Begin typing your search above and press return to search.
Volume: 23 Issue: 9 September 2025

FULL TEXT

ARTICLE
Identifying Causes and Risk Factors of 7-Day Graft Loss in Kidney Transplantation: A UNOS-Based Analysis

Objectives: Despite advancements in organ procurement, immunosuppression, and infection prophylaxis, early graft loss remains a challenge in kidney transplantation. We aimed to identify key recipient-, donor-, and transplant-related factors associated with 7-day graft loss.
Materials and Methods: We conducted a retrospective analysis (January 1, 2015-June 30, 2024) by using the United Network for Organ Sharing database to compare kidney recipients who experienced 7-day graft loss with those with graft survival of >1 year.
Results: Among 136 815 kidney transplant recipients from living and deceased donors, 1046 (0.76%) had 7-day graft loss. Causes of overall and deceased donor 7-day graft loss included primary nonfunction, graft thrombosis, and rejection. Causes of 7-day graft loss for living donor recipients included primary nonfunction, rejection, technical complications, and recurrent disease. Significant predictors of deceased donor 7-day graft loss included recipient body mass index (odds ratio 1.034, P < .001), hypertension (odds ratio 1.285, P = .001), donation after circulatory death (odds ratio 1.349, P < .001), kidney donor profile index (OR 15.402, P < .001), cold ischemia time (odds ratio 1.014, P = .002), and modern transplant era (years 2020-2024) (odds ratio 1.679, P < .001). Predictors of living donor 7-day graft loss included focal segmental glomerulosclerosis (odds ratio 2.481, P = .018), donor age (odds ratio 1.027, P = .015), modern era (odds ratio 1.811, P = .033), and antithymocyte globulin and interleukin 2 induction (odds ratio 3.697, P = .015). Risk factors for deceased donor 7-day mortality included type 2 diabetes mellitus (odds ratio 2.396, P = .031) and primary nonfunction (odds ratio 12.868, P = .013).
Conclusions: Seven-day graft loss is associated with identifiable causes and risk factors. This underscores the importance of recipient management and donor selection.


Key words : Graft survival, Living donors, Mortality, Patient survival, Renal function, Renal transplantation, Risk factors

Introduction
Kidney transplantation remains the gold standard for the management of patients with end-stage renal disease. Compared with dialysis, kidney transplant is more cost effective and has resulted in improved survival and quality of life.1 These outcomes have improved through innovations in immunosup-pressive therapy; refined HLA testing, infection prophylaxis, and treatment; and long-term mana-gement of adverse effects.2,3 Beyond financial costs, early graft loss (EGL) is associated with increased sensitization, lower quality of life and adverse psychosocial outcomes.4 Whereas long-term graft loss is driven by rejection, cardiac events, and infections, 90-day graft loss (a metric monitored by the United Network for Organ Sharing [UNOS]) is typically driven by other factors.5 Common causes of EGL are primary nonfunction (PNF), ischemia, infection, and thrombosis.6 To date, limited data exist on graft loss and mortality within the first 7 days after transplant from either living donors (LD) or deceased donors (DD). Here, we aimed to identify the etiologies and risk factors associated with 7-day graft loss (7DGL) and mortality following LD or DD transplant.

Materials and Methods
We received an exemption determination from the Institutional Review Board as the analysis of secon-dary data was without individual identifiers (IRB 1815894-2).

Data sources
We used data from the UNOS database from January 1, 2015, through June 30, 2024, to analyze LD or DD recipients who experienced graft loss or death within 7 days versus those who survived over 1 year. For recipient characteristics, we analyzed age, sex, race, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), time on wait list, retransplant status, dialysis status, primary diagnosis at the time of listing, glomerular filtration rate (GFR) at time of transplant, calculated panel reactive antibody (cPRA), and estimated posttransplant survival score (EPTS). For donor characteristics, we analyzed age, sex, race, BMI, history of diabetes mellitus (DM) and hypertension, creatinine level at donation, and kidney donor profile index (KDPI). Additional transplant characteristics were modern transplant era (2020-2024), HLA mismatch level, graft sharing status (local, regional, national), warm ischemia time (WIT), and cold ischemia time (CIT). We also analyzed induction medications such as antithymocyte globulin (ATG), alemtuzumab, interleukin 2 (IL-2), and a combination of ATG+IL-2. Primary causes of graft loss were clas-sified into PNF, graft thrombosis, rejection, infection, technical complication, and recurrent disease.

Statistical analyses
We compared recipient, donor, and transplant characteristics; induction therapy (ATG, alemtuzumab, IL-2 [BSX/daclizumab] or a combination of ATG+IL-2); diagnosis at listing; and primary causes of graft loss in the 2 aforementioned groups (graft loss or death within 7 days versus those who survived over 1 year). We used t tests or Mann-Whitney U test, as appropriate, to compare continuous variables. We assessed categorical variables with the Pearson χ2 or Fisher exact test. We performed multivariable logistic regression to identify the factors independently associated with 7DGL and mortality, adjusting for covariates. We presented results as mean (SD) or numbers (percentages). We calculated odds ratio (OR) and 95% CI. Type I error level was set at 0.05.

Results
Primary causes of graft failure
We found 1046 cases of 7DGL in 136 815 transplant recipients (0.76%). The most common cause of 7DGL was PNF (91.59%, Table 1). In addition, PNF was the most common cause of 7DGL in both DD (93.03%) and LD (66.07%) (Table 2). For the 7DGL group versus group with graft survival of >1 year, graft thrombosis was the second most common cause of 7DGL (2.49% vs 0.02%; P < .001) (Table 1). In both the DD and LD groups, graft thrombosis was also the second most common cause of 7DGL (2.12% vs 0.02% [P < .001] and 8.93% vs 0.01% [P < .001], for 7DGL vs graft survival of >1 y, respectively) (Table 2). Rejection was more common in overall transplant recipients with graft survival of >1 year (1.06% vs 0.38%; P = .033). Rejection was the third most common cause of 7DGL in patients with transplants from DD (OR 1.333 [95% CI, 1.110-1.600]; P = .002) (Table 3). Recurrent disease and technical complications were the fourth and fifth most common causes of LD 7DGL (1.79% vs 0.02% [P = .014] and 3.57% vs 0.51% [P = .034], for 7DGL vs graft survival of >1 y) (Table 2).

Recipient mortality
Of 136 979 patients, 30 (0.02%) died within 7 days of transplant. Among recipients with DM, 40% of DD cases had 7DGL 7-day mortality versus 24.2% of LD cases (P = .047) (Table 4). This trend was more notable in DD recipients (OR 2.396 [95% CI, 1.084-5.297]; P = .031) (Table 5). Nationally shared grafts from DD also substantially increased the odds of 7-day mortality (OR 4.334 [95% CI, 1.813-10.360]; P = .001) (Table 5). In contrast, locally shared grafts were associated with patient survival 1 year posttransplant (71.79% vs 53.33%; P = .025) (Table 4).

Recipient characteristics and graft loss
Recipients with 7DGL were more likely than recipients who survived >1 year to be aged ≥60 years (48.37% vs 34.76%; P < .001) (Table 1). This trend was also observed among DD recipients (49.49% vs 36.43%; P < .001). Among DD recipients, being African American increased the odds of 7DGL (OR 1.395 [95% CI, 1.220-1.596]; P < .001) (Table 3). Male sex was associated with 7DGL compared with those who survived >1 year (64.44% vs 60.63%; P = .012). Male sex also increased the odds of 7DGL in DD recipients (OR 1.167 [95% CI, 1.019-1.336]; P = .025) (Table 3). Higher BMI at transplant was associated with 7DGL (29.84 ± 5.64 vs 28.57 ± 5.49; P < .001), with similar results in DD and LD recipients (Table 2). Among DD recipients, higher BMI at transplant significantly increased the odds of 7DGL (OR 1.034 [95% CI, 1.022-1.047]; P < .001) (Table 3). Longer wait time in general (555 days [interquartile range (IQR) of 1248 days] vs 420 days [IQR of 987 days]; P < .001) correlated with 7DGL (Table 1). Those with 7DGL were more likely than recipients who survived >1 year to be on dialysis at the time of registration (89.39% vs 76.66%; P < .001) (Table 1). For DD recipients, dialysis at the time of registration increased the odds of 7DGL (OR 1.522 [95% CI, 1.220-1.899]; P < .001) (Table 3). Patients with 7DGL versus patients who survived >1 year had higher EPTS (0.59 ± 0.29 vs 0.45 ± 0.30; P < .001) (Table 1). Recipients with 7DGL versus patients who survived >1 year were more likely to have type 2 DM as a cause of end-stage renal disease than polycystic kidney disease (32.03% vs 24.36% [P < .001] and 5.26% vs 8.54% [P < .001], respectively), with similar results in DD recipients (32.83% vs 26.42% [P < .001] and 4.75% vs 5.98% [P < .001], respectively) (Table 2). In contrast, focal segmental glomerulosclerosis (FSGS) as a primary diagnosis significantly increased the odds of 7DGL in LD recipients (OR 2.481 [95% CI, 1.165-5.281]; P = .018) (Table 6).

Donor characteristics and graft loss
Donor age ≥60 years (15.30% vs 9.22%; P < .001) and donor age 40 to 59 years (59.85% vs 43.87%; P < .001) was associated with 7DGL versus graft survival of >1 year (Table 1). For DD, a similar trend was observed with donors age ≥60 years (14.85% vs 7.90%; P < .001) and donor age 40 to 59 years (60.40% vs 41.72%, P < .001) at the time of death (Table 2). Donor age in LD was positively associated with 7DGL (OR 1.027 [95% CI, 1.005-1.050]; P = .015) (Table 6). Donation after circulatory death (DCD) significantly increased the odds of 7DGL (OR 1.349 [95% CI, 1.178-1.546; P < .001) (Table 6). Other notable risk factors for overall 7DGL were higher BMI and history of hypertension and DM (Table 1). Among DD, KDPI score (OR 15.402 [95% CI, 11.124-21.326]; P < .001) and history of hypertension (OR 1.285 [95% CI, 1.105-1.496]; P = .001) were associated with higher odds of 7DGL (Table 3). Among DD, 7DGL was associated with Asian donors (3.94% vs 2.47%; P = .003) (Table 2). Left kidney transplants did not increase the odds of 7DGL for either DD (OR 1.333 [95% CI, 0.939-1.214]; P = .320) or LD (OR 0.642 [95% CI, 0.312-1.319]; P = .227) (Table 3 and Table 6).

Transplant characteristics
In our comparisons of 7DGL versus graft survival >1 year groups, we noted 7DGL was associated with transplants performed during the modern era (2020-2024) (63.79% vs 45.57%; P < .001) (Table 1). Transplants from the modern era increased the odds of 7DGL in both DD (OR 1.679 [95% CI, 1.464-1.926]; P < .001) and LD (OR 1.811 [95% CI, 1.050-3.124], P = .033) (Table 3 and Table 6). Both HLA higher mismatch levels (4.33 ± 1.35 vs 4.01 ± 1.52; P < .001) and higher CIT (19.95 ± 9.24 vs 14.13 ± 10.23 h; P < .001) were associated with 7DGL (Table 1). Higher HLA mismatch levels increased the odds of 7DGL for DD (OR 1.056 [1.007-1.108]; P = .026) (Table 3). Among DD, each additional hour of CIT was associated with a 1.4% increase in the odds of 7DGL (OR 1.014 [95% CI, 1.005-1.022]; P = .002) (Table 3). Grafts contributing to 7DGL were less likely than grafts with survival for >1 year to be locally shared and more likely to be nationally and regionally shared (Table 1). Locally shared grafts decreased the odds of 7DGL in the DD group (OR 0.786 [95% CI, 0.683-0.905]; P = .001) (Table 3).

Induction methods
In our comparisons of 7DGL versus graft survival >1 year groups, use of ATG and combination induction (ATG + IL-2) were associated with 7DGL (68.36% vs 64.20% [P = .005] and 3.82% vs 2.67% [P = .021]) (Table 1). Combination induction significantly increased the odds of 7DGL in the LD group (OR 3.697 [95% CI, 1.291-10.592]; P = .015) (Table 6). In contrast, use of IL-2 and use of alemtuzumab induction were associated with graft survival for >1 year (17.58% vs 15.11% [P = .036] and 15.56% vs 12.72% [P = .012]) (Table 1).

Discussion
Despite extensive investigations of 90-day graft loss, a direct analysis of causes and risk factors of graft loss and mortality within 7 days remains limited. Graft loss within 7 days was significant, with overall 7DGL observed in 1046 of 136 815 recipients (0.76%): 990 of 97 969 (1.01%) in DD and 56 of 38 846 (0.14%) in LD; graft loss within 7 days can be physically and emotionally devastating. Specifically, 7DGL recipients are exposed to postoperative medical complications and consequences, including sensitization to HLA, less successful retransplant, and inferior recipient survival.7

Primary nonfunction
Primary nonfunction is defined as irreversible graft failure, including graft-related death, within 7 days posttransplant.8 In our cohort, PNF was a major cause of 7DGL, accounting for 91.59% of all cases, 66.07% among LD and 93.03% among DD recipients (P = .001). Prior investigations identified higher KDPI and prolonged CIT as strong independent predictors of PNF.9 Our data supported these associations, as both KDPI and CIT were significantly associated with 7DGL. Within the DD cohort, KDPI was a profound predictor of 7DGL, with recipients experiencing over 15-fold increased odds (OR 15.402; 95% CI, 11.124-21.326; P < .001). These results reinforce that PNF is largely a manifestation of donor-related factors rather than recipient-specific characteristics.10 Given the devastating consequences of PNF, patients should be counseled on the higher risk associated with accepting a high KDPI kidney, framed within the context of organ shortage, where the benefits of timely transplant may still outweigh the risks of prolonged wait times.

Graft thrombosis
The pathogenesis of renal graft thrombosis is multifactorial, involving donor-related, recipient-specific, and technical factors. Although graft salvage may be possible with prompt thrombectomy (ideally within 15-20 h of symptom onset), most cases result in irreversible graft loss.11 Multiple investigations suggested the promising effects of aspirin and the combined use of aspirin and anticoagulants on reducing the risk of graft thrombosis. However, the risk of bleeding complications has been shown to be increased.12 Consistent with prior reports, our analysis identified graft thrombosis as one of the leading causes of graft failure in LD, DD, and the overall transplant cohort.

Recurrence
Recurrent disease emerged as one of the significant causes of 7DGL in the LD cohort, occurring in 3.57% of cases (P = .034). Unsurprisingly, recurrent disease was not a significant contributor within the overall and DD cohorts. Compared with DD, LD is associated with a higher risk of recurrent primary glomerulonephritis, particularly FSGS. Although living-related transplant offers the advantage of improved HLA matching, concern is growing regarding a higher risk of recurrence, especially primary glomerulonephritis.13,14 Although others have documented the association between LD and DD and FSGS recurrence posttransplant, our data unveiled a novel and important link between LD 7DGL and FSGS recurrence.

Rejection
Rejection was significant across the overall cohort and within DD 7DGL, occurring in 0.38% (P = .033) and 0.40% (P = .022) of cases. We had no cases of 7DGL from rejection among LD. Our regression analysis demonstrated a similar pattern, showing a 33.3% increased odds of DD 7DGL (OR 1.333 [95% CI, 1.110-1.600]; P = .002). Previously, others reported a higher incidence of acute rejection within the first few weeks posttransplant, with factors including HLA mismatches, positive crossmatch, and history of blood transfusions.15 Clinical rejection within the first year was more common, occurring in 10% to 15% of recipients.16 Given this timeline, the 7-day posttransplant period may be too early to capture the full immunologic burden of alloimmune-mediated injury. Nonetheless, our analysis demonstrated that rejection within the first week posttransplant was one of the significant causes of EGL, warranting close monitoring and further investigation to mitigate the effects of early rejection on graft loss.

Technical complications
Advancements in surgical technique and immuno-suppressive regimens have markedly reduced both the incidence and severity of technical complications. However, albeit infrequent, these complications still occur, resulting in a detrimental effect on post-transplant outcomes. These events are typically detected in the early postoperative period, although some may present later. Complications include arterial and venous thromboses, renal artery stenosis, vascular anastomotic hemorrhage, and urethral and scrotal complications. In our analysis, technical complication was only significant within the LD 7DGL group (1.79%; P = .014). We surmise that LD transplants yield fewer ischemic injuries compared with DD, overshadowing the statistical effect of technical errors.

Recipient mortality
Mortality within 7 days was extremely rare, occurring in only 0.02% of recipients. It is difficult to discern whether PNF precipitated death or if death occurred through another mechanism that resulted in PNF. This ambiguity suggested shared unmeasured risk factors with early posttransplant mortality.17 Unsurprisingly, PNF had the strongest correlation with 7-day mortality (OR 12.868 [95% CI, 1.727-95.892]; P = .013) within DD, mirroring the trend observed between 1-year mortality and EGL.7 The disproportionate effect of PNF on early outcomes reinforces the need to refine predictive models and early detection strategies. Although multiple risk factors for early post-transplant mortality have been identified, recipients with T2DM experience higher 30-day postoperative mortality, especially in patients who are on dialysis.18 In our regression analysis, DD recipients with DM also had an increased likelihood of 7-day mortality compared with non-DM recipients (OR 2.396 [95% CI, 1.084-5.297]; P = .031). Optimization of DM is a requirement when listing patients for transplant. However, there is no standardized goal for control in this setting.

Sex, age, and race as recipient risk factors
Several recipient characteristics were independently associated with an increased risk of 7DGL, with distinct differences between the overall, DD, and LD transplant groups. Male sex and recipient age ≥60 years were significant predictors in the overall and DD groups, consistent with prior investigations.19,20 No significant sex- and age-associated data were observed with LD recipients. Our analysis revealed that African American recipients of DD transplants have a higher incidence of 7DGL compared with White (43.23% vs 32.42%) and Hispanic recipients (43.23% vs 14.95%) (Table 2). African American recipients of DD transplants also had increased odds of 7DGL by approximately 40% (OR 1.395 [95% CI, 1.220-1.596]; P < .001). No race-associated risk was observed in LD recipients. This highlights previously known disparities and calls for further individualization of care based on risk factors and use of genetic tools to identify APOL1 mutations, for instance.21 Although comorbidities such as FSGS and type 2 DM are more prevalent among African American people and are independently associated with increased risk of EGL, they do not fully account for the observed disparity. This suggests the potential role of unmeasured variables, such as differential access to pretransplant optimization, delayed transplant, and elevated immunologic risk.

Diabetes mellitus and body mass index as recipient metabolic risk factors
Presence of type 2 DM in recipients was a significant variable for 7DGL in the overall and DD groups (P < .001), potentially reflecting the compounded multisystem vascular and immune effects of type 2 DM.22,23 No significant association was observed in LD transplants. Body mass index is a known risk factor among recipients because of its association with impaired wound healing.24 Body mass index at time of transplant is also linked to an increased risk of DM, graft failure, mortality, and other surgical complications.25 Unsurprisingly, our analysis identi-fied a strong association between increased BMI at transplant and 7DGL across all 3 cohorts. This further strengthens the previously proposed idea that obesity increases surgical complexity, delays recovery, and worsens graft outcomes.24,25 The established link between type 2 DM and elevated BMI also indicates that these factors may produce cumulative effects on posttransplant graft survival.25

Retransplant status, dialysis exposure, and wait time-related recipient risk factors
Retransplant status was not a significant risk factor for 7DGL in any cohort (P > .05). Dialysis depen-dence at the time of registration and dialysis vintage were linked to increased risk of 7DGL in the overall and DD groups, reflecting the detrimental effects of prolonged pretransplant dialysis on cardiovascular stability and allograft viability.23,26,27 For the LD group, only dialysis vintage suggested an association with 7DGL (P = .012). Among our cohorts, only the overall group had a risk association between 7DGL and longer wait time (P < .001). Collectively, our data emphasized the need for strategies to reduce pretransplant dialysis exposure and shorten wait times to improve early graft outcomes.

Recipient renal function, immunologic risk, and predicted posttransplant survival
In the overall cohort, lower GFR was shown in the 7DGL group compared with the group having graft survival >1 year (12.59 ±5.23 vs 13.32 ± 4.79 mL/min; P = .01), but no significant association was seen in the DD or LD subgroups. A similar trend was observed with cPRA, with higher cPRA values within the overall 7DGL group only (23.84 ± 35.69 vs 22.51 ± 35.25; P = .016). In both the overall and DD 7DGL groups, EPTS scores were a significant variable.

Recipient primary diagnosis at time of listing
Focal segmental glomerulosclerosis recurrence after transplant is a known major risk of graft loss, increasing the likelihood of loss by 5-fold.13,28 Notably, the risk is higher with living-related donation transplant.13,29 Although posttransplant recurrence can be managed with treatment modalities such as plasmapheresis, corticosteroids, and high-dose calci-neurin inhibitors, FSGS recurrence remains a major challenge.30 In our analysis, FSGS only markedly increased the odds of 7DGL in LD recipients (OR 2.481 [95% CI, 1.165-5.281]; P = .018), consistent with the high recurrence rates and aggressive course of this disease posttransplant.13,28-30 The substantial association between FSGS and LD 7DGL warrants both clinical vigilance and advancement in treatment strategies to mitigate the effect of FSGS. Of other primary diagnoses at the time of listing, only type 2 DM was significantly associated with 7DGL among the overall and DD cohorts. This potentially reflects the burden of advanced diabetic complications. These findings underscore the multi-factorial nature of EGL and the importance of individualized pre- and perioperative management strategies to decrease the risk.

Sex, age, and race as donor risk factors
No significant association was shown between donor sex and 7DGL in any of the 3 cohorts, consistent with prior investigations.19,20,31 Advanced donor age was strongly associated with 7DGL, with donors aged ≥60 years and 40 to 59 years more frequently represented in overall and DD (P < .001). The association between donors aged ≥60 years and 7DGL (P = .015) persisted in the LD subgroup, similarly unveiling the link between advanced donor age and inferior renal graft outcomes posttransplant.19,20,31 Donor race was not a significant factor for 7DGL in the overall and LD groups. However, among DD cohort, having an Asian donor was more commonly associated with 7DGL (P = .003). This association may reflect suboptimal HLA and blood group matching within a predominantly White donor pool, suggesting that the influence of donor race on 7DGL is likely driven primarily by immunologic compatibility.18

Donor comorbidities and body mass index at time of death
Donor history of type 2 DM, hypertension, and BMI at the time of death were significantly associated with 7DGL in only the overall and DD groups (P < .001). None of these comorbidities were iden-tified to be significant among the LD 7DGL group, suggesting compounded risk factors, including ischemia injury, delayed graft function, and potential use of marginal organ quality within the overall and DD cohorts.24,25,32 Donor hypertension is a variable associated with early graft dysfunction, likely due to chronic vascular injury and impaired renal recovery.32 In our cohort, DD recipients with a history of hypertension had 29% higher odds of graft loss within 7 days (OR 1.29 [95% CI, 1.113-1.501]; P = .001). Higher donor BMI at time of death was significantly associated with overall and DD 7DGL, but showed no significant association in LD recipients (P < .001). This reflects a possible association that obesity in donors contributes to metabolic and hemodynamic stress on the kidney, increasing vulnerability to early graft dysfunction.24,25,32

Donor procurement characteristics and organ quality metrics
Our data also revealed that, within the DD 7DGL group, DCD resulted in a 32% higher odds of graft failure (OR 1.349 [95% CI, 1.178-1.546]; P < .001), further supporting prior literature linking DCD with early graft complications.33 A similar association was identified in the overall cohort (P < .001). Donors in the overall and DD 7DGL groups also exhibited higher terminal creatinine levels compared with those with graft survival of >1 year (1.37 ± 0.92 vs 1.33 ± 0.86 mg/dL; P < .001), underscoring the detrimental effects of impaired donor renal function before procurement on early posttransplant outcomes.34 Similarly, higher KDPI scores were strongly associated with 7DGL in the overall and DD cohorts. The left kidney is generally preferred for kidney transplants due to the longer and firmer left renal vein, which can make implantation easier. Our data showed no decreased risk of 7DGL in the LD group (OR 0.642 [95% CI, 0.312-1.319]; P = .642). The risk of 7DGL was also not significant in the DD group (OR 1.067 [95% CI, 0.939-1.213]; P = .320).

Association with modern era of transplant
Our data demonstrated an unexpected association between 7DGL and transplant years 2020 to 2024 among all cohorts. We surmised that this is most likely related to attempts to push the boundaries of accepted organs, leading to an increase in average CIT, delayed graft function, and more national sharing. Another factor could be the willingness to accept higher KDPI kidneys among older recipients.35,36

Association with locally shared, regionally shared, and nationally shared organs
Within the overall cohort, 7DGL was shown in 22.85% of regionally and 24.67% of nationally shared organs (P < .001). A similar pattern was observed among DD, with 24.14% and 26.06% in regionally and nationally shared organs, respectively (P < .001). These associations further support the idea that locally shared kidneys have better short-term outcomes because of shorter CIT and subsequently lower rates of delayed graft function.37

Effects of cold and warm ischemia times
Warm ischemia time is linked to poor renal transplant outcomes.9 Although both WIT and CIT can adversely affect transplant success, prolonged CIT causes greater cellular damage, leading to an increased risk of graft loss. Our analysis indicated that CIT, but not WIT, increased the risk of 7DGL in the overall and the DD cohorts (P < .001). There was no significant association in LD. Multivariable regression further unveiled that each additional hour of CIT increased the odds of DD 7DGL by 1.4% (OR 1.014 [95% CI, 1.005-1.022]; P = .002), underscoring the time-sensitive nature of DD transplant and its associated effect on outcomes.38

HLA mismatch
Although the emergence of potent immunosup­pressive agents minimized the effects of HLA compatibility, a significant association between graft survival and HLA mismatch persists, particularly for HLA-DR and HLA-DQ mismatches.39 Six-antigen-matched kidneys consistently demonstrate superior allograft survival.40 Our analysis demonstrated that increased HLA mismatch was associated with higher odds of 7DGL in the DD group (OR 1.054 [95% CI, 1.005-1.105]; P = .032). HLA mismatch was also significant among the overall 7DGL group (4.34; P < .001) but not significantly associated with LD.

Induction medication
In 2022, 92.1% of all adult kidney transplants had induction immunosuppression.41 Investigations have shown that patients who had rabbit ATG had lower rates of graft loss and mortality compared with those who had IL-2 receptor antagonists (IL2RAs).42,43 Rabbit ATG currently represents the most frequently utilized induction agent in kidney transplant in the United States, comprising 56% of all induction therapies over the past 2 decades.42,44 In contrast, 7DGL was notably higher in recipients who received rabbit ATG (P = .005) and in those who received a combination of rabbit ATG + IL2RAs (P = .021) among the overall cohort. Other induction modalities were not significant contributors for the DD and LD cohorts. We attribute this result to the systematic use of thymoglobulin among patients with high-risk grafts. Regression analysis also did not show differences with alemtuzumab or IL-2, further supporting that, after adjustment for other variables, ATG is probably a confounder and not a direct correlate of 7DGL.43,45 Although the ATG + IL-2 combination appears to correlate with a worse 7DGL in LD but not in DD, this may be attributed to the small number of LD cases (n = 4; Table 2).

Strengths and limitations
To our knowledge, this is the first investigation that analyzed the risks and causes of both LD and DD 7DGL and mortality after kidney transplant. We leveraged a large public database (UNOS) to power the statistical analysis given the relatively small number of graft failures within 7 days of transplant. The retrospective investigation also allowed a thorough assessment of various risks and outcomes. However, because of its retrospective nature, our report only established correlation rather than causation. A notable limitation is the lack of prior investigations on 7DGL, which made it difficult to compare our conclusions. Although a multivariable logistic regression analysis was performed, LD mortality was precluded because of its significantly low sample size. Nonetheless, our analysis serves as a foundation for future research to better understand the association between 7DGL and its underlying causes and risk factors.

Conclusions
Graft loss within the first week of transplant remains a devastating outcome, with PNF and graft throm-bosis as leading causes. Risk factors for graft loss and mortality differ between donor and recipient profiles. Donor-specific risk factors for graft loss include high KDPI, DCD, and hypertension. Among recipients, FSGS and hypertension were identified as risk factors for graft loss. In contrast, mortality was more frequently observed in recipients with type 2 DM and PNF. These variables should be communicated to patients, as they reflect unfavorable outcomes for graft loss and mortality. The current scarcity of kidney grafts and the necessity of striking a balance with the increased demand for transplant continue to challenge transplant centers in their search for optimal outcomes. Although these findings, espe-cially regarding KDPI, should be communicated to patients, they should not serve as a deterrent to accepting higher KDPI kidneys. Unlike prior reports limited to 30- and 90-day graft loss, our analysis further quantified their effects during the critical early posttransplant period. This report provides a foundation for articulating risks during informed consent discussions, guiding resource allocation, and planning remuneration strategies. Incorporating 7DGL risk profiles into reimbursement policies could promote greater equity in transplant center benchmarking and resource distribution.


References:



    1. Tonelli M, Wiebe N, Knoll G, et al. Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant. 2011;11(10):2093-2109. doi:10.1111/j.1600-6143.2011.03686.x
    CrossRef - PubMed
    2. Marcen R, Fernandez-Rodriguez A, Rodriguez-Mendiola N, et al. Evolution of rejection rates and kidney graft survival: a historical analysis. Transplant Proc. 2009;41(6):2357-2359. doi:10.1016/j.transproceed.2009.06.049
    CrossRef - PubMed
    3. Lentine KL, Smith JM, Lyden GR, et al. OPTN/SRTR 2023 annual data report: kidney. Am J Transplant. 2025;25(2). doi:10.1016/j.ajt.2025.01.020
    CrossRef - PubMed
    4. Kang MS, Kim DY, Kim SH, et al. Comparison of depression and suicide between dialysis and kidney transplant recipients in Korea: a nationwide population study. Clin Transplant Res. 2024;38(2):98-105. doi:10.4285/ctr.24.0004
    CrossRef - PubMed
    5. Brooks JT, Mitro G, Becker K, et al. Identifying risk factors for graft loss within 90 days of kidney transplantation in the modern era: a review of single center and UNOS databases. Trends Transplant. 2017;10(4). doi:10.15761/tit.1000234
    CrossRef - PubMed
    6. Zaza G, Ferraro PM, Tessari G, et al. Predictive model for delayed graft function based on easily available pre-renal transplant variables. Intern Emerg Med. 2015;10:135-141. doi:10.1007/s11739-014-1119-y
    CrossRef - PubMed
    7. Hamed MO, Chen Y, Pasea L, et al. Early graft loss after kidney transplantation: risk factors and consequences. Am J Transplant. 2015;15(6):1632-1643. doi:10.1111/ajt.13162
    CrossRef - PubMed
    8. Ploeg RJ, D'Alessandro AM, Knechtle SJ, et al. Risk factors for primary dysfunction after liver transplantation-a multivariate analysis. Transplantation. 1993;55(4):807-813. doi:10.1097/00007890-199304000-00024
    CrossRef - PubMed
    9. Swinarska JT, Stratta RJ, Rogers J, et al. Early graft loss after deceased-donor kidney transplantation: what are the consequences? J Am Coll Surg. 2021;232(4):493-502. doi:10.1016/j.jamcollsurg.2020.12.005
    CrossRef - PubMed
    10. Loza J, Alghannam K, Howard B, et al. Clinical and histologic risk factors for the development of early allograft dysfunction in donation after circulatory death kidney transplantation. Transplant Proc. 2025;57(5):764-770. doi:10.1016/j.transproceed.2025.03.022
    CrossRef - PubMed
    11. Keller AK, Jorgensen TM, Jespersen B. Identification of risk factors for vascular thrombosis may reduce early renal graft loss: a review of recent literature. J Transplant. 2012;2012:793461. doi:10.1155/2012/793461
    CrossRef - PubMed
    12. Guerra R, Kawano PR, Amaro MP, et al. Acute graft thrombosis in patients who underwent renal transplant and received anticoagulant or antiplatelet agents: a systematic review and meta-analysis. Am J Clin Exp Urol. 2022;10(3):129-141
    CrossRef - PubMed
    13. Bai J, Zhang T, Wang Y, et al. Incidence and risk factors for recurrent focal segmental glomerulosclerosis after kidney transplantation: a meta-analysis. Ren Fail. 2023;45(1):2201341. doi:10.1080/0886022X.2023.2201341
    CrossRef - PubMed
    14. Gipson DS, Wang CS, Salmon E, et al. FSGS Recurrence Collaboration: report of a symposium. Glomerular Dis. 2023;4(1):1-10. doi:10.1159/000535138
    CrossRef - PubMed
    15. Akhil R, Mathew E, Prasannan B, Urs VD, Unni VN. Incidence, risk factors, and treatment outcome of acute renal allograft rejection. Indian J Transplant. 2024;18(4):419-424. doi:10.4103/ijot.ijot_54_24
    CrossRef - PubMed:
    16. Hariharan S, Israni AK, Danovitch G. Long-term survival after kidney transplantation. N Engl J Med. 2021;385(8):729-743. doi:10.1056/NEJMra2014530
    CrossRef - PubMed
    17. Al-Shraideh Y, Stratta R, Farney A, et al. Primary non function after deceased donor kidney transplantation: risks and consequences. Abstract 2484. Transplantation. 2014;98(suppl):631.
    CrossRef - PubMed:
    18. Hakeem AR, Asthana S, Johnson R, et al. Impact of Asian and Black donor and recipient ethnicity on the outcomes after deceased donor kidney transplantation in the United Kingdom. Transpl Int. 2024;37:12605. doi:10.3389/ti.2024.12605
    CrossRef - PubMed
    19. Saparbay J, Assykbayev M, Abdugafarov S, et al. Kidney transplantation outcomes: single center experience. Transplant Rep. 2022;7(3):100105. doi:10.1016/j.tpr.2022.100105
    CrossRef - PubMed:
    20. Augliene R, Dalinkeviciene E, Kuzminskis V, et al. Factors influencing renal graft survival: 7-year experience of a single center. Medicina (Kaunas). 2017;53(4):224-232. doi:10.1016/j.medici.2017.07.003
    CrossRef - PubMed
    21. Milwid TG, Fabian J, Adam A, et al. The impact of deceased versus living donor graft status on kidney transplant outcomes: a Johannesburg single-center 48 years' experience of 1685 patients. Curr Urol. 2024;18(4):336-341. doi:10.1097/CU9.0000000000000041
    CrossRef - PubMed
    22. Tsarpali V, Midtvedt K, Lønning K, et al. A comorbidity index and pretransplant physical status predict survival in older kidney transplant recipients: a national prospective study. Transplant Direct. 2022;8:e1307. doi:10.1097/TXD.0000000000001307
    CrossRef - PubMed
    23. Gritane K, Jusinskis J, Malcevs A, et al. Influence of pretransplant dialysis vintage on repeated kidney transplantation outcomes. Transplant Proc. 2018;50(5):1249-1257. doi:10.1016/j.transproceed.2018.01.056
    CrossRef - PubMed
    24. Nicoletto BB, Fonseca NK, Manfro RC, et al. Effects of obesity on kidney transplantation outcomes: a systematic review and meta-analysis. Transplantation. 2014;98:167-176. doi:10.1097/TP.0000000000000028
    CrossRef - PubMed
    25. Schold JD, Augustine JJ, Huml AM, et al. Effects of body mass index on kidney transplant outcomes are significantly modified by patient characteristics. Am J Transplant. 2021;21(2):751-765. doi:10.1111/ajt.16196
    CrossRef - PubMed
    26. Dinh A, Ku E. Pretransplant dialysis exposure and outcomes after kidney transplantation-where quantity and quality intersect? Am J Transplant. 2020;20(9):2301-2302. doi:10.1111/ajt.16007
    CrossRef - PubMed
    27. Gill JS, Clark S, Kadatz M, Gill J. The association of pretransplant dialysis exposure with transplant failure is dependent on the state-specific rate of dialysis mortality. Am J Transplant. 2020;20(9):2481-2490. doi:10.1111/ajt.15917
    CrossRef - PubMed
    28. Wood EL, Kwan L, Burrows JE, Singh G, Veale J, Lum EL. Early recurrence of focal segmental glomerulosclerosis in kidney transplant recipients: when to consider regifting. Transplant Rep. 2023;8(2):100130. doi:10.1016/j.tpr.2023.100130
    CrossRef - PubMed:
    29. Kennard AL, Jiang SH, Walters GD. Increased glomerulonephritis recurrence after living related donation. BMC Nephrol. 2017;18(1):25. doi:10.1186/s12882-016-0435-z
    CrossRef - PubMed
    30. Uro-Coste C, Lambert C, Audard V, et al. Prophylactic treatment of FSGS recurrence in patients who relapsed on a previous kidney graft. Nephrol Dial Transplant. 2024;40(3):475-483. doi:10.1093/ndt/gfae108
    CrossRef - PubMed
    31. Lebranchu Y, Baan C, Biancone L. Pretransplant identification of acute rejection risk following kidney transplantation. Transpl Int. 2013;27(2):129-138. doi:10.1111/tri.12205
    CrossRef - PubMed
    32. Ponticelli C, Cucchiari D, Graziani G. Hypertension in kidney transplant recipients. Transpl Int. 2011;24(6):523-533. doi:10.1111/j.1432-2277.2011.01242.x
    CrossRef - PubMed
    33. Summers DM, Watson CJE, Pettigrew GJ, et al. Kidney donation after circulatory death (DCD): state of the art. Kidney Int. 2015;88(2):241-249. doi: 10.1038/ki.2015.88.
    CrossRef - PubMed
    34. Maanaoui M, Provôt F, Bouyé S, et al. Impaired renal function before kidney procurement has a deleterious impact on allograft survival in very old deceased kidney donors. Sci Rep. 2021;11(1):12226. doi:10.1038/s41598-021-91843-7
    CrossRef - PubMed
    35. Nimmo A, Gardiner D, Ushiro-Lumb I, et al. The global impact of COVID-19 on solid organ transplantation: two years into a pandemic. Transplantation. 2022;106(7):1312-1329. doi:10.1097/TP.0000000000004151
    CrossRef - PubMed
    36. Bae S, McAdams-DeMarco MA, Massie AB, et al. Early changes in kidney transplant immunosuppression regimens during the COVID-19 pandemic. Transplantation. 2020;105(1):170-176. doi:10.1097/tp.0000000000003502
    CrossRef - PubMed
    37. Kayler LK, et al. Import kidney transplants from nonmandatory share deceased donors: characteristics, distribution, and outcomes. Am J Transplant. 2011;11(1):77-85. doi: 10.1111/j.1600-6143.2010.03359.x.
    CrossRef - PubMed
    38. Petrochenkow E, Bencini G, Martinino A, et al. Analyzing the impact of cold ischemia time on the largest reported cohort of robotic kidney transplantation from deceased donors. Transplant Direct. 2024;10(9):e1671. doi:10.1097/TXD.0000000000001671
    CrossRef - PubMed
    39. Alelign T, Ahmed MM, Bobosha K, Tadesse Y, Howe R, Petros B. Kidney transplantation: the challenge of human leukocyte antigen and its therapeutic strategies. J Immunol Res. 2018;2018:5986740. doi:10.1155/2018/5986740
    CrossRef - PubMed
    40. Oweira H, Ramouz A, Ghamarnejad O, et al. Risk factors of rejection in renal transplant recipients: a narrative review. J Clin Med. 2022;11(5):1392. doi:10.3390/jcm11051392
    CrossRef - PubMed
    41. US Department of Health and Human Services, Health Resources and Services Administration. Organ Procurement and Transplantation Network, Scientific Registry of Transplant Recipients. OPTN/SRTR 2023 annual data report. 2025. Accessed April 11, 2025. https://www.srtr.org/reports/optnsrtr-annual-data-report/
    CrossRef - PubMed:
    42. Alloway RR, Woodle ES, Abramowicz D, et al. Rabbit anti-thymocyte globulin for the prevention of acute rejection in kidney transplantation. Am J Transplant. 2019;19(8):2252-2261. doi:10.1111/ajt.15342
    CrossRef - PubMed
    43. Hellemans R, Bosmans JL, Abramowicz D. Induction therapy for kidney transplant recipients: do we still need anti-IL2 receptor monoclonal antibodies? Am J Transplant. 2017;17(1):22-27. doi:10.1111/ajt.13884
    CrossRef - PubMed
    44. Vu VA, Bhayana S, Sweiss H, et al. Impact of cumulative 6 mg/kg antithymocyte globulin on early posttransplant outcomes in kidney transplant recipients with delayed graft function. Prog Transplant. 2024;34(1-2):47-52. doi:10.1177/15269248241237816
    CrossRef - PubMed
    45. Park BH, Kim YN, Shin HS, Jung Y, Rim H. Current use of antithymoglobulin as induction regimen in kidney transplantation: a review. Medicine (Baltimore). 2024;103(9):e37242. doi:10.1097/MD.0000000000037242
    CrossRef - PubMed



Volume : 23
Issue : 9
Pages : 571 - 582
DOI : 10.6002/ect.2025.0207


PDF VIEW [287] KB.
FULL PDF VIEW

From the 1Touro College of Osteopathic Medicine, Middletown, NY; the 2Albany Medical College, Albany, NY; the 3Albany Medical Center, Division of Nephrology, Albany, NY; the 4George Mason University, Fairfax, VA; and the 5Garnet Health Medical Center, Department of Surgery, Middletown, NY, USA
Acknowledgements: This study was partially funded by the National Science Foundation (NSF - IIS/ENG:SCH:/2123683). The authors have no declarations of potential conflicts of interest.
Disclaimer: The data reported here have been supplied by the United Network for Organ Sharing as the contractor for the Organ Procurement and Transplantation Network. The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy of or interpretation by the OPTN or the US Government.
Corresponding author: Riah Lee, Touro College of Osteopathic Medicine-Middletown, 60 Prospect Ave, Middletown, NY 10940, USA
Phone: +1 224 723 9376 E-mail: slee20@student.touro.edu