Delayed Graft Function and Its Impact on Short- and Long-Term Outcomes After Kidney Transplantation

doi:10.21203/rs.3.rs-8506208/v1

Introduction:

Kidney transplantation is an effective treatment for end-stage renal disease, markedly improving survival and quality of life. However, delayed graft function (DGF) remains a notable early post-transplant complication. This study aims to determine the impact of DGF on mortality, hypertension, graft survival, and other post-transplant complications.

Methods

This retrospective study included adult recipients (≥ 18 years) who underwent kidney transplantation at the Organ Transplant Unit of Diyarbakır Gazi Yaşargil Training and Research Hospital between 1 January 2013 and 31 December 2023. A total of 285 patients with at least 12 months of follow-up were analyzed. Demographic characteristics, presence of post-transplant hypertension, immunosuppressive regimens, and laboratory parameters related to graft function were extracted from the Hospital Information Management System (HIMS) using a standardized abstraction form. Post-transplant hypertension was defined according to the KDIGO 2021 guideline; details of the analytic approach are described in the Statistics section.

Results

In this cohort of 285 kidney transplant recipients, DGF occurred significantly more often following deceased-donor transplantation (p < 0.001) and was associated with inferior short- and long-term outcomes. Patients with DGF had markedly lower eGFR at discharge (p < 0.001), with differences persisting at the 3rd month (p = 0.045), 6th month (p = 0.030), 3rd year (p = 0.041), and 6th year (p = 0.027). Postoperative complications, particularly bleeding, were more frequent in the DGF group (p = 0.003 and p < 0.01, respectively), and mortality was significantly higher among patients with DGF (p < 0.001). In multivariate analysis, serum creatinine (p = 0.001) and urine protein levels (p = 0.001) at discharge remained independent predictors of DGF, whereas demographic and pre-transplant variables were not.

Conclusion

DGF significantly compromises both short- and long-term outcomes after kidney transplantation. Its strong association with deceased donation, early graft injury, and persistently reduced GFR highlights the importance of early identification and vigilant post-transplant management to improve graft and patient survival.

Kidney Transplantation

Post-transplant Hypertension

Delayed Graft Function

Graft Dysfunction

Immunosuppression

Chronic kidney disease (CKD) is recognized worldwide as a major public health problem. The global prevalence of CKD is estimated at 13.4%, and the number of patients with end-stage kidney disease (ESKD) requiring renal replacement therapy is projected to be 4.9–7.1 million (1). The term ESKD generally refers to chronic kidney failure requiring renal replacement therapy, typically when the glomerular filtration rate (GFR) falls below 15 mL/min/1.73 m².

To sustain life, patients must receive either dialysis or a kidney transplant. Kidney transplantation is regarded as the most effective option for this population, playing a key role in prolonging survival and reducing morbidity (2). Nevertheless, a range of early and late post-transplant complications can occur. Early recognition and effective management of these complications are critical for both graft survival and patient survival.

DGF, one of the complications following renal transplantation, is defined as the delayed recovery of graft function after kidney transplantation and is most commonly identified by the need for dialysis within the first week post-transplant. The incidence of DGF varies between 20% and 50% in cadaveric donor transplants, whereas it is considerably lower in living donor transplants (3).

Evaluating pre-transplant factors that may contribute to DGF alongside post-transplant outcomes such as mortality, hypertension, graft survival, renal function, and other complications can provide valuable insights. By identifying these determinants, it may be possible to optimize kidney transplant outcomes, enhancing both graft longevity and overall patient prognosis.

Study design and ethics: This was a national, single-center, retrospective cross-sectional study conducted at the Organ Transplant Center of SBÜ Diyarbakır Gazi Yaşargil Training and Research Hospital. The protocol was approved by the hospital’s Clinical Research Ethics Committee (Decision No. 179; date: 2024), and the study adhered to the Declaration of Helsinki and Good Clinical Practice guidelines.

Setting and population: We screened all patients who underwent kidney transplantation between 1 January 2013 and 31 December 2023.

Inclusion criteria

Age ≥ 18 years
≥ 1 year of post-transplant follow-up
Availability of regular, traceable follow-up data

Exclusion criteria

Active malignancy or infection before transplant
Recurrent acute rejection episodes
Development of multiple organ failure
Incomplete or insufficient follow-up data

Data sources and variables: Data were retrieved from the hospital’s electronic medical record and paper charts using a standardized abstraction form.

Demographics: age, sex, body mass index (BMI), donor type (deceased vs. living).
Pre-transplant variables: comorbidities; etiology of chronic kidney disease (e.g., diabetic nephropathy, hypertensive nephropathy, glomerulonephritis); erythropoietin use; dialysis status (peritoneal dialysis, hemodialysis, or pre-emptive transplant); echocardiography findings including ejection fraction (EF); and pre-transplant blood pressure measurements.
Post-transplant follow-up: blood pressure at predefined time points (post-operative day 1, month 3, month 6, year 1, year 2, and last visit); immunosuppressive regimen (calcineurin inhibitors, mTOR inhibitors, etc.); graft function indices (serum creatinine, eGFR, proteinuria); incidence and management of post-transplant hypertension; and graft survival/loss and related factors.

Statistical analysis: Analyses were performed using IBM SPSS (IBM Corp., Armonk, NY, USA). Continuous variables are presented as mean ± standard deviation (SD) or median (interquartile range, IQR), and categorical variables as n (%). Between-group comparisons used the χ² test for categorical data and the independent-samples t test or Mann–Whitney U test for continuous data, as appropriate. To assess factors associated with post-transplant hypertension and the effect on graft function, multivariable regression models were fitted. A two-sided p value < 0.05 was considered statistically significant.

A total of 285 kidney transplant recipients were evaluated, including 259 living donors (90.9%) and 26 deceased donors (9.1%). Recipient age, gender distribution, and BMI were similar between groups (p > 0.05). However, deceased donor kidneys came from significantly older donors compared to living donors (54.58 ± 21.42 vs. 43.68 ± 11.31 years, p < 0.001). Kinship analysis showed that all deceased donor transplantations were from non-relatives, while most living donor transplants were parent/child or spouse related (p < 0.001). The standard immunosuppressive regimen (ATG + TAC + MMF + Prednisone) was used in 92.3% of cases, more frequently in deceased donor recipients (96.1%, p = 0.001).

Pre-transplant hypertension prevalence did not differ between groups (p = 0.169). The etiology of kidney disease showed a higher rate of unknown cause in the deceased donor group (65.4% vs. 41.7%, p = 0.020). Erythropoietin use was significantly more common among deceased donor recipients (88.5% vs. 26.6%, p < 0.001). Pathological echocardiographic findings and left ventricular diastolic dysfunction were more frequent in the deceased donor group (p = 0.013 and p = 0.009, respectively). Hemodialysis was the predominant pre-transplant dialysis modality, especially among deceased donor recipients (96.2%, p < 0.001), who also had longer dialysis durations (90 vs. 2 months, p < 0.001). Among deceased donor patients, the leading cause of death was pneumonia (65.4%) (Table 1).

Table 1

Pre-Transplant Clinical Characteristics of the Patients
Variable	Living Donor (n = 259)	Deceased Donor (n = 26)	Total (n = 285)	p-values
Recipient Gender
Male	159 (61.4%)	12 (46.2%)	171 (60.0%)	0.131
Female	100 (38.6%)	14 (53.8%)	114 (40.0%)	0.131
Donor Gender
Male	95 (36.7%)	11 (42.3%)	106 (37.2%)	0.571
Female	164 (63.3%)	15 (57.7%)	179 (62.8%)	0.571
Recipient Age (years)	36.25 ± 12.29	39.46 ± 11.23	36.55 ± 12.22	0.203
Donor Age (years)	43.68 ± 11.31	54.58 ± 21.42	44.68 ± 12.90	< 0.001**
Recipient BMI (kg/m²)	23.39 ± 4.54	22.71 ± 3.81	23.33 ± 4.48	0.461
Donor BMI (kg/m²)	27.17 ± 4.22	26.23 ± 5.79	27.08 ± 4.39	0.301
Kinship (Degree of Relation)
Spouse	88 (34.0%)	0	88 (30.9%)	< 0.001**
Parent/Child	99 (38.2%)	0	99 (34.7%)
Sibling/Grandparent/Grandchild	47 (18.1%)	0	47 (16.5%)
Uncle/Aunt/Nephew/Niece	8 (3.1%)	0	8 (2.8%)
Third-degree relative	4 (1.5%)	0	4 (1.4%)
Fourth-degree or beyond	2 (0.8%)	0	2 (0.7%)
Non-relative	11 (4.2%)	26 (100%)	37 (13.0%)
Immunosuppressive Therapy
ATG + TAC + MMF + PRED	238 (91.9%)	25 (96.1%)	263 (92.3%)	0.001*
Pre-Tx Hypertension
Present	113 (43.6%)	15 (57.7%)	128 (44.9%)	0.169
Absent	146 (56.4%)	11 (42.3%)	157 (55.1%)	0.169
Etiology of Chronic Kidney Disease
Unknown	108 (41.7%)	17 (65.4%)	125 (43.9%)	0.020*
Hypertension	66 (25.5%)	4 (15.4%)	70 (24.6%)
Diabetes Mellitus	20 (7.7%)	0	20 (7.0%)
Others (FSGS, GN, PKD, etc.)	Various (< 5% each)
Erythropoietin Use
Yes	69 (26.6%)	23 (88.5%)	92 (32.3%)	< 0.001**
No	190 (73.4%)	3 (11.5%)	193 (67.7%)	< 0.001**
Echocardiography Findings
Normal	104 (40.2%)	4 (15.4%)	108 (37.9%)	0.013*
Pathological	155 (59.8%)	22 (84.6%)	177 (62.1%)	0.013*
Left atrial enlargement	46 (17.8%)	8 (30.8%)	54 (18.9%)	0.093
Left ventricular hypertrophy	120 (46.3%)	17 (65.4%)	137 (48.1%)	0.064
Left ventricular diastolic dysfunction	92 (35.5%)	16 (61.5%)	108 (37.9%)	0.009*
Pre-Tx Ejection Fraction (%)	60 (40–65)	60 (55–65)	60 (40–65)	0.218
Dialysis Type Before Transplant
Preemptive	102 (39.4%)	0	102 (35.8%)	< 0.001**
Hemodialysis	154 (59.5%)	25 (96.2%)	179 (62.8%)
CAPD	2 (0.8%)	1 (3.8%)	3 (1.1%)
HD + CAPD	1 (0.4%)	0	1 (0.4%)
Dialysis Duration (months)	2 (0–240)	90 (12–204)	3 (0–240)	< 0.001**
Cause of Death (Deceased Donor)
Pneumonia	–	17 (65.4%)	–
MODS	–	4 (15.4%)	–
COVID-19	–	2 (7.7%)	–
BK Virus	–	2 (7.7%)	–
Subarachnoid Hemorrhage	–	1 (3.8%)	–

TX, transplantation; Pre-TX, pre-transplant; Post-TX, post-transplant; BMI, body mass index; ATG, anti-thymocyte globulin; TAC, tacrolimus; MMF, mycophenolate mofetil; PRED, methylprednisolone; CYC, cyclosporine; EVERO, everolimus; CKD, chronic kidney disease; VUR, vesicoureteral reflux; FSGS, focal segmental glomerulosclerosis; SLE, systemic lupus erythematosus; MPGN, membranoproliferative glomerulonephritis; FMF, familial Mediterranean fever; GN, glomerulonephritis; PKD, polycystic kidney disease; LVH, left ventricular hypertrophy; LVDD, left ventricular diastolic dysfunction; EF, ejection fraction; HD, hemodialysis; CAPD, continuous ambulatory peritoneal dialysis; MI, myocardial infarction.

Among the transplant cohort, no significant differences were observed between DGF and non-DGF groups in terms of recipient sex, age, BMI, erythropoietin use, pre-transplant hypertension prevalence, immunosuppressive regimen, family history of hypertension, or dialysis type (p > 0.05). However, the DGF group had significantly older donors (50.7 ± 18.0 vs. 43.9 ± 11.9 years, p = 0.006) and a higher proportion of unrelated donors (41.9% vs. 9.4%, p = 0.001). Hypertension duration was longer in the non-DGF group (p = 0.046). CKD etiology also differed significantly (p = 0.014), with unknown etiology more frequent in DGF and hypertensive nephropathy more common in non-DGF cases. Diastolic dysfunction and LA enlargement/LVH patterns were more frequently seen in the DGF group compared to non-DGF (p = 0.045). Dialysis duration was longer in patients who developed DGF (18 vs. 2 months, p = 0.008). Additionally, DGF was more common in deceased-donor transplants (35.5% vs. 5.9%, p < 0.001) (Table 2).

Table 2

Pre-Transplant Clinical Characteristics of All Patients According to the Presence of DGF
Pre-TX Clinical Features	DGF Present (n:31)	DGF Absent (n:254)	P values
Recipient Sex	Male 21 (67.7) Female 10 (32.3)	Male 150 (59.1) Female 104 (40.9)	0.351
Donor Sex	Male 7 (22.6) Female 24 (77.4)	Male 99 (39.0) Female 155 (61.0)	0.075
Recipient Age (years)	38.55 ± 13.21 (20–72)	36.30 ± 12.09 (18–69)	0.335
Donor Age (years)	50.71 ± 18.04 (6–84)	43.94 ± 11.97 (16–84)	0.006*
Recipient BMI (kg/m²)	23.24 ± 4.40 (17–34)	23.34 ± 4.49 (16–40)	0.906
Donor BMI (kg/m²)	26.36 ± 5.93 (14–39)	27.17 ± 4.17 (19–38)	0.334
Recipient–Donor Relationship	Spouse 6 (19.4) Parent/Child 9 (29.0) Sibling/Grandparent/Grandchild 2 (6.5) Uncle/Aunt/Niece/Nephew 1 (3.2) Non-relative 13 (41.9)	Spouse 82 (32.3) Parent/Child 90 (35.4) Sibling/Grandparent/Grandchild 45 (17.7) Uncle/Aunt/Niece/Nephew 7 (2.8) Non-relative 24 (9.4)	0.001*
Immunosuppression	TAC + PRED + PROGRAF 31 (100)	Other regimens	0.676
Pre-TX Hypertension	Yes 18 (58.1) No 13 (41.9)	Yes 110 (43.3) No 144 (56.7)	0.119
Antihypertensive Count	0–5 (median 2)	0–5 (median 2)	0.269
Hypertension Duration (years)	2.00 (1–8)	3.00 (0.3–30)	0.046*
CKD Etiology (selected)	Unknown 20 (64.5) Hypertension 3 (9.7) DM 1 (3.2)	Unknown 105 (41.3) Hypertension 67 (26.4) DM 19 (7.5)	0.014*
Erythropoietin Use	Yes 13 (41.9) No 18 (58.1)	Yes 79 (31.1) No 175 (68.9)	0.223
Echocardiography	Normal 11 (35.5) Pathologic 20 (64.5)	Normal 97 (38.2) Pathologic 157 (61.8)	0.769
Pathologic ECHO Findings	LA Enlargement 10 (32.3) LVH 13 (41.9) Diastolic Dysf. 16 (51.6)	LA Enlargement 44 (17.3) LVH 124 (48.8) Diastolic Dysf. 92 (36.2)	0.045*
Ejection Fraction (%)	60.00 (40–65)	60.00 (40–65)	0.064
Recipient Family Hypertension	Yes 9 (29.0) No 22 (71.0)	Yes 83 (32.7) No 171 (67.3)	0.682
Donor Family Hypertension	Yes 16 (51.6) No 15 (48.4)	Yes 129 (50.8) No 125 (49.2)	0.931
Dialysis Type (Pre-TX)	Preemptive 9 (29.0) HD 22 (71.0)	Preemptive 93 (36.6) HD 157 (61.8)	0.643
Dialysis Duration (months)	18.00 (0–216)	2.00 (0–240)	0.008*
Donor Type	Living 20 (64.5) Deceased 11 (35.5)	Living 239 (94.1) Deceased 15 (5.9)	< 0.001**

CKD: Chronic Kidney Disease

eGFR values were significantly higher in living donor recipients compared with deceased donor recipients at almost all follow-up time points (p < 0.05). Renal function improved markedly after transplantation and remained relatively stable over long-term follow-up, with a significant overall time-effect in both donor groups (p < 0.001) (Table 3).

Table 3

Post-Transplant GFR (ml/min) by Donor Type and Follow-up Period
Measurement Time	Living Donor (n = 259)	Cadaveric Donor (n = 26)	p-value
Preoperative	12.25 ± 6.45 (4–40)	7.80 ± 2.65 (4–15)	0.001 *
0 month	74.87 ± 27.83 (11–174)	44.03 ± 27.92 (7–132)	< 0.001 **
3rd Month	75.66 ± 21.74 (16–170)	58.58 ± 28.40 (17–122)	< 0.001 **
6th Month	75.84 ± 21.19 (18–157)	59.37 ± 23.04 (26–107)	< 0.001 **
1st Year	74.86 ± 20.30 (31–131)	58.70 ± 28.71 (24–138)	< 0.001 **
2nd Year	75.65 ± 22.21 (4–132)	61.74 ± 27.10 (23–126)	0.007 *
3rd Year	77.08 ± 19.49 (23–128)	64.43 ± 25.46 (22–125)	0.008 *
4th Year	76.96 ± 21.88 (14–134)	62.20 ± 26.96 (19–126)	0.007 *
5th Year	76.15 ± 20.17 (15–128)	59.33 ± 24.80 (27–125)	0.002 *
6th Year	73.21 ± 19.97 (16–110)	53.75 ± 12.71 (31–77)	0.001 *
7th Year	73.84 ± 21.71 (21–120)	45.67 ± 13.79 (28–63)	0.002 *
8th Year	76.24 ± 22.13 (9–116)	52.00 ± 8.54 (44–61)	0.064
9th Year	75.85 ± 20.74 (11–114)	—	—
10th Year	77.03 ± 18.57 (35–110)	—	—
11th Year	69.65 ± 30.58 (13–108)	—	—
Repeated Measures ANOVA (F)	18.884	10.075
p-value (Overall Time Effect)	< 0.001 **	< 0.001 **

A p value < 0.05 was considered statistically significant (*), and p < 0.001 was considered highly significant (**). Dashes (—) indicate unavailable data due to insufficient follow-up duration.

Patients without DGF demonstrated significantly higher GFR values at almost all follow-up periods compared to those with DGF. The most prominent difference was at discharge (73.9 vs. 27.7 mL/min, p < 0.001), and continued to be significant at 3rd month (p = 0.045), 6th month (p = 0.030), 3rd year (p = 0.041), and 6th year (p = 0.027). Although GFR gradually declined over long-term follow-up in the DGF group, non-DGF patients maintained better renal function throughout the study period (Table 4).

Table 4

Preoperative and Postoperative GFR Results of All Patients According to the Presence of DGF
Measurement Time	Delayed Graft Function (n:31)	No Delayed Graft Function (n:254)	p-value
GFR (mL/min)	Median (Min–Max)	Median (Min–Max)
Preoperative	8.90 (4–24)	10.60 (4–40)	0.089
At Discharge	27.70 (7–117)	73.90 (29–174)	< 0.001**
3rd Month	63.80 (17–114)	73.70 (16–170)	0.045*
6th Month	62.40 (26–109)	74.10 (18–157)	0.030*
1st Year	60.05 (24–108)	73.90 (24–138)	0.054
2nd Year	56.90 (23–126)	74.75 (4–132)	0.053
3rd Year	54.50 (22–125)	77.50 (23–128)	0.041*
4th Year	50.00 (19–126)	77.50 (14–134)	0.161
5th Year	57.00 (27–125)	78.00 (15–128)	0.139
6th Year	55.00 (30–59)	74.00 (16–110)	0.027*
7th Year	42.00 (30–54)	76.00 (21–120)	0.067
8th Year	51.00 (51–51)	81.00 (9–116)	0.235
9th Year	—	78.00 (11–114)	—
10th Year	—	81.00 (35–110)	—
11th Year	—	72.50 (13–108)	—

A p value < 0.05 was considered statistically significant (*), and p < 0.001 was considered highly significant (**). Dashes (—) indicate unavailable data due to insufficient follow-up duration.

Postoperative complications were significantly more frequent in the DGF group (45.2% vs 20.9%, p = 0.003), especially bleeding (p < 0.01). Post-transplant hypertension and antihypertensive drug use were more common in DGF, but not statistically significant. Post-transplant dialysis need showed no difference. Recipient mortality was significantly higher in patients with DGF (25.8% vs 5.5%, p < 0.001) (Table 5).

Table 5

Post-Transplant (Post-TX) Clinical Characteristics of All Patients According to the Presence of DGF
Post-TX Clinical Features	DGF (n:31)	No-DGF (n:254)	p-value
Postoperative Complication
Present	14 (45.2%)	53 (20.9%)	0.003*
Absent	17 (54.8%)	201 (79.1%)	0.003*
Types of Postoperative Complications
Renal Artery Thrombosis	0	5 (2.0%)		0.003*
Bleeding	11 (35.5%)	31 (12.2%)
Lymphocele	1 (3.2%)	10 (3.9%)
Urinoma	1 (3.2%)	9 (3.5%)
Seroma	1 (3.2%)	9 (3.5%)
Post-TX Hypertension
Present	22 (71.0%)	148 (58.3%)		0.174
Absent	9 (29.0%)	106 (41.7%)		0.174
Time of Post-TX Hypertension Onset
0 Month	17 (77.3%)	97 (65.5%)		0.276
3rd Month	1 (4.5%)	7 (4.7%)
6th Month	2 (9.1%)	4 (2.7%)
1st Year	1 (4.5%)	9 (6.1%)
2nd Year	1 (4.5%)	14 (9.5%)
Over 2 Years	0	17 (11.5%)
Use of Antihypertensive Drugs Post-TX
Present	22 (71.0%)	148 (58.3%)		0.187
Absent	9 (29.0%)	106 (41.7%)		0.187
Post-TX Dialysis
Received	3 (9.7%)	22 (8.7%)		0.743
Not Received	28 (90.3%)	232 (91.3%)		0.743
Recipient Mortality		11.191ᵇ
Alive	23 (74.2%)	240 (94.5%)		0.001**
Exitus	8 (25.8%)	14 (5.5%)		0.001**
Cause of Death		4.468ᶜ
Pneumonia	1 (12.5%)	3 (21.4%)		0.751
MODS	1 (12.5%)	2 (14.3%)
COVID-19	2 (25.0%)	5 (35.7%)
BK Virus	0	1 (7.1%)
SAH	1 (12.5%)	1 (7.1%)
MI	3 (37.5%)	1 (7.1%)
Malignancy	0	1 (7.1%)

DGF, delayed graft function; Post-TX, post-transplantation; MODS, multiple organ dysfunction syndrome; COVID-19, coronavirus disease 2019; BK virus, BK polyomavirus infection; SAH, subarachnoid hemorrhage; MI, myocardial infarction.

Among slow-deceased donor subgroups, post-operative complications tended to be more common in DGF patients (45.5% vs 6.7%), though not statistically significant. Number of HLA mismatches differed significantly (p = 0.022), with DGF patients more frequently having ≥ 4 mismatches. Post-transplant hypertension, antihypertensive use, and dialysis needs were similar between groups. Mortality was higher in DGF patients (36.4% vs 6.7%), although not statistically significant (Table 6).

Table 6

Post-TX Clinical Characteristics of Cadaveric Donor Transplant Patients According to the Presence of Delayed Graft Function (DGF)
Post-TX Clinical Features	DGF (n:11)	No-DGF (n:15)	p-value
Postoperative Complication
Present	5 (45.5%)	1 (6.7%)	0.054
Absent	6 (54.5%)	14 (93.3%)
Types of Postoperative Complications
Bleeding	4 (36.4%)	1 (6.7%)
Lymphocele	1 (9.1%)	0
Post-TX Hypertension
Present	8 (72.7%)	10 (66.7%)	> 0.05
Absent	3 (27.3%)	5 (33.3%)	> 0.05
Time of Post-TX Hypertension Onset		4.099ᶜ
0 Month	6 (75.0%)	7 (70.0%)	0.294
6th Month	2 (25.0%)	0
1st Year	0	2 (20.0%)
2nd Year	0	1 (10.0%)
Post-TX Antihypertensive Use
Present	8 (72.7%)	10 (66.7%)	> 0.05
Absent	3 (27.3%)	5 (33.3%)	> 0.05
Number of Matches
0	0	4 (26.7%)	0.022*
1	1 (9.1%)	1 (6.7%)
2	1 (9.1%)	2 (13.3%)
3	1 (9.1%)	5 (33.3%)
4	5 (45.5%)	0
5	3 (27.3%)	3 (20.0%)
Post-TX Dialysis
Received	3 (27.3%)	4 (26.7%)	> 0.05
Not Received	8 (72.7%)	11 (73.3%)	> 0.05
Recipient Mortality
Alive	7 (63.6%)	14 (93.3%)	0.128
Exitus	4 (36.4%)	1 (6.7%)	0.128
Cause of Death
Pneumonia	1 (25.0%)	0	> 0.05
COVID-19	2 (50.0%)	1 (100%)
MI	1 (25.0%)	0

TX, transplantation; Post-TX, post-transplantation; MI, myocardial infarction; COVID-19, coronavirus disease 2019

Among living-donor kidney transplant recipients, DGF patients showed significantly higher rates of postoperative complications compared with non-DGF recipients (45% vs. 21.8%, p = 0.027), with bleeding more frequent in the DGF group (35% vs. 12.6%). Post-transplant hypertension frequency was similar between groups, and timing of onset showed no significant differences. The number of HLA matches and need for post-transplant dialysis were comparable.Mortality was significantly higher in the DGF group (20% vs. 5.4%, p = 0.032), although causes of death did not differ statistically (Table 7).

Table 7

Post-TX Clinical Characteristics of Living Donor Transplant Patients According to the Presence of DGF
Post-TX Clinical Features	DGF (n:20)	No-DGF (n:239)	p-value
Postoperative Complication
Present	9 (45.0%)	52 (21.8%)	0.027*
Absent	11 (55.0%)	187 (78.2%)	0.027*
Types of Postoperative Complications
Renal Artery Thrombosis	0	5 (2.1%)	0.027*
Bleeding	7 (35.0%)	30 (12.6%)
Lymphocele	0	10 (4.2%)
Urinoma	1 (5.0%)	9 (3.8%)
Seroma	1 (5.0%)	9 (3.8%)
Post-TX Hypertension		1.144ᵃ
Present	14 (70.0%)	138 (57.7%)	0.285
Absent	6 (30.0%)	101 (42.3%)	0.285
Time of Post-TX Hypertension Onset
0 Month	11 (78.6%)	90 (65.2%)	0.709
3rd Month	1 (7.1%)	7 (5.1%)
6th Month	0	4 (2.9%)
1st Year	1 (7.1%)	7 (5.1%)
2nd Year	1 (7.1%)	13 (9.4%)
Over 2 Years	0	17 (12.3%)
Number of Matches
0	3 (15.0%)	42 (17.6%)	0.788
1	2 (10.0%)	23 (9.6%)
2	4 (20.0%)	24 (10.0%)
3	5 (25.0%)	70 (29.3%)
4	1 (5.0%)	30 (12.6%)
5	3 (15.0%)	25 (10.5%)
6	2 (10.0%)	25 (10.5%)
Post-TX Dialysis
Received	0	18 (7.5%)	0.375
Not Received	20 (100%)	221 (92.5%)	0.375
Mortality
Alive	16 (80.0%)	226 (94.6%)	0.032*
Exitus	4 (20.0%)	13 (5.4%)	0.032*
Cause of Death
Pneumonia	0	3 (23.1%)	0.399
MODS	1 (25.0%)	2 (15.4%)
COVID-19	0	4 (30.8%)
BK Virus	0	1 (7.7%)
SAH (Subarachnoid Hemorrhage)	1 (25.0%)	1 (7.7%)
MI (Myocardial Infarction)	2 (50.0%)	1 (7.7%)
Malignancy	0	1 (7.7%)

DGF, delayed graft function; Post-TX, post-transplantation; MODS, multiple organ dysfunction syndrome; COVID-19, coronavirus disease 2019; BK virus, BK polyomavirus infection; SAH, subarachnoid hemorrhage; MI, myocardial infarction.

Postoperative complications were significantly more frequent among deceased recipients compared with survivors (45.5% vs 21.7%, p = 0.012). Although the distribution of specific complication types differed numerically, no individual postoperative complication category showed a statistically significant difference between groups. DGF was markedly more common in patients who died than in those who survived (36.4% vs 8.7%, p < 0.001).

Post-transplant hypertension and the timing of its development did not differ significantly between survivors and deceased recipients (p = 0.841). Similarly, the use of antihypertensive medications, post-transplant dialysis requirement, and HLA match count were comparable between groups (p > 0.05 for all) (Table 8).

Table 8

Post-TX Clinical Characteristics of All Patients According to Mortality Status
Post-TX Clinical Features	Alive (n = 263) n (%)	Deceased (n = 22) n (%)	p
Postoperative Complication			0.012*
Present	57 (21.7)	10 (45.5)
Absent	206 (78.3)	12 (54.5)
Postoperative Complications			0.012*
Renal Artery Thrombosis	4 (1.5)	1 (4.5)
Hemorrhage	38 (14.4)	4 (18.2)
Lymphocele	10 (3.8)	1 (4.5)
Urinoma	6 (2.3)	4 (18.2)
Seroma	9 (3.4)	1 (4.5)
Post-TX Hypertension
Present	161 (61.2)	9 (40.9)
Absent	102 (38.8)	13 (59.1)
Time of Post-TX Hypertension Development
0 Month	105 (65.2)	9 (100)	0.841
3rd Month	8 (5.0)	0
6th Month	6 (3.7)	0
1st Year	10 (6.2)	0
2nd Year	15 (9.3)	0
> 2nd Year	17 (10.6)	0
Post-TX Antihypertensive Use		3.479
Yes	161 (61.2)	9 (40.9)	0.062
No	102 (38.8)	13 (59.1)	0.062
Delayed Graft Function
Present	23 (8.7)	8 (36.4)	< 0.001**
Absent	240 (91.3)	14 (63.6)	< 0.001**
Match Count
0	47 (17.9)	2 (9.1)	0.176
1	25 (9.5)	2 (9.1)
2	29 (11.0)	2 (9.1)
3	78 (29.7)	3 (13.6)
4	32 (12.2)	4 (18.2)
5	30 (11.4)	4 (18.2)
6	22 (8.4)	5 (22.7)
Post-TX Dialysis
Received	22 (8.4)	3 (13.6)	0.423
Not received	241 (91.6)	19 (86.4)	0.423

DGF, delayed graft function; Post-TX, post-transplantation; MODS, multiple organ dysfunction syndrome; COVID-19, coronavirus disease 2019; BK virus, BK polyomavirus infection; SAH, subarachnoid hemorrhage; MI, myocardial infarction.

In univariate logistic regression analysis, postoperative complications (OR = 3.95, 95% CI 1.54–10.15, p = 0.004), creatinine at discharge (OR = 96.06, 95% CI 16.20–569.66, p < 0.001), and urine protein at discharge (OR = 1.007 per unit increase, 95% CI 1.001–1.013, p = 0.026) were significantly associated with DGF. Other variables, including recipient age, sex, kinship degree, hypertension status, dialysis duration, and echocardiographic ejection fraction, were not statistically significant.

In multivariate analysis, creatinine at discharge (OR = 567.12, 95% CI 24.31–13,231.90, p = 0.001) and total protein at discharge (OR = 1.017, 95% CI 1.007–1.027, p = 0.001) remained independent predictors of DGF, whereas postoperative complications lost statistical significance after adjustment (Table 9).

Table 9

Univariate and Multivariate Logistic Regression Analysis of Factors Associated with Delayed Graft Function
Variable	B	OR (Exp(B))	95% CI for OR	p value	B	OR (Exp(B))	95% CI for OR	p value
	Univariate				Multivariate
Recipient sex (male vs female)	−0.683	0.505	0.178–1.436	0.200
Recipient age (years)	0.000	1.000	0.963–1.038	0.983
Kinship (overall)	—	—	—	0.833
└ Spouse	−1.111	0.329	0.058–1.880	0.211
└ Parent/Child	−0.799	0.450	0.084–2.411	0.351
└ Sibling/Grandparent	−1.609	0.200	0.025–1.611	0.131
└ Uncle/Aunt/Cousin	−0.442	0.643	0.048–8.618	0.739
└ Distant relatives (≥ 3rd degree)	—	0.000	Not calculable	0.999
Postoperative complication (yes)	1.374	3.951	1.539–10.145	0.004*	1.327	3.769	.391-36.361	.251
Pre-transplant hypertension	0.718	2.050	0.808–5.198	0.131
Post-transplant hypertension	0.535	1.708	0.634–4.597	0.289
Number of antihypertensive drugs	0.219	1.245	0.791–1.960	0.344
Creatinine at discharge (mg/dL)	4.565	96.062	16.199–569.658	< 0.001*	6.341	567.123	24.307-13231.899	.0001
Urine protein at discharge	0.007	1.007	1.001–1.013	0.026*	0.017	1.017	1.007–1.027	.001
Pre-TX echocardiographic EF (%)	−0.089	0.915	0.836–1.002	0.055
Dialysis duration (months)	0.004	1.004	0.994–1.013	0.460

OR, odds ratio; CI, confidence interval; EF, ejection fraction; Pre-TX, pre-transplantation

In this study, the effects of DGF on short- and long-term clinical outcomes in kidney transplant recipients were comprehensively evaluated. Our findings demonstrate that the development of DGF has a significantly negative impact on patient survival (< 0.001). Notably, the incidence of DGF and related complications was higher in transplants from deceased donors. This can be attributed to factors such as older donor age, hemodynamic instability, and suboptimal perfusion conditions in deceased donors (6, 7).

In our cohort, several clinical and transplant-related factors were associated with the development of DGF. Although recipient age itself was not a significant predictor in univariate analysis, donors in the DGF group were significantly older, underscoring the well-established impact of donor age on early graft performance. Longer pre-transplant dialysis duration and prolonged pre-transplant hypertension were also associated with a higher risk of DGF, reflecting the cumulative burden of cardiovascular and uremic injury before transplantation (8). Donor type emerged as a major determinant of early graft function. DGF occurred far more frequently in recipients of deceased-donor kidneys than in those receiving living-donor grafts (p:0.001), consistent with ischemia–reperfusion injury and prolonged cold ischemia times inherent to deceased donation. Indeed, while the vast majority of patients without DGF received kidneys from living donors, more than one-third of deceased-donor recipients developed DGF. However, ischemia–reperfusion injury and cold ischemia time were not directly evaluated or quantified in the present study, and therefore their contribution to the observed association could not be assessed. Postoperative factors also played an important role. In univariate analysis, the presence of postoperative complications—particularly bleeding—was associated with an increased risk of DGF. However, this association did not persist after multivariate adjustment, suggesting that postoperative events may act as intermediaries rather than independent drivers of DGF (8–11).

Markers of early graft function were the strongest predictors of DGF (8). Higher serum creatinine levels at discharge showed a robust and independent association with DGF in both univariate and multivariate models. In parallel, elevated urine protein levels at discharge were independently associated with DGF, even after adjustment for confounding variables. This finding highlights early post-transplant proteinuria as a marker of acute graft injury, likely reflecting glomerular and tubular damage related to ischemia–reperfusion injury or early endothelial dysfunction (9, 10). Taken together, our findings emphasize that DGF is a multifactorial process influenced by donor characteristics, pre-transplant recipient burden, and early postoperative graft injury. Among these, donor type, discharge creatinine, and early urine protein excretion appear to be the most informative indicators of impaired early graft recovery (8–11).

In our cohort, patients who developed DGF consistently exhibited poorer renal function both in the early postoperative period and during long-term follow-up. GFR was markedly lower in the DGF group at discharge and remained significantly reduced at the 3rd and 6th months, as well as at the 3rd and 6th years after transplantation. Although differences at intermediate time points such as the 1st and 2nd years approached but did not always reach statistical significance, the overall trajectory clearly demonstrated a sustained disadvantage in graft function among recipients with DGF. These findings indicate that DGF should not be regarded as a transient postoperative event, but rather as a condition with long-lasting functional consequences for the renal allograft (12).

A similar pattern was observed when graft function was analyzed according to donor type. Recipients of kidneys from deceased donors had significantly lower post-transplant GFR values at nearly all follow-up time points compared with living donor recipients, with differences persisting for up to seven years. This prolonged functional gap highlights the cumulative impact of ischemia–reperfusion injury and donor-related factors, which are more pronounced in deceased donor transplantation(12–14).

From a pathophysiological perspective, DGF typically reflects acute tubular necrosis secondary to ischemia–reperfusion injury (5). However, accumulating evidence indicates that this initial insult may trigger persistent inflammatory and fibrotic processes, ultimately contributing to chronic allograft nephropathy. Our findings reinforce the need for meticulous early postoperative management in patients with DGF, including careful hemodynamic optimization, avoidance of nephrotoxic exposures, individualized immunosuppressive strategies, and close surveillance of graft function and proteinuria (12–14).

Although our findings are generally consistent with the existing literature, several limitations should be acknowledged. The single-center, retrospective design may limit the homogeneity and generalizability of the sample. Additionally, the relatively small number of patients may have reduced statistical power for certain subgroup analyses. Furthermore, the markedly high odds ratios observed for creatinine at discharge should be interpreted with caution, as this variable demonstrated a skewed distribution and may have disproportionately influenced the magnitude of effect estimates in the regression models.

Nevertheless, the strengths of this study include the comparative assessment of living- and deceased-donor transplants, the availability of long-term follow-up data, and the multidimensional analysis of clinical parameters.

In this study, delayed graft function (DGF) was associated with significantly worse short- and long-term outcomes after kidney transplantation, including reduced patient survival. DGF occurred predominantly in deceased-donor transplants and was closely linked to donor age and early graft injury. Higher serum creatinine and increased urine protein levels at discharge emerged as the strongest independent predictors of DGF, highlighting their value as early markers of graft damage. Importantly, recipients with DGF demonstrated persistently lower GFR during follow-up, indicating that DGF is not a transient event but a determinant of long-term allograft dysfunction. These findings underscore the need for early risk stratification and intensive post-transplant monitoring in high-risk patients.

Ethics approval and consent to participate: The study protocol was approved by the hospital’s Clinical Research Ethics Committee (Decision No. 179; 2024) and was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Due to the retrospective nature of the study and the use of anonymized data, the requirement for informed consent to participate was waived by the Clinical Research Ethics Committee.

Consent for publication: Not applicable.

Declaration regarding organ procurement: The authors confirm that no transplant organs were procured from prisoners or other institutionalized individuals, and all kidney transplant procedures included in this study were performed in accordance with national regulations and ethical standards.

Availability of data and materials: The datasets used and/or analyzed during the current study are not publicly available due to institutional data protection policies but are available from the corresponding author upon reasonable request.
Corresponding author: Jehat KILIÇ, MD
E-mail: [email protected]

Competing interests: The authors declare that they have no competing interests.

Funding: This study received no external funding.

Authors’ contributions: All authors contributed to the study. R.E. contributed to the study design; Ö.F.A. to data collection; J.K. and C.V. to statistical analysis; and J.K., D.K.K., and R.D. to manuscript writing and critical revision. All authors approved the final manuscript and take responsibility for its content.

Acknowledgements: The authors declare no acknowledgements.

Clinical Trial Number: Not applicable.

Conflicts of interest:

There are no conflict of interest

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No competing interests reported.

Delayed Graft Function and Its Impact on Short- and Long-Term Outcomes After Kidney Transplantation

Status:

Version 1

Abstract

Introduction:

Methods

Results

Conclusion

INTRODUCTION

MATERIALS AND METHODS

Inclusion criteria

Exclusion criteria

RESULTS

CKD: Chronic Kidney Disease

TX, transplantation; Post-TX, post-transplantation; MI, myocardial infarction; COVID-19, coronavirus disease 2019

OR, odds ratio; CI, confidence interval; EF, ejection fraction; Pre-TX, pre-transplantation

DISCUSSION

CONCLUSION

Declarations

References

Additional Declarations

Status:

Version 1