| P50 | author | Hertzel C. Gerstein | Q41696958 |
| | Daniela Dunkler | Q54258757 |
| | Georg Heinze | Q57012893 |
| | Sheldon W. Tobe | Q58091532 |
| | Koon Teo | Q60611748 |
| P2093 | author name string | Catherine M Clase | |
| | Rainer Oberbauer | |
| | Peggy Gao | |
| | Johannes F E Mann | |
| | Shun Fu Lee | |
| | ONTARGET and ORIGIN Investigators | |
| P2860 | cites work | Albumin-to-creatinine ratio in random urine samples might replace 24-h urine collections in screening for micro- and macroalbuminuria in pregnant woman with type 1 diabetes | Q28304133 |
| | Prevalence of chronic kidney disease in the United States | Q29614191 |
| | Telmisartan, ramipril, or both in patients at high risk for vascular events | Q33156143 |
| | Predicting the risk of chronic Kidney Disease in men and women in England and Wales: prospective derivation and external validation of the QKidney Scores | Q33611383 |
| | Population based screening for chronic kidney disease: cost effectiveness study | Q34286311 |
| | Risk models to predict chronic kidney disease and its progression: a systematic review. | Q34489517 |
| | Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study | Q34740928 |
| | Changes in albuminuria predict mortality and morbidity in patients with vascular disease | Q35108899 |
| | A risk score for chronic kidney disease in the general population | Q35774399 |
| | Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts | Q37648704 |
| | Diet and kidney disease in high-risk individuals with type 2 diabetes mellitus | Q38446459 |
| | National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification | Q39513412 |
| | A predictive model for progression of chronic kidney disease to kidney failure | Q39761717 |
| | Risk scores for predicting outcomes in patients with type 2 diabetes and nephropathy: the RENAAL study | Q40182836 |
| | Risk factors for renal dysfunction in type 2 diabetes: U.K. Prospective Diabetes Study 74. | Q40321393 |
| | Basal insulin and cardiovascular and other outcomes in dysglycemia | Q42507791 |
| | Development and progression of nephropathy in type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS 64). | Q44242786 |
| | Predicting end-stage renal disease: Bayesian perspective of information transfer in the clinical decision-making process at the individual level | Q44390538 |
| | Development and validation of a general population renal risk score | Q44460457 |
| | Rationale, design, and baseline characteristics of 2 large, simple, randomized trials evaluating telmisartan, ramipril, and their combination in high-risk patients: the Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial | Q44950867 |
| | Renal outcomes with telmisartan, ramipril, or both, in people at high vascular risk (the ONTARGET study): a multicentre, randomised, double-blind, controlled trial. | Q46426098 |
| | Rationale, design, and baseline characteristics for a large international trial of cardiovascular disease prevention in people with dysglycemia: the ORIGIN Trial (Outcome Reduction with an Initial Glargine Intervention). | Q46848592 |
| | Screening for proteinuria in US adults: a cost-effectiveness analysis. | Q50735258 |
| | Main risk factors for nephropathy in type 2 diabetes mellitus are plasma cholesterol levels, mean blood pressure, and hyperglycemia. | Q50888604 |
| | Estimated glomerular filtration rate and albuminuria as predictors of outcomes in patients with high cardiovascular risk: a cohort study. | Q51052932 |
| | n-3 fatty acids and cardiovascular outcomes in patients with dysglycemia. | Q51355736 |
| | Comparing the importance of prognostic factors in Cox and logistic regression using SAS. | Q51639203 |
| | Building multivariable regression models with continuous covariates in clinical epidemiology--with an emphasis on fractional polynomials. | Q51958432 |
| | Cardiovascular disease risk profiles. | Q52461317 |
| | Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. | Q52933297 |
| | Predicting the Risk of Dialysis and Transplant Among Patients With CKD: A Retrospective Cohort Study | Q57234471 |
| | Polytomous logistic regression analysis could be applied more often in diagnostic research | Q57259942 |
| | Prediction of Kidney-Related Outcomes in Patients With Type 2 Diabetes | Q57312406 |
| | Cost-Effectiveness of Screening and Optimal Management for Diabetes, Hypertension, and Chronic Kidney Disease: A Modeled Analysis | Q59167606 |
| | The relative importance of prognostic factors in studies of survival | Q72307754 |
| | Predicting renal risk in the general population: do we have the right formula? | Q84434855 |
| P433 | issue | 8 | |
| P921 | main subject | type 2 diabetes | Q3025883 |
| P304 | page(s) | 1371-1379 | |
| P577 | publication date | 2015-07-14 | |
| P1433 | published in | Clinical Journal of the American Society of Nephrology | Q15757929 |
| P1476 | title | Risk Prediction for Early CKD in Type 2 Diabetes | |
| P478 | volume | 10 | |