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ARTICLE
Correlation and Prediction of Living-Donor Remaining Function by Using Predonation Computed Tomography-Based Volumetric Measurements: Role of Remaining Kidney Volume

Objectives: Kidney volume in healthy living donors may serve as a surrogate marker of renal function. Here, we evaluated whether preserved kidney volume correlated with and could predict donor renal function at 2 years postdonation using the CKD-EPI estimated glomerular filtration rate equation.

Materials and Methods: Healthy living donors (n = 208) with computed tomography volume measurements were evaluated for renal function before and after donation. Preserved kidney volume was adjusted to body surface area. Demographic characteristics (including race/ethnicity and sex) and renal function variables of donors were analyzed for postdonation renal function.

Results: Donor mean age was 39.4 ± 10.7 years (36.2% males, 91.9% white). Median adjusted preserved kidney volume was 180.6 mL. At 2 years postdonation, median estimated glomerular filtration rate was 62.4 mL/min (interquartile range, 54.8-73.2 mL/min). Predonation estimated glomerular filtration rate, age, and adjusted preserved kidney volume were found to be inde-pendent predictors of 2-year estimated glomerular filtration rate (P < .001). We further analyzed data by stratifying preserved kidney volumes into tertiles. Mean 2-year estimated glomerular filtration rates were 57.9 ± 12, 65 ± 16, and 73 ± 17 mL/min for lowest to highest tertile groups, respectively (P < .05). The odds ratio of having a 2-year postdonation estimated glomerular filtration rate of < 60 mL/min for donors in the lowest tertile group was 3.51 (95% confidence interval, 1.9-6.4; P < .001), whereas the risk for donors in the highest tertile group was 0.23 (95% confidence interval, 0.12-0.44; P < .001). Sensitivity analysis result was 0.764 (95% confidence interval, 0.69-0.82; P = .005) for adjusted preserved kidney volume and estimated glomerular filtration rate of < 60 mL/min.

Conclusions: Remaining kidney volume before donation correlated with and predicted estimated glomerular filtration rate after donation. Remaining kidney volume should be assessed when selecting kidneys from healthy donors.


Key words : CKD-EPI, Donor volume, Renal function

Introduction

The careful assessment and prediction of donor residual renal function are of utmost importance when considering living-donor nephrectomy due to the risk of leaving the donor with a detrimental lower renal function.1,2 Although many studies to date have investigated donor factors associated with recipient renal function and outcomes, scarce data are available on factors associated with renal function in the remaining kidney after donation.3-5 Kidney volume as a surrogate marker of nephron mass and renal function has been shown by some authors to be a good predictor of recipient renal function.3,4,6-8 Kidney volume adjusted to body size has been proposed to be a useful aid in renal function estimation before kidney donation.9 There is also new evidence that unilateral nephrectomy in healthy individuals is associated with subtle cardiovascular structural and functional changes in donors after 1 year.10,11

Many different equations and measurements have been previously used to calculate donor kidney function. The CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) formula has been proposed to possibly be a more accurate assessment of healthy living donors than the Modification of Diet in Renal Disease (MDRD) formula.12-15 The MDRD eGFR has the potential to underestimate the true measured GFR.

Computed tomography (CT) scans with 3-dimen-sional reconstruction are used for preoperative evaluation of living kidney donors. Apart from giving anatomic details of the kidney, vasculature, and collecting systems, these scans can also be used to reliably estimate kidney volume.16,17 We and others have shown that it is a valid tool to serve as a surrogate measure of renal function and to assess split renal function.8

We thus hypothesized that the remaining kidney volume may impact donor renal function after donation, just as it has been shown and proposed as a predictor of recipient graft function. Our aim was to evaluate whether remaining preserved kidney volume (PKV) predicts donor renal function 2 years after donation as measured by the CKD-EPI equation. We chose this time point because it is now mandated for transplant centers to follow donors for 2 years after donation and because, as the more important physiologic fact, any changes in functional adaptation or hyperfiltration would have adequately occurred and stabilized by 2 years. Therefore, this time point would be ideal to study long-term donor outcomes versus earlier time points of 6 months or 1 year after donation.

Materials and Methods

We retrospectively reviewed data of patients who underwent laparoscopic living-donor nephrectomy at our institution between January 2008 and November 2012. This study was approved by our institutional review board, with data collected from an institutional review board-approved database. The clinical and research activities being reported are consistent with the Principles of the Declaration of Istanbul as outlined in the Declaration of Istanbul on Organ Trafficking and Transplant Tourism.

All donors underwent preoperative imaging evaluation by CT scan with 3-dimensional recon-struction. Kidney volume was measured by an automated segmentation algorithm from the 1-mm images reconstructed at 0.8-mm intervals. Methods of volume calculations have been described in our prior publication and have shown good correlation with nuclear split renal function scans.15 At our center, our selection policy is to not accept donors for living donation if the difference between the 2 kidney volumes is greater than 20%. Selection of laterality of the kidney is based on anatomy and surgical aspects of the donor kidneys, with an attempt to leave the donor with the higher functioning kidney.

Total kidney volume for each donor was defined as the sum of the volume of both kidneys. An adjusted PKV for donor body surface area (BSA) was calculated for each side (adjusted kidney volume [1 cm3/1.73 m2] = kidney volume [cm3] × 1.73/donor BSA [m2]). Similar methods have been previously used to adjust graft kidney volume to recipient BSA.

We used the following formula to calculate the PKV ratio (or split kidney volume; %): (PKV ratio [%] = PKV [cm3] × 100/total kidney volume [cm3]). For each donor, estimated glomerular filtration rate (eGFR) was determined using the CKD-EPI formula before surgery and at 2 years after donation.18 Donors (n = 52; 20% of cohort) with missing renal follow-up laboratory results at 2 years were not included in the postdonation correlation studies.

Statistical analyses

To assess outcomes, we analyzed predictors of eGFR at 2 years (determined using the CKD-EPI formula) by simple and multiple linear regression analyses. Variables included age, sex, BSA, side, preoperative eGFR, and PKV. Only significant variables were included for multivariate analysis. Preserved kidney volume and PKV ratio were analyzed as continuous variables. For further subanalysis, the adjusted PKV was divided into tertiles (low, medium, and high). For dichotomous analysis, a 2-year eGFR of < 60 mL/min was chosen as the cutoff. Median (interquartile range) and frequency (%) were used to describe continuous and categorical variables, respectively. Statistical analyses were carried out using SPSS software version 24 (SPSS, Chicago, IL, USA). Statistical significance was defined as P < .05.

Results

We identified and included 208 donors who had valid CT volume measurements during the study period. Baseline demographics of all donors are shown in Table 1. The distribution frequency of adjusted PKV is shown in Figure 1A. The mean and median pre- and postdonation eGFR (determined with CKD-EPI) box plots are shown in Figure 2, and the distribution frequency of 2-year eGFR is shown in Figure 1B.

There were notable significant expected dif-ferences between male and female donors and donor volumes as shown in Table 2. However, we observed no significant differences between predonation eGFR (determined with CKD-EPI) of men and women versus their absolute change in eGFR at 2 years. No significant difference was shown in adjusted PKV versus side of nephrectomy (mean left nephrectomy volume of 179 ± 31 mL vs right nephrectomy volume of 183.2 ± 33 mL; P = .32).

Table 3 shows correlations among different variables. Adjusted PKV significantly correlated with age, predonation serum creatinine level, predonation eGFR, postdonation 2-year eGFR, and 2-year postdonation serum creatinine level. We observed no significant correlation of adjusted PKV with BSA or body mass index alone. The level of correlation of adjusted PKV with 2-year eGFR was modest, with a Pearson correlation of 0.456, but was weaker for 2-year serum creatinine, with a Pearson correlation of -0.255. The direct correlation between 2-year eGFR and adjusted PKV is shown in Figure 3. We observed no correlation between total kidney volume and PKV ratio (Pearson correlation of -0.30; P = .632).

We also observed no differences in PKV ratio when compared between sex, race, tertile groups, and postdonation eGFR < 60 mL/min.

At 2 years after donation, the proportion of donors with eGFR (determined with CKD-EPI) of > 90, 60-89, 45-59, and < 45 mL/min/1.73m2 was 10.0%, 45.6%, 37.1%, and 7.2%, respectively.

Predonation eGFR had a weak but significant correlation with adjusted PKV (Pearson correlation of 0.376; P < .001). In further receiver operating charac-teristic (ROC) curve analysis, the areas under the curve (AUC) showed 0.805 (95% confidence interval [CI], 0.653-0.956; P = 0.07) for predonation eGFR > 60 mL/min, 0.730 (95% CI, 0.654-0.806; P < .001) for predonation eGFR > 80 mL/min, 0.639 (95% CI, 0.564-0.714; P = .001) for predonation eGFR > 90 mL/min, and 0.666 (95% CI, 0.601-0.732; P < .001) for predonation eGFR > 100 mL/min (data not shown).

Predictors of 2-year eGFR were then assessed by multiple linear regression analyses. Adjusted PKV was found to be an independent predictor of 2-year eGFR, as shown in Table 4.

Further subanalysis was done to assess the strength of the prediction and correlation between adjusted PKV and remaining renal function by dividing the study population of donor adjusted PKV into tertiles (low, medium, and high; Figure 4). Detailed donor variables of the tertile groups are presented in Table 5. Predonation and 2-year postdonation serum creatinine levels, BSA, and body mass index did not differ significantly between the 3 tertile groups. However, predonation eGFR and 2-year postdonation eGFR (both determined with CKD-EPI) were significantly correlated with each tertile group, along with age, female sex, and 24-hour measured creatinine clearance. Patients in each adjusted PKV tertile were then cross-tabulated with eGFR < 60 or ≥ 60 mL/min (Table 6). We observed a significantly higher proportion of donors in the lowest tertile group with eGFR < 60 mL/min (47.8% vs 20.7%; P < .05) and a significantly lower proportion of donors with eGFR of < 60 mL/min in the highest tertile group (18.5% vs 49.1%; P < .05). There was no significant difference in proportions of donors in the middle tertile group.

The sensitivity and specificity for risk of eGFR (per CKD-EPI) of < 60 mL/min were maximized at cutoff of adjusted PKV of 181 mL, giving sensitivity of 0.67 and specificity of 0.71 with ROC analysis and an AUC of 0.747. The sensitivity and specificity were maximized for risk of eGFR < 60 mL/min at PKV of 105.9 mL, giving sensitivity of 0.60 and specificity of 0.88 with ROC analysis and an AUC of 0.834. For adjusted PKV and eGFR together, whether summed or averaged, the sensitivity and specificity were maximized at 281.3 mL, giving sensitivity of 0.71 and specificity of 0.79 with ROC analysis and an AUC of 0.826.

The odds ratio of 2-year postdonation eGFR < 60 mL/min for donors in the lowest adjusted PKV tertile group was 3.51 (95% CI, 1.9-6.4; P < .001). Conversely, the odds ratio of having an eGFR < 60 mL/min for donors in the highest adjusted PKV tertile group was 0.23 (95% CI, 0.12-0.44; P < .001). Box plots of 2-year eGFR (per CKD-EPI) for the 3 tertile groups are presented in Figure 5.

Key variables were also subanalyzed by dividing donors with 2-year eGFR data (per CKD-EPI) into 2 groups: those with eGFR < 60 mL/min and those with eGFR ≥ 60 mL/min (Table 7). Those with 2-year eGFR < 60 mL/min had significantly lower adjusted PKV (165 ± 29 mL) than those with 2-year eGFR ≥ 60 mL/min (mean adjusted PKV = 194 ± 30 mL).

To assess the ability of adjusted PKV to predict eGFR (per CKD-EPI) of < 60 mL/min, we constructed additional ROC curve and AUC assessments (Figure 6). Our results showed AUC of 0.763 (95% CI, 0.69-0.82), which was statistically significant (P < .005).

We also analyzed differences between the selected and remaining kidneys of our donors. Our analyses showed mean and median volume differences of only 3% between the kidneys, with a mean and median absolute volume difference of 8 and 5 mL, respectively. This is likely due to our selection process policy of laterality, as mentioned in Materials and Methods. Of total donors, 21% had greater than 10% difference between the 2 kidneys. We observed no correlations regarding predonation to post-donation drop in eGFR (Pearson coefficient = -0.11; P = .932) in this group. Only a minority of donors (3%) had difference of 20% or greater, which did not reach statistical difference (Pearson coefficient 0.647; P = .060) when we compared predonation to postdonation eGFR drop.

Discussion

Preoperative living-donor volume assessment before kidney donation in our opinion is an important component of living donation to ascertain whether residual renal function is sufficient for the kidney donor and to ensure that the recipient kidney graft has acceptable function. Living-donor renal function is assessed by using an endogenous filtration marker (eGFR) or creatinine clearance; however, measure-ment methods are difficult, time consuming, and costly. Volume assessment adds another dimension and facet to the tools available to evaluate whether the donor has adequate renal function in the remaining kidney. Many variables have been shown to correlate with preoperative CT-estimated kidney volume, including measured creatinine clearance, eGFR, and graft weight. Hence, kidney volume serves as a surrogate marker of nephron mass.16,19 Herts and associates showed that a kidney volume-based model outperformed the MDRD formula in estimating unadjusted GFR in renal donors.9 Other authors have also reported that kidney volume estimated by CT scan was a good predictor of graft renal function, with larger kidney volume adjusted for recipient’s BSA correlated with higher graft function at 2 years.3,4,7,17 Similarly, another study showed that kidney transplant recipients in the highest tertile group for ratio between donated kidney cortical volume and recipient pretransplant weight have higher mean eGFR values at all time points over 24 months than recipients in the lower tertiles. In addition, recipients in the highest tertile had significantly lower risk of development of diminished renal function at 12 and 24 months after transplant.20

We found PKV adjusted for BSA (adjusted PKV) to be an independent predictor of donor renal function at 2 years. We also showed that there was graded risk of having of an eGFR of < 60 mL/min if the remaining donor volume is in the lowest tertile. This finding is consistent with and supports and extends a previous report by Yakoubi and associates who had studied the same assessment at 1 year by using the MDRD equation and a study from Jeon and associates who found that lower preoperative remaining kidney volume adjusted for BSA was correlated with delayed recovery of renal function in donors at 6 months postsurgery.5,19 However, these 2 studies are quite different from our study as they used the MDRD equation and used earlier time points for outcomes.

We noted an average reduction in eGFR of 33 mL/min (range, 25-44 mL/min), which is similar to the average decrease of 26 mL/min/1.73 m2 (range, 8-50 mL/min/1.73 m2) reported by others.1,21 A cutoff of < 60 mL/min/1.73 m2 after renal donation was used to define a cutoff for renal function. However, the labeling of living donors as having chronic kidney disease (CKD) after renal donation is incorrect and inappropriate. Most authors argue that the high rate of being classified as having moderate CKD after kidney donation is artifactual and more of a technical categorization. The definition of CKD depending on GFR levels does not consider other factors, such as cause of CKD or age. As such, donors do not have any “disease” in the kidney, except for a reduction in total GFR compared with before donation and also should not have any progressive disease. Donors are also generally healthy, and their muscle mass should not change over time compared with certain true CKD states where there can be loss of muscle and protein due to intrinsic and metabolic systemic disease states. Similar to our results, Barri and associates found stage 3 CKD after uninephrectomy in 53 donors (27%) as measured by iothalamate GFR and in 73 donors (38%) as measured by Cockroft-Gault eGFR.22 In addition, in a case series from the University of Minnesota, 35% of donors had eGFR < 60 mL/min (per MDRD); however, when measured by iohexol clearance, only 14% had eGFR < 60 mL/min.23

We acknowledge that not having iothalamate measurements at 2 years postdonation limited the accuracy of our data. However, in routine clinical practice, iothalamate measurements are rarely performed. Our data provide insight to the transplant community, particularly for donor follow-up labo-ratory results, which we used in cross-evaluation with predonation kidney volume. Our data can also be used to educate donors and primary care physicians and nontransplant nephrologists, who are quite often the responsible health care team of donors over the long term. Knowledge of remaining volume can predict eGFR and avoid occasional unnecessary “red flags.” This knowledge can also be used in insight with regard to on-going laboratory and clinic visits if the donor is mislabeled as having CKD per insurance. However, we must acknowledge that some donors may truly develop CKD, although rarely, which warrants further long-term follow-up.

Recent data have shown that donors may develop minor cardiovascular structural and functional changes, such as increased left ventricular mass and mass-to-volume ratio and decreased aortic dis-tensibility and global circumferential strain.10,11 Donors may also undergo biochemical changes and show higher serum uric acid, parathyroid hormone, and fibroblast growth factor 23, display high-sensitivity C-reactive protein and flow-mediated dilatation, and have higher vascular cell adhesion molecule levels, with some of these independent of blood pressure changes.10,11 Hence, reduced GFR can be regarded as a potential risk factor for cardio-vascular events, although these data have not been proven to be strongly linked with any hard cardiovascular endpoints.24,25 Other studies have shown that all-cause mortality and risk of cardio-vascular events are similar among donors and healthy nondonors, although 1 study indicated a 5% increase in all-cause mortality after 25 years that was attributable to donation.26

Apart from the use of split renal function to decide on laterality, volumetric measurements should be used to aid in selecting the correct laterality. Like many other centers, we routinely utilize CT-based volumes, and every effort is made to leave the donor with the higher functioning or larger volume kidney. This is partly reflected by our high right-sided donor nephrectomy rate (36.5%) compared with national US average of less than 15%.27 Although anecdotally many centers use a 10% or 20% cutoff to select laterality, there are no guidelines as such, and other aspects usually dictate the selection of the side. The intent of this paper was not to study the laterality selection process, as many other biases would then be introduced.

Our study has some other limitations, including its retrospective design, which is known to be associated with bias. However, in studies of living donors, there will likely never be a prospective randomized trial to directly assess the effects of volume on donor or recipient function. Second, there are no standardized methods to measure renal volume.9,19 Computed tomography volumetry tech-niques (modified ellipsoid volume, smart region of interest volume, renal cortex volume) have been utilized, with correlations to preoperative assessments in living donors.28 The voxel method was found to be a more accurate technique and have low interobserver variability; cortical measurements have also been shown to be a reliable technique.8,9,28,29 The voxel method might include some nonfunctional kidney tissue. However, measurement of kidney weight after nephrectomy should also include these nonfunctional kidney tissues. Measuring cortical tissue is also not perfectly accurate due to missing corticomedullary nephron mass and is operator dependent. Another limitation of our study was lack of measured remaining kidney volume at 2 years after donation, as it is possible that there was compensatory growth (as reflected by hyperfiltration) in the actual volume of the remaining kidney. This would require subjecting the donor to another CT angiogram with its associated risks of radiation and contrast. We also did not have measured proteinuria or blood pressure readings after donation, which could have been used to correlate any possible relationship between donor volumes and risk of proteinuria or hypertension.

For this study, renal function was evaluated by the CKD-EPI formula. In a study that used data from the Scientific Registry of Transplant Recipients, 53% of living donors had predonation CKD-EPI eGFR high enough to ensure ≥ 95% probability that predonation measured GFR was ≥ 90 mL/min/1.73 m2, suggesting that measured GFR may not be necessary in a large proportion of donor candidates.30 The CKD-EPI equation is now recommended by KDIGO as the preferred creatinine-based equation and has been shown14 to be more accurate for estimating measured GFR, better in defining CKD prevalence, and more accurate in risk prediction. Many laboratories are now reporting eGFR both per CKD-EPI and MDRD. The MDRD formula can underestimate GFR by between 9 and 29 mL/min in kidney donors.31-33 The best formula (CKD-EPI, MDRD, or the addition of cystatin C to CKD-EPI) to assess healthy donor renal function based on serum laboratory results remains debatable.13,14 Cystatin C is not routinely available in clinical practice; hence, most laboratories assess serum creatinine using either MDRD or CKD-EPI.

Despite the above limitations, our data add to the current literature by suggesting a role of PKV in predicting renal outcomes in the donor. We chose not to analyze donor outcomes at 6 months or at 1 year after donation, as done by Yakoubi and associates,5 due to the possible dynamic hyperfiltration state that may still be occurring at these earlier time points. Adaptation appears to occur between 1 and 2 years after donation. Future studies should explore the relationship between kidney volume and inulin or iothalamate GFR, as it is considered the criterion standard for measuring renal function. Later time points at 5 years or 10 years should also be included in future studies, as other risk factors, such as cardiovascular events or other changes in medical conditions, medications, and weight, were not considered, and these may affect measured serum creatinine.

Our report does not imply that certain donors should be excluded from donation if they fall in the lowest tertile of volume and have a high predicted risk of eGFR of < 60 mL/min after donation. Rather, it adds a tool to be used to decide on laterality if surgically possible and provide more clinical information that can be useful in interpreting follow-up examinations. This is akin to the risk calculators that have been developed for predicting post-donation diabetes, hypertension, or proteinuria and having eGFR of < 60 mL/min or < 30 mL/min or end-stage renal disease, which are useful in selection and counseling. Ultimately, remaining volume in donors could be added as a variable in these risk calculators, although it was outside our scope to develop a comprehensive calculator.

In conclusion, PKV in a living kidney donor, as assessed by preoperative CT scan, represents an independent predictor of remaining renal function in the donor at 2 years after living donor nephrectomy.


References:

  1. Garg AX, Muirhead N, Knoll G, et al. Proteinuria and reduced kidney function in living kidney donors: A systematic review, meta-analysis, and meta-regression. Kidney Int. 2006;70(10):1801-1810.
    CrossRef - PubMed
  2. Doshi M, Garg AX, Gibney E, Parikh C. Race and renal function early after live kidney donation: an analysis of the United States Organ Procurement and Transplantation Network Database. Clin Transplant. 2010;24(5):E153-157.
    CrossRef - PubMed
  3. Poggio ED, Hila S, Stephany B, et al. Donor kidney volume and outcomes following live donor kidney transplantation. Am J Transplant. 2006;6(3):616-624.
    CrossRef - PubMed
  4. Hugen CM, Polcari AJ, Farooq AV, Fitzgerald MP, Holt DR, Milner JE. Size does matter: donor renal volume predicts recipient function following live donor renal transplantation. J Urol. 2011;185(2):605-609.
    CrossRef - PubMed
  5. Yakoubi R, Autorino R, Kassab A, Long JA, Haber GP, Kaouk JH. Does preserved kidney volume predict 1 year donor renal function after laparoscopic living donor nephrectomy? Int J Urol. 2013;20(9):931-934.
    CrossRef - PubMed
  6. Young A, Kim SJ, Garg AX, et al. Living kidney donor estimated glomerular filtration rate and recipient graft survival. Nephrol Dial Transplant. 2014;29(1):188-195.
    CrossRef - PubMed
  7. Sikora MB, Shaaban A, Beddhu S, et al. Effect of donor kidney volume on recipient outcome: does the "dose" matter? Transplantation. 2012;94(11):1124-1130.
    CrossRef - PubMed
  8. Halleck F, Diederichs G, Koehlitz T, et al. Volume matters: CT-based renal cortex volume measurement in the evaluation of living kidney donors. Transpl Int. 2013;26(12):1208-1216.
    CrossRef - PubMed
  9. Herts BR, Sharma N, Lieber M, Freire M, Goldfarb DA, Poggio ED. Estimating glomerular filtration rate in kidney donors: a model constructed with renal volume measurements from donor CT scans. Radiology. 2009;252(1):109-116.
    CrossRef - PubMed
  10. Yilmaz BA, Caliskan Y, Yilmaz A, et al. Cardiovascular-renal changes after kidney donation: one-year follow-up study. Transplantation. 2015;99(4):760-764.
    CrossRef - PubMed
  11. Moody WE, Ferro CJ, Edwards NC, et al. Cardiovascular effects of unilateral nephrectomy in living kidney donors. Hypertension. 2016;67(2):368-377.
    CrossRef - PubMed
  12. Shaffi K, Uhlig K, Perrone RD, et al. Performance of creatinine-based GFR estimating equations in solid-organ transplant recipients. Am J Kidney Dis. 2014;63(6):1007-1018.
    CrossRef - PubMed
  13. Matsushita K, Mahmoodi BK, Woodward M, et al. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate. JAMA. 2012;307(18):1941-1951.
    CrossRef - PubMed
  14. Stevens LA, Schmid CH, Greene T, et al. Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2. Am J Kidney Dis. 2010;56(3):486-495.
    CrossRef - PubMed
  15. Diez A, Powelson J, Sundaram CP, et al. Correlation between CT-based measured renal volumes and nuclear-renography-based split renal function in living kidney donors. Clinical diagnostic utility and practice patterns. Clin Transplant. 2014;28(6):675-682.
    CrossRef - PubMed
  16. Hwang HS, Yoon HE, Park JH, et al. Noninvasive and direct measures of kidney size in kidney donors. Am J Kidney Dis. 2011;58(2):266-271.
    CrossRef - PubMed
  17. Dias J, Malheiro J, Almeida M, et al. CT-based renal volume and graft function after living-donor kidney transplantation: Is there a volume threshold to avoid? Int Urol Nephrol. 2015;47(5):851-859.
    CrossRef - PubMed
  18. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-612.
    CrossRef - PubMed
  19. Jeon HG, Lee SR, Joo DJ, et al. Predictors of kidney volume change and delayed kidney function recovery after donor nephrectomy. J Urol. 2010;184(3):1057-1063.
    CrossRef - PubMed
  20. Juluru K, Rotman JA, Masi P, et al. Semiautomated CT-based quantification of donor kidney volume applied to a predictive model of outcomes in renal transplantation. AJR Am J Roentgenol. 2015;204(5):W566-572.
    CrossRef - PubMed
  21. Kasiske BL, Anderson-Haag T, Israni AK, et al. A prospective controlled study of living kidney donors: three-year follow-up. Am J Kidney Dis. 2015;66(1):114-124.
    CrossRef - PubMed
  22. Barri YM, Parker T, 3rd, Daoud Y, Glassock RJ. Definition of chronic kidney disease after uninephrectomy in living donors: what are the implications? Transplantation. 2010;90(5):575-580.
    CrossRef - PubMed
  23. Ibrahim HN, Foley R, Tan L, et al. Long-term consequences of kidney donation. N Engl J Med. 2009;360(5):459-469.
    CrossRef - PubMed
  24. Garg AX, Meirambayeva A, Huang A, et al. Cardiovascular disease in kidney donors: matched cohort study. BMJ. 2012;344:e1203.
    CrossRef - PubMed
  25. Reese PP, Bloom RD, Feldman HI, et al. Mortality and cardiovascular disease among older live kidney donors. Am J Transplant. 2014;14(8):1853-1861.
    CrossRef - PubMed
  26. Lam NN, Lentine KL, Levey AS, Kasiske BL, Garg AX. Long-term medical risks to the living kidney donor. Nat Rev Nephrol. 2015;11(7):411-419.
    CrossRef - PubMed
  27. Khalil A, Mujtaba MA, Taber TE, et al. Trends and outcomes in right vs. left living donor nephrectomy: an analysis of the OPTN/UNOS database of donor and recipient outcomes--should we be doing more right-sided nephrectomies? Clin Transplant. 2016;30(2):145-153.
    CrossRef - PubMed
  28. Wahba R, Franke M, Hellmich M, et al. Computed tomography volumetry in preoperative living kidney donor assessment for prediction of split renal function. Transplantation. 2016;100(6):1270-1277.
    CrossRef - PubMed
  29. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461-470.
    CrossRef - PubMed
  30. Huang N, Foster MC, Lentine KL, et al. Estimated GFR for living kidney donor evaluation. Am J Transplant. 2016;16(1):171-180.
    CrossRef - PubMed
  31. Barlow AD, Taylor AH, Elwell R, Buttress AS, Moorhouse J, Nicholson ML. The performance of three estimates of glomerular filtration rate before and after live donor nephrectomy. Transpl Int. 2010;23(4):417-423.
    CrossRef - PubMed
  32. Issa N, Meyer KH, Arrigain S, et al. Evaluation of creatinine-based estimates of glomerular filtration rate in a large cohort of living kidney donors. Transplantation. 2008;86(2):223-230.
    CrossRef - PubMed
  33. Rule AD, Gussak HM, Pond GR, et al. Measured and estimated GFR in healthy potential kidney donors. Am J Kidney Dis. 2004;43(1):112-119.
    CrossRef - PubMed


DOI : 10.6002/ect.2018.0080


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From the Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
Acknowledgements: The authors have no sources of financial support or conflicts of interest to declare. Portions of this manuscript were presented as poster presentations at ATC Meetings in 2016 and 2017. We are also deeply indebted to our living-donor coordinators Tracy Perry, Kelly Coffey, Laura Beckerich, Carol Fountain, and Kathryn Carnes for their dedicated care of our living donors, donor follow-up, accurate data capture, database maintenance, and parts of data collection.
Corresponding author: Asif Sharfuddin, 550 N. Univ Blvd, UH 46202, Indiana University Health Hospital, Indianapolis, IN 46202, USA
Phone: +317 944 4370
E-mail: asharfud@iu.edu