Diagnosing the Decades-Long Rise in the Deceased Donor Kidney Discard Rate in the United States

Stewart, Darren; García, Victoria Domínguez; Rosendale, John D.; Klassen, David K.; Carrico, Bob

doi:10.1097/tp.0000000000001539

Cited by 128 publications

(170 citation statements)

References 36 publications

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“…The mixed‐effects logistic regression models were adjusted for previously identified donor factors in the literature, including donor age > 50 or not, either kidney biopsied, glomerulosclerosis > 20% or not if biopsied, cytomegalovirus (CMV) status, KDPI, cause death due to cerebrovascular accident (CVA), donation after cardiac death (DCD) status, height, weight, history of tattoo, either kidney pumped, cold ischemica time, hepatitis B core antibody status, hepatitis B surface antigen status, history of diabetes, history of hypertension, history of cocaine use, history of IV drug use (IVDU), terminal creatinine >1.5 mg/dL or not, ABO blood type, transplant year, and race. We did not find multicollinearity between individual elements of KDPI (10 donor variables) and KDPI score; therefore, we decided to keep KDPI in the multivariable mixed‐effects logistic regression models.…”

Section: Patients and Methods/materials And Methodsmentioning

confidence: 99%

Trends in utilization of deceased donor kidneys based on hepatitis C virus status and impact of public health service labeling on discard

Ariyamuthu

Sandikçi

AbdulRahim

et al. 2019

Transplant Infectious Dis

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Background Kidneys from deceased donors infected with hepatitis C virus (HCV) are underutilized. Most HCV virus‐infected donors are designated as Public Health Service increased donors (PHS‐IR). Impact of PHS and HCV designations on discard is not well studied. Methods We queried the UNOS data set for all deceased donor kidneys between January 2015 and December 2018. The final study cohort donors (n = 38 702) were stratified into three groups based on HCV antibody (Ab) and NAT status: (a) Ab−/NAT− (n = 35 861); (b) Ab+/NAT− (n = 973); and (c) Ab±/NAT+ (n = 1868). We analyzed utilization/discard rates of these organs, the impact of PHS‐IR and HCV designations on discard using multivariable two‐level hierarchical logistic regression models, forecasted number of HCV viremic donors/kidneys by 2023. Results During the study period, (a) the number of viremic donor kidneys increased 2 folds; (b) the multilevel mixed‐effects logistic regression models showed that, overall, the PHS labeling (OR 1.20, CI 95% CI 1.15‐1.29) and HCV designation (OR 2.29; 95% CI 2.15‐2.43) were independently associated with increased risk of discard; (c) contrary to the general perception, PHS‐IR kidneys across all HCV groups, compared to PHS‐IR kidneys were more likely to be discarded; (d) we forecasted that the number of kidneys from HCV viremic donor kidneys might increase from 1376 in 2019 to 2092 in 2023. Conclusion Hepatitis C virus viremic kidneys might represent 10%‐15% of deceased donor organ pool soon with the current rate of the opioid epidemic. PHS labeling effect on discard requires further discussion of the utility of this classification.

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Section: Patients and Methods/materials And Methodsmentioning

confidence: 99%

Trends in utilization of deceased donor kidneys based on hepatitis C virus status and impact of public health service labeling on discard

Ariyamuthu

Sandikçi

AbdulRahim

et al. 2019

Transplant Infectious Dis

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“…Not only could the need for deceased donor kidneys increase in the near future, the discard rate has stagnated between 18% and 20% . Although the static kidney discard rate has been associated with the proportion of marginal deceased donor kidneys within the donor pool, there is evidence to suggest that some of these kidneys are viable for transplantation . Therefore, there is a need to make sure that every viable kidney is placed with a suitable recipient.…”

Section: Introductionmentioning

confidence: 99%

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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“…As a result of these endeavors, an upturn in the number of “marginal” donors such as expanded criteria donors (ECD), donation after cardiocirculatory death (DCD) donors, donors with prolonged warm or cold ischemia time (CIT), dual kidneys from donors at the extremes of age, or donors with acute kidney injury (AKI) occurred . Commensurate with efforts to enlarge the donor pool and with changes in the Kidney Allocation System (KAS) including implementation of the Kidney Donor Profile Index (KDPI), the kidney discard rate increased from 10% in 1998 to 20% in 2017 …”

Section: Introductionmentioning

confidence: 99%

“…The increasing number of discarded DD kidneys has become a national crisis, particularly since it is believed by many that a substantial proportion of these kidneys may be “usable” for transplantation in the “right” recipient. With kidneys recovered from older donors, high KDPI donors, or ECDs, >50% are discarded . Anatomic considerations are one of the primary reasons for kidney discard.…”

Section: Introductionmentioning

confidence: 99%

Eversion endarterectomy of the deceased donor renal artery to prevent kidney discard

Khan

Hennawy

Jones

et al. 2018

Clinical Transplantation

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Diagnosing the Decades-Long Rise in the Deceased Donor Kidney Discard Rate in the United States

Cited by 128 publications

References 36 publications

Trends in utilization of deceased donor kidneys based on hepatitis C virus status and impact of public health service labeling on discard

Trends in utilization of deceased donor kidneys based on hepatitis C virus status and impact of public health service labeling on discard

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

Eversion endarterectomy of the deceased donor renal artery to prevent kidney discard

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