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(Hypertension. 2005;45:198.)
© 2005 American Heart Association, Inc.
Scientific Contributions |
From the Glostrup University Hospital (H.I., M.H.O., K.W.), Denmark; Steno Diabetes Centre (K.B.-J.), Gentofte, Denmark; Umeå University Hospital (L.H.L.), Sweden; Århus University Hospital (C.E.M.), Denmark; Sahlgrenska University Hospital/Östra (B.D.), Göteborg, Sweden; Weill Medical College of Cornell University (R.B.D.), New York, NY; Karolinska University Hospital (U.de F.), Stockholm, Sweden; Helsinki University Hospital (F.F., M.S.N.), Finland; University of Michigan (S.J.), Ann Arbor; Ullevaal University Hospital (S.E.K.), Oslo, Norway; Viborg Hospital (O.L.-P.), Denmark; Haukeland University Hospital (P.O.), Bergen, Norway; University of Alabama (S.O.), Birmingham; and Merck Research Laboratories (Y.W.), West Point, PA.
Correspondence to Hans Ibsen, Chief Physician, Medical Department M, Glostrup Hospital, DK-2600 Glostrup, Denmark. E-mail haib{at}glostruphosp.kbhamt.dk
| Abstract |
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Key Words: albuminuria angiotensin antagonist blood pressure cardiovascular diseases
| Introduction |
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Although baseline level of urinary albumin excretion is a powerful risk predictor, there are no data from a comprehensive study population to clarify whether a reduction in albuminuria during antihypertensive treatment relates to a reduction in cardiovascular risk. The aim of the present study was to examine whether changes in albuminuria during antihypertensive treatment in the LIFE study predicted changes in cardiovascular risk.
| Methods |
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Urine Albumin Measurement
A morning spot-urine sample was collected in 90% of the overall LIFE study population at baseline and repeated each year of follow-up. Urine albumin concentration was determined by a standard turbidometric method on a single urine specimen. Serum and urine creatinine concentrations were analyzed using the Jaffé reaction without deproteinizing and quantified by a photometric method using the same analyzer. Urine albumin concentration (mg/L) was expressed as a ratio to urinary creatinine concentration (mmol/L) to provide a composite measure of renal glomerular capillary permeability adjusting for urine dilution (that is, UACR, mg/mmol). To derive US measures of UACR in mg/g, UACR in mg/mmol is multiplied by 8.84, indicating that the "traditional" limits for microalbuminuria, UACR 30 to 300 mg/g, is very close to UACR 3.5 to 35.0 mg/mmol. Cross-laboratory validation studies were performed between the 2 central laboratories, which were located in the United States and Europe. This did not reveal any differences in determination of UACR.10
End Points
This report is based on analyses of 971 primary composite end points, which were defined as the first occurrence of cardiovascular death, nonfatal stroke, and nonfatal myocardial infarction. Further analyses were conducted on the individual components of the primary end point: cardiovascular death (without regard to any previous nonfatal end points; n=383), fatal and nonfatal myocardial infarction (without regard to any previous stroke; n=344), and fatal and nonfatal stroke (without regard to any previous myocardial infarction; n=479). An independent committee adjudicated all end points based on definitions provided in an end point classification manual.
Statistics
The present analyses were prespecified as part of the LIFE albuminuria protocol. SPSS version 10.1 statistical software (SPSS) and SAS 8.2 (SAS Institute) were used. Clinical events were analyzed using Cox proportional hazard models, and reported hazard ratios are based on these models. Baseline and in-treatment values of UACR were classified into 4 categories (
0.5 mg/mmol, 0.5 to 1 mg/mmol, 1 to 3 mg/mmol, and >3 mg/mmol) and were included as time-varying covariates in Cox regression models. To determine whether in-treatment UACR was predictive of cardiovascular outcomes, hazard ratios for in-treatment UACR were calculated. The results of this analysis are displayed using modified KaplanMeier curves; the modification is that the risk sets for each UACR category change over time, and patients can shift among the different cohorts because their UACR level changes over the study process. Note that in-treatment values of UACR were used in these analyses rather than changes from baseline because changes are highly correlated with baseline values. For example, decreases tend to occur in patients with the highest baseline values (ie, those at highest cardiovascular risk), which would bias an analysis of changes. In another attempt to circumvent the problem that those with high baseline values and high risk have the greatest reduction in UACR, the patient population was divided into 4 groups, according to the median value of UACR at baseline (1.21 mg/mmol) and the median value at year 1 of treatment (0.67 mg/mmol). We display the result by calculating crude event rates within the 4 subgroups. In this part of the analysis, patients with a cardiovascular end point within the first year of treatment were disregarded because of a possible influence of an end point on the level of UACR at year 1.
| Results |
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Figure 1 shows the rate of primary composite end point according to 4 levels of baseline and in-treatment value of UACR (
0.5 mg/mmol, 0.5 to 1 mg/mmol, 1 to 3 mg/mmol, >3 mg/mmol). Cut points were chosen to create reasonably large sample sizes in each of the strata. Figure 1 shows that the risk for a subsequent cardiovascular end point increases 3- to 4-fold from the lowest (
0.5 mg/mmol) to the highest (>3 mg/mmol) strata. The number of at-risk patients in the strata indicates that patients tended to shift from a higher level of UACR at baseline to a lower level at years 2 and 4. This implies that when UACR is reduced from the >3 mg/mmol level to the
0.5 mg/mmol level the risk is reduced accordingly. When baseline and in-treatment levels of systolic blood pressure are introduced into the Cox proportional hazard model, the hazard ratio for in-treatment UACR is only slightly modified; for example, the hazard ratio for the composite end point is only changed from 1.184 to 1.180. This implies that only a small fraction of the risk expressed by time-varying UACR is explained by relation to in-treatment systolic blood pressure. If antihypertensive treatment (losartan versus atenolol) is introduced into the model as a covariate, the pattern of the curves is only slightly modified, in accordance with the findings that the superior effect of losartan on reduction in albuminuria compared with atenolol only explained a minor part of the benefit in favor of losartan observed in the LIFE study.10
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Table 2 and Figure 2 display the end point rates for the 4 groups of patients, subdivided according to above or below the median value of UACR at baseline (1.21 mg/mmol) and above or below median value at year 1 (0.67 mg/mmol). Data show that risk increases stepwise in each group from the group with low baseline/low year 1 level to the group with high baseline/high year 1 level; for example, the primary composite end point rate increases from 5.5% to 8.6% to 9.4% to 13.5%. Note that the rates for those with values below the median at baseline and above the median at year 1 were similar to the rates for those with values above the median at baseline and below the median at year 1. The rates for the individual end points follow the same pattern of stepwise increases in risk.
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Data for the composite end point are displayed as a KaplanMeier curve in Figure 2, which shows the likelihood of the primary composite end point during 60 months of treatment. Comparing the group with low baseline/low year 1 value to the group with high baseline/high year 1 value, the probability of the event increases from
5% to 14%. When this analysis is adjusted for baseline and year 1 systolic blood pressure in a Cox proportional hazard model, the risk estimate is not significantly modified (data not shown). Again, this indicates that the level of systolic blood pressure during treatment does not influence the risk conferred by UACR to any important degree during treatment.
| Discussion |
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Our analyses were confined to in-treatment levels of albuminuria instead of the magnitude of changes from baseline during treatment. This approach was used to circumvent the problem that patients with the highest baseline value, and the highest cardiovascular risk, most likely also would have the greatest changes in albuminuria. In fact, of the 3606 patients with UACR below the baseline median value, only 801 (22%) had a decrease greater than the median year 1 change, whereas 2784 of 3574 (78%) patients with UACR above the median baseline value had a decrease above the median year 1 change, which was as expected because of blood pressure lowering and a regression-toward-the-mean phenomenon. Therefore, an analysis focusing on changes would bias the results. Thus, we analyzed the data based on dichotomization according to the median values of UACR at baseline and year 1. With this analysis, we found a stepwise decrease in event rate, indicating that lowering of UACR would also lead to a lowering of risk in those with high, as well as low, UACR at baseline.
The effects of lowering UACR were further analyzed by the time-varying albuminuria model. This model assumes that an individual can change stratum of albuminuria by increasing or decreasing UACR within the 4 strata specified in the analysis. The clinical interpretation is that an individual with high UACR at baseline whose UACR decreased (by
1 strata) during antihypertensive treatment will accordingly have a decreased cardiovascular risk.
One of the important correlates for baseline and in-treatment level of albuminuria is the level of blood pressure.5 However, when baseline and in-treatment values of systolic blood pressure were introduced in a Cox proportional hazard model for time-varying UACR, the risk assessment expressed by UACR was only modified to a minor degree. Accordingly, when our analysis on the groups divided according to median baseline in year 1 level of UACR were adjusted for baseline and in-treatment level of systolic blood pressure, the hazard ratios were not influenced to any significant degree. This indicates that a major part of the risk predicted by values of albuminuria during treatment was not explained by the level of systolic blood pressure.
Why is the level of albuminuria a risk predictor independent of other established risk factors? We and others have proposed that albuminuria is an integrated marker of structural and functional abnormalities in hypertension, such as hypertensive vascular abnormalities, endothelial dysfunction, hypertensive cardiac abnormalities, and impairment of renal function.4,7,1013 Consequently, reductions in levels of albuminuria during treatment translate to regression of a number of vascular abnormalities in hypertension, and thereby a decrease in risk in general. Albuminuria is believed to be a measure of generalized vascular leakiness for albumin.6 This proposition is strengthened by our finding of parallel relationship between albuminuria and degree of LVH.5,8
We have shown previously that treatment with losartan confers a greater reduction in albuminuria during the study period compared with atenolol.10 We also showed that only part of the benefit of losartan relative to atenolol (
17% with very wide 95% confidence limits between 9% to 66%) was explained by its superior influence on albuminuria.10 In concordance, the outcome of the time-varying albuminuria model does not change substantially when treatment (losartan versus atenolol) is introduced as a covariate in the model.
We are not aware of any other data from a large group of hypertensive patients elucidating the influence of antihypertensive treatment on change in albuminuria and its relationship to risk. In type 2 diabetes with diabetic nephropathy,1416 but also in nondiabetic renal disease,17 there are data that indicate that the magnitude of decreases in albuminuria during renin-angiotensin-aldosterone system intervention relates to the degree of renal protection but also to the degree of reduction in cardiovascular risk.16
We believe that our data show the importance of monitoring of albuminuria in hypertensive individuals before, as well as during, treatment, a concept strongly argued for by de Zeeuw et al in patients with type 2 diabetes.14,18 Based on the present results and our previously published data,3 the risk for serious cardiovascular events already increases significantly at a level of UACR of
1.2 mg/mmol in a hypertensive population with LVH. This is a level that is much lower than the classical definition of microalbuminuria defined from diabetic population (ie,
3.5 mg/mmol), a level at which the risk in the present LIFE population already is increased
2- to 3-fold compared with the level
0.5 mg/mmol. We propose that measurement of albuminuria should be an integrated part of the management of arterial hypertension. It should be assessed before treatment and measured at yearly intervals. If the level remains high (ie, >1.0 mg/mmol) or not influenced by antihypertensive treatment, the clinician should carefully consider whether blood pressure is adequately controlled or whether other modifiable risk factors, such as smoking, lipid abnormalities, and glucose metabolism, need further intervention to decrease patient risk.
There are some limitations to this analysis. In the present study, albuminuria was characterized by determination of UACR in a single spot-urine collection at baseline and each year of follow-up; however, previous studies have documented a close correlation between spot-urine UACR and measures of albuminuria from overnight or 24-hour urine collection.19 Considering the variability in determination of UACR, only 1 measurement at each time point will weaken the relationship between UACR and outcome measures. On the other hand, this will be balanced to a major extent by the large sample size in this analysis. Patients qualified for enrollment into the study by specified ECG-LVH criteria, and hence, these results might not strictly apply to patients without ECG-LVH.
| Conclusion |
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Perspectives
Our results indicate that measurement of albuminuria should be an integrated part of management of patients with hypertension. Reduction in albuminuria might be a therapeutic goal in itself. If the level of albuminuria is not modified by a patients current antihypertensive and other treatment, further intervention directed toward blood pressure control and other modifiable risk factors should be carefully considered.
| Acknowledgments |
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Received September 8, 2004; first decision September 28, 2004; accepted December 13, 2004.
| References |
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R. Pontremoli, G. Leoncini, F. Viazzi, E. Ratto, V. Vaccaro, V. Falqui, A. Parodi, N. Conti, C. Tomolillo, and G. Deferrari Evaluation of Subclinical Organ Damage for Risk Assessment and Treatment in the Hypertensive Patient: Role of Microalbuminuria. J. Am. Soc. Nephrol., April 1, 2006; 17(4_suppl_2): S112 - S114. [Abstract] [Full Text] [PDF] |
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J. Redon Measurement of microalbuminuria - what the nephrologist should know Nephrol. Dial. Transplant., March 1, 2006; 21(3): 573 - 576. [Full Text] [PDF] |
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H. Ibsen, M. H. Olsen, K. Wachtell, K. Borch-Johnsen, L. H. Lindholm, C. E. Mogensen, B. Dahlof, S. M. Snapinn, Y. Wan, and P. A. Lyle Does Albuminuria Predict Cardiovascular Outcomes on Treatment With Losartan Versus Atenolol in Patients With Diabetes, Hypertension, and Left Ventricular Hypertrophy?: The LIFE study. Diabetes Care, March 1, 2006; 29(3): 595 - 600. [Abstract] [Full Text] [PDF] |
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N. Khosla and G. Bakris Lessons Learned from Recent Hypertension Trials about Kidney Disease Clin. J. Am. Soc. Nephrol., March 1, 2006; 1(2): 229 - 235. [Full Text] [PDF] |
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E. Ritz Reduction of Microalbuminuria by {beta} Blockers: Beyond Renin-Angiotensin System Blockade Hypertension, December 1, 2005; 46(6): 1254 - 1255. [Full Text] [PDF] |
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G. L. Bakris, V. Fonseca, R. E. Katholi, J. B. McGill, F. Messerli, R. A. Phillips, P. Raskin, J. T. Wright Jr, B. Waterhouse, M. A. Lukas, et al. Differential Effects of {beta}-Blockers on Albuminuria in Patients With Type 2 Diabetes Hypertension, December 1, 2005; 46(6): 1309 - 1315. [Abstract] [Full Text] [PDF] |
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G. Mancia and G. Grassi Efficacy of antihypertensive treatment: which endpoints should be considered? Nephrol. Dial. Transplant., November 1, 2005; 20(11): 2301 - 2303. [Full Text] [PDF] |
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M. R. Weir Blood pressure salt sensitivity: a biomeasure of kidney disease susceptibility in diabetics? Nephrol. Dial. Transplant., October 1, 2005; 20(10): 2022 - 2024. [Full Text] [PDF] |
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S. Nathan, C. J. Pepine, and G. L. Bakris Calcium Antagonists: Effects on Cardio-Renal Risk in Hypertensive Patients Hypertension, October 1, 2005; 46(4): 637 - 642. [Abstract] [Full Text] [PDF] |
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K. Rossing, K. J. Schjoedt, U. M. Smidt, F. Boomsma, and H.-H. Parving Beneficial Effects of Adding Spironolactone to Recommended Antihypertensive Treatment in Diabetic Nephropathy: A randomized, double-masked, cross-over study Diabetes Care, September 1, 2005; 28(9): 2106 - 2112. [Abstract] [Full Text] [PDF] |
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X. J, L. G, W. P, V. H, Y. X, L. Y, W. Y, P. A, C. S, D. GV, et al. Kidney and Blood Pressure--The Story Unfolds: Renalase Is a Novel, Soluble Monoamine Oxidase That Regulates Cardiac Function and Blood Pressure. J Clin Invest J. Am. Soc. Nephrol., September 1, 2005; 16(9): 2521 - 2527. [Full Text] [PDF] |
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G. Bakris Proteinuria: A Link to Understanding Changes in Vascular Compliance? Hypertension, September 1, 2005; 46(3): 473 - 474. [Full Text] [PDF] |
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C. W, Y. PX, L. BM, C. RD, M. DL, M. RH, I. H, O. MH, W. K, B.-J. K, et al. Anorexia and Cachexia in Renal Failure--Is Leptin the Culprit?: Role of Leptin and Melanocortin Signaling in Uremia-Associated Cachexia. J Clin Invest 115: 1659-1665, 2005 J. Am. Soc. Nephrol., August 1, 2005; 16(8): 2245 - 2250. [Full Text] [PDF] |
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D. de Zeeuw Albuminuria, Just a Marker for Cardiovascular Disease, Or Is It More? J. Am. Soc. Nephrol., July 1, 2005; 16(7): 1883 - 1885. [Full Text] [PDF] |
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J. Redon Urinary Albumin Excretion: Lowering the Threshold of Risk in Hypertension Hypertension, July 1, 2005; 46(1): 19 - 20. [Full Text] [PDF] |
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F. Togel, Z. Hu, K. Weiss, J. Isaac, C. Lange, C. Westenfelder, T. Stasko, M.D. Brown, J.A. Carucci, S. Euvrard, et al. Amelioration of Acute Renal Failure by Stem Cell Therapy--Paracrine Secretion Versus Transdifferentiation into Resident Cells: Administered Mesenchymal Stem Cells Protect against Ischemic Acute Renal Failure through Differentiation-Independent Mechanisms. Am J Physiol Renal Physiol E-pub February 15, 2005 J. Am. Soc. Nephrol., May 1, 2005; 16(5): 1153 - 1163. [Full Text] [PDF] |
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M. R. Weir Reduction in Microalbuminuria: A Biomeasure of Therapeutic Success? Hypertension, February 1, 2005; 45(2): 181 - 182. [Full Text] [PDF] |
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