Fig 1.
Flow-chart patient eligibility criteria.
Eligible for inclusion in our dataset were all deceased-donor solitary kidney transplant recipients with complete data between January 1, 2000 and December 31, 2012.
Table 1.
Baseline study population characteristics.
Fig 2.
Adjusted Cox-regression analysis and hazards of graft failure.
Adjusted Cox-regression analysis showing the hazards of graft failure with corresponding 95% CIs using the following variables: CMV risk constellation of +donor/-recipient, recipient age at transplantation, donor age, recipient body height, donor body height, warm ischemia time, cold ischemia time, dialysis vintage, number of mismatches, peak panel reactive antibody (%) in categories (0, 1–19, ≥20),number of prior transplants, diabetes in the recipient, transplants performed in the "Eurotransplant Senior Programme", and HCV status of the recipient. The risk of graft failure is highest in sex mismatched recipient-donor pairs when the recipient weight is greater than the donor weight. Adjusted relative hazards for graft failure were calculated using the following pairing system: sex-identical transplant (MDMR & FDFR) with weight difference recipient <10 kg than donor (R = D), sex-identical transplant (MDMR & FDFR) with weight difference recipient ≥10 kg than donor (R>D), sex-disparate transplant (MDFR & FDMR) with weight difference recipient <10 kg than donor (R = D), and sex-disparate transplant (MDFR & FDMR) with weight difference recipient ≥10 kg than donor (R>D), MD = male donor, MR = male recipient, FD = female donor, FR = female recipient, 95% CI = 95% confidence interval, R = D recipient weight equal to or smaller than donor weight, R>D recipient weight greater than donor weight, the category sex-identical transplant with a weight difference of <10 kg was used as reference.
Fig 3.
Recipient to donor weight difference per year.
Boxplot graphs showing the mean absolute weight difference between recipient and donor in each study year. Although, there was a tendency to increasing interquartile ranges and numbers of outliers, we did not detect a significant increase in recipient-donor weight mis-match in our transplant cohort over an observation period of 13 years. The graphs show lower extreme, lower quartile, median, upper quartile, upper extreme and outliers. R = recipient, D = donor.
Table 2.
Hazard-ratios for graft loss using recipient-donor absolute weight differences and donor-recipient sex concordant and discordant pairing.