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      Fit and match hypothesis for kidney transplantation.

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          Abstract

          The importance of HLA matching for cadaver-donor transplants is often ignored due to the small (10%) difference in graft survival rates between the best and worst matched pairs. A new "fit and match" hypothesis is proposed to improve the predictive value of matching. Graft and functional survival rates of kidney transplants were calculated for living and cadaver-donors by the standard Kaplan and Meier methods. Mean discharge serum creatinine (SCr) values were computed after excluding patients who died or lost their grafts before discharge. Donor size, recipient size, age of donor kidney, damage caused by cold ischemia time, and mode of donor death all had substantial effects on the average SCr levels at discharge. These SCr levels correlated with one- and five-year graft survival rates. Transplants that had extremely different graft survival rates, such as those from living donors and cadaver donors, were found to have similar rates when reclassified by SCr levels at discharge. By examining the combined effects of the fit and match factors, transplants with the best fit and match exhibited a 95% one-year graft survival rate, whereas those with the worst fit and match had a 75% survival rate. This 20% difference increased to 36% after five years (84% vs. 48%). We conclude that the fit and match hypothesis provides a theoretical basis for devising a more critical method of predicting cadaver kidney transplant survival rates. Furthermore, it suggests a vital need to develop methods for estimating functional donor renal mass.

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          Author and article information

          Journal
          Transplantation
          Transplantation
          Ovid Technologies (Wolters Kluwer Health)
          0041-1337
          0041-1337
          Aug 27 1996
          : 62
          : 4
          Affiliations
          [1 ] Department of Surgery, UCLA Medical School 90095-1652, USA.
          Article
          10.1097/00007890-199608270-00003
          8781607
          71902a0a-1efa-4e7e-9cba-b0f05d96237a
          History

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