Use of estimated glomerular filtration rate to predict incident chronic kidney disease in patients at risk of cardiovascular disease: a retrospective study

Autor: Romona D. Govender, Dybesh Regmi, Saif Al-Shamsi, Abderrahim Oulhaj
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Nephrology
Male
medicine.medical_specialty
Time Factors
030232 urology & nephrology
Renal function
030204 cardiovascular system & hematology
lcsh:RC870-923
urologic and male genital diseases
Nomogram
03 medical and health sciences
0302 clinical medicine
Interquartile range
Sub-distribution hazards model
Risk Factors
Internal medicine
Diabetes mellitus
Chronic kidney disease
medicine
Diabetes Mellitus
Outpatient clinic
Humans
Estimated glomerular filtration rate
Renal Insufficiency
Chronic

Retrospective Studies
Glycated Hemoglobin
business.industry
Retrospective cohort study
Middle Aged
lcsh:Diseases of the genitourinary system. Urology
medicine.disease
Cardiovascular disease
Nomograms
Cholesterol
ROC Curve
Cardiovascular Diseases
Calibration
Regression Analysis
Female
business
Prediction
Kidney disease
Research Article
Glomerular Filtration Rate
Zdroj: BMC Nephrology
BMC Nephrology, Vol 20, Iss 1, Pp 1-10 (2019)
ISSN: 1471-2369
Popis: Background Patients with cardiovascular disease are at an increased risk of chronic kidney disease (CKD). However, data on incident CKD in patients with multiple vascular comorbidities are insufficient. In this study, we identified the predictors of CKD stages 3–5 in patients at risk of cardiovascular disease and used their estimated glomerular filtration rate (eGFR) to construct a nomogram to predict the 5-year risk of incident CKD. Methods Ambulatory data on 622 adults with preserved kidney function and one or more cardiovascular disease risk factors who attended outpatient clinics at a tertiary care hospital in Al-Ain, United Arab Emirates were obtained retrospectively. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation and assessed every 3 months from baseline to December 12, 2017. Fine and Gray competing risk regression model was used to identify the independent variables and construct a nomogram to predict incident CKD at 5 years, which is defined as eGFR
Databáze: OpenAIRE