R Open Source Programming Code for Calculation of the Kidney Donor Profile Index and Kidney Donor Risk Index

Bikbov, Boris

doi:10.1159/000492427

Cited by 12 publications

(11 citation statements)

References 20 publications

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“…ECD was defined using United Network for Organ Sharing definition [15]. Kidney Donor Profile Index (KDPI) [16] was calculated using "ktx.kdpi.optn," an R open source programming code [17]. tAR included all episodes of acute allograft dysfunction, treated with methylprednisolone and/or rabbit antithymocyte globulin (rATG), regardless of biopsy.…”

Section: Definitionsmentioning

confidence: 99%

Exploring the causes of the high incidence of delayed graft function after kidney transplantation in Brazil: a multicenter study

et al. 2021

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This retrospective multicenter (n = 18) cohort study evaluated the incidence, risk factors, and the impact of delayed graft function (DGF) on 1year kidney transplant (KT) outcomes. Of 3992 deceased donor KT performed in 2014-2015, the incidence of DGF was 54%, ranging from 29.9% to 87.7% among centers. Risk factors ( lower-bound-95%CI OR upper-bound-95% CI ) were male gender ( 1.066 1.249 1.463 ), diabetic kidney disease ( 1.053 1.296 1.595 ), time on dialysis ( 1.005 1.007 1.009 ), retransplantation ( 1.035 1.397 1.885 ), preformed anti-HLA antibodies ( 1.011 1.383 1.892 ), HLA mismatches ( 1.006 1.066 1.130 ), donor age ( 1.011 1.017 1.023 ), donor final serum creatinine (sCr) ( 1.239 1.317 1.399 ), cold ischemia time (CIT) ( 1.031 1.043 1.056), machine perfusion ( 0.401 0.542 0.733 ), and induction therapy with rabbit antithymocyte globulin (rATG) ( 0.658 0.800 0.973 ). Duration of DGF > 4 days was associated with inferior renal function and DGF > 14 days with the higher incidences of acute rejection, graft loss, and death. In conclusion, the incidence and duration of DGF were high and associated with inferior graft outcomes. While late referral and poor donor maintenance account for the high overall incidence of DGF, variability in donor and recipient selection, organ preservation method, and type of induction agent may account for the wide variation observed among transplant centers.

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Section: Definitionsmentioning

confidence: 99%

Exploring the causes of the high incidence of delayed graft function after kidney transplantation in Brazil: a multicenter study

et al. 2021

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“…a Expressed as difference of means, difference in medians, or difference in proportions as appropriate. b Calculated with the OPTN, mapping coefficients for the 2017 year by kidney.epi R package [24].…”

Section: Discussionmentioning

confidence: 99%

“…A two-sided p value of less than 0.05 was considered statistically significant. The analyses were performed with R version 3.5.2 (R Foundation, Vienna, Austria) using the survival [21], epitools [22], mice [21], nephro [23], and kidney.epi [24] packages, and with STATA version 15 for longitudinal GFR data.…”

Section: Statistical Analysesmentioning

confidence: 99%

Long-Term Outcomes of Kidney Transplants from Older/Marginal Donors: A Cohort Study

Bikbov

Ruggenenti

Perna

et al. 2021

Nephron

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Introduction: To safely expand the donor pool, we introduced a strategy of biopsy-guided selection and allocation to single or dual transplantation of kidneys from donors >60 years old or with hypertension, diabetes, and/or proteinuria (older/marginal donors). Here, we evaluated the long-term performance of this approach in everyday clinical practice. Methods: In this single-center cohort study, we compared outcomes of 98 patients who received one or two biopsy-evaluated grafts from older/marginal donors (“recipients”) and 198 patients who received nonhistologically assessed single graft from ideal donors (“reference-recipients”) from October 2004 to December 2015 at the Bergamo Transplant Center (Italy). Results: Older/marginal donors and their recipients were 27.9 and 19.3 years older than ideal donors and their reference-recipients, respectively. KDPI/KDRI and donor serum creatinine were higher and cold ischemia time longer in the recipient group. During a median follow-up of 51.9 (interquartile range 23.1–88.6) months, 11.2% of recipients died, 7.1% lost their graft, and 16.3% had biopsy-proven acute rejection (BPAR) versus 3.5, 7.6, and 17.7%, respectively, of reference-recipients. Overall death-censored graft failure (rate ratio 0.78 [95% CI 0.33–2.08]), 5-year death-censored graft survival (94.3% [87.8–100.0] vs. 94.2% [90.5–98.0]), BPAR incidence (rate ratio 0.87 [0.49–1.62]), and yearly measured glomerular filtration rate decline (1.18 ± 3.27 vs. 0.68 ± 2.42 mL/min/1.73 m2, p = 0.37) were similar between recipients and reference-recipients, respectively. Conclusions: Biopsy-guided selection and allocation of kidneys from older/marginal donors can safely increase transplant activity in clinical practice without affecting long-term outcomes. This may help manage the growing gap between organ demand and supply without affecting long-term recipient and graft outcomes.

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“…Moreover, a history of diabetes enjoys a higher score than the absence of such a history. [ 25 26 30 ] It is suggested that if a country or a group of researchers want to create a new model, they must study the different models of different countries and consider their differences and create their own native model.…”

Section: Discussionmentioning

confidence: 99%

Scoring systems of kidney donation from deceased donors

Moghbeli

Jangi

Ebnehoseini

2021

Journal of Education and Health Promotion

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Renal disease is the most prevalent disease. Kidney failure can cause physical problems. Hence, patients need to use dialysis therapy or kidney transplantation, and actually, people are in the waiting list for a transplant. This research aimed to extract the prognostic models that evaluate the preparation of kidney donors diagnosed with brain death (DBD). This research was a systematic review of PubMed, Science Direct, and general explorers up until 2020. It followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-P protocol. The assessment of the articles was done by the authors. This evaluation was supposed to be in the form of scoring, prioritizing, and ranking the donors in terms of their preparation. Eleven sources of information included 9 academic articles along with 2 Grey Sources from 7 different countries. 9 algorithms and models were extracted which included, overall 10 factors. All the models were comprised of 4 factors and about 90% of these models considered 4 or 5 factors to evaluate the preparation of kidney donors DBD. Over 60% of the models had taken into account age, blood pressure history, and creatinine factors. Disease prognosis facilitates a doctor's decision-making on the emergence of the disease. Prognostic models of renal diseases can be a great help to patients. A review of the related literature revealed that all the models received a high score in terms of the two factors they included, age and history of blood pressure.

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R Open Source Programming Code for Calculation of the Kidney Donor Profile Index and Kidney Donor Risk Index

Cited by 12 publications

References 20 publications

Exploring the causes of the high incidence of delayed graft function after kidney transplantation in Brazil: a multicenter study

Exploring the causes of the high incidence of delayed graft function after kidney transplantation in Brazil: a multicenter study

Long-Term Outcomes of Kidney Transplants from Older/Marginal Donors: A Cohort Study

Scoring systems of kidney donation from deceased donors

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