ArticleClinical transplantation2025
Multivariable Predictors of Poorer Renal Function Among 1119 Deceased Donor Kidney Transplant Recipients During the First Year Post-Transplant, With a Particular Focus on the Influence of Individual KDRI Components and Donor AKI.
Article in Clinical transplantation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Assessing Deceased-Donor Kidneys Through Posttransplant Survival Prediction Algorithms.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2026Article
- Maximizing Robotic Efficiency in Paired Kidney Transplantation at a Resource-Limited County Hospital.JSLS : Journal of the Society of Laparoendoscopic SurgeonsArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Given our desire to reduce kidney transplant waiting times by utilizing more difficult-to-place ("higher-risk") DD kidneys, we wanted to better understand post-transplant renal function among 1119 adult DD recipients consecutively transplanted during 2016-2019. Stepwise linear regression of eGFR (CKD-EPI formula) at 3-, 6-, and 12-months post-transplant (considered as biomarkers for longer-term outcomes), respectively, was performed to determine the significant multivariable baseline predictors, using a type I error ≤ 0.01 to avoid spurious/weak associations. Three unfavorable characteristics were selected as highly significant in all three models: Older DonorAge (yr) (p < 0.000001), Longer StaticColdStorage Time (hr) (p < 0.000001), and Higher RecipientBMI (p ≤ 0.00003). Other significantly unfavorable characteristics included: Shorter DonorHeight (cm) (p ≤ 0.00001), Higher Natural Logarithm {Initial DonorCreatinine} (p ≤ 0.001), Longer MachinePerfusion Time (p ≤ 0.003), Greater DR Mismatches (p = 0.01), DonorHypertension (p ≤ 0.004), Recipient HIV+ (p ≤ 0.006), DCD Kidney (p = 0.002), Cerebrovascular DonorDeath (p = 0.01), and DonorDiabetes (p = 0.01). Variables not selected into any model included DonorAKI Stage (p ≥ 0.24), Any DonorAKI (p ≥ 0.04), and five KDRI components: two DonorAge splines at 18 years (p ≥ 0.52) and 50 years (p ≥ 0.28), BlackDonor (p ≥ 0.08), DonorHCV+ (p ≥ 0.06), and DonorWeight spline at 80 kg (p ≥ 0.03), indicating that DonorAKI and the weaker KDRI components have little, if any, prognostic impact on renal function during the first 12 months post-transplant. Additionally, biochemical determinations with skewed distributions such as DonorCreatinine are more accurately represented by natural logarithmic transformed values. In conclusion, one practical takeaway is that donor AKI may be ignored when evaluating DD risk.
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