Supplemental material
Renal Failure
Volume 42, 2020 - Issue 1
Related Research Data
Standards of medical care in diabetes—2017 abridged for primary care providers
Source:
American Diabetes Association
Development and progression of nephropathy in type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS 64).
Source:
Elsevier BV
Diabetic Kidney Disease
Source:
Springer Milan
Prevalence of chronic kidney disease in China: a cross-sectional survey
Source:
Elsevier BV
Prediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus – a population-based retrospective cohort study
Source:
BioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcnephrol/
A Meta-analysis
Source:
American Medical Association (AMA)
Biomarkers of diabetic kidney disease
Source:
Springer Nature
mice: Multivariate Imputation by Chained Equations in R
Source:
Foundation for Open Access Statistic
Multiple predicting K-fold cross-validation for model selection
Source:
Informa UK Limited
Prediction of kidney-related outcomes in patients with type 2 diabetes.
Source:
Elsevier BV
Diabetic kidney disease: a report from an ADA Consensus Conference.
Source:
American Diabetes Association
White blood cell fractions correlate with lesions of diabetic kidney disease and predict loss of kidney function in Type 2 diabetes.
Source:
HAL CCSD
Chronic kidney disease: global dimension and perspectives
Source:
Elsevier BV
Cross-validation for selecting a model selection procedure
Source:
Elsevier BV
External Validation of the Kidney Failure Risk Equation and Re-Calibration with Addition of Ultrasound Parameters
Source:
American Society of Nephrology (ASN)
A Prediction Model for the Risk of Incident Chronic Kidney Disease
Source:
Elsevier BV
Cystatin C improves the diagnosis and stratification of chronic kidney disease, and the estimation of glomerular filtration rate in diabetes
Source:
Elsevier BV
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