Single-kidney transplantation with discarded partner kidney vs. Dual kidney transplantation: results from a national cohort study

Abstract

Background

The transplantation of a single kidney, while its partner kidney is discarded despite both having been initially offered (dual-offered, single-transplanted; DOST), represents a missed opportunity to preserve nephron mass and optimize donor utilization. Dual kidney transplantation (DKT) preserves nephron mass by transplanting both kidneys from a higher-risk donor, but its benefits relative to DOST remain underexplored.

Methods

In this nationwide multicenter cohort (2008–2021), we analyzed 36 DKT and 20 DOST recipients. Both groups were propensity-matched 1:2 to 112 regular single-kidney transplant recipients (RegT) based on donor and recipient characteristics. The primary endpoint was estimated glomerular filtration rate (eGFR) at 12 months. Secondary endpoints included eGFR through 5 years, death-censored graft and patient survival, perioperative metrics, and 12-month quality of life (EQ-5D).

Results

At 12 months, median eGFR was higher in DKT (50.8 ml/min/1.73 m²) than DOST (33.5 ml/min/1.73 m²) or RegT (38.0 ml/min/1.73 m²; p < 0.001), with differences sustained through 5 years. Graft and patient survival were similar. DKT involved longer surgery (270 vs. 163 min; p < 0.001), greater blood loss (550 vs. 300 ml; p = 0.084), and more transfusions (75% vs. 30%; p = 0.0017) but no increase in delayed graft function or major complications. EQ-5D scores were higher in DKT (85.0) than DOST (70.0) and RegT (71.0; p = 0.048).

Conclusion

DKT is an effective approach for higher-risk donor kidneys and was associated with higher graft function and quality of life. Despite increased operative complexity and transfusion requirements, there was no evidence of increased postoperative morbidity. Broader adoption may reduce unnecessary kidney discards and improve transplant outcomes, although findings should be interpreted in light of the limited sample size and observational design.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-026-04945-7.

Introduction

Kidney transplantation is the preferred treatment option for end-stage kidney disease (ESKD), offering superior survival rates, better quality of life, and greater cost-effectiveness compared to long-term dialysis [1]. Despite its benefits, access to kidney transplantation remains constrained by a persistent shortage of donor organs. In Switzerland, approximately 350 kidney transplants are performed each year, yet around 1,450 patients remain on the waiting list [2].

As populations age and donor demographics shift, more organs are procured from older or medically complex donors. This trend has contributed to rising kidney discard rates. In Switzerland, the mean donor age increased from 51 years in 2008 to 57 years in 2019, during which time 20.8% of offered kidneys were discarded [3]. A similar pattern is seen in the United States, where the kidney discard rate increased from 5.1% in 1988 to 19.2% in 2015, largely due to changing donor characteristics [4]. Given these trends, finding the optimal balance between accepting higher-risk organs while ensuring recipient outcomes is becoming increasingly critical.

Dual kidney transplantation (DKT) offers a potential strategy to address this challenge by transplanting both kidneys from a higher-risk donor into a single recipient. This approach increases the total nephron mass, potentially compensating for suboptimal individual kidney quality. Since its first reports in 1996 [5], DKT has shown promising short- and long-term outcomes, including better allograft function and patient survival compared to single transplants from expanded criteria donors [6–10]. Despite its promise, DKT remains underutilized.

In Switzerland, deceased donor kidney allocation is centrally coordinated. Each kidney is offered to a recipient at one of the six national transplant centers based on the national waitlist ranking. Only if both kidneys are declined for single transplantation by all centers may they be considered for DKT. In practice, however, it is not uncommon for one kidney to be accepted while its paired organ – despite having similar characteristics – is declined and ultimately discarded. While some kidneys are discarded due to clear medical contraindications (e.g., hypoplastic kidney or procurement injury), others may represent missed opportunities where DKT could have been a viable option. This issue is not unique to Switzerland. In the United States, more than 7,600 cases of unilateral kidney discard were reported between 2000 and 2018, often attributed to procurement biopsy findings or recipient-matching challenges, rather than true medical unsuitability [11]. However, the impact of such missed opportunities on transplant outcomes remains largely unexplored.

Given the potential importance of nephron mass for allograft performance, we hypothesized that dual kidney transplantation would be associated with superior post-transplant kidney function compared with single transplantation in the setting of unilateral kidney discard. To address this question, we analyzed patient and allograft outcomes across three groups in a nationwide transplant cohort study: (1) DKT recipients; (2) recipients of a single kidney where the partner kidney was discarded without a clear medical justification; and (3) a matched cohort of standard deceased-donor transplant recipients. Our objective was to assess the impact of potentially avoidable nephron loss and evaluate whether broader utilization of DKT could represent an optimized kidney allocation strategy.

Materials and methods

Study design and patients

We conducted a nationwide, multicenter cohort study of all adult kidney transplant recipients in Switzerland from May 1, 2008, to December 31, 2021 (inclusion period). Patients were followed from the time of transplantation until death, graft loss, or last available follow-up, with follow-up data available until February 1, 2024. Recipient demographics and clinical data were obtained from the Swiss Transplant Cohort Study (STCS) [12], and donor characteristics from the Swiss Organ Allocating System (SOAS) [13]. Linkage between the two registries was achieved via unique recipient identifiers (RS-numbers). Ethical approval was granted by the medical ethics committees of all participating centers (BASEC No. EKOS 23/156), and all participants provided written informed consent.

Transplant recipients were stratified into three groups: dual kidney transplantation (DKT), dual-offered single transplant (DOST), and standard single-kidney transplant (RegT). We defined DOST as donor-recipient pairs in which one kidney was transplanted while the partner kidney was discarded for “non‑obvious” reasons. Kidneys discarded for “obvious” reasons – such as anatomical or mechanical compromise (e.g., kidney atrophy, aortic dissection with hypoperfusion, hydronephrosis, traumatic laceration, multiple or potentially malignant cysts, nephrolithiasis, or prior renal surgery) – were not considered DOST and were excluded from this group. The classification of discard reasons as “obvious” or “non-obvious” was performed retrospectively based on review of allocation records and clinical documentation by two investigators (DS and CK) prior to outcome analysis. This process was not based on a predefined standardized list and therefore relied on clinical judgment; discrepancies were resolved through consensus review. We further excluded those undergoing multi-organ or living-donor transplantation and pediatric en-bloc transplants.

Recipient variables were collected at baseline, with follow-up data at 12 months post-transplant, and annually thereafter. They included recipient characteristics such as age, sex, baseline BMI, history of previous kidney transplantation, previous dialysis mode and duration, serum creatinine, cold ischemia time (CIT), induction therapy, quality of life (QoL), and both patient and allograft survival. For DKT recipients, CIT was defined as the mean of the individual CITs of both kidneys, providing a single representative value at the recipient level and allowing comparability with single-kidney transplant recipients. Donor characteristics included age, sex, BMI, cause of death, history of diabetes, last creatinine level before procurement, hepatitis C antibody status, and donation type (DCD vs. DBD). Additional periprocedural parameters for DKT and DOST recipients (duration of surgery, estimated intraoperative blood loss, blood transfusions, delayed graft function [DGF; defined as at least one dialysis within the first 7 days after transplantation], length of hospital stay, and Clavien-Dindo classification) were retrieved from patient charts.

For each transplanted organ, the Kidney Donor Risk Index (KDRI) and Kidney Donor Profile Index (KDPI) were calculated according to the guide for calculating and interpreting KDPI [14], using the 2017 U.S. donor reference population. As donor ethnicity was not routinely collected and the vast majority of donors in Switzerland are Caucasian, all donors were classified as “non-Black” for these calculations. KDPI and KDRI were derived using the U.S. reference model and included to provide a standardized description of overall donor risk across groups, without being used for outcome analyses.

Endpoints and statistical analysis

The primary endpoint was kidney function 12 months post-transplant, assessed by the estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009 formula [15], a surrogate marker for long-term graft outcomes [16]. In a sensitivity analysis, eGFR was set to 0 ml/min/1.73 m² in cases of primary non-function, allograft loss, or patient death within the first year to account for potential survivorship bias.

Secondary endpoints included eGFR at 2, 3 and 5 years, cumulative allograft failure, patient death, and QoL at 12 months post-transplant. For DKT and DOST, further secondary outcomes comprised periprocedural parameters including duration of surgery, estimated intraoperative blood loss, necessity of blood transfusions, Clavien-Dindo score, DGF, and length of hospital stay.

To account for heterogeneity in donor and recipient characteristics between groups and to enable robust comparison with RegT, optimal propensity score matching was performed. DKT and DOST recipients were pooled into a single “expanded allocation” group for matching, as both represent non-standard transplant strategies involving higher-risk donor kidneys. Pooling was performed to facilitate matching to a comparable reference cohort and to improve covariate balance, given the limited sample size and the need to ensure sufficient overlap between groups. Matching was conducted in a 1:2 ratio using a logistic regression model to estimate propensity scores. Matching covariates included donor age, donor sex, donor BMI, donor history of diabetes, last donor eGFR before procurement, cerebrovascular cause of death (vs. other causes of death), donor type (DCD vs. DBD), as well as recipient age and recipient sex. We did not include donor hypertension as a covariate in the propensity score model because the overall reported prevalence of hypertension in the donor cohort was low and most likely underreported, given that the expected prevalence would be considerably higher in the Swiss donor age group [17]. Optimal matching was selected over nearest-neighbor matching to reduce covariate imbalance while retaining the full treated sample. Covariate balance was assessed using standardized mean differences (SMDs), with SMD < 0.15 considered acceptable and SMD < 0.10 indicative of good balance [18].

Allograft function at 12 months, at 2, 3 and 5 years, and QoL at 12 months, were compared across transplant groups using grouped violin plots and boxplots. Kaplan–Meier curves were used to compare death-censored allograft survival between each transplant group. Additionally, allograft failure over time was analyzed using the cumulative incidence function (CIF) with death as a competing risk. The Aalen-Johansen estimator was employed to nonparametrically estimate the CIF for each group, and Gray’s test was used to assess significant differences in CIF across the three groups [19]. Censoring was performed at the date of last-follow-up. QoL was assessed at baseline and 12 months by using the EuroQol (EQ-5D) questionnaire, a standardized instrument for self-reported health-related QoL [20].

Missing data were addressed by excluding patients from specific analyses if the required variables were unavailable in their records. A p-value < 0.05 was considered statistically significant. The analysis was conducted in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines [21].

Data were analyzed using R Studio version 4.3.1. Group comparisons were conducted using the Wilcoxon rank sum test or Kruskal–Wallis test for continuous variables, and either Pearson’s chi-square test or Fisher’s exact test for categorical variables, as appropriate. Continuous variables were summarized as median and interquartile range (IQR), while categorical variables were summarized as counts (n) and percentages (%). Matching was performed using the MatchIt package in R.

Results

Patient and transplantation characteristics

A total of 3,707 kidney transplant recipients were screened. After excluding 1,626 patients, 2,081 eligible recipients of kidneys from 1,280 deceased donors were included in the analysis. Of these, 36 underwent DKT and 20 met DOST criteria; both groups were propensity-matched 1:2 to 112 RegT recipients, yielding a final analysis population of 168 patients (Fig. 1).

Fig. 1.

Study flow chart. KT: kidney transplant. DKT, dual kidney transplantation; DOST, dual-offered, single transplanted; RegT, regular transplantation

Before matching, the expanded-allocation group (DKT + DOST) differed from potential RegT controls on multiple donor and recipient characteristics (Table S1). After optimal 1:2 matching, all variables included in the propensity score model met our prespecified balance criteria (standardized mean differences < 0.15), and every covariate except recipient age (SMD = 0.11) achieved the more stringent threshold of <0.10 (Table 1). Residual imbalances in variables not used for matching were modest, with the exception of donor hypertension (SMD = 0.40), which was not included in the propensity score model.

Table 1.

Donor and recipient baseline characteristics after propensity score matching. DKT, dual kidney transplantation; DOST, dual-offered, single transplanted; RegT, regular transplantation; SMD, standardized mean difference; BMI, body mass index; HD, hemodialysis; PD, peritoneal dialysis; ATG, anti-thymocyte globulin; CNI, calcineurin inhibitor. Continuous variables: median [IQR]; categorical variables: n (%)

Donors	Overall N = 168	DKT N = 36	DOST N = 20	RegT N = 112	SMD
Sex (female)	94 (56%)	23 (64%)	9 (45%)	62 (55%)	0.04
Age	74 (69, 79)	78 (72, 80)	73 (59, 77)	73 (68, 78)	0.07
BMI (kg/m2)	25.7 (23.6, 28.1)	25.9 (23.8, 27.8)	26.5 (23.7, 29.4)	25.6 (23.6, 27.9)	0.06
Diabetes mellitus	27 (16%)	5 (14%)	4 (20%)	18 (16%)	0
Hypertension	57 (34%)	20 (56%)	6 (30%)	31 (28%)	0.4
Cerebrovascular death	111 (66%)	26 (72%)	11 (55%)	74 (66%)	0
DCD	41 (24%)	6 (17%)	7 (35%)	28 (25%)	0.04
Last eGFR (ml/min/1.73 m2)	72 (59, 88)	79 (66, 87)	70 (49, 82)	70 (59, 88)	0.02
KDPI (%)	97 (93, 99)	98 (95, 100)	97 (89, 98)	96 (93, 99)	0.16
Recipients	Overall N = 168	DKT N = 36	DOST N = 20	RegT N = 112	SMD
Sex (female)	66 (39%)	11 (31%)	10 (50%)	45 (40%)	0.05
Age	65 (59, 69)	67 (58, 70)	64 (58, 69)	65 (60, 69)	0.11
BMI (kg/m2)	25.9 (23.1, 29.1)	25.7 (23.9, 28.7)	25.4 (22.9, 27.2)	26.0 (22.7, 29.5)	0.01
Dialysis mode					0.24
HD	127 (76%)	25 (69%)	16 (80%)	86 (77%)
None	11 (6.5%)	3 (8.3%)	3 (15%)	5 (4.5%)
PD	30 (18%)	8 (22%)	1 (5.0%)	21 (19%)
Dialysis time (years)	2.88 (1.68, 4.03)	2.65 (1.15, 3.43)	2.56 (1.19, 3.77)	3.12 (2.03, 4.20)	0.28
Retransplantation	18 (11%)	3 (8.3%)	2 (10%)	13 (12%)	0.09
Induction therapy					0.12
ATG	43 (26%)	7 (21%)	5 (25%)	31 (28%)
Basiliximab	122 (74%)	26 (79%)	15 (75%)	81 (72%)
Calcineurin inhibitor (Tacrolimus)	127 (79%)	33 (94%)	14 (70%)	80 (75%)	0.25
Cold ischemia (hours)	8.9 (7.2, 11.2)	10.7 (6.8, 12.0)	8.5 (6.6, 10.0)	8.9 (7.2, 11.2)	0.15

DKT donors were older than DOST donors (median 78 vs. 73 years), more often female (64% vs. 45%), had a higher rate of cerebrovascular death (72% vs. 55%), and were less frequently DCD donors (17% vs. 35%). Their last pre-procurement eGFR was higher (79 vs. 70 ml/min/1.73 m²), and reported hypertension prevalence was 56% in DKT donors and 30% in DOST donors. KDPI was uniformly high (98% vs. 97%).

DKT recipients were of similar age (median 67 vs. 64 years), more often male (69% vs. 50%), and experienced longer cold ischemia times (10.7 vs. 8.5 hours). Body mass index, dialysis modality and vintage, and induction therapy (predominantly basiliximab) were similar between groups, and maintenance immunosuppression was tacrolimus-based in most patients.

In the matched RegT cohort (n = 112), median age was 65 years, 60% were male, median BMI was 26.0 kg/m², and 77% received hemodialysis pre-transplant. Reported donor hypertension prevalence in the RegT group was 28%. RegT recipients had a longer dialysis vintage (3.12 vs. 2.65 and 2.56 years for RegT, DKT and DOST, respectively). All DKT procedures involved bilateral extraperitoneal placement via inguinal incisions. The median follow-up for all patients was 4.5 years (IQR 2.5–6.9).

Allograft function at 12 months

At one year post-transplant, median eGFR differed significantly across groups (p < 0.001). DKT recipients achieved the highest function at 50.8 ml/min/1.73 m² (IQR 44.5–57.0), compared with 38.0 (27.9–43.0) in RegT and 33.5 (28.3–50.9) in DOST recipients (Fig. 2).

Fig. 2.

Estimated glomerular filtration rate (eGFR) at 12 months post-transplant across transplant groups. Violin plots display the distribution of eGFR values (ml/min/1.73 m²) at 12 months for recipients of dual kidney transplants (DKT), dual-offered single transplants (DOST), and regular single kidney transplants (RegT). The embedded box plots show the interquartile range and median; whiskers indicate the range. Median eGFR values are annotated next to each group

To assess potential survivorship bias, a sensitivity analysis was performed in which eGFR was set to 0 ml/min/1.73 m² for cases of primary non-function, allograft loss, or patient death within the first year (Figure S1). Median eGFR at 12 months remained significantly different across transplant groups (p < 0.001), with the highest value observed in DKT recipients (52.5 ml/min/1.73 m² [IQR 36.9–61.5]), followed by DOST (35.9 ml/min/1.73 m² [IQR 30.3–53.6]) and RegT (35.5 ml/min/1.73 m² [IQR 24.2–45.0]).

The fraction of patient with chronic kidney disease stage 4T or higher (eGFR < 30 ml/min/1.73 m²) at 12 months was 16.7% for DKT, 25.0% with DOST, and 36.7% with RegT.

Mid-term allograft function

The eGFR advantage in DKT persisted through mid-term follow-up (all p < 0.001; Figure S2). At 2 years, median eGFR was 49.5 ml/min/1.73 m² (IQR 43.8–62.9) in DKT versus 36.3 ml/min/1.73 m² (IQR 29.7–46.0) in RegT and 33.3 ml/min/1.73 m² (IQR 27.9–49.4) in DOST. Similarly, at 3 years it was 49.3 ml/min/1.73 m² (IQR 42.1–59.2) vs. 30.8 ml/min/1.73 m² (IQR 25.4–41.1) and 31.9 ml/min/1.73 m² (IQR 22.7–43.8), and at 5 years 53.0 ml/min/1.73 m² (IQR 41.8–60.0) vs. 34.1 ml/min/1.73 m² (IQR 28.4–39.7) and 29.9 ml/min/1.73 m² (IQR 17.4–44.0), respectively.

Patient and allograft survival

Death-censored allograft survival did not differ significantly among DKT, RegT, and DOST (log-rank p = 0.15; Fig. 3A). The cumulative incidence of graft failure—with death as a competing risk—was lowest in DKT, though not statistically distinct (Gray’s test p = 0.14; Fig. 3B). Patient survival rates were also similar (Gray’s test p = 0.75; Fig. 3C).

Fig. 3.

Allograft and patient survival after kidney transplantation. (A) Kaplan–Meier curve showing death-censored allograft survival. (B) Cumulative incidence of allograft loss, accounting for death as a competing risk. (C) Cumulative incidence of patient death, accounting for graft failure as a competing risk. Blue line: dual kidney transplant (DKT); orange line: dual-offered single transplant (DOST); green line: regular transplant (RegT). Shaded: 95% confidence intervals. Lower table: number of patients at risk at the start of each 2-year interval

Within the first year, 9/168 (5.4%) patients experienced an allograft loss: 1/36 (2.8%) with DKT, none with DOST, and 8/112 with RegT (7.1%). The single DKT allograft loss was caused by a bilateral renal vein thrombosis. RegT allograft losses were attributed to immunological causes (n = 4), pyelonephritis (n = 1), renal artery complications (n = 1), and other causes (n = 2). No unilateral graft nephrectomies were recorded in DKT recipients.

Meanwhile, a total 8 deaths (4.8%) occurred within the first year; 2 (5.6%) with DKT, 1 (5%) with DOST, and 5 (4.5%) in the RegT group. Reasons for death included infection and coronary artery disease for DKT, infection for DOST, and coronary artery disease (n = 2), multiorgan failure (n = 1) and unknown (unobserved death, n = 2) for RegT, respectively.

Periprocedural parameters

Periprocedural parameters for DKT and DOST recipients are summarized in Fig. 4. Blood loss values were available for 51/56 (96.1%) and operative duration for 52/56 (92.9%); all other parameters had complete data. Compared with DOST recipients, those undergoing DKT had significantly longer durations of surgery (median 270 min [IQR 232–322] vs. 163 min, [IQR 141–186]; p < 0.001) and greater estimated intraoperative blood loss (median 550 ml, [IQR 350–738] vs. 300 ml, [IQR 200–500]; p = 0.084). They were also more likely to require blood transfusion (27/36 [75.0%] vs. 6/20 [30.0%]; p = 0.0017).

Fig. 4.

Perioperative parameters in dual kidney transplant (DKT) versus dual-offered single transplant (DOST) recipients. (A) Operation duration. (B) Intraoperative blood loss. (C) Blood transfusion. (D) Postoperative complications, categorized by Clavien–Dindo classification. (E) Incidence of delayed graft function (DGF). (F) Median length of hospital stay. Boxes and bars represent medians or percentages, with shading and error bars indicating interquartile range or category proportions, as appropriate

There were no significant differences between DKT and DOST recipients in terms of DGF (17/36 [47.2%] vs. 8/20 [40.0%]; p = 0.78), median length of hospital stay (13 days [IQR 10–18] vs. 13 days [IQR 10–22]; p = 0.95), or the proportion of patients experiencing a Clavien–Dindo grade ≥ IIIb complication (4/36 [11.1%] vs. 2/20 [10.0%]; p = 1). In the DKT group, grade ≥ IIIb complications included a re-laparotomy with partial colectomy for bowel perforation, a re-laparotomy for incisional hernia and mechanical ileus, one death due to NSTEMI and cardiogenic shock, and explantation of both kidneys due to graft thrombosis. In the DOST group, complications consisted of a re-operation with sublay mesh repair for burst abdomen, and evacuation of a hematoma due to bleeding from the inferior epigastric artery.

Quality of life

EQ-5D questionnaires at 12 months were completed by 52.8% of DKT, 55.0% of DOST, and 50.9% of RegT recipients. Among respondents, median QoL scores differed significantly across groups (p = 0.048), with the highest median observed in DKT recipients (85.0 [IQR 67.5–90.0]), followed by RegT (71.0 [IQR 55.5–84.0]) and DOST (70.0 [IQR 47.0–74.5]) (Figure S3). The proportion of patients with a functioning graft who completed the QoL questionnaire was not different between groups, with 57.6%, 57.9% and 59.4% for DKT, DOST and RegT, respectively. Baseline EQ-5D scores did not differ significantly between the groups (median DKT 65.0 [IQR 57.5–80.0], DOST 60.0 [IQR 48.0–73.5], RegT 70.0 [IQR 50.0–83.0]; p = 0.56).

Discussion

This study is examinates the clinical impact of missed DKT opportunities – cases in which one kidney is transplanted while its paired organ is discarded without clear medical justification (DOST). Our findings show that DKT recipients from higher-risk donors achieved significantly superior allograft function at 12 months compared with both DOST and propensity-matched single-kidney transplant recipients (RegT). Consistent with prior reports of significantly lower 12-month eGFR in DKT recipients who subsequently lost one of the transplanted kidneys [22, 23], our data reinforce the concept that cumulative nephron mass is a key determinant of allograft performance.

Twelve-month eGFR is a robust surrogate for long-term graft survival [16], which is reflected in the sustained eGFR advantage observed in the DKT group at 2, 3, and 5 years post-transplant in our study. Sustained higher eGFR has been associated with a reduced risk of CKD-related complications, including anemia, metabolic acidosis, and cardiovascular morbidity [24–26]. Although our sample size and follow-up precluded definitive survival differences, the observed trend toward lower graft failure in DKT supports the expectation that higher eGFR also translates into improved long-term outcomes.

DKT inherently involves greater surgical complexity: bilateral extraperitoneal implantation added a median 107 minutes and 250 ml of blood loss compared to single transplants, resulting in more transfusions – findings consistent with previous reports [22]. Crucially, however, this increased surgical burden did not translate into higher postoperative morbidity: rates of DGF, major complications, and length of hospital stay were comparable to those observed in DOST recipients. These safety data align with prior single-center studies reporting no net increase in surgical revisions or serious adverse events following DKT [9], suggesting that DKT can be performed safely in experienced centers. At the same time, DKT may involve specific anatomical considerations, as implantation of both kidneys could limit space for potential future retransplantation. In addition, the need for multiple vascular anastomoses may theoretically increase the risk of vascular complications. However, this was not reflected in higher rates of major postoperative complications in our cohort. In an older recipient population, improved graft function and potentially prolonged allograft survival may reduce the need for retransplantation, which is often challenging due to sensitization and limited donor availability.

Beyond functional metrics, DKT recipients also reported higher health‑related quality of life (QoL) at 12 months. However, these findings should be interpreted with caution given the limited number of available QoL assessments. While the precise mechanisms underlying a possible improvement remain unknown, the higher eGFR achieved with DKT may be associated with a reduced medication burden, a key determinant of post-transplant well-being [27]. Superior renal clearance might also preserve cognitive function and mitigate uremic symptoms, thereby supporting mental and physical health [28]. Given that QoL reflects intertwined physical, psychological, and social dimensions, these combined benefits may contribute to the observed advantage in the DKT cohort. This finding is particularly relevant for older recipients, who are especially susceptible to treatment-related burdens.

Unilateral kidney discards are often justified by marginal histology or recipient-matching challenges rather than true organ unsuitability. In a UNOS analysis of 7,625 unilateral discards, procurement biopsy accounted for 22% of cases, followed by the lack of a suitable recipient in 13% [11]. However, given the shared donor characteristics of paired kidneys, reliance on biopsy alone is debatable, especially as the predictive value of procurement histology for long‑term outcomes remains uncertain [29–31]. In our cohort, DOST and RegT recipients had comparable outcomes in terms of 12-month eGFR, graft survival, and quality of life, suggesting that discarding the paired kidneys may not have been clinically warranted. Supporting this, other studies have reported that discarded kidneys often show quality metrics similar to those of transplanted grafts, with 1-year death-censored graft survival exceeding 90%, regardless of biopsy findings [32]. These observations indicate that factors beyond intrinsic organ quality often influence discard decisions.

While fast‑track allocation programs have been proposed to direct higher-risk kidneys to high‑acceptance centers [11], they do not consistently prevent unilateral discards when a partner graft remains unassigned. In contrast, DKT ensures use of both kidneys and preserves nephron mass. Although we did not assess whether the discarded kidneys in our DOST group were suitable for single transplantation into other recipients, our findings support DKT as a pragmatic rescue strategy for organs at risk of discard. Adopting DKT in such cases could improve individual outcomes, reduce unnecessary organ loss, and enhance utilization of the donor pool.

The strengths of our study lie in its multicenter design, the completeness of registry data, extended follow-up, and the inclusion of both objective outcomes and patient-reported QoL. However, several limitations must be acknowledged. The numbers of DKT and DOST included were small, limiting statistical power. Because DKT and DOST were not directly matched to each other, comparisons between these groups should be interpreted cautiously and may be influenced by residual confounding inherent to the observational study design. Additionally, classification of discard reasons into “obvious” and “non-obvious” categories was performed retrospectively and was not based on predefined standardized criteria, but rather on review of allocation records and clinical documentation. Although independent assessment and consensus procedures were used to enhance consistency, this approach involves clinical judgment and may be subject to misclassification bias. Furthermore, there was residual imbalance in the prevalence of reported donor hypertension, which was not included in matching due to suspected underreporting and was highest in DKT donors. While some bias from this cannot be excluded, any such effect would have disadvantaged the DKT group. Additionally, data on postoperative complications related to the additional surgery in DKT are not routinely collected in the STCS and were retrospectively collected for DKT and DOST cases only.

Cost-effectiveness was not assessed in this study. Given the increased procedural complexity of DKT, future studies should evaluate whether improved graft function and potential long-term benefits offset higher upfront costs.

In conclusion, our findings support the broader use of DKT for higher-risk donor kidneys – particularly in cases where the paired organ would otherwise be discarded without clear justification. By preserving nephron mass, DKT is associated with improved allograft function and likely better QoL, without evidence of increasing perioperative risk. This strategy holds promise for reducing organ waste in particular in the extended donor pool and enhancing outcomes in kidney transplantation.

Electronic supplementary material

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Abbreviations

BMI

Body Mass Index

CIF

Cumulative Incidence Function

CKD

Chronic Kidney Disease

CKD-EPI

Chronic Kidney Disease Epidemiology Collaboration

CIT

Cold Ischemia Time

DBD

Donation after Brain Death

DCD

Donation after Circulatory Death

DGF

Delayed Graft Function

DKT

Dual Kidney Transplantation

DOST

Dual-Offered Single Transplant

eGFR

Estimated Glomerular Filtration Rate

EQ-5D

EuroQol Five-Dimension Questionnaire

ESKD

End-Stage Kidney Disease

KDPI

Kidney Donor Profile Index

KDRI

Kidney Donor Risk Index

QoL

Quality of Life

RegT

Standard Single-Kidney Transplant

SMD

Standardized Mean Difference

SOAS

Swiss Organ Allocating System

STCS

Swiss Transplant Cohort Study

UNOS

United Network for Organ Sharing

Author contributions

Si.S., D.S., and C.K. contributed to the conception and design of the study. D.G., F.H., F.I., T.S., St.S., D.S., and C.K. provided cohort patient data. S.N., Si.S., and C.K. drafted the initial version of the manuscript, which was subsequently revised based on feedback from all authors. All authors critically reviewed the article, approved the final version, and agreed to its publication.

Funding

None.

Data availability

The Swiss Transplant Cohort Study (STCS) and Swiss Organ Allocating System (SOAS) data that support the findings of this study are not publicly available due to national data protection regulations and cohort governance policies. Access to these data requires approval by the STCS Scientific Committee and the responsible ethics authorities. Data can be made available upon reasonable request and with permission of the STCS (www.stcs.ch) and Swisstransplant.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and all applicable national regulations. The Swiss Transplant Cohort Study (STCS) received ethical approval from the regional ethics committees of all participating transplant centers (lead committee: Ethikkommission Ostschweiz, BASEC No. EKOS 23/156), which cover nationwide data collection and follow-up of all Swiss transplant recipients. All participants provided written informed consent at enrollment in the STCS, permitting the use of their clinical data for research purposes.

Competing interests

The authors declare no competing interests.

Consortium Members

Members of the Swiss Transplant Cohort Study: Patrizia Amico⁹, Adrian Bachofner⁴, Vanessa Banz¹², Sonja Beckmann¹³, Guido Beldi¹², Christoph Berger¹⁴, Ekaterine Berishvili¹⁵, Annalisa Berzigotti¹², Pierre-Yves Bochud¹⁶, Petra Borner¹⁷, Sanda Branca¹⁸, Anne Cairoli¹⁹, Emmanuelle Catana²⁰, Yves Chalandon²¹, Philippe Compagnon²², Sabina De Geest¹³, Sophie De Seigneux⁶, Michael Dickenmann⁹, Joëlle Lynn Dreifuss²³, Thomas Fehr⁷, Sylvie Ferrari-Lacraz²⁴, Andreas Flammer²⁵, Jaromil Frossard¹⁸, Nicolas Goossens²⁶, Jörg Halter⁸, Christoph Hess²⁷, Sven Hillinger²⁸, Hans Hirsch²⁹, Patricia Hirt⁸, Linard Hoessly¹⁸, Uyen Huynh-Do¹¹, Nina Khanna³⁰, Michael Koller¹⁸, Angela Koutsokera³¹, Andreas E. Kremer³², Thorsten Krueger³³, Arnaud L’Huillier³⁴, Bettina Laesser³⁵, Frédéric Lamoth³⁶, Roger Lehmann³⁷, Alexander Leichtle³⁸, Oriol Manuel³⁶, Hans-Peter Marti³⁹, Michele Martinelli⁴⁰, Valérie McLin⁴¹, Katell Mellac¹⁸, Aurélia Merçay⁴², Karin Mettler⁴³, Sara Christina Meyer⁴⁴, Zou Ming¹⁸, Nicolas Müller⁴⁵, Jelena Müller¹⁸, Ulrike Müller-Arndt⁸, Mirjam Nägeli⁴⁶, Dionysios Neofytos⁴⁷, Jakob Nilsson⁴⁸, Manuel Pascua¹⁵, Rosmarie Pazeller⁴³, David Reineke⁴⁹, Juliane Rick¹⁸, Fabian Rössler⁵⁰, Silvia Rothlin⁵¹, Dominik Schneidawind⁴, Macé Schuurmans⁵², Thierry Sengstag⁵³, Federico Simonetta⁵⁴, Jürg Steiger⁹, Guido Stirnimann¹², Christian Van Delden⁴⁷, Jean-Pierre Venetz⁵, Jean Villard⁵⁵, Julien Vionnet⁵, Laura Walti⁵⁶, Caroline Wehmeier⁹, Patrick Yerly⁵⁷

¹²Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland

¹³Department Public Health, Institute of Nursing Science, University of Basel, Basel, Switzerland

¹⁴Translational Immunology, Department of Biomedicine, University of Basel, Basel, Switzerland; Interdisciplinary Center for Immunology, Departments of Dermatology, Internal Medicine, and Rheumatology, University Hospital Basel, Basel, Switzerland

¹⁵Laboratory of Tissue Engineering and Organ Regeneration, Department of Surgery, University of Geneva, Geneva, Switzerland

¹⁶Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland

¹⁷Finanz- und Rechnungswesen, University Hospital Basel, Basel, Switzerland

¹⁸Swiss Transplant Cohort Study, Data Center, University Hospital Basel, Basel, Switzerland

¹⁹Service of Haematology, Department of Oncology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland

²⁰Swiss Transplant Cohort Study, Data Center, Lausanne University Hospital, Lausanne, Switzerland

²¹Hôpitaux Universitaires de Genève and Faculty of Medicine, University of Geneva, Geneva, Switzerland

²²Department of Surgery, Divisions of Abdominal and Transplant surgery, Geneva University Hospitals, Geneva, Switzerland

²³Swiss Transplant Cohort Study, Data Center, University Hospital Zurich, Zurich, Switzerland

²⁴Transplant Immunology Unit, Geneva University Hospitals, Geneva, Switzerland

²⁵University Heart Center, University Hospital of Zurich, Switzerland; Center for Translational and Experimental Cardiology, Schlieren, Switzerland; University of Zurich, Zurich, Switzerland

²⁶Division of Gastroenterology and Hepatology, Geneva University Hospital, Geneva, Switzerland

²⁷Department of Biomedicine, Immunobiology, University of Basel and University Hospital of Basel, Basel, Switzerland

²⁸Department of Pathology, University Hospital Zurich, Zurich, Switzerland

²⁹Transplantation & Clinical Virology, Department of Biomedicine, University of Basel, Basel Switzerland

³⁰Division of Infectious Diseases, University Hospital Basel, University of Basel, Basel, Switzerland

³¹Department of Respiratory Medicine, University Hospital of Lausanne, Lausanne, Switzerland

³²Department of Gastroenterology and Hepatology, University Hospital Zürich, University of Zürich, Zürich, Switzerland

³³Department of Thoracic Surgery, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland

³⁴Unit of Immunology and Vaccinology, Division of General Pediatrics, Department of Pediatrics, Gynecology and Obstetrics, University of Geneva, Geneva, Switzerland

³⁵Swiss Transplant Cohort Study, Data Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

³⁶Infectious Diseases Service, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland

³⁷Department of Endocrinology, Diabetes and Clinical Nutrition, University Hospital Zurich, Zurich, Switzerland

³⁸Insel Data Science Center (IDSC), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

³⁹Department of Clinical Medicine, University of Bergen, 5020 Bergen, Norway

⁴⁰Centre for Advanced Heart Failure, Department of Cardiology, Inselspital, Bern University Hospital, Bern, Switzerland

⁴¹Faculty of Medicine, Department of Pediatrics, Gynecology and Obstetrics, University Hospitals Geneva, Geneva, Switzerland

⁴²Swiss Transplant Cohort Study, Data Center, Geneva University Hospitals, Geneva, Switzerland

⁴³Swiss Transplant Cohort Study, Patient Advisory Board

⁴⁴Department of Hematology and Central Hematology Laboratory, Inselspital, Bern University Hospital, Bern, Switzerland

⁴⁵Division of Infectious Diseases and Hospital Epidemiology, Zurich University Hospital, Zurich, Switzerland

⁴⁶Department of Dermatology, University Hospital Zurich, Zurich, Switzerland

⁴⁷Transplant Infectious Diseases Unit, Service of Infectious Diseases, University Hospitals Geneva, University of Geneva, Geneva, Switzerland

⁴⁸Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland

⁴⁹Department of Cardiac Surgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

⁵⁰Department of Surgery and Transplantation, University Hospital Zurich, Zürich, Switzerland

⁵¹Swiss Transplant Cohort Study, Data Center, HOCH Cantonal Hospital St.Gallen, St. Gallen, Switzerland

⁵²Division of Pulmonology, University Hospital Zurich, and the Faculty of Medicine, University of Zurich, Zurich, Switzerland

⁵³SIB Swiss Institute of Bioinformatics and SciCORE Computing Center, University of Basel, Basel, Switzerland

⁵⁴Hematology Service, Department of Oncology, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland

⁵⁵Transplantation Immunology Unit and National Reference Laboratory for Histocompatibility, Department of Diagnostic, Geneva University Hospitals, Geneva, Switzerland

⁵⁶Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

⁵⁷Cardiovascular Department, Lausanne University Hospital (CHUV), Switzerland