TY - JOUR AU - Coresh Josef AU - Woodward Mark AU - Ballew Shoshana AU - Levey Andrew AU - Heerspink Hiddo AU - Köttgen Anna AU - Eckardt Kai-Uwe AU - Hemmelgarn Brenda AU - Carrero Juan AU - Grams Morgan AU - Sang Yingying AU - Djurdjev Ognjenka AU - Ho Kevin AU - Ito Sadayoshi AU - Marks Angharad AU - Naimark David AU - Nash Danielle AU - Navaneethan Sankar AU - Sarnak Mark AU - Stengel Benedicte AU - Visseren Frank AU - Wang Angela AB -
Patients with chronic kidney disease and severely decreased glomerular filtration rate (GFR) are at high risk for kidney failure, cardiovascular disease (CVD) and death. Accurate estimates of risk and timing of these clinical outcomes could guide patient counseling and therapy. Therefore, we developed models using data of 264,296 individuals in 30 countries participating in the international Chronic Kidney Disease Prognosis Consortium with estimated GFR (eGFR)s under 30 ml/min/1.73m. Median participant eGFR and urine albumin-to-creatinine ratio were 24 ml/min/1.73mand 168 mg/g, respectively. Using competing-risk regression, random-effect meta-analysis, and Markov processes with Monte Carlo simulations, we developed two- and four-year models of the probability and timing of kidney failure requiring kidney replacement therapy (KRT), a non-fatal CVD event, and death according to age, sex, race, eGFR, albumin-to-creatinine ratio, systolic blood pressure, smoking status, diabetes mellitus, and history of CVD. Hypothetically applied to a 60-year-old white male with a history of CVD, a systolic blood pressure of 140 mmHg, an eGFR of 25 ml/min/1.73mand a urine albumin-to-creatinine ratio of 1000 mg/g, the four-year model predicted a 17% chance of survival after KRT, a 17% chance of survival after a CVD event, a 4% chance of survival after both, and a 28% chance of death (9% as a first event, and 19% after another CVD event or KRT). Risk predictions for KRT showed good overall agreement with the published kidney failure risk equation, and both models were well calibrated with observed risk. Thus, commonly-measured clinical characteristics can predict the timing and occurrence of clinical outcomes in patients with severely decreased GFR.
BT - Kidney Int C1 - https://www.ncbi.nlm.nih.gov/pubmed/29605094?dopt=Abstract DO - 10.1016/j.kint.2018.01.009 J2 - Kidney Int. LA - eng N2 -Patients with chronic kidney disease and severely decreased glomerular filtration rate (GFR) are at high risk for kidney failure, cardiovascular disease (CVD) and death. Accurate estimates of risk and timing of these clinical outcomes could guide patient counseling and therapy. Therefore, we developed models using data of 264,296 individuals in 30 countries participating in the international Chronic Kidney Disease Prognosis Consortium with estimated GFR (eGFR)s under 30 ml/min/1.73m. Median participant eGFR and urine albumin-to-creatinine ratio were 24 ml/min/1.73mand 168 mg/g, respectively. Using competing-risk regression, random-effect meta-analysis, and Markov processes with Monte Carlo simulations, we developed two- and four-year models of the probability and timing of kidney failure requiring kidney replacement therapy (KRT), a non-fatal CVD event, and death according to age, sex, race, eGFR, albumin-to-creatinine ratio, systolic blood pressure, smoking status, diabetes mellitus, and history of CVD. Hypothetically applied to a 60-year-old white male with a history of CVD, a systolic blood pressure of 140 mmHg, an eGFR of 25 ml/min/1.73mand a urine albumin-to-creatinine ratio of 1000 mg/g, the four-year model predicted a 17% chance of survival after KRT, a 17% chance of survival after a CVD event, a 4% chance of survival after both, and a 28% chance of death (9% as a first event, and 19% after another CVD event or KRT). Risk predictions for KRT showed good overall agreement with the published kidney failure risk equation, and both models were well calibrated with observed risk. Thus, commonly-measured clinical characteristics can predict the timing and occurrence of clinical outcomes in patients with severely decreased GFR.
PY - 2018 SP - 1442 EP - 1451 T2 - Kidney Int TI - Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. VL - 93 SN - 1523-1755 ER -