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1186 related items for PubMed ID: 23901055
21. Renal function in heart failure: a disparity between estimating function and predicting mortality risk. Plischke M, Neuhold S, Kohl M, Heinze G, Sunder-Plassmann G, Pacher R, Hülsmann M. Eur J Heart Fail; 2013 Jul; 15(7):763-70. PubMed ID: 23429976 [Abstract] [Full Text] [Related]
23. GFR estimation using standardized serum cystatin C in Japan. Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S, Collaborators Developing the Japanese Equation for Estimated GFR. Am J Kidney Dis; 2013 Feb; 61(2):197-203. PubMed ID: 22892396 [Abstract] [Full Text] [Related]
29. Simple cystatin C formula compared to serum creatinine-based formulas for estimation of glomerular filtration rate in patients with mildly to moderately impaired kidney function. Bevc S, Hojs R, Ekart R, Gorenjak M, Puklavec L. Kidney Blood Press Res; 2012 Sep 23; 35(6):649-54. PubMed ID: 23095576 [Abstract] [Full Text] [Related]
31. Estimating glomerular filtration rate in hypertensive subjects: comparison of the chronic kidney disease epidemiology collaboration (CKD-EPI) and modification of diet in renal disease (MDRD) study equations. Korhonen PE, Kivelä SL, Aarnio PT, Kautiainen H, Järvenpää S, Kantola IM. Ann Med; 2012 Aug 23; 44(5):487-93. PubMed ID: 22149718 [Abstract] [Full Text] [Related]
33. [Assessment of the new CKD-EPI equation to estimate the glomerular filtration rate]. Montañés Bermúdez R, Bover Sanjuán J, Oliver Samper A, Ballarín Castán JA, Gràcia García S. Nefrologia; 2010 Aug 23; 30(2):185-94. PubMed ID: 20038962 [Abstract] [Full Text] [Related]
34. Impact of the CKD-EPI equation for estimating renal function on eligibility for cisplatin-based chemotherapy in patients with urothelial cancer. Tsao CK, Moshier E, Seng SM, Godbold J, Grossman S, Winston J, Oh WK, Galsky MD. Clin Genitourin Cancer; 2012 Mar 23; 10(1):15-20. PubMed ID: 22130294 [Abstract] [Full Text] [Related]
35. Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. White SL, Polkinghorne KR, Atkins RC, Chadban SJ. Am J Kidney Dis; 2010 Apr 23; 55(4):660-70. PubMed ID: 20138414 [Abstract] [Full Text] [Related]
36. Comparison of association of glomerular filtration rate with metabolic syndrome in a community-based population using the CKD-EPI and MDRD study equations. Hong N, Oh J, Lee YH, Youn JC, Park S, Lee SH, Jang Y, Chung N, Kim S, Jee SH, Kang SM. Clin Chim Acta; 2014 Feb 15; 429():157-62. PubMed ID: 24360849 [Abstract] [Full Text] [Related]
37. Performance of creatinine-based equations compared in older patients. Koppe L, Klich A, Dubourg L, Ecochard R, Hadj-Aissa A. J Nephrol; 2013 Feb 15; 26(4):716-23. PubMed ID: 23843047 [Abstract] [Full Text] [Related]
38. Comparison of MDRD, CKD-EPI, and Cockcroft-Gault equation in relation to measured glomerular filtration rate among a large cohort with diabetes. Schwandt A, Denkinger M, Fasching P, Pfeifer M, Wagner C, Weiland J, Zeyfang A, Holl RW. J Diabetes Complications; 2017 Sep 15; 31(9):1376-1383. PubMed ID: 28711195 [Abstract] [Full Text] [Related]
39. Clinical risk implications of the CKD Epidemiology Collaboration (CKD-EPI) equation compared with the Modification of Diet in Renal Disease (MDRD) Study equation for estimated GFR. Matsushita K, Tonelli M, Lloyd A, Levey AS, Coresh J, Hemmelgarn BR, Alberta Kidney Disease Network. Am J Kidney Dis; 2012 Aug 15; 60(2):241-9. PubMed ID: 22560843 [Abstract] [Full Text] [Related]
40. Comparison of associations of outcomes after stroke with estimated GFR using Chinese modifications of the MDRD study and CKD-EPI creatinine equations: results from the China National Stroke Registry. Wang X, Luo Y, Wang Y, Wang C, Zhao X, Wang D, Liu L, Liu G, Wang Y, China National Stroke Registry Investigators. Am J Kidney Dis; 2014 Jan 15; 63(1):59-67. PubMed ID: 24100127 [Abstract] [Full Text] [Related] Page: [Previous] [Next] [New Search]