title: What Should the Serum Creatinine Be After Transplantation? An Approach to Integrate Donor and Recipient Information to Assess Posttransplant Kidney Function.
abstract: BACKGROUND
  Knowledge of an optimal expected serum creatinine (SCr) would be useful to detect early renal dysfunction after transplantation. Current measurements of posttransplant function rely on the recipient's SCr and calculations of estimated glomerular filtration rate (eGFR), based on recipient age, weight, and sex. Renal function after transplantation, however, also depends on the donor supply of functioning nephrons and adaptation in GFR of a single kidney.
  
  
  METHODS
  We developed a formula to predict the optimal expected SCr after transplantation derived from donor and recipient Cockroft-Gault GFRs and adjusted for the single kidney adaptive response. We compared the expected SCr with the lowest observed SCr in a cohort of living (79) and deceased (67) donor allograft recipients followed up over 5 years.
  
  
  RESULTS
  Expected SCr correlated with the observed SCr in both living and deceased donor kidney recipients, correlation was stronger among living donor kidney recipients. Recipient-to-donor body weight ratio was significantly associated with the difference between expected and observed SCr, suggesting that recipient body weight is a major predictor of posttransplant renal function. The difference between expected and observed SCr was significantly greater among deceased donor kidney recipients, suggesting poorer function in these patients, which was not detected by SCr or estimated GFR alone.
  
  
  CONCLUSIONS
  Calculation of expected renal function for a given donor-recipient combination adds relevant information to assessment of allograft function. Future studies will permit determination of a threshold difference between expected and observed SCr that should trigger investigation and potential intervention to improve allograft function.
authors.affiliation: 1 Division of Nephrology and Transplant Immunology, Department of Medicine, University of Alberta, Edmonton, Canada. 2 Department of Medicine, College of Medicine and KKUH, King Saud University, Riyadh, Saudi Arabia. 3 Division of Nephrology, Helios Clinics Wuppertal, University of Witten-Herdecke, Witten, Germany. 4 Division of Nephrology, University Hospital Zurich, Zurich, Switzerland.
authors.forename: Riyadh
authors.initials: R
authors.lastname: Al-Sehli
authors.forename: Scott
authors.initials: S
authors.lastname: Grebe
authors.forename: Zija
authors.initials: Z
authors.lastname: Jacaj
authors.forename: Siwei
authors.initials: S
authors.lastname: Chen
authors.forename: Stone
authors.initials: S
authors.lastname: Li
authors.forename: Kelly
authors.initials: K
authors.lastname: Craig
authors.forename: Valerie
authors.initials: V
authors.lastname: Luyckx
authors.forename: Thomas
authors.initials: T
authors.lastname: Mueller
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D003404:Creatinine / Q000097:blood*; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007668:Kidney / Q000503:physiopathology*; D016030:Kidney Transplantation / Q000009:adverse effects*; D019520:Living Donors; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011237:Predictive Value of Tests; D055031:Primary Graft Dysfunction / Q000097:blood / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology; D013997:Time Factors; D014019:Tissue Donors; D066027:Transplant Recipients; D016896:Treatment Outcome
chemical_list: D015415:Biomarkers; D003404:Creatinine