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• W3019858486 abstract "There are limited data on the nonprocurement of kidneys from solid organ donors. Analysis of Standard Transplant Analysis and Research files was undertaken on all deceased donors in the United States with at least 1 solid organ recovered. From 2000 to 2018, 21 731 deceased donor kidneys (averaging 1144 kidneys per year) were not procured. No kidneys were procured from 8% of liver donors, 3% of heart donors, and 3% of lung donors. Compared to donors with all kidneys procured, those with none procured were older and more likely obese, black, hypertensive, diabetic, hepatitis C positive, smokers, Public Health Service – Increased Risk designated, deceased after cardiac death, or deceased after cerebrovascular accident. Although these donors had lower quality kidneys (median Kidney Donor Risk Index (interquartile range) 1.9 (1.0) vs 1.2 (0.7)), there was substantial overlap in quality between nonprocured and procured kidneys. Nearly one third of nonprocurements were attributed to donor history. Donors with elevated terminal creatinine likely resulting from acute kidney injury (AKI) had higher odds of kidney nonprocurement. Nonprocurement odds varied widely across Organ Procurement and Transplantation Network regions, with a positive correlation between donor kidney nonprocurements and kidney discards at the donation service area level. These findings suggest current discard rates underestimate the underutilization of deceased donor kidneys and more research is needed to optimize safe procurement and utilization of kidneys from donors with AKI. There are limited data on the nonprocurement of kidneys from solid organ donors. Analysis of Standard Transplant Analysis and Research files was undertaken on all deceased donors in the United States with at least 1 solid organ recovered. From 2000 to 2018, 21 731 deceased donor kidneys (averaging 1144 kidneys per year) were not procured. No kidneys were procured from 8% of liver donors, 3% of heart donors, and 3% of lung donors. Compared to donors with all kidneys procured, those with none procured were older and more likely obese, black, hypertensive, diabetic, hepatitis C positive, smokers, Public Health Service – Increased Risk designated, deceased after cardiac death, or deceased after cerebrovascular accident. Although these donors had lower quality kidneys (median Kidney Donor Risk Index (interquartile range) 1.9 (1.0) vs 1.2 (0.7)), there was substantial overlap in quality between nonprocured and procured kidneys. Nearly one third of nonprocurements were attributed to donor history. Donors with elevated terminal creatinine likely resulting from acute kidney injury (AKI) had higher odds of kidney nonprocurement. Nonprocurement odds varied widely across Organ Procurement and Transplantation Network regions, with a positive correlation between donor kidney nonprocurements and kidney discards at the donation service area level. These findings suggest current discard rates underestimate the underutilization of deceased donor kidneys and more research is needed to optimize safe procurement and utilization of kidneys from donors with AKI. Kidney transplantation is the treatment of choice for end-stage kidney disease (ESKD) and is associated with improved survival, quality of life, and long-term cost compared to dialysis.1Tonelli M Wiebe N Knoll G et al.Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes.Am J Transplant. 2011; 11: 2093-2109Crossref PubMed Scopus (736) Google Scholar,2Wolfe RA Ashby VB Milford EL et al.Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant.N Engl J Med. 1999; 341: 1725-1730Crossref PubMed Scopus (3918) Google Scholar However, access to transplantation in the United States is limited by the shortage of available organs. Recent efforts to expand the organ donor pool have identified suboptimal deceased donor kidney utilization and concerns about the adequacy of procurement efforts.3United States Executive Office of the President [Donald J. Trump]: Executive Order 13,879: Advancing American Kidney Health.Fed Regist. 2019; 84: 33817-33819Google Scholar Although there remains debate over how to identify the true number of eligible deaths in order to determine the full extent of available organs in the United States, the number of solid organ donors—and in particular, the number of donors from whom a kidney was not procured—is known. Kidneys are the most commonly procured organs from deceased donors and tend to have less stringent criteria for acceptance than the heart or lungs.4Israni AK Zaun D Rosendale JD Schaffhausen C Snyder JJ Kasiske BL. OPTN/SRTR 2017 annual data report: deceased organ donation.Am J Transplant. 2019; 19: 485-516Crossref PubMed Google Scholar Organ procurement organizations (OPOs) attempt to be appropriately selective in organ procurement to optimize their efforts to obtain the largest number of organs that are going to be transplanted and avoid procuring organs that will subsequently be discarded. For example, organs with tumors and those with significant anatomical abnormalities that would preclude transplantation are usually not procured.5Hart A Smith JM Skeans MA et al.OPTN/SRTR 2017 annual data report: kidney.Am J Transplant. 2019; 19: 19-123Crossref PubMed Google Scholar However, it is surprising that in some donation service areas (DSAs), over 10% of deceased donors who have given other solid organs were not also kidney donors.6King KL Husain SA Mohan S. Geographic variation in the availability of deceased donor kidneys per wait-listed candidate in the United States.Kidney Int Rep. 2019; 4: 1630-1633Abstract Full Text Full Text PDF PubMed Google Scholar,7Mohan S Foley K Chiles MC et al.The weekend effect alters the procurement and discard rates of deceased donor kidneys in the United States.Kidney Int. 2016; 90: 157-163Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar There remains limited information on the extent of kidney nonprocurement in donors who have given at least 1 other solid organ for transplant, that is, a heart, lung, and/or liver, or the factors that contribute to this phenomenon.8Gore SM Taylor RM Wallwork J. Availability of transplantable organs from brain stem dead donors in intensive care units.BMJ. 1991; 302: 149-153Crossref PubMed Scopus (52) Google Scholar We attempt to measure the extent of kidney nonprocurement from deceased solid organ donors, identify factors associated with nonprocurement, and analyze variations in procurement practices across OPOs. Using United Network for Organ Sharing (UNOS) Standard Transplant Analysis and Research (STAR) files based on the national Organ Procurement and Transportation Network (OPTN) database as of March 15, 2019, we conducted a retrospective cohort study on all deceased donors with at least 1 solid organ recovered between January 1, 2000 and December 31, 2018. Over the study period, we identified 152 702 deceased donors in the United States with 1 or more solid organs recovered, that is, kidney(s), liver, heart, lung(s), intestine, and pancreas (Figure S1). We then excluded donors where consent for kidney donation was not requested or obtained (n = 2359), donors whose kidneys were recovered for reasons other than transplant (eg, research) (n = 1022), procurements that were restricted by the medical examiner (n = 115), donors with ESKD reported by the OPO (n = 20), and donors with only a pancreas procured (n = 4) or only an intestine procured (n = 4). We also excluded donors with missing terminal serum creatinine values (n = 106), implausible terminal creatinine values (<0.1 or >40 mg/dL) (n = 11), and age <1 year or body weight <10 kg (n = 2349). Nonprocurement was defined as the failure by the procurement team to recover a kidney from the deceased donor, in contrast to kidney discard, in which the organ is recovered but not transplanted into a recipient. Our final cohort of 146 712 deceased donors was categorized into 3 groups, based on the status of their kidney procurement: (1) no kidneys procured (n = 10 291); (2) single kidney procured (n = 1149); and (3) all kidneys procured (n = 135 252), which included cases where only 1 kidney was procured due to an absent partner kidney at the time of death (n = 345) (Figure S1). The data that support the findings of this study are available via request to the OPTN. Reported reasons for kidney nonprocurement were mapped to 7 categories (Table S1): (1) poor organ quality and function, (2) anatomical abnormality, (3) donor history, (4) inability to locate a recipient, (5) logistical challenges, (6) procurement injury, and (7) other. When the code for “Other specify” was used, 2 authors reviewed the free-text field and mapped the field to 1 of the 7 categories. When moving from organ-level reasons to donor-level reasons (Tables 2 and 3), donors with different nonprocurement reasons listed for the left vs right kidney were assigned to an eighth category: (8) discordant. Organ quality was estimated using the Kidney Donor Risk Index (KDRI). The KDRI estimates the relative risk of posttransplant allograft failure, with lower values suggestive of better quality kidneys.9Rao PS Schaubel DE Guidinger MK et al.A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index.Transplantation. 2009; 88: 231-236Crossref PubMed Scopus (667) Google Scholar,10Zhong Y Schaubel DE Kalbfleisch JD Ashby VB Rao PS Sung RS. Reevaluation of the Kidney Donor Risk Index (KDRI).Transplantation. 2019; 103: 1714-1721Crossref PubMed Scopus (20) Google Scholar The KDRI was calculated using 10 donor-specific characteristics (age, height, weight, ethnicity, history of hypertension, history of diabetes, cause of death, terminal creatinine, hepatitis C-positive [HCV+] status, and donation after cardiac death [DCD])11The Organ Procurement and Transplantation Network UN for Organ Sharing. A Guide to Calculating and Interpreting the Kidney Donor Profle Index (KDPI). https://optn.transplant.hrsa.gov/media/1512/guide_to_calculating_interpreting_kdpi.pdf. 2019. Accessed July 17, 2019.Google Scholar and mapped onto a cumulative percentage scale using the 2017 scaling factor to generate the Kidney Donor Profile Index (KDPI).11The Organ Procurement and Transplantation Network UN for Organ Sharing. A Guide to Calculating and Interpreting the Kidney Donor Profle Index (KDPI). https://optn.transplant.hrsa.gov/media/1512/guide_to_calculating_interpreting_kdpi.pdf. 2019. Accessed July 17, 2019.Google Scholar,12The Organ Procurement and Transplantation Network UN, for Organ Sharing. KDRI to KDPI mapping table. https://optn.transplant.hrsa.gov/media/2150/kdpi_mapping_table.pdf. Updated March 9, 2018. Accessed July 22, 2019.Google Scholar Organ quality assessment is a complex, multifactorial clinical decision and the presence of multiple unfavorable characteristics can adversely affect perceptions of organ quality. To examine the potential additive impact of donors having multiple negative characteristics, we identified 14 donor characteristics previously shown to increase the risk of kidney discard, thus also likely making the kidneys less favorable for procurement and generated a count for each donor.13Brennan C Husain SA King KL et al.A donor utilization index to assess the utilization and discard of deceased donor kidneys perceived as high risk.Clin J Am Soc Nephrol. 2019; 14: 1634-1641Crossref PubMed Scopus (0) Google Scholar,14Mohan S Chiles MC Patzer RE et al.Factors leading to the discard of deceased donor kidneys in the United States.Kidney Int. 2018; 94: 187-198Abstract Full Text Full Text PDF PubMed Scopus (123) Google Scholar These high-risk characteristics included age >50 years, black race, Public Health Service – Increased Risk (PHS-IR) designation, HCV+ status, death due to cerebrovascular accident (CVA), obesity (body mass index [BMI] >35 kg/m2), DCD, history of hypertension, history of diabetes, history of cancer, chronic smoking (>20 cigarette packs per year), history of drug use (non-IV), terminal creatinine >2 mg/dL, and KDPI > 85%.14Mohan S Chiles MC Patzer RE et al.Factors leading to the discard of deceased donor kidneys in the United States.Kidney Int. 2018; 94: 187-198Abstract Full Text Full Text PDF PubMed Scopus (123) Google Scholar,15Brennan C Husain SA King KL et al.A donor utilization index to assess the utilization and discard of deceased donor kidneys perceived as high risk.Clin J Am Soc Nephrol. 2019; 14 (Manuscript submitted for publication.): 1634-1641Crossref PubMed Scopus (0) Google Scholar Missing data for any of these variables were counted as not having the risk factor. The total number of unfavorable characteristics in a deceased donor ranged from 0 to a maximum of 14. With donor as our unit of analysis, we compared donors with no kidneys procured to donors with all kidneys procured. Pearson’s chi-square tests and the nonparametric Wilcoxon rank sum or equality of medians tests were performed for categorical and continuous variables, respectively. We used logistic regression models to identify factors associated with kidney nonprocurement (vs procurement). Donors with only 1 of 2 available kidneys recovered were excluded from logistic regression analyses due to uncertainty over the degree to which the nonprocured kidneys differed from their procured counterparts and the possibility that nonprocurements secondary to unilateral abnormalities were potentially appropriate nonprocurements. Bivariable analysis was performed on each donor characteristic. All donor characteristics were used to generate an initial multivariable model. To avoid overfitting, well-defined risk factors for chronic kidney disease—including obesity, black race, hypertension, diabetes, HCV+ status, and proteinuria—were used along with terminal creatinine in the final multivariable model.16Denker M Boyle S Anderson AH et al.Chronic renal insufficiency cohort study (CRIC): overview and summary of selected findings.Clin J Am Soc Nephrol. 2015; 10: 2073-2083Crossref PubMed Scopus (75) Google Scholar,17Grams ME Yang W Rebholz CM et al.Risks of adverse events in advanced CKD: the chronic renal insufficiency cohort (CRIC) study.Am J Kidney Dis. 2017; 70: 337-346Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar Pearson correlation and linear regression were used to assess the relationship between the proportion of donors with no kidneys procured and the proportion of procured kidneys that were discarded within DSAs. To examine potential associations between OPOs and background donor risk level in explaining the aforementioned relationship, OPOs were stratified into “high-,” “medium-,” and “low”-risk groups based on the percentage of their available donors with KDPI over 85%: low proportion (<15%) of donors with KDPI > 85% (n = 20), medium proportion (16%-20%) of donors with KDPI > 85% (n = 23), and high proportion (21%-30%) of donors with KDPI > 85% (n = 14). To analyze how procurement decisions have changed over the study period, we stratify potential donors by donation year (2000-2006, 2007-2012, and 2013-2018). Within these 3 time periods we calculate the crude and adjusted odds of kidney nonprocurement by donor terminal creatinine levels and other donor risk factors. The degree of overlap in quality of procured and nonprocured kidneys was assessed using the Bhattacharyya coefficient, a measure of the similarity between 2 distributions in which a value of 1 reflects complete overlap and a value of 0 reflects no overlap.18Bhattacharyya A. On a measure of divergence between two multinomial populations.Sankhyā. 1946; 7: 401-406Google Scholar Statistical analyses were performed using Stata 15.1 (StataCorp, College Station, TX). Statistical significance was set at the 95% confidence level (P < .05). From 2000 to 2018, we identified 146 712 deceased organ donors, among whom 10 291 (7.1%) had no kidneys recovered for transplant and another 1149 (0.8%) had only 1 of 2 available kidneys recovered (Figure S1). A total of 21 731 deceased donor kidneys, averaging 1144 kidneys/y, were left behind over our 19-year study period. Compared to donors with all kidneys procured, those with no kidneys procured were older and more likely to be obese, black, hypertensive, diabetic, HCV+, smokers, or PHS-IR designated (all P < .001; Table 1). Donors with no kidneys procured were also more likely to have died from a cerebrovascular accident or donated after cardiovascular death (all P < .001). These donors had lower quality kidneys (median KDRI 1.9 vs 1.2), higher terminal creatinine (3.7 ± 3.0 vs 1.2 ± 1.0 mg/dL), and higher numbers of unfavorable donor characteristics (Figure S2) than donors with all kidneys procured (all P < .001). Although nonprocured kidneys had higher KDRI scores and terminal creatinine levels than procured kidneys, there were large overlaps (Bhattacharya coefficients 0.88 and 0.87, respectively) in the quality of nonprocured vs procured donor kidneys (Figure 1A,B). Donors with any missing data (n = 13 300) had more than 2-fold higher odds of kidney nonprocurement, compared to donors with no missing data (n = 132 268) (P < .001; Table 1).TABLE 1Donor characteristics by kidney procurement statusn (%) or mean ± SDNo kidneys recovered1No kidneys recovered – 0 kidneys procured from the deceased donor. (n = 10 296)All kidney(s) recovered2All kidneys recovered – 2 kidneys procured (n = 134 927), or 1 kidney procured from donors who were missing the other kidney (due to previous living donation, congenital absence, previous nephrectomy, etc) (n = 345). (n = 135 272)Age (y)50.8 ± 17.139.5 ± 17.3Age >505440 (53%)41 826 (31%)Age >75735 (7%)847 (0.6%)Female4126 (40%)54 752 (40%)BMI (kg/m2)28.3 ± 7.127.2 ± 6.8Obese (BMI > 35)1496 (15%)15 495 (12%)Black/African American2575 (25%)19 022 (14%)History of hypertension6448 (63%)40 814 (30%)History of diabetes3067 (30%)11 856 (9%)History of cancer626 (6%)4049 (3%)Death due to CVA5017 (49%)49 896 (37%)Terminal creatinine (mg/dL)3.7 ± 3.01.2 ± 1.0Terminal creatinine >26632 (64%)12 765 (9%)Known clinical infection3Known Clinical Infection: Deceased donor has an infection (viral, bacterial, fungal, mycobacterial, or parasitic) that is potentially transmissible to the recipient.4965 (48%)69 658 (52%)DCD2204 (21%)16 504 (12%)HCV+ (Ab+ or NAT)1581 (15%)5687 (4%)Median KDRI (IQR)1.9 (1.0)1.2 (0.7)Median KDPI (%) (IQR)4KDPI calculated based on the 2017 median KDRI value among all deceased donor kidneys procured as the scaling factor.88 (34)50 (53)Proteinuria6255 (61%)54 463 (40%)Smoked >20 cigarette packs/y3403 (33%)36 083 (27%)Alcohol abuse1270 (12%)19 698 (15%)History of drug use (IV)988 (10%)7182 (5%)History of drug use (non-IV)3056 (30%)45 315 (34%)PHS-IR2265 (22%)16 057 (12%)Organs recoveredLiver9831 (96%)112 025 (83%)Heart1128 (11%)44 139 (33%)Lung879 (9%)28 369 (21%)Note: Data displayed as column % or mean ± SD P < .001 for all comparisons between donors with no kidneys procured and donors with all kidneys procured, except female gender (P = .52).5Pearson chi-square tests and nonparametric Wilcoxon rank-sum tests were performed for categorical and continuous variables, respectively.1 No kidneys recovered – 0 kidneys procured from the deceased donor.2 All kidneys recovered – 2 kidneys procured (n = 134 927), or 1 kidney procured from donors who were missing the other kidney (due to previous living donation, congenital absence, previous nephrectomy, etc) (n = 345).3 Known Clinical Infection: Deceased donor has an infection (viral, bacterial, fungal, mycobacterial, or parasitic) that is potentially transmissible to the recipient.4 KDPI calculated based on the 2017 median KDRI value among all deceased donor kidneys procured as the scaling factor.5 Pearson chi-square tests and nonparametric Wilcoxon rank-sum tests were performed for categorical and continuous variables, respectively. Open table in a new tab Note: Data displayed as column % or mean ± SD P < .001 for all comparisons between donors with no kidneys procured and donors with all kidneys procured, except female gender (P = .52).5Pearson chi-square tests and nonparametric Wilcoxon rank-sum tests were performed for categorical and continuous variables, respectively. Kidneys were the most commonly procured organs from deceased donors and were the only organs procured in 20 051 (13.7%) donors—including 19 848 bilateral kidney-only donors and 203 unilateral kidney-only donors (Figure 2; Figure S3). In contrast, 8% of liver donors (n = 9831) had no kidneys recovered for transplant, whereas 3% of heart (n = 1128) and 3% of lung donors (n = 765) had no kidneys recovered (Table S3). Compared to donors with all kidneys procured, donors with no kidneys procured were more likely to have a liver, and less likely to have a heart or lung recovered (Table 1). Liver donors who did not have a kidney procured were older and more likely to be obese, black, hypertensive, diabetic, HCV+, smokers, and designated PHS-IR (Table S2). These donors had higher median KDRI scores and terminal creatinine. The 1772 donors in whom a heart and/or lung was recovered but the kidneys were not (Figure 2) tended to be younger and have a lower BMI, in addition to being more likely to be black or have proteinuria, PHS-IR designation, or elevated creatinine than donors with all kidneys procured (Table S2). Approximately half (54%) of kidney nonprocurements were attributed to poor organ quality and function (Table 2), but nearly a third (30%) were for donor history—which presumably should have affected the procurement of the other solid organs as well. Over 1 in 8 kidney nonprocurements occurred due to allocation system-related reasons including purported inability to locate a recipient or logistical challenges. Donors whose kidneys were not procured because of an anatomical abnormality, procurement injury, or logistical challenges were significantly younger and less likely to be black, hypertensive, or diabetic (Table 3). They were also the least likely to be HCV+, smokers, designated PHS-IR, or died due to a CVA or have DCD status. Notably, kidney nonprocurement due to the inability to locate a recipient had higher rates of HCV+ (65%) and PHS-IR designation (49%) compared to other groups. Anatomical abnormality and procurement injury were more commonly cited as the reason for unilateral nonprocurement than bilateral nonprocurement (24% vs 1% and 3% vs 0.2%, respectively) (Table 2). Over two thirds of unilateral nonprocurements cited reasons that typically should have affected the partner kidney equally, that is, poor organ quality and function (46%), donor history (20%), and inability to locate a recipient (4%).19Husain SA Chiles MC Lee S et al.Characteristics and performance of unilateral kidney transplants from deceased donors.Clin J Am Soc Nephrol. 2018; 13: 118-127Crossref PubMed Scopus (34) Google ScholarTABLE 2Common reasons for kidney nonprocurement from donors by kidneys not procured (n = 11 440 deceased donors)Poor organ quality and functionDonor historyInability to locate a recipientAnatomical abnormalityProcurement injuryLogistical challengesOtherDiscordant reasons for L/R kidneysn (row %)6125 (54)3349 (29)1432 (12)379 (3)56 (0.5)17 (0.2)69 (0.6)27 (0.24)Nonprocurement typeBilateral nonprocurement2Bilateral nonprocurement – 0 kidneys procured from the deceased donor.54301310.20.20.40.3Unilateral nonprocurement3Unilateral nonprocurement – 1 kidney procured from donors with 2 kidneys.462042434No observations.24No observations.Organ qualityKidney Donor Risk Index1.8 (1.0)1.9 (1.1)1.9 (1.1)1.4 (0.8)1.4 (0.4)1.4 (1.2)1.5 (0.9)1.7 (1.0)Bilateral nonprocurement1.8 (1.0)1.9 (1.1)1.9 (1.1)1.6 (0.8)1.4 (0.2)1.4 (1.2)1.8 (1.2)1.7 (1.0)Unilateral nonprocurement1.1 (0.6)1.4 (0.7)1.4 (0.4)1.3 (0.7)1.3 (0.4)4No observations.1.2 (0.6)4No observations.Terminal creatinine (mg/dL)3.4 (3.5)2.2 (3.8)1.5 (1.8)1 (0.7)1.1 (0.7)0.9 (3.2)1.4 (1.1)1.3 (1.7)Bilateral nonprocurement3.6 (3.4)2.4 (4.0)1.6 (1.8)0.9 (0.9)1.0 (0.8)0.9 (3.2)1.6 (1.8)1.3 (1.7)Unilateral nonprocurement1.1 (0.8)1.2 (0.8)0.9 (0.7)1.0 (0.7)1.1 (0.7)****No observations.1.2 (0.8)****No observations.Note: Data displayed as row % or median (interquartile range). P < .001 for all comparisons between groups.1Pearson chi-squared tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively.1 Pearson chi-squared tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively.2 Bilateral nonprocurement – 0 kidneys procured from the deceased donor.3 Unilateral nonprocurement – 1 kidney procured from donors with 2 kidneys.4 No observations. Open table in a new tab TABLE 3Characteristics of donors with 1 or more kidneys not procured stratified by the reason for kidney nonprocurement (n = 11 440)Poor organ quality and functionDonor historyInability to locate a recipientAnatomical abnormalityProcurement injuryLogistical challengesOtherDiscordant reasons for L/R kidneysn (row %)6125 (54)3349 (29)1432 (12)379 (3)56 (0.5)17 (0.2)69 (0.6)27 (0.24)Donor characteristics1Pearson chi-square tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively.Age49.4 ± 17.750.9 ± 17.050.3 ± 16.440.7 ± 21.040.2 ± 19.343.8 ± 25.440.9 ± 23.648.1 ± 18.9Female3844424436474256BMI28.8 ± 7.327.7 ± 6.927.6 ± 6.326.1 ± 6.228.5 ± 8.725.0 ± 8.224.3 ± 5.026.7 ± 5.3Black/African American252519154182219History of hypertension5868523829353681History of diabetes27352194121419HCV+51365340619Chronic smokers3231402827124537PHS-IR132749776115Death due to a CVA4654394332354270DCD222117111618411Note: Data displayed as column % or mean ± SD P < .001 for all comparisons between groups.1Pearson chi-square tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively.1 Pearson chi-square tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively. Open table in a new tab Note: Data displayed as row % or median (interquartile range). P < .001 for all comparisons between groups.1Pearson chi-squared tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively. Note: Data displayed as column % or mean ± SD P < .001 for all comparisons between groups.1Pearson chi-square tests and the nonparametric equality of median tests were performed for categorical and continuous variables, respectively. Kidneys from donors who were older, obese, black, smokers, died due to a CVA, or had DCD status experienced higher odds of kidney nonprocurement (all P < .001, Table 4). Furthermore, donors with hypertension, diabetes, HCV+ status, PHS-IR designation, proteinuria, or a history of cancer were at least 2-4 times more likely to not have kidneys procured. Every unit increase in KDRI corresponded to 5-fold higher odds of nonprocurement (OR = 5.39 P < .001) and each 1% unit increase in KDPI corresponded to 4% higher odds of nonprocurement (OR = 1.04, P < .001). Kidneys with KDPI scores >85% were at 6-fold higher odds of nonprocurement (OR = 6.08, P < .001). The more unfavorable characteristics a donor had, the greater the likelihood that their kidneys would not be procured; compared to donors with no unfavorable characteristics, those possessing ≥1 characteristic experienced anywhere from a 1.99-fold (for 1 characteristic) to 38.09-fold (for ≥5 characteristics) higher odds of kidney nonprocurement (all P < .001). Among donors with no kidneys procured, 1 in 7 (n = 1432) had 2 or fewer unfavorable donor characteristics.TABLE 4Bivariable and multivariable logistic regression model of the odds of kidney nonprocurement from 2000 to 2018ParametersCrude OR (95% CI)Adjusted OR (95% CI)All variablesAdjusted OR (95% CI)Risk factors for CKDAge (y)1.04 (1.04-1.04)1.04 (1.04-1.05)Age >502.51 (2.41-2.61)Age >7512.20 (11.03-13.50)Female0.99 (0.95-1.03)1.20 (1.13-1.28)BMI1.02 (1.02-1.03)0.96 (0.96-0.96)0.96 (0.96-0.97)Obese (BMI > 35)1.32 (1.24-1.39)Black/African American2.04 (1.95-2.14)1.23 (1.16-1.30)1.11 (1.04-1.17)History of hypertension3.88 (3.73-4.05)1.62 (1.53-1.72)2.74 (2.60-2.88)History of diabetes4.42 (4.22-4.63)2.05 (1.93-2.18)2.38 (2.25-2.53)History of cancer2.10 (1.92-2.29)1.70 (1.49-1.93)Death due to CVA1.63 (1.56-1.70)1.07 (0.99-1.16)Terminal creatinine (mg/dL) (ref = sCr<1)1.00-1.491.62 (1.50-1.75)1.40 (1.29-1.52)1.48 (1.37-1.61)1.50-2.003.50 (3.211-3.816)2.74 (2.50-3.00)2.89 (2.64-3.16)>2.0025.11 (23.58-26.75)25.22 (23.47-27.11)22.67 (21.17-24.28)Terminal creatinine >217.39 (16.63-18.17)DCD1.96 (1.87-2.06)1.16 (1.08-1.25)HCV+4.13 (3.89-4.39)6.61 (6.07-7.21)6.93 (6.44-7.46)KDRI (unit = 1)5.39 (5.21-5.57)KDPI (unit = 1%)1.04 (1.04-1.04)KDPI > 85%6.08 (5.84-6.34)Proteinuria2.30 (2.21-2.39)1.39 (1.31-1.47)1.34 (1.28-1.40)Smoked >20 cigarette packs/y (ref = no)Yes1.38 (1.32-1.44)0.92 (0.86-0.98)Unknown1.73 (1.50-1.99)0.86 (0.69-1.06)Alcoholism (ref = no)Yes0.80 (0.75-0.85)0.65 (0.60-0.71)Unknown1.41 (1.22-1.63)0.82 (0.65-1.03)IV drug use (ref = no)Yes1.93 (1.80-2.07)1.09 (0.96-1.23)Unknown1.56 (1.31-1.86)0.86 (0.66-1.11)History of drug use (non-IV) (ref = no)Yes0.85 (0.81-0.88)0.78 (0.73-0.84)Unknown1.45 (1.25-1.69)0.94 (0.74-1.20)Known clinical infection0.88 (0.84-0.91)0.70 (0.67-0.73)PHS-IR2.09 (1.99-2.20)1.84 (1.72-1.97)Risk count1Potential risk factors (14) for nonrecovery include: Age >50 y, history of hypertension, history of diabetes, PHS-IR, terminal sCr > 2, HCV+, death due to CVA, BMI > 35, DCD, Black/African American, history o" @default.
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