners for specialist advice.

Exclusion criteria:

  • Age lower than 18 years and greater than 70 years
  • Known diabetes or fasting glycaemia⩾126 mg per 100 ml
  • Grade II–III (World Health Organization classification) obesity (body mass index (BMI)>35 kg/m2)
  • Known renal, renovascular, malignant or endocrine hypertension
  • Known proteinuria and haematuria
  • Previous known nephritic diseases and hereditary renal diseases
  • Heart failure
  • Positive history or clinical signs of ischaemic heart disease
  • Positive history or clinical signs of cerebrovascular diseases
  • Major non-cardiovascular diseases
  • Unreliable 24-h urine collection. (that is, creatinine excretion <10 mg kg−1 for women and <15 mg kg−1 for men was considered undercollection; a urinary creatinine ouptut>30 mg kg−1 in men and>25 mg kg−1 in women was considered as overcollection).10

Endocrine and renovascular hypertension was ruled out by clinical examination, and determination of serum electrolytes, plasma renin activity, plasma aldosterone, plasma catecholamines and where appropriate, by performing renal echography, echo-doppler of renal arteries and renoscintigraphy. Written informed consent was obtained from each subject and the study was approved by the local review board.

In all subjects, careful clinical history and physical examination were performed. Body weight, height and waist circumference were measured by a nurse and clinic blood pressure was recorded by a doctor, following the recommendations of the 2007 European Society of Hypertension/ European Society of Cardiology guidelines.1 Clinic blood pressure was considered as the mean of three consecutive measurements obtained by a mercury sphygmomanometer, after 5 min of rest in sitting position. Blood samples were drawn to perform routine blood chemistry.

Measurements

Serum and urine creatinine concentrations were determined by the kinetic picrate method using an autoanalyser (Monarch 2000 autoanalyser; Instrumentation Laboratories, Lexington, MA, USA). The same analyser was used to determine the other routine biochemical parameters. The 24-h albumin excretion rate (AER) was assayed by radioimmunological analysis (Techno Genetics RIA Kit). In subjects with urinary tract infections, AER was determined only after appropriate antibacterial treatment. Urine collections were carried out on non-working days. The patients were advised to avoid excessive physical efforts on the day before and during the 24-h urine collections. Collections were postponed in female participants reporting menstruation or febrile illnesses at the time of collection.

The GFR was estimated (eGFR) by the abbreviated prediction equation of the Modification Diet in Renal Disease Study (MDRD):11

186 × Serum creatinine (mg per 100 ml)–1.154 × Age (years)–0.203 ( × 0.742 for Women).

The ethnicity factor of the equation was not used because our study population was exclusively white.

Albuminuria was considered as 24-h AER>20 μg min−1. Microalbuminuria and macroalbuminuria were defined as 24-h AER 20–199 μg min−1 and ⩾200 μg min−1, respectively.

We used the classification proposed by the US NKF K/DOQI guidelines for CKD to define the stages of renal function impairment.4 CKD stages were defined as follows: stage 1, eGFR greater than 90 ml min−1 per 1.73 m2 and 24-h AER>20 μg min−1; stage 2, eGFR of 60 to 89 ml min−1 per 1.73 m2 and 24-h AER>20 μg min−1; stage 3, eGFR of 30 to 59 ml−1min−1 per 1.73 m2; stage 4, eGFR of 15 to 29 ml min−1 per 1.73 m2; stage 5, eGFR less than 15 ml min−1 per 1.73 m2.4

Statistics

A total of 402 subjects met the exclusion criteria. Therefore, the final analysis involved 1856 patients.

Continuous variables were given as mean±s.d., except for AER, which, because of its skewed distribution, was expressed as the median and interquartile range. It was therefore log-transformed before starting the statistical tests.

We used one-way ANOVA for independent samples to evaluate differences in means. Comparisons of each stage of CKD with the group of subjects without CKD were performed, if the overall F-test was significant, by using the Holm post hoc test.

Proportional differences between groups were assessed by the χ2-test, with Yates' correction.

The relationship between eGFR and AER was tested by the Pearson's correlation coefficients.

To investigate the independent correlates of each stage of CKD, multiple logistic regression analyses were performed by calculating odd ratios and their 95% confidence limits, after adjustment for age, systolic (SBP) and diastolic (DBP) blood pressures, waist circumference, serum uric acid (SUA), triglycerides, high-density lipoprotein (HDL) cholesterol, total cholesterol, duration of hypertension (included as continuous variables), gender, previous treatment for hypertension, smoking habit (included as categorical variables). For this analysis, patients of stage 4 and stage 5 were pooled in a single group because the low number of subjects belonging to the stage 5.

In all multiple regression analyses, a backward stepwise procedure was used, with α=0.15 as the cut-off for entry or removal of variables, which is the default value of the SYSTAT statistical package.

The null hypothesis was rejected at a two-tailed P⩽0.05.

The statistical analyses were performed using the SYSTAT DATA software package, version 5.2 (Systat, Evanston, IL, USA).


Results

The mean age of the 1856 patients enrolled in the study was 47±14 years, 53% of whom were men. The median value and interquartile range of AER were 9 (5–18.5) μg min−1. Microalbuminuria and macroalbuminuria were detected, respectively, in 22.7 and 0.7% of the entire population. The mean values of serum creatinine and estimated GFR were, respectively, 0.97±0.58 mg per 100 ml and 89.7±26 ml min−1 per 1.73m2. Only 5.2% of the overall population had simultaneously albuminuria and an estimated GFR less than 60 ml min−1 per 1.73m2. AER and eGFR were weakly (r=−0.13), but significantly (P<0.001) inversely related.

The prevalence of the five stages of renal dysfunction is shown in Figure 1. The main clinical characteristics of the hypertensive patients with the different stages of CKD, compared to those without CKD, are given in Table 1 .

Of the patients enrolled in the study, 70% were already pharmacologically treated for hypertension. The antihypertensive treatment of this subgroup was based on: ACE inhibitors (alone and in combination with a diuretic; 35%); AT1 blockers (alone and in combination with a diuretic; 25%), β-blockers or α-β-blockers (alone and in combination with a diuretic; 11%), α-blockers (3%), calcium antagonists (12%), a combination of two or more of these drugs (14%). The distribution of the antihypertensive therapy and of the classes of BP-lowering drugs among the patients divided according to the level of renal function is reported in Table 2 . Even if the prevalence of patients treated for hypertension was higher in the group of subjects belonging to stage 1 and stage 2 CKD, when compared to the group without kidney dysfunction, the percentage of subjects treated with ACE inhibitors or AT1-blockers or other classes of antihypertensive drugs did not differ significantly in the various groups.

A stepwise multiple logistic regression model (Table 3 ) in which each stage of CKD was considered as outcome variable and including as covariates age, SBP and DBP, waist circumference, SUA, triglycerides, HDL cholesterol, total cholesterol, duration of hypertension, gender, previous treatment for hypertension, smoking habit, revealed that SBP was independently associated with stage 1, stage 2 and stage 3 CKD, whereas waist circumference was positively related to stage 1 and stage 2 CKD and inversely associated with stage 3 and stages 4–5 CKD. The same analysis showed that SUA was an independent predictor of stage 3 and stages 4–5 CKD and age was negatively associated with stage 1 and positively related to stage 3 CKD. Previous pharmacological antihypertensive therapy was positively related to stage 1 and stage 2 CKD but these associations attain statistical significance only for stage 2 CKD (Table 3).


Discussion

This study showed that, in a population of non-diabetic hypertensive subjects without CV complications, the factors associated with milder forms of renal dysfunction are, in part, different from those associated with more advanced stages of kidney dysfunction.

Indeed, multiple logistic regression analysis disclosed that waist circumference, SBP and previous pharmacological therapy for hypertension were independent correlates of both stage 1 and stage 2 CKD, even if this latter association reached statistical significance only for stage 2 CKD. These findings are consistent with several previous studies showing that SBP and abdominal obesity are two important determinants of microalbuminuria,12, 13, 14, 15, 16 a key component of the two first stages of the NKF classification of CKD.

The greater proportion of subjects, pharmacologically treated for high BP, we found in the group with stage 1 and stage 2 CKD when compared to the group without renal dysfunction is probably due to the longer duration of hypertension, the higher BP values and the greater BMI observed in the former in comparison to the latter. It is likely that all these characteristics prompted the general practitioners to treat these patients with antihypertensive drugs more frequently than those without CKD.

The inverse association we found between age and stage 1 is likely attributable to the inclusion in this stage of subjects with normal estimated GFR, which is inversely related to age in the equation used to calculate it by the MDRD study formula.11 Probably for the opposite reason we found a direct association between age and stage 3 CKD. This stage was also independently related to increased SUA and higher SBP values. Although SUA elevations have long been recognized as marker of renal disease, they are not usually considered to have a causal role in kidney dysfunction.17 However, recent epidemiologic studies have identified SUA elevations as an independent risk factor for CKD.17, 18 On the other hand, it well known that the kidney may be both a cause and a victim of high BP and there is now a consensus that systolic, rather than diastolic, BP poses the greater risk for renal function deterioration.19

Besides these expected relationships of stage 3 with SUA and SBP elevations, we observed an inverse association between waist circumference and stage 3 and stage 4–5 CKD. This finding seems to be in contrast with recent evidence that highlighted the importance of obesity as risk factor for end-stage renal disease.20, 21 However, it is noteworthy that this evidence arises chiefly from longitudinal studies performed in the general population,20, 21 also including severely obese subjects. In our study, patients with BMI greater than 35 kg/m2 were excluded to reduce the potential influence on the prevalence of kidney dysfunction of our population of the glomerulopathy related to an increased BMI and especially to severe degrees of obesity. Moreover, in some studies, conducted in hypertensive persons, lower levels of BMI were detected in subjects with decreased values of GFR, such as in our study6, 8, 22 and more recently the Framingham Offspring Study showed that obesity was not associated per se with an independent risk to develop stage 3 CKD, after adjustment for known CV disease risk factors.23 Observational investigations suggested that nutritional status deteriorates as GFR declines.24, 25 Therefore, undernutrition may contribute to explain the negative relationship we found between obesity and advanced stages of CKD. However, the cross-sectional design of this study does not allow us to establish the direction of causality relations between obesity and renal insufficiency. Some other aspects of our study need to be discussed.

Increased AER and reduced eGFR were only weakly related to each other (r=0.13). This implies that these two markers of renal dysfunction identify, in part, different groups of patients in the hypertensive population. In fact, only 5.2% of patients had simultaneously albuminuria and a reduced eGFR. Moreover, the factors associated with stages 1–2 CKD were at least, in part, distinct from those related to stages 3–5 CKD. This observation suggests that milder forms of renal dysfunction and more advanced stages of kidney dysfunction have partially different pathogenetic mechanisms and may provide complementary information regarding CV risk. Our findings are, in part, in line with recent observations obtained in hypertensive individuals26, 27 and in general population.28, 29, 30 All these data support recent recommendations defining CKD4 and stratifying subsequent risks based on both decreased GFR and albuminuria.1, 2, 3

To estimate the GFR we used the four-variable formula proposed by the MDRD study, a method that is now considered the best predictor of true GFR in clinical settings4, 31, 32 and a reliable tool for determining impaired kidney function in several populations.3, 32 This formula has been recently questioned, because it may underestimate the true GFR in the normal-high range.31 Consequently, the MDRD equation should be used with caution in patients with GFR>60 ml min−1 per 1.73 m2. Despite this limitation, it has been clearly documented that the GFR estimated by the MDRD formula is a powerful prognosticator for adverse CV outcomes.6, 8, 20, 28, 29, 30, 33 Moreover, in the hypertensive population of the VALUE trial, the MDRD study equation was a better predictor of CV events than the creatinine clearance rate calculated by the Cockcroft–Gault formula.8

Study limitations

Our study should be interpreted within the context of its limitations.

The main limitation is the cross-sectional nature of our investigation that precluded assessment of the temporality of the observed associations and thus determination of causality.

Another possible weakness in our results could be represented by the influence of pharmacologic treatment, even if it was taken into account in the multivariate analyses. Moreover, the percentage of subjects treated with ACE inhibitors or AT1-blockers or other classes of antihypertensive drugs did not differ significantly in the various groups.

It is well known that there is a considerable intrapersonal variation of urinary albumin excretion.4, 13 Therefore, the measurement of only one value of AER may be another limitation of our study. However, as reported in the methods section, we adopted several precautions to reduce the variability of AER. We previously performed a study in 70 never-treated hypertensive subjects, which underwent two measurements of the 24-h AER at 1 week interval, using the same precautions employed in this study.34 We found a Spearman's correlation coefficient for these two measurements of 0.75 (P<0.0001). Of those participants with microalbuminuria at the fist examination, 81% had microalbuminuria at the second evaluation.34 Moreover, it is important to note that in several studies, in which a relationship between AER and CV prognosis was found, only one measurement was performed.13

In conclusion, in non-diabetic hypertensive patients without CV complications the factors associated with milder forms of renal dysfunction are, in part, different from those associated with more advanced stages of kidney dysfunction. This may suggest partially distinct pathogenetic mechanisms.


Conflict of interest

The authors declare no conflict of interest.


This work was supported, in part, by the Italian Ministry for University and Scientific Research (MURST) grants (‘ex 60% quotas').


References
Mancia G,De Backer G,Dominiczak A,Cifkova R,Fagard R,Germanò G,et al. 2007 guidelines for the management of arterial hypertension: the task force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC)J HypertensYear: 2007251105118717563527
Joint National Committee on Detection, Evaluation and Treatment of High Blood PressureThe Seventh Report of The Joint National Committee,Evaluation and treatment of high blood pressureJAMAYear: 200315724132446
Sarnak MJ,Levey AS,Schoolwerth AC,Coresh J,Culleton B,Hamm LL,et al. American heart association councils on kidney in cardiovascular disease, high blood pressure research, clinical cardiology, and epidemiology and prevention. 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 preventionHypertensionYear: 2003421050106514604997
National Kidney FoundationK/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratificationAm J Kidney DisYear: 200239S1S26611904577
Ruilope LM,Salvetti A,Jamerson K,Hansson L,Warnold I,Wedel H,et al. Renal function and intensive lowering of blood pressure in hypertensive participants of the Hypertension Optimal Treatment (HOT) studyJ Am Soc NephrolYear: 20011221822511158211
Rahman M,Brown CD,Coresh J,Davis BR,Eckfeldt JH,Kopyt N,Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial Collaborative Research Groupet al. The prevalence of reduced glomerular filtration rate in older hypertensive patients and its association with cardiovascular diseaseArch Intern MedYear: 200416496997615136305
de Leeuw PW,Ruilope LM,Palmer CR,Brown MJ,Castaigne A,Mancia G,et al. Clinical significance of renal function in hypertensive patients at high risk. Results from the INSIGHT trialArch Intern MedYear: 20041642459246415596636
Ruilope LM,Zanchetti A,Julius S,McInnes GT,Segura J,Stolt P,et al. VALUE Investigators. Prediction of cardiovascular outcome by estimated glomerular filtration rate and estimated creatinine clearance in the high-risk hypertension population of the VALUE trialJ HypertensYear: 2007251473147917563571
Cerasola G,Mulè G,Cottone S,Nardi E,Cusimano P. Hypertension, microalbuminuria and renal dysfunction. The REDHY (REnal Dysfunction in HYpertension) studyJ NephrolYear: 20082136837318587725
Rose BD. Clinical assessment of renal functionIn: Rose BD (ed).Pathophysiology of Renal Disease2nd edn.McGraw-Hill: New York (USA)Year: 1987123
Levey AS,Greene T,Kusek J,Beck G. A simplified equation to predict glomerular filtration rate from serum creatinineJ Am Soc NephrolYear: 200011155A
Cerasola G,Cottone S,Mulè G,Nardi E,Mangano MT,Andronico G,et al. Microalbuminuria, renal dysfunction and cardiovascular complication in essential hypertensionJ HypertensYear: 1996149159208818932
Pedrinelli R,Dell'Omo G,Di Bello V,Pontremoli R,Mariani M. Microalbuminuria an integrated marker of cardiovascular risk in essential hypertensionJ Hum HypertensYear: 200216798911850764
Cerasola G,Cottone S. Microalbuminuria as a marker of vascular damage in hypertension: influence of blood pressure and metabolic patternNutr Metab Cardiovasc DisYear: 199779295
Liese AD,Hense H-W,Döring A,Stieber J,Keil U. Microalbuminuria, central adiposity and hypertension in the non-diabetic urban population of the MONICA Augsburg survey 1994/95J Hum HypertensYear: 20011579980411687925
Bonnet F,Marre M,Halimi JM,Stengel B,Lange C,Laville M,DESIR Study Groupet al. Waist circumference and the metabolic syndrome predict the development of elevated albuminuria in non-diabetic subjects: the DESIR StudyJ HypertensYear: 2006241157116316685216
Feig DI,Kang DH,Johnson RJ. Uric acid and cardiovascular riskN Engl J MedYear: 20083591811182118946066
Obermayr RP,Temml C,Knechtelsdorfer M,Gutjahr G,Kletzmayr J,Heiss S,et al. Predictors of new-onset decline in kidney function in a general middle-European populationNephrol Dial TransplantYear: 2008231265127318039642
Bakris L,Ritz E,on behalf of the World Kidney Day Steering CommitteeThe message for World Kidney Day 2009: hypertension and kidney disease—a marriage that should be preventedJ Hum HypertensYear: 20092322222519158823
Iseki K,Ikemiya Y,Kinjo K,Inoue T,Iseki C,Takishita S. Body mass index and the risk of development of end-stage renal disease in a screened cohortKidney IntYear: 2004651870187615086929
Hsu C,Iribarren C,Go A. Body mass index and risk for end-stage renal diseaseAnn Intern MedYear: 200614470170216670146
Hailpern SM,Cohen HW,Alderman MH. Renal dysfunction and ischemic heart disease mortality in a hypertensive populationJ HypertensYear: 2005231809181616148603
Foster MC,Hwang SJ,Larson MG,Lichtman JH,Parikh NI,Vasan RS,et al. Overweight, obesity, and the development of stage 3 CKD: the Framingham Heart StudyAm J Kidney DisYear: 200852394818440684
Kopple JD,Greene T,Chumlea WC,Hollinger D,Maroni BJ,Merrill D,et al. Relationship between nutritional status and the glomerular filtration rate: results from the MDRD studyKidney IntYear: 2000571688170310760105
Carvalho KT,Silva MI,Bregman R. Nutritional profile of patients with chronic renal failureJ Ren NutrYear: 2004149710015060874
Leoncini G,Ratto E,Viazzi F,Conti N,Falqui V,Parodi A,et al. Global risk stratification in primary hypertension: the role of the kidneyJ HypertensYear: 20082642743218300851
Färbom P,Wahlstrand B,Almgren P,Skrtic S,Lanke J,Weiss L,et al. Interaction between renal function and microalbuminuria for cardiovascular risk in hypertension: the nordic diltiazem studyHypertensionYear: 20085211512218504324
Foster MC,Hwang SJ,Larson MG,Parikh NI,Meigs JB,Vasan RS,et al. Cross-classification of microalbuminuria and reduced glomerular filtration rate: associations between cardiovascular disease risk factors and clinical outcomesArch Intern MedYear: 20071671386139217620532
Cirillo M,Lanti MP,Menotti A,Laurenzi M,Mancini M,Zanchetti A,et al. Definition of kidney dysfunction as a cardiovascular risk factor: use of urinary albumin excretion and estimated glomerular filtration rateArch Intern MedYear: 200816861762418362254
Astor BC,Hallan SI,Miller ER 3rd,Yeung E,Coresh J. Glomerular filtration rate, albuminuria, and risk of cardiovascular and all-cause mortality in the US populationAm J EpidemiolYear: 20081671226123418385206
Stevens LA,Coresh J,Greene T,Levey AS. Assessing kidney function--measured and estimated glomerular filtration rateN Engl J MedYear: 20063542473248316760447
Cirillo M,Anastasio P,De Santo NG. Relationship of gender, age, and body mass index to errors in predicted kidney functionNephrol Dial TransplantYear: 2005201791179815998649
Go AS,Chertow GM,Fan D,McCulloch CE,Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalizationN Engl J MedYear: 20043511296130515385656
Mulè G,Cottone S,Vadalà A,Volpe V,Mezzatesta G,Mongiovì R,et al. Relationship between albumin excretion rate and aortic stiffness in untreated essential hypertensive patientsJ Intern MedYear: 2004256222915189362

Article Categories:
  • Original Article

Keywords: arterial hypertension, renal dysfunction, albuminuria, estimated glomerular filtration rate.

Previous Document:  The epidemiology and management of severe hypertension.
Next Document:  Aortic pulse pressure and atherosclerotic structural alterations of coronary arteries.