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1.
Prev Med ; 57(4): 357-62, 2013 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-23783072

RESUMO

OBJECTIVE: To determine the incidence and prevalence of CKD and of progressive GFR decline, to identify modifiable risk factors of and to develop a predictive risk model for progressive GFR decline in high risk primary care patients. METHODS: Retrospective observational study of 803 patients with or at high risk of CKD exclusively managed in primary care. Baseline data was collected in 2003, follow-up data in 2006. High risk was defined as inadequately controlled hypertension or diabetes, and GFR<60, progressive GFR decline as annual GFR decline >2.5mlmin(-1) 1.73m(-2). RESULTS: CKD was present in 25.4% at baseline and developed in further 13.7% during follow-up, 42.5% demonstrated progressive GFR decline. Obesity, proteinuria, heart failure, inadequate hypertension and diabetes control, lacking angiotensin-converting-enzyme-inhibitors or angiotensin-receptor-blockers, radio contrast, and dual renin-angiotensin-aldosterone-system blockade were identified as modifiable, independent risk factors of progressive GFR decline. The risk model, containing 7 readily obtainable variables, showed good discriminative ability. CONCLUSIONS: High risk primary care patients demonstrated high CKD prevalence and incidence, and rate of progressive GFR decline. Identified risk factors can be modified in primary care. Our risk model may aid primary care physicians to predict patients at high risk of progressive GFR decline.


Assuntos
Insuficiência Renal Crônica/etiologia , Idoso , Complicações do Diabetes/epidemiologia , Progressão da Doença , Feminino , Taxa de Filtração Glomerular , Insuficiência Cardíaca/complicações , Insuficiência Cardíaca/epidemiologia , Humanos , Hipertensão/complicações , Hipertensão/epidemiologia , Incidência , Masculino , Pessoa de Meia-Idade , Modelos Biológicos , Obesidade/complicações , Obesidade/epidemiologia , Prevalência , Proteinúria/complicações , Proteinúria/epidemiologia , Insuficiência Renal Crônica/epidemiologia , Insuficiência Renal Crônica/prevenção & controle , Estudos Retrospectivos , Fatores de Risco
2.
Scand J Urol Nephrol ; 46(6): 448-53, 2012 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-22725614

RESUMO

OBJECTIVE: The aims of this study were to compare estimated glomerular filtration rate (eGFR) by Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations, to assess the classification of chronic kidney disease (CKD) stages by both equations, and to identify factors associated with differences between both equations in patients with or at high risk of CKD managed in primary care. MATERIAL AND METHODS: This was an observational study of 803 patients with CKD, long-standing, severe hypertension and diabetes exclusively managed in primary care. Bias and precision between the two equations used to calculate eGFR were quantified as proposed by Bland and Altman. RESULTS: In 1534 eGFR calculations, mean eGFR(MDRD) was 0.8 ± 3.6 ml/min/1.73 m(2) higher than eGFR(CKD-EPI). Precision between the two equations was ±7.1 ml/min/1.73 m(2). Classification of CKD stages by MDRD or CKD-EPI equations agreed in 93.3% of cases. Age above 70 years, eGFR below 60 and above 120 ml/min/1.73 m(2) were associated with higher eGFR(MDRD) values; and age below 50 years and inadequately controlled hypertension with higher eGFR(CKD-EPI) values. CONCLUSIONS: Comparison of eGFR calculated by MDRD and CKD-EPI equations demonstrated no clinically relevant difference. In addition, CKD classification by both equations agreed highly. As both equations performed equally well, the simpler and more established MDRD equation should be preferred in patients with or at high risk of CKD managed in primary care. Patients' characteristics seem to account for previously reported differences in the performance of CKD-EPI and MDRD equations.


Assuntos
Diabetes Mellitus/fisiopatologia , Taxa de Filtração Glomerular/fisiologia , Hipertensão/fisiopatologia , Atenção Primária à Saúde/métodos , Fatores Etários , Idoso , Algoritmos , Pressão Sanguínea , Índice de Massa Corporal , Creatinina/sangue , Feminino , Humanos , Masculino , Pessoa de Meia-Idade
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