Predictors of Deceased Donor Kidney Discard in the United States

Marrero, Wesley J.; Naik, Abhijit S.; Friedewald, John; Xu, Yongcai; Hutton, David; Lavieri, Mariel S.; Parikh, Neehar D.

doi:10.1097/tp.0000000000001238

Cited by 60 publications

(80 citation statements)

References 24 publications

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“…For example, the NLP model highlights specific types of PHS risk (ie, intravenous drug use) associated with discard. This finding is aligned with research on kidney offer declines in addition to the similar factors, hypertension, diabetes, and insulin use used in previous models . Having a directional understanding of these nuanced associations, in relation to PHS risk, is important given that the Centers for Disease Control and Prevention (CDC) is reevaluating PHS risk definitions…”

Section: Discussionsupporting

confidence: 54%

Can donor narratives yield insights? A natural language processing proof of concept to facilitate kidney allocation

Placona

Martinez

McGehee

et al. 2020

American Journal of Transplantation

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Although expedited placement could ameliorate stagnant kidney utilization, precisely identifying difficult‐to‐place organs is crucial to mitigate potential harms associated with this policy. Existing algorithms have only leveraged structured data from the Organ Procurement and Transplantation Network (OPTN); however, detailed, free text case information about a donor exists. No known research exists about the utility of these data. We developed a model to predict the probability of delay or discard for adult deceased kidney donors between 2010 and 2018, leveraging donor free text data. The resultant model had a c‐statistic of 0.75 compared to 0.80 ( Reduced Probability of Delay or Discard [model], r‐PODD) and 0.77 ( Kidney Donor Profile Index, KDPI) on the test dataset. Analysis of the top predictive words suggest both known and potentially novel clinical factors (ie, a known factor such as hypertension vs a novel factor such as stents), and nuanced social factors (intravenous drug use) could negatively affect kidney utilization. These findings suggest that donor narratives have utility; the natural language processing (NLP) model is only moderately correlated with existing indices and provides directional evidence about additional cardiovascular risk factors that may affect kidney utilization. More research is needed to understand the potential to enhance existing indices of kidney utilization to better enable and mitigate the effects of policy interventions such as expedited placement.

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Section: Discussionsupporting

confidence: 54%

Can donor narratives yield insights? A natural language processing proof of concept to facilitate kidney allocation

Placona

Martinez

McGehee

et al. 2020

American Journal of Transplantation

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“…Marrero et al . , using data from a more recent era (2000–2012), similarly found that a terminal creatinine >1.5 mg/dl was associated with an increase in the risk of discard (OR 4.31). During the period studied in our analysis, 2399 donors with AKI had both kidneys procured but discarded and 699 donors with AKI had one kidney transplanted and one kidney discarded.…”

Section: Discussionmentioning

confidence: 91%

Outcomes of kidney transplant from deceased donors with acute kidney injury and prolonged cold ischemia time - a retrospective cohort study

et al. 2019

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Summary While deceased donor renal transplants (DDRT) from donors with either acute kidney injury (AKI) or long cold ischemia time (CIT) are associated with increased risk of delayed graft function (DGF), recipients of these kidneys have good patient and allograft survival. There are limited data on whether kidneys with both AKI and long CIT have outcomes similar to kidneys with only one of these insults. Using data from the Scientific Registry of Transplant Recipients, we analyzed transplant outcomes in patients (2005–2015) receiving kidneys with AKI (terminal creatinine ≥2.0 mg/dl) and CIT 24–30 h (n = 1289), 30–36 h (n = 734), and >36 h (n = 614), using kidneys with AKI and CIT <24 h (n = 5434) as a reference. DGF was more common with increasing CIT up to 36 h, then decreased slightly (41.2% vs. 46.8% vs. 52.5% vs. 50.2%, P < 0.001). Death‐censored graft survival (DCGS) at 3 years was better with CIT <24 h compared with other groups (92.5% vs. 90.8% vs. 92% vs. 89.2%, P = 0.018). On multivariable analysis, donor creatinine was predictive of DCGS, whereas only CIT >36 h was predictive of DCGS (aHR 1.27, P = 0.03). Recipients transplanted with kidneys with both AKI and long CIT have excellent intermediate‐term outcomes.

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“…Currently, only one-third of patients undergo transplant within 5 years of listing, and many die or become too sick before receiving an organ offer. 7 Among factors that may be associated with increased rates of kidney discard is the decision to perform a procurement biopsy, 8 to assess the "quality" of deceased donor organs, especially those previously classified as from expanded-criteria donors (ECDs). 6 Although the new US kidney allocation system included provisions designed to increase placement of high-risk organs, 3 the high rate of kidney discard persists, thought to reflect both changing donor demographics and transplant program concerns about performance metrics and optimizing outcomes.…”

Section: Introductionmentioning

confidence: 99%

Variation in use of procurement biopsies and its implications for discard of deceased donor kidneys recovered for transplantation

Lentine

Naik

Schnitzler

et al. 2019

American Journal of Transplantation

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The use of procurement biopsies in deceased donor kidney acceptance is controversial. We analyzed Scientific Registry of Transplant Recipients data (n = 59 328 allografts, 2014-2018) to describe biopsy practices across US organ procurement organizations (OPOs) and examine relationships with discards, using hierarchical modeling to account for OPO and donor factors. Median odds ratios (MORs) provide the median of the odds that allografts with identical reported traits would be biopsied or discarded from 2 randomly drawn OPOs. Biopsies were obtained for 52.7% of kidneys. Biopsy use rose in a graded manner with kidney donor profile index (KDPI).Biopsy rates differed significantly among OPOs (22.8% to 77.5%), even after adjustment for KDPI and other donor factors. Discard rates also varied from 6.6% to 32.1% across OPOs. After adjustment for donor factors and OPO, biopsy was associated with more than 3 times the likelihood of discard (adjusted odds ratio [ 95%LCL aOR 95%UCL ], 3.29 3.51 3.76 ). This association was most pronounced for low-risk (KDPI <20) kidneys (aOR, 5.45 6.47 7.69 ), with minimal impact at KDPI >85 (aOR, 0.88 1.15 1.51 ). Adjusted MORs for kidney discard and biopsy were greatest for low-risk kidneys. Reducing the rate of unnecessary biopsy and improving the accuracy of histologic assessments in higher KDPI organs may help reduce graft discard rates. K E Y W O R D Sbiopsy, clinical research/practice, donors and donation: deceased, health services and outcomes research, kidney transplantation/nephrology, organ procurement, organ procurement and allocation, Scientific Registry for Transplant Recipients (SRTR)

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Predictors of Deceased Donor Kidney Discard in the United States

Abstract: We have characterized several important predictors of deceased donor kidney discard. Better understanding of factors that lead to increased deceased donor kidney discard can allow for targeted interventions to reduce discard.

Cited by 60 publications

References 24 publications

Can donor narratives yield insights? A natural language processing proof of concept to facilitate kidney allocation

Can donor narratives yield insights? A natural language processing proof of concept to facilitate kidney allocation

Outcomes of kidney transplant from deceased donors with acute kidney injury and prolonged cold ischemia time - a retrospective cohort study

Variation in use of procurement biopsies and its implications for discard of deceased donor kidneys recovered for transplantation

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