Evaluation of Transplanting Organs from Drowned Donors
Author Information1
Caleb Han2, Seraphina Ho3, Isaac Jung4
1All authors are listed in alphabetical order.
2Mclean High School,VA, 3James Madison High School,VA, 4Flintridge Preparatory School, C
Background
Donor-derived infections, transmitted from organ donor to organ recipient, while infrequent, often lead to the death of the organ recipient because of their compromised immune systems. A recent CDC publication reported that organ transplants from drowned organ donors potentially exposed to environmental molds (e.g. Scedosporium) through the aspiration of water may lead to invasive mold infections (IMIs) in the recipients of the exposed organs [1]. Scedosporium, a pathogenic soil-dwelling saprophyte often found in polluted water bodies, has emerged as the most common cause of drowned donor derived invasive fungal infections (IFIs), and can manifest as pneumonia, CNS disease, and dissemination [2]. Despite the significant developments made in regards to understanding IMIs from drowned donors, between 2000 and 2016, out of the 61 published cases of scedosporiosis following solid organ transplantation (SOT), 36 of these cases resulted in death, a high mortality rate of 59% [3]. Furthermore, in 2023, Xiaoli Lin and colleagues analyzed the perioperative infections, microbiological results, early transplant outcomes, and first-year clinical outcomes of 38 drowned donor renal recipients. The analyses revealed that when compared to the control group, drowned donors exhibited a significantly higher rate of positive fungal cultures (36.84% vs.13.15%,), and recipients displayed an increased prevalence of gram-negative bacteria (23.68% vs.5.26%) as well as multidrug-resistant GNB infections (18.42% vs. 3.95%) [4]. Additionally, studies regarding IMIs have identified a correlation between the necessary immunosuppressive medications taken by SOT recipients required to prevent organ rejection, and increased risks of contracting invasive mold infections (IMIs) [1, 5]. Currently, one of the most pressing issues in transplantation is the shortage of organs. To address this challenge, there is a growing emphasis on promoting the use of deceased donors, including drowned donors, in organ transplantation, despite the risk of IMIs. Due to persistent shortage of kidneys and livers for transplantation, most transplant centers have been considered to obtain and use the organs even from drowned donors [6]. However, there has been no report on the effects of kidney and/or liver transplants from drowned donors in light of graft failure and recipients’ mortality rates.
Thus, studies on the outcomes of drowned donor kidney and liver transplants are required in comparison to other common accidents and injuries (i.e. Drug intoxication, Gunshot wound, Blunt injury, and Asphyxiation) to understand potentials of the drowned donor kidney and liver transplantation as another transplant resource.
Objective
We aimed to investigate differences in graft failure and patient mortality rate between drowning, gunshot, drug intoxication, asphyxiation, and blunt injury.
Materials and Methods
Data and Data Sources
A retrospective analysis was performed using the UNOS database between January 1, 2010 and June 30, 2022. Pediatric patients, recipients of pediatric donors, and multiple-organ transplants were excluded. Separate UNOS data files that record the cause of the donors’ death prior to the time of the transplant were merged to the main data that record the information at the time of transplant and conventional transplant outcome data (e.g., graft failure and patient mortality). For the different mechanical causes of the donors, the analysis kept the transplant recipients who received a kidney from a donor who died from either drowning, gunshot, drug intoxication, asphyxiation, and blunt Injury. In the analyses, recipients who received organs from donors who died from different mechanical causes of death were separated into different groups. The final dataset contained the data of 100,031 kidney transplant recipients and their donor and 49,363 liver transplant recipients and their donors. Of the kidney recipients, 880 (0.88%) received a kidney from a drowned donor, 19,362 (19.35%) received a kidney from a donor who died from gunshot, 21,865 (21.86%) received a kidney from a donor who died from drug intoxication, 8,878 (8.88%) received a kidney from a donor who died from asphyxiation, and 49,046 (49.03%) received a kidney from a donor who died from a blunt injury. For the liver recipients, 407 (0.83%) received a liver from a drowned donor, 10,822 (21.92%) received a liver from a donor who died from gunshot, 10,505 (21.28%) received a liver from a donor who died from drug intoxication, 3,916 (7.93%) received a liver from a donor who died from asphyxiation, and 23,713 (48.04%) received a liver from a donor who died from a blunt injury.
Outcome and Explanatory Variables
Transplant outcomes graft failure and patient death were compared by the mechanical cause of the death of donors. Other recipient characteristics used for the analyses included sex, age, race, days on waitlist, retransplant recipient, diabetes status, dialysis status, glomerular filtration rate (GFR), BMI, and calculated panel reactive antibody (cPRA) at the time of transplant, and human leukocyte antigens (HLA) mismatch level. For donor characteristics, we queried age, sex, race, BMI, creatinine level, history of hypertension, and measures for organ quality including Kidney Donor Profile Index (KDPI), kidneys from the donors with cardiac death (DCD) and expanded criteria donors (ECD). Additional transplant-related variables, such as HLA mismatch level as well as cold ischemic time (CIT) and organ sharing status (local, regional and national), were also included.
Statistical Analysis
The basic patient, donor and transplant characteristics were compared between the three cohorts using ANOVA tests for continuous, and Chi-sq. Exact tests for categorical variables, depending on the sample size and the distribution of the variables included. Survival curves and the estimates for the outcomes were obtained using the Kaplan-Meier (KM) Product Limit method. In the survival analyses of transplant outcomes, graft failure (for graft survival) or patient death (for patient survival) were the end-points. The recipients who did not experience any of these end-points or whose health or graft/patient status was unknown were censored on the last follow-up or the last day of the study. For those outcome variables used in the KM survival analyses, corresponding multivariable Cox regression analyses were also performed to investigate the risk factors for respective outcomes after controlling for covariates. As in other regressions, the mechanical cause of death of the donor, as well as aforementioned recipient, donor, and transplant characteristics were investigated as potential risk factors. Statistical significance was defined by p<0.05 in the analysis.
Results
Table 1 demonstrates significant variations in kidney patient, kidney donor and transplant characteristics across different mechanical causes of death. Most notably, patients who received kidneys from drowned donors were more likely to be male (63.41%, p<0.001), Asian (8.52%, p<0.001), Hispanic (19.89%, p<0.001), and were more likely to be on dialysis at the time of transplant (83.64%, p<0.001) compared to other causes of mechanical death.
[Table 1: Descriptive analysis Kidney table]| Characteristics | Drowned(n=880) | GUNSHOT(n=19,362) | Drug intoxication (n=21,865) | Asphyxiation(n=8,878) | Blunt Injury(n=49,046) | P-value |
| Patient Characteristics | ||||||
| Male, n (%) | 558.00 (63.41%) | 11,601.00 (59.92%) | 13,580.00 (62.11%) | 5,425.00 (61.11%) | 29,576.00 (60.30%) | <0.001 |
| Age, mean (sd) | 51.69 (13.60) | 49.19 (13.53) | 52.44 (13.25) | 51.14 (13.44) | 50.47 (13.38) | <0.001 |
| Race, n (%) | ||||||
| White | 324.00 (36.82%) | 7,796.00 (40.26%) | 8,859.00 (40.52%) | 3,673.00 (41.37%) | 21,152.00 (43.13%) | <0.001 |
| African American | 277.00 (31.48%) | 7,052.00 (36.42%) | 7,802.00 (35.68%) | 2,816.00 (31.72%) | 15,451.00 (31.50%) | <0.001 |
| Hispanic | 175.00 (19.89%) | 3,163.00 (16.34%) | 3,453.00 (15.79%) | 1,539.00 (17.33%) | 8,577.00 (17.49%) | <0.001 |
| Asian | 75.00 (8.52%) | 996.00 (5.14%) | 1,319.00 (6.03%) | 633.00 (7.13%) | 2,860.00 (5.83%) | <0.001 |
| Other | 29.00 (3.30%) | 355.00 (1.83%) | 432.00 (1.98%) | 217.00 (2.44%) | 1,006.00 (2.05%) | <0.001 |
| Wait time (in days), median (IQR) | 743 (234, 1376) | 672 (235, 1269) | 613 (166, 1302) | 678 (206, 1358) | 670 (235, 1287) | <0.001 |
| Retransplant, n (%) | 105.00 (11.93%) | 2,895.00 (14.95%) | 2,507.00 (11.47%) | 1,159.00 (13.05%) | 6,968.00 (14.21%) | <0.001 |
| Diabetes at the time of TX, n (%) | 302.00 (34.51%) | 5,848.00 (30.37%) | 8,059.00 (36.92%) | 3,016.00 (34.09%) | 15,501.00 (31.78%) | <0.001 |
| BMI at the time of TX, mean (sd) | 28.12 (5.35) | 28.13 (5.54) | 28.82 (5.53) | 28.51 (5.50) | 28.05 (5.49) | <0.001 |
| Dialysis at the time of TX, n (%) | 736.00 (83.64%) | 16,036.00 (82.84%) | 18,168.00 (83.09%) | 7,371.00 (83.03%) | 40,158.00 (81.89%) | <0.001 |
| cPRA at the time of TX, mean (sd) | 23.17 (36.05) | 28.11 (38.70) | 22.96 (35.73) | 24.81 (36.83) | 26.71 (37.80) | <0.001 |
| GFR at the time of TX, mean (sd) | 12.32 (5.10) | 12.52 (4.99) | 12.70 (4.97) | 12.91 (4.95) | 12.93 (4.93) | <0.001 |
| Donor Characteristics | ||||||
| Age, mean (sd) | 36.13 (13.00) | 32.28 (11.75) | 34.58 (10.04) | 36.33 (11.98) | 37.00 (13.85) | <0.001 |
| Male , n (%) | 583.00 (66.25%) | 16,503.00 (85.23%) | 13,015.00 (59.52%) | 5,814.00 (65.49%) | 36,886.00 (75.21%) | <0.001 |
| Race, n (%) | ||||||
| White | 602.00 (68.41%) | 11,526.00 (59.53%) | 17,624.00 (80.60%) | 6,757.00 (76.11%) | 35,390.00 (72.16%) | <0.001 |
| African American | 83.00 (9.43%) | 4,415.00 (22.80%) | 1,664.00 (7.61%) | 641.00 (7.22%) | 4,361.00 (8.89%) | <0.001 |
| Hispanic | 114.00 (12.95%) | 3,052.00 (15.76%) | 2,122.00 (9.71%) | 1,118.00 (12.59%) | 7,911.00 (16.13%) | <0.001 |
| Asian | 68.00 (7.73%) | 169.00 (0.87%) | 224.00 (1.02%) | 207.00 (2.33%) | 826.00 (1.68%) | <0.001 |
| Other | 13.00 (1.48%) | 200.00 (1.03%) | 231.00 (1.06%) | 155.00 (1.75%) | 558.00 (1.14%) | <0.001 |
| Creatinine at the time of TX, mean (sd) | 1.72 (1.95) | 1.30 (0.93) | 1.69 (1.62) | 1.32 (1.29) | 1.11 (0.83) | <0.001 |
| Diabetes at the time of TX, n (%) | 24.00 (2.73%) | 561.00 (2.91%) | 961.00 (4.44%) | 473.00 (5.37%) | 2,039.00 (4.19%) | <0.001 |
| Hypertensive at the time of TX, n (%) | 116.00 (13.18%) | 2,211.00 (11.49%) | 4,060.00 (18.78%) | 1,300.00 (14.77%) | 7,273.00 (14.96%) | <0.001 |
| BMI at the time of TX, mean (sd) | 26.84 (5.14) | 26.76 (5.52) | 28.39 (6.48) | 26.87 (6.26) | 27.01 (5.49) | <0.001 |
| KDPI, mean (sd) | 0.33 (0.22) | 0.25 (0.19) | 0.33 (0.21) | 0.32 (0.21) | 0.30 (0.23) | <0.001 |
| Donor after Cardiac Death, n (%) | 283.00 (32.16%) | 2,442.00 (12.61%) | 4,413.00 (20.18%) | 3,048.00 (34.33%) | 8,923.00 (18.19%) | <0.001 |
| Expanded Criteria Donor, n (%) | 48.00 (5.45%) | 501.00 (2.59%) | 409.00 (1.87%) | 383.00 (4.31%) | 3,345.00 (6.82%) | <0.001 |
| Transplant Characteristics | ||||||
| HLA mismatch level, mean (sd) | 3.95 (1.67) | 3.90 (1.67) | 4.13 (1.48) | 4.01 (1.56) | 3.82 (1.72) | <0.001 |
| Cold Ischemic time (hrs), mean (sd) | 19.76 (10.72) | 17.90 (8.64) | 18.16 (8.60) | 17.88 (8.44) | 17.94 (8.62) | <0.001 |
| Locally shared, n (%) | 601.00 (68.30%) | 13,572.00 (70.10%) | 13,557.00 (62.00%) | 6,279.00 (70.73%) | 34,592.00 (70.53%) | <0.001 |
| Regionally shared, n (%) | 106.00 (12.05%) | 2,039.00 (10.53%) | 3,559.00 (16.28%) | 1,033.00 (11.64%) | 4,937.00 (10.07%) | <0.001 |
| Nationally shared, n (%) | 173.00 (19.66%) | 3,751.00 (19.37%) | 4,749.00 (21.72%) | 1,566.00 (17.64%) | 9,517.00 (19.40%) | <0.001 |
Table 2 demonstrates significant variations in liver patient, liver donor and transplant characteristics across different causes of mechanical death. Most notably, patients who received liver from drowned donors were more likely to be Hispanic (19.66%, p<0.001) or Asian (7.86%, p<0.001), and were less likely to have a retransplant (4.18%, p<0.001) compared to other causes of mechanical death. Drowned kidney donors were more likely to be Asian (6.88%, p<0.001) and exhibited higher levels of creatinine (2.36, p<0.001).
[Table 2: Descriptive analysis Liver table]| Characteristics | Drowned(n=407) | GUNSHOT(n=10,822) | Drug intoxication (n=10,505) | Asphyxiation(n=3,916) | Blunt Injury(n=23,713) | P-value |
| Patient Characteristics | ||||||
| Male, n (%) | 272.00 (66.83%) | 7,384.00 (68.23%) | 7,221.00 (68.74%) | 2,575.00 (65.76%) | 16,099.00 (67.89%) | 0.015 |
| Age, mean (sd) | 55.16 (10.35) | 52.84 (11.12) | 54.64 (10.95) | 54.37 (11.24) | 53.50 (10.76) | <0.001 |
| Race, n (%) | ||||||
| White | 264.00 (64.86%) | 7,785.00 (71.94%) | 7,729.00 (73.57%) | 2,804.00 (71.60%) | 17,101.00 (72.12%) | <0.001 |
| African American | 24.00 (5.90%) | 1,030.00 (9.52%) | 928.00 (8.83%) | 300.00 (7.66%) | 1,934.00 (8.16%) | <0.001 |
| Hispanic | 80.00 (19.66%) | 1,409.00 (13.02%) | 1,345.00 (12.80%) | 582.00 (14.86%) | 3,429.00 (14.46%) | <0.001 |
| Asian | 32.00 (7.86%) | 412.00 (3.81%) | 374.00 (3.56%) | 183.00 (4.67%) | 183.00 (4.67%) | <0.001 |
| Other | 7.00 (1.72%) | 186.00 (1.72%) | 129.00 (1.23%) | 47.00 (1.20%) | 276.00 (1.16%) | <0.001 |
| Wait time (in days), median (IQR) | 70 (13, 269) | 63 (10, 251) | 67 (10, 255) | 78 (13, 266) | 78 (13, 273) | <0.001 |
| Retransplant, n (%) | 17.00 (4.18%) | 789.00 (7.29%) | 514.00 (4.89%) | 219.00 (5.59%) | 1,534.00 (6.47%) | <0.001 |
| Diabetes at the time of TX, n (%) | 101.00 (25.00%) | 2,485.00 (23.25%) | 2,707.00 (25.88%) | 1,010.00 (25.97%) | 5,637.00 (24.11%) | <0.001 |
| BMI at the time of TX, mean (sd) | 29.27 (6.04) | 29.03 (5.80) | 29.15 (5.87) | 29.11 (5.84) | 28.93 (5.69) | 0.101 |
| Donor Characteristics | ||||||
| Age, mean (sd) | 34.69 (13.71) | 31.04 (11.66) | 34.61 (10.47) | 35.84 (13.12) | 35.95 (15.12) | <0.001 |
| Male , n (%) | 268.00 (65.85%) | 9,238.00 (85.36%) | 6,236.00 (59.36%) | 2,509.00 (64.07%) | 17,657.00 (74.46%) | <0.001 |
| Race, n (%) | ||||||
| White | 270.00 (66.34%) | 6,177.00 (57.08%) | 8,368.00 (79.66%) | 2,877.00 (73.47%) | 16,965.00 (71.54%) | <0.001 |
| African American | 47.00 (11.55%) | 2,715.00 (25.09%) | 945.00 (9.00%) | 358.00 (9.14%) | 2,390.00 (10.08%) | <0.001 |
| Hispanic | 59.00 (14.50%) | 1,734.00 (16.02%) | 1,011.00 (9.62%) | 505.00 (12.90%) | 3,694.00 (15.58%) | <0.001 |
| Asian | 28.00 (6.88%) | 88.00 (0.81%) | 86.00 (0.82%) | 105.00 (2.68%) | 417.00 (1.76%) | <0.001 |
| Other | 7.00 (1.72%) | 186.00 (1.72%) | 129.00 (1.23%) | 47.00 (1.20%) | 276.00 (1.16%) | <0.001 |
| Creatinine at the time of TX, mean (sd) | 2.36 (2.52) | 1.52 (1.37) | 2.02 (2.04) | 1.51 (1.52) | 1.23 (1.12) | <0.001 |
| Diabetes at the time of TX, n (%) | 19.00 (4.67%) | 254.00 (2.36%) | 548.00 (5.27%) | 275.00 (7.08%) | 1,101.00 (4.67%) | <0.001 |
| Hypertensive at the time of TX, n (%) | 49.00 (12.04%) | 1,033.00 (9.60%) | 2,012.00 (19.38%) | 621.00 (15.99%) | 3,351.00 (14.24%) | <0.001 |
| Donor after Cardiac Death, n (%) | 60.00 (14.74%) | 473.00 (4.37%) | 843.00 (8.02%) | 669.00 (17.08%) | 1,677.00 (7.07%) | <0.001 |
| Expanded Criteria Donor, n (%) | 31.00 (7.62%) | 348.00 (3.22%) | 404.00 (3.85%) | 298.00 (7.61%) | 2,343.00 (9.88%) | <0.001 |
| Transplant Characteristics | ||||||
| HLA mismatch level, mean (sd) | 4.62(1.08) | 4.68(1.07) | 4.62(1.10) | 4.63(1.12) | 4.61(1.08) | 0.018 |
| Cold Ischemic time (hrs), mean (sd) | 6.31(2.42) | 6.74(3.12) | 6.16(2.52) | 6.37(2.60) | 6.77(2.97) | <0.001 |
| Locally shared, n (%) | 270.00(66.34%) | 7202.00(66.55%) | 5882.00(55.99%) | 2452.00(62.61%) | 16019.00(67.55%) | <0.001 |
| Regionally shared, n (%) | 107.00(26.29%) | 2851.00(26.34%) | 3007.00(28.82%) | 6039.00(25.47%) | 107 (26.29%) | <0.001 |
| Nationally shared, n (%) | 30.00(7.37%) | 769.00(7.11%) | 1816.00(15.38%) | 385.00(9.83%) | 1655.00(6.98%) | <0.001 |
Graft Failure
Figure 1
Figure one demonstrates that the graft failure rate for kidney transplant patients did not show any statistically significant difference between the different mechanical causes of death (Drowned, Gunshot wound, Drug intoxication, Asphyxiation, and Blunt injury, p = 0.5).
[Figure 1: Kidney Graft failure KM Survival Curve]
Figure 2
We observed that the graft failure of patients who received a liver from a drowned donor was significantly higher than that of the patients from the other groups (Gunshot wound, Drug intoxication, Asphyxiation, and Blunt injury, p<0.001).
[Figure 2: Liver Graft failure KM Survival Curve]
Table 3 and 4 summarize the results of COX regressions for kidney and liver transplants respectively, showing risk factors correlated with graft failure adjusted for covariates.
Table 3
We used the same dataset of 100,031 kidney transplant recipients, as described above, no significant difference was seen between five groups in terms of different mechanical causes of donor death (Table 3). There were no statistically significant differences regarding graft failure rates between the five groups (P>1.25).
Patients who were Hispanic (HR=0.789, <0.001), Asian (HR=0.654, p=<0.001), or had a higher GFR rate (HR=0.9865, p=<0.001) reduced the risk of graft failure by 21.1% , 34.5% and 1.3% respectively. Patients who were male (HR=1.21, p<0.001), older (HR=1.016, p=0.002), retransplant patients (HR=1.095, p=0.042), having a higher BMI (HR=1.012, p<0.001), having diabetes (HR=1.464, p<0.001), receiving dialysis (HR=1.312, p=<0.001), having a higher CPRA (HR=1.002, p<0.001), having a higher HLA mismatch level (HR=1.043, p<0.001), having a higher kidney donor profile index (HR=2.143, p<0.001), and received organs with a longer cold ischemic time at the time of transplant (HR=1.004, p=0.021) increased the risk of graft failure by 21%, 1.6%, 9.5%, 1.2%, 46.4%, 31.2, 0.2%, 4.3%, and 114.3% respectively.
[Table 3: Kidney Graft failure Cox regression results]| Variable | HR | p-value | [95% | C.I.] |
| Male | 1.210 | <0.001 | 1.141 | 1.283 |
| Recipient Age | 1.016 | <0.001 | 1.013 | 1.018 |
| Hispanic recipient¹ | 0.789 | <0.001 | 0.715 | 0.871 |
| Asian recipient¹ | 0.654 | <0.001 | 0.569 | 0.752 |
| Total Days on the Waiting List (Including Inactive Time) | 1.000 | 0.010 | 1.000 | 1.000 |
| Retransplant recipient | 1.095 | 0.042 | 1.003 | 1.196 |
| BMI at the time of transplant | 1.012 | <0.001 | 1.006 | 1.017 |
| Diabetes at the time of transplant | 1.464 | <0.001 | 1.381 | 1.551 |
| Dialysis status | 1.312 | <0.001 | 1.234 | 1.396 |
| CPRA at the time of transplant | 1.003 | <0.001 | 1.002 | 1.004 |
| Glomerular filtration rate | 0.987 | <0.001 | 0.980 | 0.990 |
| HLA mismatch level | 1.043 | <0.001 | 1.024 | 1.062 |
| Kidney Donor Profile Index | 2.143 | <0.001 | 1.862 | 2.466 |
| Cold ischemic time | 1.004 | 0.021 | 1.001 | 1.007 |
| Donors died from | ||||
| gunshot injury² | 1.046 | 0.758 | 0.785 | 1.394 |
| drug intoxication² | 0.959 | 0.773 | 0.720 | 1.276 |
| asphyxiation² | 0.980 | 0.893 | 0.731 | 1.314 |
| blunt injury² | 0.995 | 0.974 | 0.750 | 1.321 |
1 The reference group is recipients who are white
2 The reference group is drowned donors
Table 4
The same dataset of 49,363 liver transplant recipients were used to examine liver graft failure rates given five patient groups. Once again, no significant difference was seen between five groups in terms of different mechanical causes of donor death (Table 4). Specifically, there were no statistically significant differences regarding graft failure rates between the five groups (p>1.05).
The results for liver donor transplants were similar. Being Asian (HR=0.769, p<0.001) and having a higher BMI (HR=0.996, p=0.006) reduced the risk of graft failure by 23.1% and 0.4% respectively. Being male (HR=1.056, p=0.003), older (HR=1.013, p<0.001), African American (HR=1.303, p<0.001), a retransplant patient (HR=1.713, p<0.001), having diabetes (HR=1.266, p<0.001) increased the risk of graft failure by 5.6%, 1.3%, 30.3%, 71.3%, and 26.6% respectively. Receiving a liver from a donor after cardiac death (HR=1.282, p<0.001), receiving a liver from an expanded criteria donor (HR=1.321, p<0.001), and receiving a liver with a longer cold ischemic time (HR=1.024, p<0.001) also increased the risk of graft failure by 28.2%, 32.1%, and 2.4% respectively.
[Table 4: Liver Graft failure Cox regression results]| Variable | HR | p-value | [95% | C.I.] |
| Male | 1.056 | 0.003 | 1.019 | 1.094 |
| Recipient Age | 1.013 | <0.001 | 1.011 | 1.015 |
| African American recipient¹ | 1.303 | <0.001 | 1.234 | 1.376 |
| Asian recipient¹ | 0.769 | <0.001 | 0.699 | 0.845 |
| Retransplant recipient | 1.713 | <0.001 | 1.615 | 1.817 |
| Diabetes at the time of TX | 1.266 | <0.001 | 1.219 | 1.315 |
| BMI at the time of TX | 0.996 | 0.006 | 0.993 | 0.999 |
| Donor after Cardiac Death | 1.282 | <0.001 | 1.202 | 1.368 |
| Expanded Criteria Donor | 1.321 | <0.001 | 1.243 | 1.405 |
| Cold ischemic time | 1.024 | <0.001 | 1.02 | 1.029 |
| Donors died from | ||||
| gunshot injury² | 0.999 | 0.991 | 0.831 | 1.201 |
| drug intoxication² | 0.894 | 0.236 | 0.742 | 1.077 |
| asphyxiation² | 0.963 | 0.697 | 0.795 | 1.166 |
| blunt injury² | 1.017 | 0.857 | 0.847 | 1.221 |
1 The reference group is recipients who are white
2 The reference group is drowned donors
Patient Mortality
Figure 3
We noted that there was a statistically significant difference in the patient mortality rates between the five groups. More specifically, patients who received a kidney from donors who died from drowning had a significantly higher patient mortality rate compared to those who received kidneys from donors who died from other causes of death.
[Figure 3: Kidney Patient mortality KM Survival curve]
Figure 4
The patient mortality rate of patients who received a liver from a drowned donor was significantly higher than that of the patients from the other groups between the different mechanical causes of death (Drowned, Gunshot wound, Drug intoxication, Asphyxiation, and Blunt injury, p = 0.2).
[Figure 4: Liver Patient mortality KM Survival curves]
Table 5 and 6 summarize the results of COX regressions for kidney and liver transplants respectively, showing risk factors correlated with patient mortality adjusted for covariates.
Table 5
Using the same dataset which has been previously mentioned, which consists of 100,031 kidney transplant recipients, no statistically significant difference in patient mortality was seen between the five different mechanical causes of donor death groups (Table 5, p>1.10).
For kidney transplants, being African American (HR=0.909, p=0.009), Hispanic (HR=0.770, p<0.001) or Asian(HR=0.558, p<0.001), and having a higher GFR (HR=0.984, p<0.001) reduced the risk of patient mortality by 9.1%, 23%, 44.2% and 1.6% respectively. Being male (HR=1.282, p<0.001), older (HR=1.016, p<0.001), a retransplant patient (HR=1.015, p<0.001), a diabetic patient (HR=1.768, p<0.001), on dialysis at the time of transplant (HR=1.421, p<0.001), having a higher BMI (HR=1.012, p<0.001), and having a higher CPRA (HR=1.003, p<0.001) increased the risk of patient mortality by 28.2%, 1.6%, 1.5%, 76.8%, 42.1%, 1.2%, and 0.3% respectively.
[Table 5: Kidney Patient Mortality Cox regression results]| Variable | HR | p-value | [95% | C.I.] |
| Male | 1.282 | <0.001 | 1.206 | 1.369 |
| Recipient Age | 1.016 | <0.001 | 1.013 | 1.018 |
| African American recipient¹ | 0.909 | 0.009 | 0.846 | 0.976 |
| Hispanic recipient¹ | 0.77 | <0.001 | 0.691 | 0.86 |
| Asian recipient¹ | 0.558 | <0.001 | 0.476 | 0.654 |
| Total Days on the Waiting List (Including Inactive Time) | 1 | <0.001 | 1 | 1 |
| Retransplant recipient | 1.015 | <0.001 | 1.009 | 1.022 |
| BMI at the time of transplant | 1.012 | <0.001 | 1.006 | 1.018 |
| Diabetic patient | 1.768 | <0.001 | 1.662 | 1.882 |
| Dialysis status | 1.421 | <0.001 | 1.329 | 1.52 |
| CPRA at the time of transplant | 1.003 | <0.001 | 1.002 | 1.004 |
| Glomerular filtration rate | 0.984 | <0.001 | 0.977 | 0.991 |
| Kidney Donor Profile Index | 1.876 | <0.001 | 1.644 | 2.141 |
| HLA mismatch level | 1.025 | 0.01 | 1.006 | 1.045 |
| Regionally shared organ² | 1.118 | 0.016 | 1.021 | 1.224 |
| Donors died from | ||||
| gunshot injury³ | 0.87 | 0.362 | 0.6442 | 1.174 |
| drug intoxication³ | 0.847 | 0.628 | 0.628 | 1.143 |
| asphyxiation³ | 0.82 | 0.206 | 0.628 | 1.143 |
| blunt injury³ | 0.822 | 0.193 | 0.612 | 1.104 |
1 The reference group is recipients who are white
2 The reference group is nationally shared organs
3 The reference group is drowned donors
Table 6
The dataset mentioned previously which 49,363 liver transplant recipients, and no significant difference regarding graft failure rates was seen between five different mechanical causes of donor death groups (Table 6, p>1.10).
The results for liver transplants were similar. Being Hispanic (HR= 0.887, p<0.001) or Asian (HR=0.703, p<0.001) reduced the risk of patient mortality by 11.3% 29.7% respectively. Being male (HR=1.077, p<0.001), older (HR=1.023, p<0.001), African American (HR=1.224, p<0.001), a retransplant patient (HR=1.676, p<0.001), and a diabetic patient (HR=1.302, p<0.001) increased the risk of patient mortality by 7.7%, 2.3%, 22.4%, 67.6% and 30.2% respectively. Receiving a liver from an expanded criteria donor (HR=1.262, p<0.001) and receiving a liver with a longer cold ischemic time (HR=1.017, p<0.001) also increased the risk of patient mortality by 26.2% and 1.7% respectively.
[Table 3: Liver Patient Mortality Cox regression results]| Variable | HR | p-value | [95% | C.I.] |
| Male | 1.077 | <0.001 | 1.039 | 1.118 |
| Recipient Age | 1.023 | <0.001 | 1.021 | 1.025 |
| African American recipient¹ | 1.224 | <0.001 | 1.156 | 1.297 |
| Hispanic recipient¹ | 0.887 | <0.001 | 0.8411 | 0.935 |
| Asian recipient¹ | 0.703 | <0.001 | 0.6362 | 0.7769 |
| Total Days on the Waiting List (Including Inactive Time) | 1 | 0.002 | 0.9999 | 1 |
| Retransplant recipient | 1.676 | <0.001 | 1.577 | 1.78 |
| Diabetes at the time of TX | 1.302 | <0.001 | 1.254 | 1.352 |
| Expanded Criteria Donor | 1.262 | <0.001 | 1.185 | 1.345 |
| Cold ischemic time | 1.017 | <0.001 | 1.012 | 1.022 |
| Donors died from | ||||
| gunshot injury² | 0.9869 | 0.893 | 0.8153 | 1.195 |
| drug intoxication² | 0.9439 | 0.558 | 0.7783 | 1.145 |
| asphyxiation² | 1 | 0.997 | 0.8203 | 1.22 |
| blunt injury² | 1.008 | 0.933 | 0.8344 | 1.218 |
1 The reference group is recipients who are white
2 The reference group is drowned donors
Conclusion
In conclusion, kidney and liver transplants using organs from drowned donors are associated with a higher risk of both graft failure and patient mortality. Kidney and liver transplants using organs from donors who died from asphyxiation appear to reduce the risk of both graft failure and patient mortality post transplant.
References
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