Predicting the risk of end-stage renal disease in the population-based setting: a retrospective case-control study

Abstract

BackgroundPrevious studies of predictors of end-stage renal disease (ESRD) have limitations: (1) some focused on patients with clinically recognized chronic kidney disease (CKD); (2) others identified population-based patients who developed ESRD, but lacked earlier baseline clinical measures to predict ESRD. Our study was designed to address these limitations and to identify the strength and precision of characteristics that might predict ESRD pragmatically for decision-makers--as measured by the onset of renal replacement therapy (RRT).MethodsWe conducted a population-based, retrospective case-control study of patients who developed ESRD and started RRT. We conducted the study in a health maintenance organization, Kaiser Permanente Northwest (KPNW). The case-control study was nested within the adult population of KPNW members who were enrolled during 1999, the baseline period. Cases and their matched controls were identified from January 2000 through December 2004. We evaluated baseline clinical characteristics measured during routine care by calculating the adjusted odds ratios and their 95% confidence intervals after controlling for matching characteristics: age, sex, and year.ResultsThe rate of RRT in the cohort from which we sampled was 58 per 100,000 person-years (95% CI, 53 to 64). After excluding patients with missing data, we analyzed 350 cases and 2,114 controls. We identified the following characteristics that predicted ESRD with odds ratios ≥ 2.0: eGFR<60 mL/min/1.73 m2 (OR = 20.5; 95% CI, 11.2 to 37.3), positive test for proteinuria (OR = 5.0; 95% CI, 3.5 to 7.1), hypertension (OR = 4.5; 95% CI, 2.5 to 8.0), gout/positive test for uric acid (OR = 2.5; 95% CI, 1.8 to 3.5), peripheral vascular disease (OR = 2.2; 95% CI, 1.4 to 3.6), congestive heart failure (OR = 2.1; 95% CI, 1.4 to 3.3), and diabetes (OR = 2.1; 95% CI, 1.5 to 2.9).ConclusionsThe clinical characteristics needed to predict ESRD--for example, to develop a population-based, prognostic risk score--were often documented during routine care years before patients developed ESRD and required RRT.

Risk of End-Stage Renal Disease and Death After Cardiovascular Events in Chronic Kidney Disease

“…25 The particular biological mechanism involved in the higher ESRD risk in our study is unclear, but may have been the result of irreparable worsening of kidney disease during the CV event that was superimposed on the underlying kidney disease as a result of renal ischemia from heart failure, 9,26 or nephrotoxins such as intravenous contrast used in the invasive management of high-risk acute coronary syndrome. 11 Alternatively, interim CV events may have served as a marker for patients who had especially progressive ischemic nephropathy.…”

Gout and risk of chronic kidney disease and nephrolithiasis: meta-analysis of observational studies

“…Twelve studies examined CKD [ 22 - 33 ], 15 studies examined nephrolithiasis [ 13 , 34 - 47 ], and two studies examined both CKD and nephrolithiasis [ 48 , 49 ] (Table 1 ). Nineteen cross-sectional studies [ 13 , 22 , 25 , 27 , 29 , 30 , 32 , 34 - 38 , 40 - 42 , 46 - 49 ], one case–control study [ 26 ], and nine cohort studies [ 23 , 24 , 28 , 31 , 33 , 39 , 43 - 45 ] were identified. Six of the nine cohort studies included relevant outcome data only at baseline and so were treated as cross-sectional studies [ 24 , 31 , 33 , 43 - 45 ].…”

Early chronic kidney disease: diagnosis, management and models of care

“…69–71 It is an active area of research, and new prediction models are regularly published. 72–76 More work is needed to validate and refine these models. It is important to examine the generalizability of findings across patient groups: while a model may be appropriate for one patient population in one geographic region, it may be less accurate – or even lead to erroneous conclusions – when applied for others.…”