Relative survival and quality of life benefits of pancreas-kidney transplantation, deceased kidney transplantation and dialysis in type 1 diabetes mellitus-a probabilistic simulation model.

For patients with type 1 diabetes mellitus who progress to the point of requiring renal replacement therapy, the relative benefits of simultaneous pancreas and kidney transplantation (SPK) and deceased donor kidney transplantation across different age categories compared to dialysis are uncertain. Using Australian and New Zealand registry data from 2006 to 2016, a probabilistic Markov model (n = 10 000) was built comparing patient survival between SPK and deceased donor kidney transplantation with dialysis. Compared to dialysis, the average life years saved (LYS) and quality-adjusted life years (QALY) for SPK and deceased donor kidney transplantation were 5.48 [95% CI 5.47, 5.49] LYS and 6.48 [6.47, 6.49] QALY, and 3.38 [3.36, 3.40] LYS and 2.46 [2.45, 2.47] QALY, respectively. For recipients aged 50 years or younger, receiving a deceased donor kidney, the average incremental gains compared to dialysis were 4.13 [4.10, 4.16] LYS and 2.99 [2.97, 3.01] QALY, and for recipients older than 50 years, 3.05 [3.02, 3.08] LYS and 2.25 [2.23, 2.27] QALY. Compared to dialysis, SPK transplantation incurs the greatest benefits in LYS and QALY for patients with type 1 diabetes requiring renal replacement therapy. Patients older than 50 years still experience survival benefits from deceased donor kidney transplantation compared to dialysis.

Unexpected donor-derived infectious transmissions by kidney transplantation: A systematic review.

BACKGROUND: Unexpected donor-derived transmission of infections is rare, but is associated with significant morbidity and mortality. We aimed to provide an overview of published cases on unexpected infectious transmissions. METHODS: We systematically reviewed all published evidence describing any unexpected donor-derived viral, bacterial, fungal, and parasitic infections in kidney transplant recipients. RESULTS: In all, 119 studies (case reports [n = 36], case series [n = 78], cohort studies [n = 2], and case-control studies [n = 3]) involving 139 donors and 207 kidney recipients were included. Donor-derived viral (n = 116, 56.0%) infections were most prevalent, followed by bacterial (32, 15.5%), fungal (32, 15.5%), and parasitic (27, 13.0%) infections. The most commonly reported viral infections were human immunodeficiency virus (HIV) (n = 20, 9.7%), human T-cell lymphotrophic virus (HTLV) (n = 20, 9.7%), and West Nile virus (WNV) (n = 13, 6.3%). The most frequent bacterial infections were caused by Mycobacterium tuberculosis (10, 4.8%) and Pseudomonas aeruginosa (9, 4.3%). Candida species were the most frequent causes of fungal donor-derived infections (8, 3.9%). Toxoplasma gondii accounted for seven (3.4%) cases of transmitted parasitic infections. Patients with rabies experienced the highest probability of recipient death from virus-related complications at 90.0%, within a median time of 2.8 months after transplantation. CONCLUSION: The frequency of donor-derived infectious transmission appears low in kidney transplantation, with viral transmissions being most commonly reported overall.

Survival and Quality of Life Impact of a Risk-based Allocation Algorithm for Deceased Donor Kidney Transplantation.

BACKGROUND: To determine the incremental gains in graft and patient survival under a risk-based, deceased donor kidney allocation compared with the current Australian algorithm. METHODS: Risk-based matching algorithms were applied to first graft, kidney only recipients (n = 7513) transplanted in Australia between 1994 and 2013. Probabilistic models were used to compare the waiting time, life, and QALYs and graft years between the 8 risk-based allocation strategies against current practice. RESULTS: Compared with current practice, Kidney Donor Risk Index-Estimated Posttransplant Survival matching of the lowest 20% of scores reduced median waiting time by 0.64 years (95% confidence interval [CI], 0.52-0.73) for recipients aged 30 years or younger, but increased waiting time by 0.94 years (95% CI, 0.79-1.09) for recipients older than 60 years. Among all age groups, the greatest gains occurred if Kidney Donor Risk Index-Estimated Posttransplant Survival matching of the lowest 30% of scores was used, incurring a median overall gain of 0.63 (95% CI, 0.03-1.25) life years and 0.78 (95% CI, 0.30-1.26) graft years compared with the current practice. A median gain in survival of 1.91 years for younger recipients (aged 30-45 years) was offset by a median reduction in survival (by 0.95 life years) among the older recipients. Prioritization of lower-quality donor kidneys for older candidates reduced the waiting time for recipients older than 45 years, but no changes in graft and patient survivals were observed. CONCLUSIONS: Risk-based matching engendered a moderate, overall increase in graft and patient survivals, accrued through benefits for recipients 45 years or younger but disadvantage to recipients older than 60 years.