Chronic kidney disease - determinants of progression and cardiovascular risk. PROGREDIR cohort study: design and methods
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Citações na Scopus
9
Tipo de produção
article
Data de publicação
2017
Título da Revista
ISSN da Revista
Título do Volume
Editora
ASSOCIACAO PAULISTA MEDICINA
Citação
SAO PAULO MEDICAL JOURNAL, v.135, n.2, p.133-139, 2017
Resumo
CONTEXT AND OBJECTIVE: Chronic kidney disease (CKD) has become an important public health issue. The socioeconomic burden of renal replacement therapy (RRT) is very high, as is CKD-related cardiovascular mortality and morbidity. Preventive and therapeutic measures only have modest impact and more research is needed. Few cohort studies have been conducted on populations with CKD. Our aim was to establish a cohort that would include more advanced forms of CKD (stages 3 and 4). Data collection was focused on renal and cardiovascular parameters. DESIGN AND SETTING: Prospective cohort study; Sao Paulo, Brazil. METHODS: Recruitment took place in Hospital das Clinicas, Sao Paulo, from March 2012 to December 2013. Data relating to medical history, food-frequency questionnaire, anthropometry, laboratory work-up, calcium score, echocardiography, carotid intimal-medial thickness, pulse-wave velocity, retinography and heart rate variability were collected. A biobank including serum, plasma, post-oral glucose tolerance test serum and plasma, urine (morning and 24-hour urine) and DNA was established. RESULTS: 454 participants (60% men and 50% diabetics) of mean age 68 years were enrolled. Their mean estimated glomerular filtration rate-CKD Epidemiology Collaboration was 38 ml/min/1.73m(2). Follow-up is ongoing and the main outcomes are the start of RRT, cardiovascular events and death. CONCLUSIONS: The PROGREDIR cohort is a promising prospective study that will allow better understanding of CKD determinants and validation of candidate biomarkers for the risks of CKD progression and mortality.
Palavras-chave
Renal insufficiency, chronic, Cardiovascular diseases, Renal replacement therapy, Biomarkers, Risk factors
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