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Variability in estimated glomerular filtration rate by area under the curve predicts renal outcomes in chronic kidney disease.

Chen SC, Lin MY, Huang TH, Hung CC, Chiu YW, Chang JM, Tsai JC, Hwang SJ, Chen HC - ScientificWorldJournal (2014)

Bottom Line: A significant improvement in model prediction was based on the -2 log likelihood ratio statistic.In an adjusted Cox model, a smaller initial eGFR AUC%_12M (P < 0.001), a smaller peak eGFR AUC%_12M (P < 0.001), and a larger negative eGFR slope_12M (P < 0.001) were associated with a higher risk of renal end point.Two calculated formulas: initial eGFR AUC%_12M and eGFR slope_12M were the best predictors.

View Article: PubMed Central - PubMed

Affiliation: Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, 100 Shih-Chuan 1st Road, Kaohsiung 807, Taiwan ; Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan ; Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan.

ABSTRACT
Greater variability in renal function is associated with mortality in patients with chronic kidney disease (CKD). However, few studies have demonstrated the predictive value of renal function variability in relation to renal outcomes. This study investigates the predictive ability of different methods of determining estimated glomerular filtration rate (eGFR) variability for progression to renal replacement therapy (RRT) in CKD patients. This was a prospective observational study, which enrolled 1,862 CKD patients. The renal end point was defined as commencement of RRT. The variability in eGFR was measured by the area under the eGFR curve (AUC)%. A significant improvement in model prediction was based on the -2 log likelihood ratio statistic. During a median 28.7-month follow-up, there were 564 (30.3%) patients receiving RRT. In an adjusted Cox model, a smaller initial eGFR AUC%_12M (P < 0.001), a smaller peak eGFR AUC%_12M (P < 0.001), and a larger negative eGFR slope_12M (P < 0.001) were associated with a higher risk of renal end point. Two calculated formulas: initial eGFR AUC%_12M and eGFR slope_12M were the best predictors. Our results demonstrate that the greater eGFR variability by AUC% is associated with the higher risk of progression to RRT.

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Related in: MedlinePlus

Derivation of patient cohort from all patients registered between February 2002 and September 2007; 1,862 patients were included in the analysis cohort.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig1: Derivation of patient cohort from all patients registered between February 2002 and September 2007; 1,862 patients were included in the analysis cohort.

Mentions: Between February 2002 and September 2008, 3,475 patients who joined the ICKD (Integrated CKD care program) prospective observation study from two affiliated hospitals (Kaohsiung Medical University Hospital and Kaohsiung Municipal Hsiao-Kang Hospital) of Kaohsiung Medical University were included and followed until May 2010. CKD was defined by using the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines, and the CKD stage was classified using each subject's baseline eGFR [15]. Patients who had only two serum creatinine measurements during follow-up (n = 413) or whose follow-up period was less than 12 months (n = 1048) were excluded. Besides, patients with CKD stages 1 and 2 (n = 152) were excluded. The final study population consisted of 1,862 CKD patients. Figure 1 showed the flowchart of the derivation of the cohort. Baseline variables included demographic features (age and sex), medical history (diabetes mellitus [DM], hypertension, and cardiovascular disease), examination findings (body mass index [BMI] and blood pressure), and laboratory data (albumin, fasting glucose, triglyceride, total cholesterol, hemoglobin, total calcium, phosphate, calcium-phosphorous product [Ca × P product], uric acid, and urine protein-to-creatinine ratio). DM and hypertension were defined by clinical diagnosis. Cardiovascular disease was defined as clinical diagnosis of heart failure, acute or chronic ischemic heart disease, and cerebrovascular disease. The laboratory data 3 months before and after enrollment in the CKD care system were averaged and analyzed. In addition, information of medications using angiotensin converting enzyme inhibitors (ACEI) and angiotensin II receptor blockers (ARB) during the study period was obtained from medical records.


Variability in estimated glomerular filtration rate by area under the curve predicts renal outcomes in chronic kidney disease.

Chen SC, Lin MY, Huang TH, Hung CC, Chiu YW, Chang JM, Tsai JC, Hwang SJ, Chen HC - ScientificWorldJournal (2014)

Derivation of patient cohort from all patients registered between February 2002 and September 2007; 1,862 patients were included in the analysis cohort.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4226187&req=5

fig1: Derivation of patient cohort from all patients registered between February 2002 and September 2007; 1,862 patients were included in the analysis cohort.
Mentions: Between February 2002 and September 2008, 3,475 patients who joined the ICKD (Integrated CKD care program) prospective observation study from two affiliated hospitals (Kaohsiung Medical University Hospital and Kaohsiung Municipal Hsiao-Kang Hospital) of Kaohsiung Medical University were included and followed until May 2010. CKD was defined by using the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines, and the CKD stage was classified using each subject's baseline eGFR [15]. Patients who had only two serum creatinine measurements during follow-up (n = 413) or whose follow-up period was less than 12 months (n = 1048) were excluded. Besides, patients with CKD stages 1 and 2 (n = 152) were excluded. The final study population consisted of 1,862 CKD patients. Figure 1 showed the flowchart of the derivation of the cohort. Baseline variables included demographic features (age and sex), medical history (diabetes mellitus [DM], hypertension, and cardiovascular disease), examination findings (body mass index [BMI] and blood pressure), and laboratory data (albumin, fasting glucose, triglyceride, total cholesterol, hemoglobin, total calcium, phosphate, calcium-phosphorous product [Ca × P product], uric acid, and urine protein-to-creatinine ratio). DM and hypertension were defined by clinical diagnosis. Cardiovascular disease was defined as clinical diagnosis of heart failure, acute or chronic ischemic heart disease, and cerebrovascular disease. The laboratory data 3 months before and after enrollment in the CKD care system were averaged and analyzed. In addition, information of medications using angiotensin converting enzyme inhibitors (ACEI) and angiotensin II receptor blockers (ARB) during the study period was obtained from medical records.

Bottom Line: A significant improvement in model prediction was based on the -2 log likelihood ratio statistic.In an adjusted Cox model, a smaller initial eGFR AUC%_12M (P < 0.001), a smaller peak eGFR AUC%_12M (P < 0.001), and a larger negative eGFR slope_12M (P < 0.001) were associated with a higher risk of renal end point.Two calculated formulas: initial eGFR AUC%_12M and eGFR slope_12M were the best predictors.

View Article: PubMed Central - PubMed

Affiliation: Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, 100 Shih-Chuan 1st Road, Kaohsiung 807, Taiwan ; Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan ; Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan.

ABSTRACT
Greater variability in renal function is associated with mortality in patients with chronic kidney disease (CKD). However, few studies have demonstrated the predictive value of renal function variability in relation to renal outcomes. This study investigates the predictive ability of different methods of determining estimated glomerular filtration rate (eGFR) variability for progression to renal replacement therapy (RRT) in CKD patients. This was a prospective observational study, which enrolled 1,862 CKD patients. The renal end point was defined as commencement of RRT. The variability in eGFR was measured by the area under the eGFR curve (AUC)%. A significant improvement in model prediction was based on the -2 log likelihood ratio statistic. During a median 28.7-month follow-up, there were 564 (30.3%) patients receiving RRT. In an adjusted Cox model, a smaller initial eGFR AUC%_12M (P < 0.001), a smaller peak eGFR AUC%_12M (P < 0.001), and a larger negative eGFR slope_12M (P < 0.001) were associated with a higher risk of renal end point. Two calculated formulas: initial eGFR AUC%_12M and eGFR slope_12M were the best predictors. Our results demonstrate that the greater eGFR variability by AUC% is associated with the higher risk of progression to RRT.

Show MeSH
Related in: MedlinePlus