2015
DOI: 10.1155/2015/657624
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Predictors of a Rapid Decline of Renal Function in Patients with Chronic Kidney Disease Referred to a Nephrology Outpatient Clinic: A Longitudinal Study

Abstract: Background. Predicting the progression of kidney failure in patients with chronic kidney disease is difficult. The aim of this study was to assess the predictors of rapid kidney decline in a cohort of patients referred to a single outpatient nephrology clinic. Design. Longitudinal, prospective cohort study with a median follow-up of 3.39 years. Methods. Data were obtained from 306 patients with chronic renal failure based on serum creatinine-estimated glomerular filtration rate (eGFR creat ) < 90 mL/min/1.73 m… Show more

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Cited by 14 publications
(16 citation statements)
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“…A subset of patients with at least 10-year follow-up were further evaluated with the aim of assessing the longitudinal changes in graft function, using eGFR values at discharge after transplant (baseline) and at the annual follow-up visits, in the whole group and in KTRs stratified according to age ranges. A longitudinal multivariable linear regression model was applied to determine the relationship between the yearly change in eGFR after transplantation and the performance related to PA [ 32 , 33 ]. The analysis was conducted by fitting a mixed-effect (random-and-fixed) linear-regression model (for repeated measures), considering that the model assumes that the determinations from a single subject share a set of latent, unobserved, random effects which are used to generate an association structure between the repeated measurements [ 34 ].…”
Section: Methodsmentioning
confidence: 99%
“…A subset of patients with at least 10-year follow-up were further evaluated with the aim of assessing the longitudinal changes in graft function, using eGFR values at discharge after transplant (baseline) and at the annual follow-up visits, in the whole group and in KTRs stratified according to age ranges. A longitudinal multivariable linear regression model was applied to determine the relationship between the yearly change in eGFR after transplantation and the performance related to PA [ 32 , 33 ]. The analysis was conducted by fitting a mixed-effect (random-and-fixed) linear-regression model (for repeated measures), considering that the model assumes that the determinations from a single subject share a set of latent, unobserved, random effects which are used to generate an association structure between the repeated measurements [ 34 ].…”
Section: Methodsmentioning
confidence: 99%
“…One particular omission from current prediction tools involves quantifying the rate of change in renal function in patients over time, which can help conceptualise an individual's risk profile more meaningfully [6,7]. Although a number of studies have explored the association of various risk factors on different rates of progression [8][9][10], there is a lack of data focusing exclusively on patients with a consistent linear rate of progression and the associations with adverse outcomes such as ESRD and mortality. These patients warrant attention as their linear eGFR trajectory represents a clear paradigm for understanding true CKD progression.…”
Section: Introductionmentioning
confidence: 99%
“…One particular omission from current prediction tools involves quantifying the rate of change in renal function in patients over time, which can help conceptualise an individual's risk pro le more meaningfully [6,7]. Although a number of studies have explored the association of various risk factors on different rates of progression [8][9][10], there is a lack of data focusing exclusively on patients with a consistent linear rate of progression and the associations with adverse outcomes such as ESRD and mortality. These patients warrant attention as their linear eGFR trajectory represents a clear paradigm for understanding true CKD progression.…”
Section: Introductionmentioning
confidence: 99%