Can machine perfusion decrease the likelihood of discard among biopsied kidneys?
Many factors, such as donor risk factors and renal function, have been shown to be associated with an increased likelihood of discard after recovering kidneys from deceased donors. When these factors are insufficient for assessment, renal biopsy is often performed at the time of harvest to assess suitability. Our aims were to identify factors that predict the discard of a biopsied kidney and to assess the impact of machine perfusion (MP) on kidney discard. We biopsied 678 kidneys from deceased donors aged >or=40 years from 2001 to 2006. We used a logistic regression model to estimate the adjusted odds ratios for kidney discard. Thirty-nine percent (n = 261) of biopsied kidneys were discarded. Kidneys with glomerulosclerosis (GS) > 20% had the highest likelihood of discard. Other significant predictors of discard included extreme donor age, final resistance (>40), atherosclerosis, interstitial fibrosis, arteriolosclerosis, and terminal serum creatinine value (SCr) > 1.5 mg/dL. MP kidneys (n = 69) were less likely to be discarded than cold storage (CS) kidneys after adjusting for other factors (adjusted odds ratio = .13, P < .001). In conclusion, abnormal biopsy findings were associated with the highest likelihood of discard. MP was used in only 10% of the cases; however, the use of MP was associated with a decreased likelihood of discard among biopsied kidneys.
Cho
Y W
YW
National Institute of Transplantation, Los Angeles, California 90057, USA.
Bunnapradist
S
S
Cho
E S
ES
Stadtler
M
M
Simmons
V
V
Locke
J
J
Mone
T
T
Mendez
R
R
Hutchinson
I V
IV
Gill
J
J
Shah
T
T
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001706:Biopsy; D002423:Cause of Death; D006801:Humans; D007668:Kidney / Q000473:pathology; D008875:Middle Aged; D015999:Multivariate Analysis; D009926:Organ Preservation / Q000295:instrumentation / Q000379:methods*; D018579:Patient Selection; D012044:Regression Analysis; D012189:Retrospective Studies; D014019:Tissue Donors / Q000706:statistics & numerical data