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Original ArticlesChronic Kidney Disease
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Predictors of Estimated GFR Decline in Patients with Type 2 Diabetes and Preserved Kidney Function

Giacomo Zoppini, Giovanni Targher, Michel Chonchol, Vittorio Ortalda, Carlo Negri, Vincenzo Stoico and Enzo Bonora
CJASN March 2012, 7 (3) 401-408; DOI: https://doi.org/10.2215/CJN.07650711
Giacomo Zoppini
*Sections of Endocrinology and Metabolism and
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Giovanni Targher
*Sections of Endocrinology and Metabolism and
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Michel Chonchol
†Division of Renal Diseases and Hypertension, University of Colorado, Aurora, Colorado
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Vittorio Ortalda
‡Nephrology and Dialysis, Department of Medicine, University of Verona, Verona, Italy; and
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Carlo Negri
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Vincenzo Stoico
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Enzo Bonora
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Summary

Background and objectives This study examined predictors of the annual decline in estimated GFR (eGFR) in patients with type 2 diabetes and preserved kidney function.

Design, setting, participants, & measurements In a prospective, observational cohort study, 1682 individuals with type 2 diabetes and baseline eGFR ≥60 ml/min per 1.73 m2 (as estimated by the Chronic Kidney Disease Epidemiology Collaboration equation) were followed for 10 years. Linear regression was used to estimate participants’ changes in eGFR over time.

Results During follow-up, 263 (15.6%) individuals had a rapid eGFR decline defined as >4.0% per year. Average eGFR decline was −5.8±3 and −0.6±2 ml/min per 1.73 m2 per year in rapid decliners and nondecliners, respectively. Compared with normotensive, normoalbuminuric patients (−0.2±0.2 ml/min per 1.73 m2 per year), those with hypertension (−1.0±0.1 ml/min per 1.73 m2 per year), hemoglobin A1c≥7% (−1.0±0.1 ml/min per 1.73 m2 per year), longer diabetes duration (−1.0±0.1 ml/min per 1.73 m2 per year), obesity (−1.2±0.1 ml/min per 1.73 m2 per year), insulin treatment (−1.5±0.1 ml/min per 1.73 m2 per year), microalbuminuria (−1.3±0.2 ml/min per 1.73 m2 per year), or macroalbuminuria (−2.7±0.4 ml/min per 1.73 m2 per year) had significantly faster age-adjusted annual eGFR declines. Multivariable linear regression analyses revealed that albuminuria (P<0.001) was the strongest predictor of annual eGFR decline. Other independent predictors of annual eGFR decline were older age, hypertension, insulin treatment, and lower baseline eGFR.

Conclusions Annual eGFR decline is predicted by multiple modifiable risk factors in patients with type 2 diabetes and preserved kidney function.

Introduction

Several renal functions, particularly renal hemodynamic parameters, decline in elderly individuals even in the absence of renal disease. However, aging per se seems to exert only a modest adverse effect on renal hemodynamics (1–3). Age-related loss of kidney function is mainly due to other important comorbidities, such as diabetes, hypertension, and obesity (4–6).

Diabetic nephropathy develops in 40%–60% of individuals with type 2 diabetes and is characterized by a progressive and persistent decline in kidney function that with time can lead to ESRD (7,8). The estimated GFR (eGFR) is the most widely used parameter for the evaluation of changes in kidney function in clinical practice. However, the course of GFR is very complex and heterogeneous in type 2 diabetes, mainly depending on individual, ethnic, and disease-specific conditions (8–14). For instance, it was recently reported that albuminuria is the strongest risk factor of faster annual eGFR decline in 153 Caucasian patients with type 2 diabetes with a baseline eGFR <50 ml/min per 1.73 m2 during a 2.5-year follow-up (15). Conversely, chronic hyperglycemia has been found to play a key role in decreasing eGFR and accelerating the annual eGFR decline during a 3-year follow-up period in 729 Japanese patients with type 2 diabetes and preserved kidney function (16).

To our knowledge, most published studies aimed at examining the predictors of annual eGFR decline among patients with type 2 diabetes are limited by a relatively small sample size, short length of follow-up, and lack of sequential measurements in kidney function. In addition, data on predictors of eGFR decline in patients with type 2 diabetes and preserved kidney function are scarce.

The aim of this observational study was to examine the predictors of annual eGFR decline during a 10-year follow-up in a cohort of individuals with type 2 diabetes and a baseline eGFR ≥60 ml/min per 1.73 m2. Knowledge of the rate of annual eGFR decline and its main risk factors is of clinical importance to improve the therapeutic strategies for the primary prevention of kidney disease in patients with type 2 diabetes and preserved kidney function.

Materials and Methods

Patients

The study was performed within the frame of the Verona Diabetes Study, an observational longitudinal study on chronic complications in patients with type 2 diabetes attending the diabetes clinic at the University Hospital of Verona (17). Data included in this analysis are based on the cohort of 1682 Caucasian outpatients with type 2 diabetes, who were recruited between January 2000 and January 2002 and then followed-up until January 2011. These participants represent approximately 45% of the whole cohort of outpatients with type 2 diabetes (n=3924), who regularly attended the clinic during 2000–2002, after excluding the following: patients with an eGFR <60 ml/min per 1.73 m2 (n=1229), those who had <3 GFR estimates during the follow-up (n=320), and those who had incomplete laboratory data for analysis (n=693).

Notably, baseline demographics and laboratory data, including eGFR and albuminuria, were not significantly different between the 1682 participants in the study and those who had <3 GFR estimates during the follow-up (data not shown).

The study participants were periodically seen at the diabetes clinic (every 8–12 months) for routine medical examinations of glycemic control, kidney function parameters, and chronic complications of diabetes. The local ethics committee approved the study protocol. All participants gave their informed consent.

Clinical and Laboratory Data

Body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters. BP was measured by a physician with a mercury sphygmomanometer (at the right upper arm using an appropriate cuff size) after the patient sat quietly for at least 5 minutes. Participants were considered to have hypertension if their BP was ≥140/90 mmHg or if they were taking any antihypertensive drugs.

Information on medical history and smoking status was obtained from all patients by interviews during medical examinations. Detailed information regarding specific classes of antihypertensive drugs (e.g., angiotensin-converting enzyme [ACE] inhibitors, angiotensin receptor blockers [ARBs]) was not currently available in our information database. Diagnosis of diabetic retinopathy was based on funduscopy after pupillary dilation (18).

Venous blood was drawn the morning after an overnight fast. Serum creatinine (measured using a Jaffé rate-blanked and compensated assay), lipids, and other biochemical blood measurements were determined by standard laboratory procedures (DAX 96; Bayer Diagnostics, Milan, Italy). LDL cholesterol was calculated using Friedewald’s equation. Hemoglobin A1c was measured by an automated high-performance liquid chromatography analyzer (Bio-Rad Diamat, Milan, Italy); the upper limit of normal for our laboratory was 5.6%.

GFR was estimated from the Chronic Kidney Disease Epidemiology Collaboration creatinine equation (19). eGFR was also estimated from the four-variable Modification of Diet in Renal Disease (MDRD) equation (20). The urinary albumin excretion rate was measured from a 24-hour urine sample by an immuno-nephelometric method. Presence of abnormal albuminuria (≥30 mg/d) was confirmed in a least two of three consecutive samples (8).

Statistical Analyses

Data are presented as means ± SD or SEM and frequencies. Skewed variables were logarithmically transformed to improve normality before analysis (diabetes duration, triglycerides, and eGFR). The unpaired t test and the chi-squared test with Yates’s correction for continuity (for categorical variables) were used to analyze the differences among the baseline characteristics of participants stratified by presence or absence of a rapid eGFR decline (Table 1). For each patient, a linear regression model of time on eGFR (least-squares method) was created, and the slope of the regression line was used to estimate the patient’s changes in eGFR over time. The eGFR slope was expressed as percentage per year by dividing the slope by the baseline eGFR value (i.e., annual eGFR decline). Because no definite criteria for eGFR decliner exist, individuals with a rapid decline in eGFR were defined as those who had an eGFR decline >4.0% per year, in accord with previous studies (3,16); this threshold corresponds approximately to an eGFR loss ≥3 ml/min per 1.73 m2 per year, which has been previously used as a cut-off that reflects three times more rapid decline than expected by normal aging (21). Annual eGFR decline according to different clinical features was compared among patients’ groups by analysis of covariance after adjustment for age (Table 2 and Figures 1 and 2). Multivariable linear regression analysis was also performed to test the independent associations of annual eGFR decline (i.e., the dependent variable) with baseline covariates. We formally checked that the change in eGFR over time was linear, allowing us to use a linear regression model. In the fully adjusted regression model, sex, age, BMI, hypertension (or systolic BP included as continuous variable), diabetes duration, insulin treatment, history of previous cardiovascular disease (defined as angina, myocardial infarction, or stroke), HbA1c, eGFR (or serum creatinine), and albuminuria were included as covariates (Table 3). We also tested for a formal interaction between hypertension and albuminuria in the multivariable regression model. The hypertension × albuminuria interaction term (P=0.41) was not statistically significant.

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Table 1.

Baseline clinical and biochemical characteristics of patients with type 2 diabetes and preserved kidney function stratified by eGFR decline during a 10-year follow-up period

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Table 2.

Age-adjusted annual eGFR decline in patients with type 2 diabetes and preserved kidney function stratified by different clinical categories

Figure 1.
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Figure 1.

Age-adjusted annual eGFR decline in 1682 patients with type 2 diabetes and preserved kidney function stratified by different clinical categories. Data are expressed as mean ± SEM. CVD, cardiovascular disease; eGFR, estimated GFR.

Figure 2.
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Figure 2.

Age-adjusted annual eGFR decline in 1682 patients with type 2 diabetes and preserved kidney function stratified by hypertension and albuminuria. Data are expressed as mean ± SEM. *P<0.05 versus normotensive patients with normoalbuminuria. §P<0.01 versus hypertensive patients with normoalbuminuria. eGFR, estimated GFR.

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Table 3.

Multivariable linear regression analysis: Independent predictors of annual eGFR decline in patients with type 2 diabetes and preserved kidney function

These covariates were chosen as potential confounding factors on the basis of their significance in univariate analysis or on the basis of their biologic plausibility. A multivariable logistic regression analysis was also performed with the status of rapid eGFR decliners (yes/no) as the dependent variable. The same set of covariates was included in this logistic regression model. Statistical analysis was performed with SPSS 19.0 statistical package software. P values <0.05 were considered statistically significant.

Results

The 1682 patients with type 2 diabetes (mean age 65.1±9 years; 61.7% men) included in this study had a mean baseline eGFR of 79.6±12 ml/min per 1.73 m2; 79% (n=1328) had normal albuminuria, 17.1% (n=288) had microalbuminuria, and 3.9% (n=66) had macroalbuminuria. Approximately 85% (n=1439) of patients had hypertension (BP ≥140/90 mmHg or drug treatment). Mean HbA1c was 7.5%±1.5%.

During a mean follow-up of 10 years, all patients had ≥5 measurements of serum creatinine (median 13; range, 5–25) to accurately calculate the change in eGFR over time. Annual eGFR decline of the whole cohort was −0.9±2.9 ml/min per 1.73 m2 per year without differences between sexes (−0.9±3 and −0.8±2.6 ml/min per 1.73 m2 per year in men and women, respectively; P=0.58).

During follow-up, there were 263 (15.6%) rapid decliners, defined as those with an eGFR decline >4.0% per year. Thirty-four (2% of total) patients died, 9 (3.4%) in the group of rapid decliners and 25 (1.7%) in the group of nondecliners (P=0.06 by chi-squared test). No other patients were lost to follow-up. The follow-up rate for the cohort was 98%.

Baseline characteristics of patients grouped according to presence or absence of rapid annual eGFR decline are summarized in Table 1. Rapid decliners were significantly older, had a longer duration of diabetes, and were more likely to have hypertension, diabetic retinopathy, and abnormal albuminuria, and were more likely to be smokers and treated with insulin therapy compared with nondecliners. They also had higher systolic BP and lower eGFR at the end of follow-up. Sex, BMI, diastolic BP, HbA1c, plasma lipids, and baseline eGFR did not differ between the groups.

Table 2 shows the age-adjusted annual eGFR decline among patients at different risk categories. Patients with hypertension, diabetes duration ≥15 years, HbA1c ≥7%, obesity, insulin treatment, history of cardiovascular disease, microalbuminuria, and macroalbuminuria showed significantly faster age-adjusted annual eGFR declines than their counterparts without those risks. In contrast, annual eGFR decline was not significantly different in current smokers versus ex-smokers and nonsmokers (−0.9±0.2 versus −0.7±0.1 versus −0.7±0.1 ml/min per 1.73 m2 per year, respectively; P=0.12), in those with LDL cholesterol ≥100 versus <100 mg/dl (−0.8±0.1 versus–1.0±0.2; P=0.16), in those with HDL-cholesterol ≥50 mg/dl versus <50 mg/dl (-0.8±0.1 versus −0.9±0.2; P=0.39), or in those with triglycerides ≥150 versus <150 mg/dl (−1.0±0.1 versus −0.8±0.1; P=0.21).

Figure 1 shows the age-adjusted annual eGFR decline among participants belonging at the above-mentioned risk categories compared with that observed in normotensive, normoalbuminuric patients. The fastest annual eGFR decline was observed in those with macroalbuminuria.

Figure 2 shows the age-adjusted annual eGFR decline in patients stratified by hypertension and albuminuria. Patients with abnormal albuminuria showed a faster annual eGFR decline than their counterparts with normal albuminuria, irrespective of hypertension status. Notably, the combined presence of hypertension and abnormal albuminuria was associated with the fastest eGFR decline, whereas eGFR decline did not significantly differ in normotensive patients with microalbuminuria versus normoalbuminuric patients with hypertension.

In multivariable linear regression analysis (Table 3), albuminuria strongly predicted annual eGFR decline after adjustment for potential confounders. Other significant predictors of eGFR decline were hypertension, older age, insulin treatment, and lower eGFR at baseline. The results remained essentially unchanged when baseline serum creatinine replaced eGFR as a covariate in this regression model. In fact, the annual eGFR decline was independently (P<0.05–0.001) related to age (standardized coefficient: –0.07), hypertension (standardized coefficient: –0.10), insulin treatment (standardized coefficient: –0.11), serum creatinine (standardized coefficient: –0.07), and albuminuria (standardized coefficient: –0.15).

Almost identical results were also found when we included systolic BP as a continuous variable (standardized coefficient: –0.11; P<0.01) instead of hypertension status in the multivariable linear regression model or when we performed a multivariable logistic regression model in which eGFR decliner status was included as the dependent variable (not shown). Albuminuria was also the strongest predictor (P<0.001) of annual eGFR decline in these patients.

Similar results were observed when all of the above-mentioned statistical analyses were repeated using the four-variable MDRD study equation (data not shown).

Discussion

Most published studies aimed at assessing the predictors of eGFR decline in patients with type 2 diabetes are limited by a small sample size, short length of follow-up, and lack of sequential measurements in kidney function (i.e., most studies had only two or three serum creatinine determinations to calculate the annualized changes in eGFR). In addition, epidemiologic data on the predictors of eGFR decline in patients with type 2 diabetes and preserved kidney function are limited.

In a large cohort of individuals with type 2 diabetes and a baseline eGFR ≥60 ml/min per 1.73 m2 (approximately 80% normoalbuminuric) who were followed for 10 years, we found that the rate of annual eGFR decline was −0.9±2.9 ml/min per 1.73 m2 per year without any significant difference between sexes. Notably, we found that the most powerful risk factor of faster age-adjusted annual eGFR decline was abnormal albuminuria: −1.3±0.2 ml/min per 1.73 m2 per year for microalbuminuria and −2.7±0.4 ml/min per 1.73 m2 per year for macroalbuminuria, respectively. After adjustment for established risk factors and confounders, albuminuria remained the strongest predictor of annual eGFR decline. Other independent predictors of eGFR decline were hypertension, older age, insulin treatment, and lower baseline eGFR.

Previous studies show that albuminuria, even within the normal range, predicts adverse renal outcomes in both individuals without diabetes and patients with type 2 diabetes (22–24). A small prospective study reported that microalbuminuric, but not normoalbuminuric, participants with type diabetes (n=65, follow-up 10 years) showed a faster annual decline in GFR (as measured by the 51Cr-EDTA technique) compared with participants without diabetes (25). Nelson et al. (26) reported significant annual GFR changes (as measured by urinary clearance of iothalamate) in proteinuric, but not in microalbuminuric, Pima Indians with diabetes (n=194; 4-year follow-up). Velussi et al. (27) reported a GFR decline of −2.2 ml/min per year (as measured by the 51Cr-EDTA technique) in 18 microalbuminuric patients with type 2 diabetes and hypertension, who were treated for 3 years with either cilazapril or amlodipine. Parving (28) reviewed the published studies of proteinuric patients with type 2 diabetes during any antihypertensive treatment, and reported a GFR decline of −4.8 ml/min per year. In a study involving 729 Japanese patients with type 2 diabetes and preserved kidney function and normoalbuminuria, Yokoyama et al. (16) found that the degree of chronic hyperglycemia plays a crucial role in accelerating the annual eGFR decline during a 3-year follow-up period. In a study of 227 Caucasian patients with type 2 diabetes who were followed early after the onset of diabetic nephropathy, Rossing et al. (29) identified several modifiable risk factors (including abnormal albuminuria, hypertension, higher HbA1c, and smoking) that were independently associated with a faster progression of kidney disease (as measured by the 51Cr-EDTA technique). In our study, current smokers also tended to have a faster annual eGFR decline than ex-smokers and those who never smoked; however, this difference did not reach independent statistical significance.

Albuminuria has long been regarded as a marker of the extent of glomerular damage; however, experimental and clinical studies suggest that albuminuria might also contribute to the development and progression of glomerular and tubulointerstitial lesions (8,28,30). Accordingly, in a post hoc analysis of the Reduction of End-Points in NIDDM with the Angiotensin II Receptor Antagonist Losartan (RENAAL) study, abnormal albuminuria strongly predicted the development of ESRD in patients with type 2 diabetes and nephropathy (13). Recently, Yokoyama et al. (31) confirmed that in 1002 Japanese patients with type 2 diabetes with relatively well preserved kidney function (approximately 70% normoalbuminuric) who were followed for 4 years, urinary albumin excretion was among the most important risk factors for both albuminuria progression and annual eGFR decline.

In this study, we also found that hypertension was closely associated with a faster annual eGFR decline. Studies of albuminuric patients with type 2 diabetes not receiving early antihypertensive treatment demonstrated that annual GFR decline (as measured by the 51Cr-EDTA technique) ranged from 10 to 14 ml/min per year (25). Conversely, early antihypertensive treatment significantly reduced albuminuria and improved the rate of annual GFR decline (approximately 5 ml/min per year) in albuminuric patients with type 2 diabetes (29), as was also confirmed by several other studies (28,32–34) in which GFR was directly measured by isotopic methods. Similarly, the rate of annual eGFR decline that was observed in the ARB groups of both the RENAAL and the Irbesartan Diabetic Nephropathy trials was approximately −5 ml/min per 1.73 m2 per year (35,36).

Collectively, hypertension has been demonstrated to be a strong risk factor for the development and progression of diabetic nephropathy, and several interventional trials have shown that antihypertensive treatment may reduce the incidence of nephropathy and slow the progression of kidney disease in patients with type 2 diabetes (35–40). Accordingly, several guidelines recommend an early, aggressive treatment of hypertension in patients with type 2 diabetes regardless of whether albuminuria is present (8,28,40–42). Randomized clinical trials of patients with type 2 diabetes with early or advanced nephropathy also suggest a specific renoprotective effect by ACE inhibitors or ARBs compared with other antihypertensive agents not blocking the renin-angiotensin system (13,35–40).

This study provides further strong evidence that albuminuria is the most important risk factor of faster annual eGFR decline in patients with type 2 diabetes and preserved kidney function, and that its screening may help identify individuals at increased renal risk. Thus, albuminuria represents a target for renoprotective therapy independent from BP in patients with type 2 diabetes (43,44).

Some limitations of our study merit comment. First, because our cohort comprises Caucasian individuals with type 2 diabetes who were followed at an outpatient diabetes clinic, our results may not necessarily be generalizable to other diabetic populations. Other important limitations of our study include the following: a possible selection bias of excluding the patients who either had <3 GFR estimates during the follow-up or who had incomplete laboratory data at baseline; an inability to adjust for certain specific antihypertensive agents (i.e., ACE inhibitors and ARBs that are associated with reduced eGFR and lower albuminuria); and the use of an estimated GFR instead of a directly measured GFR to define kidney function (e.g., isotopic GFR measurements). Nonetheless, current GFR estimates facilitate the detection, evaluation, and management of CKD, and many organizations recommend the use of prediction equations for the evaluation of kidney function in large epidemiologic studies and in clinical practice (8,39–41).

Strengths of our observational study include its prospective design, the large number of participants from both sexes, the long duration of follow-up, the complete nature of the dataset, the sequential determinations of serum creatinine during the follow-up within the same laboratory (all patients had ≥5 measurements of serum creatinine), the measurements of albuminuria on 24-hour urine samples, and the ability to adjust for multiple important risk factors.

In conclusion, our study demonstrates that in a large cohort of patients with type 2 diabetes and preserved kidney function who were followed for 10 years, the annual eGFR decline is predicted by multiple modifiable risk factors. The most important risk factors seem to be the presence of abnormal albuminuria and hypertension.

Disclosures

None.

Footnotes

  • Published online ahead of print. Publication date available at www.cjasn.org.

  • Received July 27, 2011.
  • Accepted January 2, 2012.
  • Copyright © 2012 by the American Society of Nephrology

References

    1. Wesson LG
    1. Wesson LG
    : Renal hemodynamics in physiologic state. In: Physiology of the Human Kidney, edited by Wesson LG, New York, Grune & Stratton, 1969, pp 96–108
    1. Anderson S,
    2. Brenner BM
    : Effects of aging on the renal glomerulus. Am J Med 80: 435–442, 1986pmid:3513560
    1. Fliser D,
    2. Ritz E
    : Renal haemodynamics in the elderly. Nephrol Dial Transplant 11[Suppl 9]: 2–8, 1996pmid:9050028
    1. Yokoyama H,
    2. Tomonaga O,
    3. Hirayama M,
    4. Ishii A,
    5. Takeda M,
    6. Babazono T,
    7. Ujihara U,
    8. Takahashi C,
    9. Omori Y
    : Predictors of the progression of diabetic nephropathy and the beneficial effect of angiotensin-converting enzyme inhibitors in NIDDM patients. Diabetologia 40: 405–411, 1997pmid:9112017
    1. Cheng SS,
    2. Wilson DM,
    3. Munn SR
    : Predictors of progression of diabetic nephropathy: Implication for timing of kidney transplantation. Clin Transplant 11: 334–336, 1997pmid:9267725
    1. Eriksen BO,
    2. Tomtum J,
    3. Ingebretsen OC
    : Predictors of declining glomerular filtration rate in a population-based chronic kidney disease cohort. Nephron Clin Pract 115: c41–c50, 2010pmid:20173349
    1. Gall MA,
    2. Nielsen FS,
    3. Smidt UM,
    4. Parving HH
    : The course of kidney function in type 2 (non-insulin-dependent) diabetic patients with diabetic nephropathy. Diabetologia 36: 1071–1078, 1993pmid:8243857
  1. American Diabetes Association: Standards of medical care in diabetes—2011. Diabetes Care 34[Suppl 1]: S11–S61, 2011pmid:21193625
    1. Taft JL,
    2. Nolan CJ,
    3. Yeung SP,
    4. Hewitson TD,
    5. Martin FI
    : Clinical and histological correlations of decline in renal function in diabetic patients with proteinuria. Diabetes 43: 1046–1051, 1994pmid:8039599
    1. Hasslacher C,
    2. Bostedt-Kiesel A,
    3. Kempe HP,
    4. Wahl P
    : Effect of metabolic factors and blood pressure on kidney function in proteinuric type 2 (non-insulin-dependent) diabetic patients. Diabetologia 36: 1051–1056, 1993pmid:8243854
    1. Hovind P,
    2. Rossing P,
    3. Tarnow L,
    4. Smidt UM,
    5. Parving HH
    : Progression of diabetic nephropathy. Kidney Int 59: 702–709, 2001pmid:11168952
    1. Christensen PK,
    2. Gall MA,
    3. Parving HH
    : Course of glomerular filtration rate in albuminuric type 2 diabetic patients with or without diabetic glomerulopathy. Diabetes Care 23[Suppl 2]: B14–B20, 2000pmid:10860186
    1. Keane WF,
    2. Brenner BM,
    3. de Zeeuw D,
    4. Grunfeld JP,
    5. McGill J,
    6. Mitch WE,
    7. Ribeiro AB,
    8. Shahinfar S,
    9. Simpson RL,
    10. Snapinn SM,
    11. Toto R
    ; RENAAL Study Investigators: The risk of developing end-stage renal disease in patients with type 2 diabetes and nephropathy: The RENAAL study. Kidney Int 63: 1499–1507, 2003pmid:12631367
    1. Ueda H,
    2. Ishimura E,
    3. Shoji T,
    4. Emoto M,
    5. Morioka T,
    6. Matsumoto N,
    7. Fukumoto S,
    8. Miki T,
    9. Inaba M,
    10. Nishizawa Y
    : Factors affecting progression of renal failure in patients with type 2 diabetes. Diabetes Care 26: 1530–1534, 2003pmid:12716817
    1. Lorenzo V,
    2. Saracho R,
    3. Zamora J,
    4. Rufino M,
    5. Torres A
    : Similar renal decline in diabetic and non-diabetic patients with comparable levels of albuminuria. Nephrol Dial Transplant 25: 835–841, 2010pmid:19762600
    1. Yokoyama H,
    2. Kanno S,
    3. Takahashi S,
    4. Yamada D,
    5. Itoh H,
    6. Saito K,
    7. Sone H,
    8. Haneda M
    : Determinants of decline in glomerular filtration rate in nonproteinuric subjects with or without diabetes and hypertension. Clin J Am Soc Nephrol 4: 1432–1440, 2009pmid:19713288
    1. Muggeo M,
    2. Verlato G,
    3. Bonora E,
    4. Bressan F,
    5. Girotto S,
    6. Corbellini M,
    7. Gemma ML,
    8. Moghetti P,
    9. Zenere M,
    10. Cacciatori V,
    11. Zoppini G,
    12. de Marco R
    : The Verona diabetes study: A population-based survey on known diabetes mellitus prevalence and 5-year all-cause mortality. Diabetologia 38: 318–325, 1995pmid:7758879
    1. Targher G,
    2. Bertolini L,
    3. Zenari L,
    4. Lippi G,
    5. Pichiri I,
    6. Zoppini G,
    7. Muggeo M,
    8. Arcaro G
    : Diabetic retinopathy is associated with an increased incidence of cardiovascular events in type 2 diabetic patients. Diabet Med 25: 45–50, 2008pmid:18199131
    1. Levey AS,
    2. Stevens LA,
    3. Schmid CH,
    4. Zhang YL,
    5. Castro AF 3rd.,
    6. Feldman HI,
    7. Kusek JW,
    8. Eggers P,
    9. Van Lente F,
    10. Greene T,
    11. Coresh J
    ; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration): A new equation to estimate glomerular filtration rate. Ann Intern Med 150: 604–612, 2009pmid:19414839
    1. Levey AS,
    2. Bosch JP,
    3. Lewis JB,
    4. Greene T,
    5. Rogers N,
    6. Roth D
    ; Modification of Diet in Renal Disease Study Group: A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Ann Intern Med 130: 461–470, 1999pmid:10075613
    1. Rifkin DE,
    2. Shlipak MG,
    3. Katz R,
    4. Fried LF,
    5. Siscovick D,
    6. Chonchol M,
    7. Newman AB,
    8. Sarnak MJ
    : Rapid kidney function decline and mortality risk in older adults. Arch Intern Med 168: 2212–2218, 2008pmid:19001197
    1. Lin J,
    2. Hu FB,
    3. Curhan GC
    : Associations of diet with albuminuria and kidney function decline. Clin J Am Soc Nephrol 5: 836–843, 2010pmid:20299364
    1. Babazono T,
    2. Nyumura I,
    3. Toya K,
    4. Hayashi T,
    5. Ohta M,
    6. Suzuki K,
    7. Kiuchi Y,
    8. Iwamoto Y
    : Higher levels of urinary albumin excretion within the normal range predict faster decline in glomerular filtration rate in diabetic patients. Diabetes Care 32: 1518–1520, 2009pmid:19435960
    1. Meguro S,
    2. Shigihara T,
    3. Kabeya Y,
    4. Tomita M,
    5. Atsumi Y
    : Increased risk of renal deterioration associated with low eGFR in type 2 diabetes mellitus only in albuminuric subjects. Intern Med 48: 657–663, 2009pmid:19420810
    1. Murussi M,
    2. Gross JL,
    3. Silveiro SP
    : Glomerular filtration rate changes in normoalbuminuric and microalbuminuric type 2 diabetic patients and normal individuals: A 10-year follow-up. J Diabetes Complications 20: 210–215, 2006pmid:16798471
    1. Nelson RG,
    2. Bennett PH,
    3. Beck GJ,
    4. Tan M,
    5. Knowler WC,
    6. Mitch WE,
    7. Hirschman GH,
    8. Myers BD
    ; Diabetic Renal Disease Study Group: Development and progression of renal disease in Pima Indians with non-insulin-dependent diabetes mellitus. N Engl J Med 335: 1636–1642, 1996pmid:8929360
    1. Velussi M,
    2. Brocco E,
    3. Frigato F,
    4. Zolli M,
    5. Muollo B,
    6. Maioli M,
    7. Carraro A,
    8. Tonolo G,
    9. Fresu P,
    10. Cernigoi AM,
    11. Fioretto P,
    12. Nosadini R
    : Effects of cilazapril and amlodipine on kidney function in hypertensive NIDDM patients. Diabetes 45: 216–222, 1996pmid:8549868
    1. Parving HH
    : Renoprotection in diabetes: Genetic and non-genetic risk factors and treatment. Diabetologia 41: 745–759, 1998pmid:9686914
    1. Rossing K,
    2. Christensen PK,
    3. Hovind P,
    4. Tarnow L,
    5. Rossing P,
    6. Parving HH
    : Progression of nephropathy in type 2 diabetic patients. Kidney Int 66: 1596–1605, 2004pmid:15458456
    1. Parving HH,
    2. Gall MA,
    3. Skøtt P,
    4. Jørgensen HE,
    5. Løkkegaard H,
    6. Jørgensen F,
    7. Nielsen B,
    8. Larsen S
    : Prevalence and causes of albuminuria in non-insulin-dependent diabetic patients. Kidney Int 41: 758–762, 1992pmid:1513098
    1. Yokoyama H,
    2. Kanno S,
    3. Takahashi S,
    4. Yamada D,
    5. Honjo J,
    6. Saito K,
    7. Sone H,
    8. Haneda M
    : Risks for glomerular filtration rate decline in association with progression of albuminuria in type 2 diabetes. Nephrol Dial Transplant 26: 2924–2930, 2011pmid:21303964
    1. Trevisan R,
    2. Vedovato M,
    3. Mazzon C,
    4. Coracina A,
    5. Iori E,
    6. Tiengo A,
    7. Del Prato S
    : Concomitance of diabetic retinopathy and proteinuria accelerates the rate of decline of kidney function in type 2 diabetic patients. Diabetes Care 25: 2026–2031, 2002pmid:12401751
    1. Nosadini R,
    2. Velussi M,
    3. Brocco E,
    4. Bruseghin M,
    5. Abaterusso C,
    6. Saller A,
    7. Dalla Vestra M,
    8. Carraro A,
    9. Bortoloso E,
    10. Sambataro M,
    11. Barzon I,
    12. Frigato F,
    13. Muollo B,
    14. Chiesura-Corona M,
    15. Pacini G,
    16. Baggio B,
    17. Piarulli F,
    18. Sfriso A,
    19. Fioretto P
    : Course of renal function in type 2 diabetic patients with abnormalities of albumin excretion rate. Diabetes 49: 476–484, 2000pmid:10868971
    1. Nielsen FS,
    2. Rossing P,
    3. Gall MA,
    4. Skøtt P,
    5. Smidt UM,
    6. Parving HH
    : Impact of lisinopril and atenolol on kidney function in hypertensive NIDDM subjects with diabetic nephropathy. Diabetes 43: 1108–1113, 1994pmid:8070610
    1. Brenner BM,
    2. Cooper ME,
    3. de Zeeuw D,
    4. Keane WF,
    5. Mitch WE,
    6. Parving HH,
    7. Remuzzi G,
    8. Snapinn SM,
    9. Zhang Z,
    10. Shahinfar S
    ; RENAAL Study Investigators: Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 345: 861–869, 2001pmid:11565518
    1. Lewis EJ,
    2. Hunsicker LG,
    3. Clarke WR,
    4. Berl T,
    5. Pohl MA,
    6. Lewis JB,
    7. Ritz E,
    8. Atkins RC,
    9. Rohde R,
    10. Raz I
    ; Collaborative Study Group: Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 345: 851–860, 2001pmid:11565517
    1. Bakris GL,
    2. Weir MR,
    3. Shanifar S,
    4. Zhang Z,
    5. Douglas J,
    6. van Dijk DJ,
    7. Brenner BM
    ; RENAAL Study Group: Effects of blood pressure level on progression of diabetic nephropathy: Results from the RENAAL study. Arch Intern Med 163: 1555–1565, 2003pmid:12860578
    1. Barnett AH,
    2. Bain SC,
    3. Bouter P,
    4. Karlberg B,
    5. Madsbad S,
    6. Jervell J,
    7. Mustonen J
    ; Diabetics Exposed to Telmisartan and Enalapril Study Group: Angiotensin-receptor blockade versus converting-enzyme inhibition in type 2 diabetes and nephropathy. N Engl J Med 351: 1952–1961, 2004pmid:15516696
    1. Jafar TH,
    2. Stark PC,
    3. Schmid CH,
    4. Landa M,
    5. Maschio G,
    6. de Jong PE,
    7. de Zeeuw D,
    8. Shahinfar S,
    9. Toto R,
    10. Levey AS
    ; AIPRD Study Group: 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, 2003pmid:12965979
  2. KDOQI: KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis 49[Suppl 2]: S12–S154, 2007pmid:17276798
  3. National Kidney Foundation: K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39[Suppl 1]: S1–S266, 2002pmid:11904577
    1. Stevens LA,
    2. Coresh J,
    3. Greene T,
    4. Levey AS
    : Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 354: 2473–2483, 2006pmid:16760447
    1. van der Velde M,
    2. Halbesma N,
    3. de Charro FT,
    4. Bakker SJ,
    5. de Zeeuw D,
    6. de Jong PE,
    7. Gansevoort RT
    : Screening for albuminuria identifies individuals at increased renal risk. J Am Soc Nephrol 20: 852–862, 2009pmid:19211710
    1. Eijkelkamp WB,
    2. Zhang Z,
    3. Remuzzi G,
    4. Parving HH,
    5. Cooper ME,
    6. Keane WF,
    7. Shahinfar S,
    8. Gleim GW,
    9. Weir MR,
    10. Brenner BM,
    11. de Zeeuw D
    : Albuminuria is a target for renoprotective therapy independent from blood pressure in patients with type 2 diabetic nephropathy: Post hoc analysis from the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) trial. J Am Soc Nephrol 18: 1540–1546, 2007pmid:17409317

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