Abstract
Background/Aim: This study investigated the follow-up rate of living kidney donors and explored the factors related to continuous follow-up and remnant renal function, enabling the optimal management of living kidney donors. Patients and Methods: We retrospectively evaluated 180 living kidney donors who underwent donor nephrectomies at our institute. Clinical information was obtained from medical charts, and remnant renal function was defined as the estimated glomerular filtration rate 12 months after donor nephrectomy. Results: Overall, 6/180 donors (3.3%) were lost to follow-up within a year, and the follow-up rate gradually declined yearly. Independent risk factors for loss to follow-up included a follow-up period <60 months and graft survival of the recipient (p=0.002 and p=0.043, respectively). Recipient survival was correlated with loss to follow-up; however, this was not significant (p=0.051). Regarding remnant renal function, age ≥60 years, preoperative estimated glomerular filtration rate <74 ml/min/1.73 m2, and a Δsingle-kidney estimated glomerular filtration rate <9.3 ml/min/1.73m2 were independent risk factors for poorly preserved remnant renal function (p=0.036, p<0.0001, and p<0.0001, respectively). Using propensity score matching to adjust for preoperative factors, a Δsingle-kidney estimated glomerular filtration rate <9.3 ml/min/1.73 m2 was the only significant postoperative factor for poorly preserved remnant renal function (p=0.023). Conclusion: An increased 5-year follow-up rate could lead to an increase in long-term follow-up, and recipient prognosis may be correlated with the living kidney donor follow-up status. Furthermore, Δsingle-kidney estimated glomerular filtration rate was identified as a factor for establishing the optimal precision follow-up management of living kidney donors.
- Donor nephrectomy
- follow-up
- living kidney donor
- living donor kidney transplantation
- remnant renal function
The gross shortage of deceased donor kidneys has led to the widespread use of living kidney donors (LKDs). Recent advancements in treatment regimens for recipients have improved this situation rapidly, and the treatment outcomes of living kidney transplantation (KT) have been regarded as superior to those of deceased KT in terms of recipient outcomes (1-3). These conditions have encouraged the use of living KT, leading to an expanded indication for LKDs, known as marginal donors (MDs).
The mortality risk of LKDs has been reported to be lower than that of the age- and sex-matched population (4, 5). However, another study reported a higher long-term risk of mortality in LKDs than in the age- and sex-matched population, and the difference in the Kaplan-Meier curve was observed approximately 15 years after donor nephrectomy (DN) (6). Similarly, a previous meta-analysis suggested that LKDs tended to have a slightly higher risk of developing severe chronic kidney disease (CKD) and end-stage renal disease (ESRD) than the healthy population (7), and it also reported a significantly higher long-term risk in LKDs than in the age- and sex-matched population (6). Furthermore, Kido et al. reported that persistent proteinuria, acute cardiovascular events, severe infection, and hospitalization because of accelerating factors for CKD were independent predictors of ESRD in LKDs. They also reported that there were no preoperative factors indicating a significant risk of ESRD (8). Another study reported the timing of ESRD to be 27.1±9.8 years after DN, and they demonstrated that ESRD was caused by diabetes mellitus (DM) or hypertension in approximately 50% of the LKDs who developed ESRD (9).
Therefore, establishing an optimal strategy for the long-term personalized follow-up of LKDs is warranted, as LKDs are widely used. A previous report from Japan showed that the follow-up rates of LKDs were 83.9%, 74.6%, and 59.2% at 1, 2, and 5 years after DN, respectively, and that approximately 75% of those not being followed up dropped out (10). Considering the long-term risks of mortality and ESRD in this population, an increase in the follow-up rate 5-10 years after DN is important, and informing LKDs of this before and after DN may lead to improved long-term prognoses and avoidance of progression to ESRD.
Previously, we reported the prognoses and remnant renal functions (RRFs) of LKDs (11-14). In this study, we focused on follow-up after DN and RRF in LKDs and aimed to explore the factors related to being lost to follow-up and the preservation of RRF. This is important because considering the factors involved in missing follow-ups and RRF may lead to the improved and optimal postoperative personalized management of LKDs.
Patients and Methods
Patient selection, data collection, and study design. This study was approved by the Research Ethics Committee of Nara Medical University through a centralized institutional review board (project identification code: 3176). The requirement for patient informed consent was waived because of the retrospective nature of this analysis, and the study was conducted in accordance with the study protocol and the provisions of the Declaration of Helsinki (2013). This study included 180 consecutive donors who underwent DN at our institute between April 2002 and March 2022. We retrospectively reviewed the medical charts of the donors and obtained their clinical information.
Definition of various factors. The follow-up rate was calculated by dividing the actual number of LKDs by the estimated number of LKDs. The follow-up status was investigated using March 31, 2023, as the final confirmation date. The estimated glomerular filtration rate (eGFR), calculated using the Chronic Kidney Disease Epidemiology Collaboration equation (15), was used to evaluate the renal function of the LKDs and the eGFR at 12 months after DN was used as a measure of the RRF for analysis.
Surgical CKD was defined as decreased renal function solely due to organ procurement, whereas medical CKD was defined as decreased renal function due to both organ procurement and the presence of complications that could be risk factors for CKD progression, including DM, hypertension, and dyslipidemia. Donor conditions were evaluated according to the Japanese LKD guideline (16) and defined as standard donors (SDs) or MDs (Table I). Furthermore, we investigated the association between single-kidney estimated glomerular filtration rate (skeGFR) and RRF. According to a previous report by van der Weijden et al. (17), an early increase or decrease in skeGFR was calculated using the following formula: ΔskeGFR=eGFR at three months after DN – (preoperative eGFR/2).
Definition of standard and marginal donors.
Outcomes. The primary outcome of this study was the follow-up rate, while the secondary outcomes included RRF after DN and factors related to missing follow-ups and the preservation of RRF.
Statistical analysis. Continuous variables are reported as medians and interquartile ranges (IQRs), while categorical variables are reported as numbers and percentages. We used the Mann-Whitney U-test, Fisher’s exact test, or chi-squared test for comparisons between groups, as appropriate. These statistical analyses were performed using GraphPad Prism 9.0 (GraphPad Software, San Diego, CA, USA), which was also used to plot figures. Additionally, a Sanky diagram was plotted using the R:4.0.1 (The R Foundation, Vienna, Austria), and survival curves were obtained using the Kaplan-Meier method.
Furthermore, we performed propensity score matching (PSM) using Easy R software (Saitama Medical Center, Jichi Medical University, Saitama, Japan) (18). The baseline characteristics were matched by calculating the propensity score for each patient using a multivariable logistic regression model based on covariates, such as age, preoperative eGFR, body mass index (BMI), hypertension, and dyslipidemia. Moreover, we performed receiver operating characteristic curve analysis to identify cutoff values for continuous variables. Two-sided tests were used in all analyses, for which a p-value <0.05 was considered statistically significant.
Results
Follow-up rate and prognosis. Figure 1A shows the current distribution of the donor status after DN. Of the 180 donors, 104 (57.8%) continued to follow up at our institute, while 55 (30.5%) were lost to follow-up owing to dropping out, 18 (10.0 %) were referred to another hospital, and three (1.7%) died during follow-up (the causes of death were Parkinson’s disease, hepatocellular carcinoma, and B-cell malignant lymphoma). Figure 1B shows the actual follow-up rates in clinical practice. Of the 180 donors, six (3.3%) were lost to follow-up within one year. Notably, the follow-up rate gradually declined every year (1 year, 96.7%; 3 years, 84.0%; 5 years, 80.6%; 10 years, 57.4%; 15 years, 45.5%).
Follow-up rate and prognoses of patient survival and remnant renal function. (A) Division of the living kidney donors (LKD)s according to their follow-up status. (B) Follow-up rates of the LKDs over time. (C) Patient survival rates over time. (D) Sankey diagram showing chronological changes in the estimated glomerular filtration rate (eGFR) within 12 months. DN: Donor nephrectomy; eGFR: estimated glomerular filtration rate.
Prognosis and remnant renal function. As described above, three donors died during the observation period of this study, and the follow-up periods of these donors were 211, 139, and 68 months. In general, the survival rate gradually declined at 5 years postoperatively (Figure 1C).
Regarding renal function, the Sankey diagram showed an early trend in eGFR decrease after DN (Figure 1D). Of 180 donors, 94 (52.2%) had an eGFR <80 ml/min/1.73 m2 preoperatively, and these donors were confirmed to have renal functions that met the living donor criteria by inulin, radioisotope, and creatinine clearance methods. However, 1 year after DN, 97 donors (55.8%) had eGFRs of 45-60 ml/min/1.73 m2, 31 (17.8%) donors had eGFRs ≥60 ml/min/1.73 m2, and 46 (26.4%) had eGFRs of 30-4 ml/min/1.73 m2.
We also evaluated chronological changes in renal function in 174 donors after one year and in 118 donors after five years. We observed that the RRF gradually improved after three months as the nadir and was approximately 60% of the preoperative renal function (Figure 2A and B). Furthermore, when comparing patients with surgical CKD (n=127) and those with medical CKD (n=47), there was a significant difference in eGFRs in both the postoperative (three months, p=0.0022; 12 months, p=0.0014) and the preoperative conditions (Figure 2C; p=0.0033) between these groups. This difference gradually decreased over time after DN, and we did not observe a significant difference four years after DN (Figure 2D).
Chronological changes in remnant renal function. (A) Estimated glomerular filtration rate (eGFR) of the living kidney donors (LKDs) over 12 months after donor nephrectomy (DN). (B) eGFR of the LKDs over 5 years after DN. (C) eGFR of the LKDs over 12 months after DN, according to their chronic kidney disease (CKD) type (surgical or medical). (D) eGFR of the LKDs over 5 years after DN, according to their CKD type (surgical or medical). (E) eGFR of the LKDs over 12 months after DN, according to their donor type (standard or marginal). (F) eGFR of the LKDs over 5 years after DN, according to their donor type (standard or marginal). RRF: Remnant renal function.
Additionally, when comparing SDs (n=118) and MDs (n=56), these groups showed a significant difference in eGFRs both postoperatively (three months, p=0.0002; 12 months, p=0.0002) and preoperatively (Figure 2E; p<0.0001). This significant difference continued until five years after DN (Figure 2F; p=0.0065).
Comparison of donors who continued or were lost to follow-up and exploration of the factors related to loss of follow-up. Table II shows the clinical characteristics of the study cohort (continuous, n=125; lost, n=55). In the continuous group, the median age and BMI at DN were 58 years (IQR=50-63) and 22.8 kg/m2 (IQR=20.8-24.9), respectively, while those for the group lost to follow-up were 54 years (IQR=48-64) and 23.6 kg/m2 (IQR=21.7-25.7), respectively (p=0.42 and p=0.095). Notably, we observed no significant difference in the male and female compositions between the two groups (p=0.25) or in the relationship between donors and recipients (genetically related or unrelated) between the two groups (p=0.33). However, preoperative eGFR tended to be higher in the group lost to follow-up than in the continuous group [p=0.077; 82.1 (IQR=72.0-94.9) vs. 78.5 (IQR=69.4-86.9)]. Additionally, the 24-hour creatinine clearance (24 h CCR) was significantly higher in the group lost to follow-up than in the continuous group [p=0.042; 106.7 (IQR=93.1-125.3) vs. 98.4 (IQR=83.4-114.4)].
Comparison of clinical information between patients with and without follow-up (n=180).
The multivariate logistic regression analysis of the factors predictive for missing follow-ups showed that a follow-up period <60 months and graft survival of the recipient were independent risk factors for missing follow-up [odds ratio (OR)=3.33; 95% confidence interval (CI)=1.56-7.08; p=0.002; and OR=2.46; 95%CI=1.03-5.88; p=0.043, respectively]. Notably, recipient survival tended to be correlated with missing follow-up; however, this did not reach a significant difference (OR=2.43; 95%CI=0.99-5.93; p=0.051) (Table III).
Multivariate analysis of predictive factors for lost follow-up.
Comparison of donors who had good or poor remnant renal function. Table IV shows the clinical characteristics of the study cohort (good preservation, n=128; poor preservation, n=46). In the good preservation group, the median age and BMI at DN were 55 years (IQR=46-62) and 22.9 kg/m2 (IQR=20.8-24.9), respectively, while those of the poor preservation group were 61 years (IQR=58-67) and 23.7 kg/m2 (IQR=22.0-26.4), respectively (p<0.0001 and p=0.023). In contrast, the number of MDs was significantly higher in the poor preservation group than in the good preservation group (p=0.0034). Regarding comorbidities, there was no significant difference in the incidence of DM between the groups (p=0.68); however, hypertension and dyslipidemia were significantly higher in the poor preservation group than in the good preservation group (p=0.0020 and p=0.016, respectively). Furthermore, preoperative renal function was significantly better in the good preservation group than in the poor preservation group (eGFR, p<0.0001; 24h CCR; p=0.012). Additionally, as a postoperative factor, skeGFRs were significantly higher in the good preservation group than in the poor preservation group (p<0.0001), while there was no significant difference in the proportions of new-onset DM and hypertension between the two groups (p=0.61 and p=1.00, respectively).
Comparison of clinical information between good and poor preservation of RRF 12 months after DN (n=174).
The multivariate logistic regression analysis of the predictive factors for the poor preservation of RRF showed that an age ≥60 years (OR=3.28; 95%CI=1.08-9.94; p=0.036), preoperative eGFR <74 mL/min/1.73m2 (OR=60.27; 95%CI=15.09-240.77; p<0.0001), and ΔskeGFR <9.3 ml/min/1.73 m2 (OR=10.23, 95%CI=2.97-35.26; p<0.0001) were independent risk factors for the poor preservation of RRF (Table V). After adjusting for preoperative factors using PSM (good preservation group, n=20; poor preservation group, n=20), we found that a ΔskeGFR <9.3 ml/min/1.73 m2 was the only significant postoperative factor for poorly preserved RRF (Figure 3A; p=0.023).
Multivariate analysis of predictive factors for poor preservation of remnant renal function.
Postoperative factors involved in remnant renal function, as well as the summary of this study. (A) Adjusted preoperative conditions between living kidney donors (LKDs) with good and poor preservation of remnant renal function (RRF). (B) Summary of the conclusions of our study. HTN: Hypertension; DM: diabetes mellitus; MD: marginal donor; skeGFR: single-kidney estimated glomerular filtration rate; BMI: body mass index; ESRD: end-stage renal disease.
Discussion
The present study showed that approximately 30% of LKDs were lost to follow-up. Moreover, a follow-up period of <60 months and graft survival of the recipients were independent factors for being lost to follow-up, while factors, such as age or the relationship between LKDs and the recipients were not correlated with missing follow-up. Regarding RRF, approximately 50% of LKDs had eGFRs of 45-60 ml/min/1.73 m2 a year after DN, and the RRF gradually improved with the nadir at 3 months after DN. Additionally, an age ≥60 years, preoperative eGFR <74 ml/min/1.73 m2, and ΔskeGFR <9.3 ml/min/1.73 m2 were independent factors for the poor preservation of RRF. However, after adjusting for preoperative factors, a ΔskeGFR <9.3 ml/min/1.73 m2 was the only factor related to the poor preservation of RRF. Figure 3B summarizes the results of the study.
Long-term follow-up is important for LKDs because events associated with mortality and ESRD often occur 310 years postoperatively. Therefore, paying attention to LKDs who have lost their recipients or graft function could lead to an increased follow-up rate and a personalized follow-up schedule, considering ≥5 years may be important for LKDs with skeGFRs <9.3 ml/min/1.73 m2.
In Japan, the 5-year follow-up rate of LKDs after DN is reportedly 21.3-59.2% (8, 10). However, in this study, the 5-year follow-up rate was 80.6%, which was better than that of previous studies. The features of our institute may be one of the reasons for this, as ours is the sole transplant facility in the Nara Prefecture, and there is a tendency for follow-ups to continue at our single facility. A previous report from the United States showed that the follow-up rates at 6, 12, and 24 months were 67%, 60%, and 50%, respectively, and various factors, such as younger age, lower educational attainment, or centers performing >40 LKD transplantations yearly were correlated with missing follow-up (19). Compared to this report, our follow-up rate was relatively higher. Notably, insurance and educational systems differ between countries; therefore, comparison or interpretation of these differences is difficult. However, as the widespread use of LKDs is increasingly common, an evaluation of the importance of long-term follow-up for LKDs is required. In this study, recipient factors were included as candidates for missing follow-up, and poor patient and graft prognoses tended to be risk factors for being lost to follow-up. Therefore, consideration of recipient statuses could also lead to the long-term follow-up of LKDs.
The preservation of RRF is controversial at any time. In fact, in LKDs, the RRF is approximately 60-70% of the preoperative eGFR, and a prospective controlled observational study revealed that RRF increased even after 3 years of DN (20, 21). Most previous reports, including ours, have focused on the selection of potential donors or the determination of the kidney to be procured, resulting in the avoidance of ESRD (7, 11-14, 22). However, Kido et al. reported that there were no preoperative factors indicating a significant risk for ESRD, whereas some postoperative factors, such as persistent proteinuria, acute cardiovascular events, and severe infection, were correlated with ESRD (8). In our cohort, none of the LKDs had persistent proteinuria, acute cardiovascular events, or severe infections; therefore, these factors could not be evaluated.
Notably, MDs tended to have lower eGFRs at any time after DN than SDs; however, being an MD was not an independent factor for the poor preservation of RRF. In contrast, age, BMI, and eGFR were independent preoperative factors for the poor preservation of RRF, while the ΔskeGFR was an independent postoperative factor. Furthermore, the cohort adjusted for preoperative factors using PSM also revealed that the skeGFR was an independent factor for poor RRF preservation. Previously, Van der Weijden et al. showed that LKDs with a more pronounced increase in the skeGFR had better long-term kidney function, regardless of preoperative renal function and age (17). Therefore, ΔskeGFR is a potential factor for classifying the risk of ESRD in LKDs, resulting in evidence-based personalized clinical practice.
Consequently, long-term (at least 10 years) follow-up is important, and follow-up becomes even more important 10 years after DN because of mortality, ESRD, cardiovascular disease, and cancer risks (6, 8, 9, 23, 24). The Kidney Disease: Improving Global Outcomes Clinical Practice Guidelines recommend a follow-up at least once annually after DN (25). Considering the risks mentioned above, annual follow-up may be sufficient for up to 10 years after DN; however, a shorter follow-up period might be appropriate for some LKDs 10 years after DN. Moreover, renal rehabilitation can be used to prevent CKD progression in LKDs with poor RRF (26). Therefore, establishing a follow-up schedule based on these risks and life expectancies may play an important role in improving the prognoses of LKDs.
Study limitations. First, the data from LKDs were obtained from a single institution, the sample size was small, and the study was retrospective. Additionally, the follow-up period was too short to evaluate the long-term outcomes of the prognoses and RRF in LKDs. Therefore, careful interpretation of the results is necessary.
Conclusion
An increase in the 5-year follow-up rate could lead to an increase in the long-term follow-up rate of LKDs. Additionally, the simultaneous consideration of recipient prognoses and graft survival may be important in avoiding the decreasing follow-up rate in LKDs. Most events, such as death, ESRD, and cardiovascular disease, occur 10 years or more after DN. Therefore, education on the importance of long-term follow-up should be continued, and postoperative factors for detecting LKDs at a high risk of ESRD should be explored. Our findings indicate the ΔskeGFR as a potential candidate for a predictor of ESRD, which may lead to precision management.
Acknowledgements
The Authors would like to thank all patients who participated in this study for their important contributions. The Authors also wish to thank Ms. Mariko Yoshimura (Department of Urology, Nara Medical University, Nara, Japan) for her invaluable help in obtaining and summarizing the data used in this study. Furthermore, the Authors would like to thank Editage (www.editage.com) for English language editing.
Footnotes
Authors’ Contributions
S.H, T.Y, and K.F contributed to conception and design. S.H, M.T, K.I, T.N, K.O, Y.M, D.G, Y.N, M.M, and K.T contributed to the acquisition of patient data, analysis of data, and interpretation of data. S.H, M.T, N.T, and T.Y performed the treatment. All Authors have been involved in drafting the manuscript and revising it critically for important intellectual content and approved the version to be published. All Authors have participated sufficiently in this work to take public responsibility for appropriate portions of the content.
Funding
No funding was obtained for the present study.
Conflicts of Interest
The Authors declare that they have no competing interests in relation to this study.
- Received March 13, 2024.
- Revision received April 9, 2024.
- Accepted April 10, 2024.
- Copyright © 2024, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
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