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      High serum creatinine nonlinearity: a renal vital sign?

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          Abstract

          <p class="first" id="d8286920e252">Patients with chronic kidney disease (CKD) may have nonlinear serum creatinine concentration (SC) trajectories, especially as CKD progresses. Variability in SC is associated with renal failure and death. However, present methods for measuring SC variability are unsatisfactory because they blend information about SC slope and variance. We propose an improved method for defining and calculating a patient's SC slope and variance so that they are mathematically distinct, and we test these methods in a large sample of US veterans, examining the correlation of SC slope and SC nonlinearity (SCNL) and the association of SCNL with time to stage 4 CKD (CKD4) and death. We found a strong correlation between SCNL and rate of CKD progression, time to CKD4, and time to death, even in patients with normal renal function. We therefore argue that SCNL may be a measure of renal autoregulatory dysfunction that provides an early warning sign for CKD progression. </p>

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          Most cited references19

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          Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study.

          The Modification of Diet in Renal Disease (MDRD) Study examined the effects of dietary protein restriction and strict blood pressure control on the decline in glomerular filtration rate (GFR) in 840 patients with diverse renal diseases. We describe a systematic analysis to determine baseline factors that predict the decline in GFR, or which alter the efficacy of the diet or blood pressure interventions. Univariate analysis identified 18 of 41 investigated baseline factors as significant (P < 0.05) predictors of GFR decline. In multivariate analysis, six factors--greater urine protein excretion, diagnosis of polycystic kidney disease (PKD), lower serum transferrin, higher mean arterial pressure, black race, and lower serum HDL cholesterol--independently predicted a faster decline in GFR. Together with the study interventions, these six factors accounted for 34.5% and 33.9% of the variance between patients in GFR slopes in Studies A and B, respectively, with proteinuria and PKD playing the predominant role. The mean rate of GFR decline was not significantly related to baseline GFR, suggesting an approximately linear mean GFR decline as renal disease progresses. The 41 baseline predictors were also assessed for their interactions with the diet and blood pressure interventions. A greater benefit of the low blood pressure intervention was found in patients with higher baseline urine protein. None of the 41 baseline factors were shown to predict a greater or lesser effect of dietary protein restriction.
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            Renal autoregulation in health and disease.

            Intrarenal autoregulatory mechanisms maintain renal blood flow (RBF) and glomerular filtration rate (GFR) independent of renal perfusion pressure (RPP) over a defined range (80-180 mmHg). Such autoregulation is mediated largely by the myogenic and the macula densa-tubuloglomerular feedback (MD-TGF) responses that regulate preglomerular vasomotor tone primarily of the afferent arteriole. Differences in response times allow separation of these mechanisms in the time and frequency domains. Mechanotransduction initiating the myogenic response requires a sensing mechanism activated by stretch of vascular smooth muscle cells (VSMCs) and coupled to intracellular signaling pathways eliciting plasma membrane depolarization and a rise in cytosolic free calcium concentration ([Ca(2+)]i). Proposed mechanosensors include epithelial sodium channels (ENaC), integrins, and/or transient receptor potential (TRP) channels. Increased [Ca(2+)]i occurs predominantly by Ca(2+) influx through L-type voltage-operated Ca(2+) channels (VOCC). Increased [Ca(2+)]i activates inositol trisphosphate receptors (IP3R) and ryanodine receptors (RyR) to mobilize Ca(2+) from sarcoplasmic reticular stores. Myogenic vasoconstriction is sustained by increased Ca(2+) sensitivity, mediated by protein kinase C and Rho/Rho-kinase that favors a positive balance between myosin light-chain kinase and phosphatase. Increased RPP activates MD-TGF by transducing a signal of epithelial MD salt reabsorption to adjust afferent arteriolar vasoconstriction. A combination of vascular and tubular mechanisms, novel to the kidney, provides for high autoregulatory efficiency that maintains RBF and GFR, stabilizes sodium excretion, and buffers transmission of RPP to sensitive glomerular capillaries, thereby protecting against hypertensive barotrauma. A unique aspect of the myogenic response in the renal vasculature is modulation of its strength and speed by the MD-TGF and by a connecting tubule glomerular feedback (CT-GF) mechanism. Reactive oxygen species and nitric oxide are modulators of myogenic and MD-TGF mechanisms. Attenuated renal autoregulation contributes to renal damage in many, but not all, models of renal, diabetic, and hypertensive diseases. This review provides a summary of our current knowledge regarding underlying mechanisms enabling renal autoregulation in health and disease and methods used for its study.
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              Trajectories of kidney function decline in the 2 years before initiation of long-term dialysis.

              Little is known about patterns of kidney function decline leading up to the initiation of long-term dialysis. Retrospective cohort study. 5,606 Veterans Affairs patients who initiated long-term dialysis in 2001-2003. Trajectory of estimated glomerular filtration rate (eGFR) during the 2-year period before initiation of long-term dialysis. Patient characteristics and care practices before and at the time of dialysis initiation and survival after initiation. We identified 4 distinct trajectories of eGFR during the 2-year period before dialysis initiation: 62.8% of patients had persistently low level of eGFR 60 mL/min/1.73 m2 (mean eGFR slope, 32.3 ± 13.4 mL/min/1.73 m2 per year), and 3.1% experienced catastrophic loss of eGFR from levels > 60 mL/min/1.73 m2 within 6 months or less. Patients with steeper eGFR trajectories were more likely to have been hospitalized and have an inpatient diagnosis of acute kidney injury. They were less likely to have received recommended predialysis care and had a higher risk of death in the first year after dialysis initiation. There is substantial heterogeneity in patterns of kidney function loss leading up to the initiation of long-term dialysis perhaps calling for a more flexible approach toward preparing for end-stage renal disease. Published by Elsevier Inc.
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                Author and article information

                Journal
                American Journal of Physiology-Renal Physiology
                American Journal of Physiology-Renal Physiology
                American Physiological Society
                1931-857X
                1522-1466
                August 2016
                August 2016
                : 311
                : 2
                : F305-F309
                Affiliations
                [1 ]Department of Medicine, Veterans Affairs Medical Center, Washington, District of Columbia;
                [2 ]Division of Renal Diseases and Hypertension, Department of Medicine, George Washington University Medical Center, Washington, District of Columbia;
                [3 ]Department of Anesthesiology and Critical Care Medicine, George Washington University Medical Center, Washington, District of Columbia;
                [4 ]Department of Medicine, University of Maryland at Baltimore, Baltimore, Maryland;
                [5 ]National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland;
                [6 ]Biostatistics Core, Veterans Affairs Medical Center, Washington, District of Columbia;
                [7 ]Department of Surgery, George Washington University School of Medicine and Health Sciences, Washington, District of Columbia
                Article
                10.1152/ajprenal.00025.2016
                4971886
                27194712
                5e293c17-cbca-4ed4-9ba4-14cabd56b1eb
                © 2016
                History

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