Donor Scoring System for Cadaveric Renal Transplantation

Transcription

1 American Journal of Transplantation 2001; 1: Copyright C Munksgaard 2001 Munksgaard International Publishers ISSN Donor Scoring System for Cadaveric Renal Transplantation Scott L. Nyberg a, *, Arthur J. Matas b, Margaret Rogers e, William S. Harmsen c, Jorge A. Velosa d, Timothy S. Larson d, Mikel Prieto a, Michael B. Ishitani a, Sylvester Sterioff a and Mark D. Stegall a a Division of Transplantation Surgery, Mayo Clinic, Rochester; the b Division of Transplantation, University of Minnesota, Minneapolis; c Section of Biostatistics, and the d Division of Nephrology and Internal Medicine, Mayo Clinic, Rochester; and e The LifeSource, Upper Midwest Organ Procurement Organization, St. Paul, MN, USA * Corresponding author: Dr S. L. Nyberg, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA We studied early renal function in 241 consecutive patients who received cadaveric renal transplants at two different transplantation centers (group 1, n Ω 90; group 2, n Ω 151). Univariate and multivariate analyses of data from group 1 showed a significant correlation between seven donor variables and early renal function after cadaveric renal transplantation. A scoring system was developed from these seven donor variables (cause of death, 0 6 points; history of hypertension, 0 6; final creatinine clearance before procurement, 0 6; age, 0 6; history of diabetes mellitus, 0 3; cold ischemia time, 0 3; and severity of renal artery plaque, 0 3). Data from group 2 were used to validate the donor scoring system and stratify cadaver kidneys on the basis of score: grade A, 0 5 points; grade B, 6 10; grade C, 11 15; and grade D, A significant decline in early renal function was observed with increasing donor score and grade of cadaver kidney. In conclusion, a donor scoring system based on information available at the time of procurement can be used to estimate early graft function after cadaveric renal transplantation and may assist in the allocation of marginal organs. Key words: Delayed graft function, marginal donor, organ allocation Received 1 November 2000, revised and accepted for publication 23 March 2001 Introduction The use of marginal donors has been adopted at many transplant centers in an attempt to address the growing shortage of cadaveric organs for renal transplantation (1). Included in the marginal donor pool are kidneys with long cold ischemic time, kidneys from donors of advanced age, and donors with a history of hypertension or diabetes (2 10). Other factors that may influence the marginal status of a donor kidney are donor creatinine clearance at procurement, percentage of nephrosclerosis on donor renal biopsy, donor renal arterial plaque, donor recipient cytomegalovirus status, donor recipient HLA match, donor sex, and mechanism of donor death (3 5). Unfortunately, the use of marginal donors has a price. Delayed graft function (DGF), prolonged hospitalization, and graft failure have been attributed to the use of marginal donors for cadaveric kidney transplantation (3,5,11,12). An association between DGF and reduced graft survival is well established (3,6,11 13). Similarly, early renal function is well established as a predictor of long-term graft survival (14). A systematic approach to assess marginal donors is needed to identify kidneys at highest risk of prolonged graft dysfunction or failure. For example, development of a scoring system based on information available at the time of donor nephrectomy could improve selection of kidneys that have a lower likelihood for prolonged post-transplantation hemodialysis and a higher likelihood of long-term success and also selection of recipients for immunosuppressive protocols (i.e. antibody induction). In this study, we devise a scoring system to identify kidneys at highest risk of early graft dysfunction and failure. The scoring system was developed from data collected from one cohort and then validated on an entirely new cohort. Subsequently, the scoring system was adopted prospectively, with encouraging preliminary results. Methods Study populations We studied the records of 241 consecutive adult cadaver renal transplant recipients at two centers (group 1, Mayo Clinic, nω90; group 2, University of Minnesota, nω151) between January 1997 and July Group 1 consisted of 76 kidney, 10 combined kidney pancreas, and four combined kidney liver transplant recipients. All group 2 patients received kidney transplants alone. None of these cadaver kidneys underwent machine perfusion before transplantation. A scoring system was developed from data in group 1 and was validated in group 2. Subsequently, the scoring system was used prospectively for a cohort of adult recipients of adult cadaver kidneys from July 1999 to December 1999 (group 3, Mayo Clinic, nω26). All donor data were obtained from our local organ procurement organization (LifeSource, Upper Midwest Organ Procurement Organization, St. Paul, MN). Institutional Review Board approval was obtained for collection of data from recipients medical records to develop the donor scoring system. 162

2 Donor Scoring System for Renal Transplantation Development of the scoring system The scoring system was developed from combined univariate and multivariate analyses of group 1 data, which included 18 risk factors for DGF (donor, 12; recipient, six; Table 1). The primary end-point of early renal function used to develop the scoring system was renal (creatinine, iothalamate) clearance on post-transplantation day 30 (D30CL). Secondary study end-points were the need for post-transplantation hemodialysis, the number of hemodialysis runs performed during the 30d after transplantation, length of hospitalization, and the cost of transplantation during the first 30d. Seven variables found to correlate with D30CL by univariate analysis or multivariate analysis were used to develop the scoring system. The distribution of points to each category for use in the scoring system was based on level of significance by multivariate (six points maximum) and univariate (three points maximum) analyses. This allocation of points provided the best prediction of early graft function (i.e. D30CL) in group 1 patients. The scoring system was then tested on an entirely new cohort of patients (group 2) within the same organ procurement organization. The system was utilized prospectively in group 3. Data collection Donor history of diabetes and hypertension was obtained from the survey filled out by the next of kin before donation. Donors with a medication history of insulin or oral hypoglycemic agent were considered to be diabetic in our analysis. Similarly, donors with an antihypertensive medication history were considered hypertensive, and the duration of hypertension was considered to be the duration of medication usage. Extent of plaque formation (none, mild, moderate, severe) in the donor renal artery was obtained from the procurement record. Cold ischemia time was determined from the recipient operative log and procurement records. HLA mismatch (zero to six antigens) was determined from mismatches in the three major donor recipient antigenic sites (A, B, Dr). Major postoperative complications were identified in the recipient s medical record (group 1); they were biopsy-confirmed allograft rejection, wound infection, ureteral leak, symptomatic lymphocele, and death. Description of end-points Delayed graft function was defined as the need for hemodialysis during the first week after transplantation. The total cost of transplantation was Table 1: Risk factors for delayed renal graft function Donor Age Cause of death Cytomegaloviris match (donor recipient) Creatinine clearance (best, worst, final) Sex History of diabetes History of hypertension (years) HLA mismatch (donor recipient) Preservation (cold ischemia) Renal biopsy (percentage sclerosis) Renal artery plaque Right or left kidney Recipient Age Cause of end-stage renal disease Sex Prior renal transplant Panel reactive antibody status Weight American Journal of Transplantation 2001; 1: determined for recipients of cadaveric kidneys at one institution (Mayo Clinic); it included the cost of initial hospitalization and costs of outpatient care and other hospitalizations during the first 30d after transplantation. Length of stay during the initial hospitalization was recorded. Determination of renal function (donor and recipient) Creatinine clearance (CrCl), estimated by the Cockcroft Gault method (15), was used as the measure of renal function in all donors. The Cockcroft Gault equation is summarized below for males and females: CrCl male (ml/min) Ω [(140 ª age) weight]/72 Cr CrCl female (ml/min) Ω 0.85 CrCl male These equations are based on age (year), weight (kg), serum creatinine level (Cr, mg/dl), and sex. Donor creatinine clearance was determined from the donor s lowest, highest, and final serum creatinine values during the hospitalization for kidney procurement. This information was obtained from the donor medical record. Four kidneys from young pediatric donors ( 12years, 40 kg) were excluded from this analysis because estimation of creatinine clearance in small donors was not considered reliable by the Cockcroft Gault equation. The Cockcroft Gault equation was used to estimate D30CL in all recipients. The recipient s age at the time of transplantation, pretransplantation (dry) weight, and day 30 serum creatinine value were used in this calculation. Group 1 recipients also underwent direct measurement of renal clearance by iothalamate technique 30d after transplantation (16). Therefore, group 1 recipients had renal function on day 30 (i.e. D30CL) determined by both direct (iothalamate) and indirect (Cockcroft Gault equation) techniques. Immunosuppression and treatment of rejection Immunosuppression protocols were similar for groups 1 and 2, and they included triple immunosuppression (tacrolimus/cyclosporine, mycophenolate mofetil, prednisone) in most patients. Recipients with DGF received antibody therapy (polyclonal or monoclonal) for 7 14d; calcineurin inhibitors were held until the graft began to function. Acute rejection episodes were treated with steroid boluses (500 mg/d) for 3d, followed by a rapid steroid taper. Steroid-resistant rejection, severe rejection, and rejection associated with vascular involvement were managed by antibody therapy. Statistical analysis Both univariate and multivariate analyses were used to assess the significance of 18 risk factors for early renal dysfunction in group 1. Univariate assessment of risk factors with two levels of variability (i.e. cause of death [COD] cerebrovascular accident or no cerebrovascular accident; history of hypertension yes or no; history of diabetes mellitus yes or no; and donor creatinine clearance above or below 90 ml/min) was made using a two-sample t-test, assuming unequal variances. Factors with three or more levels of variability, such as duration of hypertension, duration of preservation time, and severity of renal artery plaque (none, mild, moderate, severe), were initially assessed using a one-way analysis of variance, with pairwise comparisons made using a two-sample t-test, assuming unequal variances. The univariate association between donor age and D30CL was assessed by Pearson s correlation coefficient. An ordinary linear regression multivariate analysis with a backward selection procedure was performed on seven variables found to be significant by univariate analysis (Table 2). P-values 0.05 were considered to be statistically significant. Results No recipients in either group 1 or group 2 experienced graft loss due to technical failure. Four (two in each group) died 163

3 Nyberg et al. Table 2: Summary of risk factors for post-transplantation renal dysfunction Risk factor variables Predictive of renal dysfunction a Univariate analysis Multivariate analysis (n Ω 84) Donor Cause of death p p History of hypertension p p 0.01 Clearance, final p p 0.05 Age p Borderline b History of diabetes p 0.05 NS Cold ischemia p 0.05 NS Renal artery plaque p NS Clearance, best NS NP Clearance, worst NS NP HLA mismatch NS NP Sex NS NP Renal biopsy NS NP CMV status NS NP Recipient Age NS NP Cause of ESRD NS NP Sex NS NP Prior renal transplant NS NP PRA status NS NP Weight NS NP CMV, cytomegalovirus; ESRD, end-stage renal disease; NP, analysis not performed; NS, not significant; PRA, panel reactive antibody. a On the basis of values for recipient clearance 30 d after renal transplantation in group 1. b Donor age approached significance in the multivariate analysis, competing for entry with final donor creatinine clearance. with a functioning graft during the 30 d after transplantation and were excluded from the analysis of early renal function. Five patients (two, group 1; three, group 2) experienced prolonged graft dysfunction and remained hemodialysis-dependent at 30 d after transplantation. Other major postoperative complications that were identified in group 1 included biopsy-confirmed allograft rejection (14 total: mild, 10; moderate, four; severe, none), wound infection (six), symptomatic lymphocele (five), and ureteral leak (two). Univariate analysis, group 1 Seven donor variables (COD, history of hypertension, final creatinine clearance, age, history of diabetes, cold ischemia time, and severity of renal arterial plaque) were found by univariate analysis to be significantly associated with D30CL (Table 2). The 48 donors whose COD was cerebrovascular accident provided kidneys with lower D30CL than those of the 40 donors without a cerebrovascular accident ( vs ml/min; p 0.001). The influence of COD on early renal function was further emphasized by the need for hemodialysis after cadaveric transplantation. Namely, the need for hemodialysis was 53% (16/30), 25% (3/12), 16% (3/19), 7% (2/27), and 0% (0/2) in recipients of kidneys whose donors experienced intracranial hemorrhage, anoxic brain death, ischemic cerebrovascular death, traumatic head injury, and other causes (brain tumor, one; meningitis, one), respectively. Cadaveric kidneys transplanted from the seven donors with hypertension for 10 years or longer had a mean recipient D30CL of 20.1 ml/min, which was less than that of the nine donors with hypertension of less than 10 years (38.7 ml/min) and that of the 72 donors with no history of hypertension (45.9 ml/min; p 0.001). When grouped together, recipients of cadaveric kidneys from donors with a history of hypertension (16 donors) had significantly lower D30CL than did recipients of kidneys from nonhypertensive donors (30.6 vs ml/min; p 0.001). Three estimates of donor creatinine clearance were made from serum creatinine samples obtained before procurement: maximum clearance, based on lowest serum creatinine value; minimum clearance, based on highest serum creatinine value; and final creatinine clearance, based on final serum creatinine determination before procurement. The donor s final creatinine clearance (DCL f ) was most predictive of recipient D30CL (84 donors). Allografts from donors with DCL f of 90 ml/min or greater had significantly better D30CL than allografts from donors with DCL f of less than 70 ml/min (p 0.05). Of note, average D30CL was 50% of average DCL f in each category (Figure 1). The influence of donor age on D30CL is illustrated in Figure 2. As expected, an inverse relationship between donor age and early renal function was observed, with a decrease of 164 American Journal of Transplantation 2001;1:

4 Donor Scoring System for Renal Transplantation Figure 1: Influence of final donor creatinine clearance (DCL f ) on early renal function after cadaveric renal transplantation (group 1, n Ω 84). Mean (open circles) and individual (closed circles) data points are provided for each group. Day 30 renal clearance (D30CL) was significantly greater for recipients of kidneys with DCL f of at least 90 ml/min than for recipients in the lowest three groups of DCL f ( 50, pω 0.043; 50 59, p Ω 0.023; 60 69, p Ω 0.009). To convert values for creatinine clearance to ml/s, multiply by Figure 2: Influence of donor age on early renal function after cadaveric renal transplantation. Note that the linear regression curve-fit intercepts the y-axis at a day 30 renal clearance (D30CL) of 61.7 ml/min, corresponding to a kidney from the ideal young cadaveric donor (n Ω 88). To convert values for creatinine clearance to ml/s, multiply by ml/min for every decade of donor age (Pearson s correlation coefficient, ª0.513). The difference in D30CL between kidneys from the three donors with a history of diabetes and the 85 with no history of diabetes was 43.8 vs ml/min (p 0.05). The duration of cold preservation adversely influenced early renal function after cadaveric renal transplantation. Mean D30CL in recipients of donor kidneys preserved more than American Journal of Transplantation 2001; 1: h (18 recipients) was less than that in recipients of kidneys undergoing h (62) and less than 12 h (eight) of cold ischemia (35.6, 45.1, and 51.8 ml/min, respectively). This observation was further emphasized by D30CL results in the six pairs of recipients who received cadaver kidneys from the same donor. Preservation time was the only major variable to differ in these paired cases, with an average of 19.7 h for the first kidney transplanted and 28.3 h for the second kidney transplanted. Average D30CL decreased from 31.7 ml/min for first kidneys to 24.3 ml/min for second kidneys. In addition, the incidence of graft dysfunction requiring hemodialysis and the number of hemodialysis runs after transplantation were greater with second kidneys than with first kidneys (data not shown). Univariately, plaque formation in the donor renal artery correlated with D30CL. The severity of plaque formation (none, n Ω 64; mild, n Ω 11; moderate, n Ω 10; and severe, n Ω 3) weakly influenced early renal function (i.e. D30CL), although the difference between kidneys with mild plaque (35.5 ml/ min) and moderate (33.8 ml/min) or severe (31.8 ml/min) plaque was not significant. An absence of donor renal artery plaque showed the strongest correlation with D30CL (46.6 vs ml/min; p 0.001). Factors shown to influence early renal function in previous studies that were not predictive of early renal dysfunction in our univariate analysis of group 1 were cytomegalovirus serologic status of donor and recipient, cause of recipient end-stage renal disease, percentage of glomerulosclerosis on procurement biopsy, and recipient panel reactive antibody levels. HLA matching between donor and recipient also had no influence on early post-transplantation renal function, although nearly one-third of recipients in group 1 received 0- mismatched cadaveric kidneys. The influence of donor sex on early post-transplantation renal function was also not significant on the basis of D30CL data (men, ml/ min; women, ml/min). Acute rejection occurring in the first 30 d after transplantation was associated with lower D30CL (45.1 vs ml/min; p Ω 0.053). Acute rejection was not considered in the donor scoring system, however, since this information could not be obtained at the time of procurement. Multivariate analysis, group 1 Results of the multivariate analysis of risk factors for early renal dysfunction are summarized in Table 2. The multivariate analysis was performed on the subset of patients (84) in group 1 appropriate for determination of DCL f by the Cockroft Gault equation. COD, donor hypertension, and DCL f were independent risk factors for low recipient D30CL by multivariate analysis (P 0.05). Donor age was also associated with low D30CL by multivariate analysis, but to a lesser extent. Donor scorecard A scoring system, summarized in Table 3, was developed from the results of univariate and multivariate analyses of group 1 data. Points were allocated on the basis of the significance of 165

5 Nyberg et al. Table 3: Donor scorecard for cadaveric renal transplantation Risk factor Severity Score Cause of death Trauma, anoxia, other 0 Ischemic or hemorrhagic CVA 6 History of hypertension (years) None Donor clearance (ml/min) (Cockcroft Gault equation) Donor age, year History of diabetes No 0 Yes 3 Preservation time (h) Renal artery plaque None 0 Mild 1 Moderate 2 Severe 3 Donor score (0 32 points) CVA, cerebrovascular accident. the correlation of risk factor, severity, and recipient D30CL. The three most significant variables by multivariate analysis (COD, hypertension, DCL f ) were given maximum weighting (0 6 points). Donor age, another important variable by multivariate analysis, was weighted 0 5 points. The remaining three variables, selected by univariate analysis, were weighted 0 3 points. The total final score ranged from 0 to 32 points. A grade was assigned to each kidney on the basis of total score: A (0 5 points), B (6 10), C (11 15), D ( 16). Retrospective validation The scoring system was tested on data from group 2 (Table 4). We found a steady decline in early renal function (D30CL) with increasing donor score. For example, good renal function was achieved in 91% of group 2 recipients who received grade A cadaveric kidneys (donors scoring 5 points or fewer). In contrast, only 23% of grade D kidneys (scoring 16 points or more) provided good renal function to recipients 30 d after transplantation. The percentages of DGF observed in these two groups Table 4: Early renal function after cadaveric renal transplantation in group 2 (n Ω 151) Grade Score No. D30CL (ml/min) Function (%) DGF (%) d Good a Fair b Poor c A B C D a Renal clearance on post-transplantation day 30 (D30CL) 40 ml/min. b D30CL Ω ml/min. c D30CL 20 ml/min. d Delayed graft function, defined as the need for more than one hemodialysis within 30 d after transplantation. 166 American Journal of Transplantation 2001;1:

6 Donor Scoring System for Renal Transplantation were 17 and 62, respectively. Fifteen per cent of recipients of grade D cadaveric kidneys had poor renal function at 30 d and could have been relisted for cadaveric renal transplantation on the basis of creatinine clearance rates below 20 ml/min. Prospective validation We recently introduced the cadaver donor scoring system into our clinical practice (group 3). This group includes 26 kidneys accepted for cadaver transplantation and seven that were rejected. Of the seven rejected kidneys, two were turned down because of occult tumor recognized at procurement and five were refused because of unfavorable cadaver donor scores (13, 15, 19, 19, and 20). Only one grade D kidney was accepted, in a patient who was thought to be doing poorly on hemodialysis. That kidney scored 16 points and came from a 58-year-old donor with intracranial hemorrhage as the cause of death. Although the donor s final creatinine clearance was 115 ml/min, the donor had a 10-year history of hypertension, moderate donor renal artery plaque, and 19 h of cold ischemia. The recipient received three hemodialysis runs over 7 d after transplantation because of DGF. The recipient s iothalamate clearance 30 d after transplantation was 17 ml/min. Results of the 25 transplanted cadaver kidneys with scores of 11 points or fewer were significantly better. Fewer than 20% of the recipients required hemodialysis, and most had fair to good renal function 30 d after transplantation. These recent data support the results of our earlier retrospective analysis. Financial analysis by donor score To assess the potential financial impact of the donor scoring system, we obtained cost data for recipients of kidneys alone in group 1. These data included cost of the initial hospitalization, cost of outpatient care and follow-up hospitalizations during the first 30 d after transplantation, total cost of transplantation during the first 30 d, and length of stay during initial hospitalization. Results of D30CL, initial length of stay, and total cost are compared in Table 5. Recipients of grade A/B (donor score 10 points) kidneys were compared with recipients of grade C/D ( 10 points) kidneys, and grade A C (0 15 points) kidneys were compared with grade D ( 16 points) kidneys. These analyses confirmed the significant influence of donor score on D30CL. In addition, length of primary hospital stay was significantly shorter with lower donor score. The 30-d costs of transplanting grade A/B kidneys and grade A C kidneys were less expensive than those of their counterparts (grade C/D and grade D) by 9.6% and 23.5%, respectively. These differences did not reach statistical significance because costs varied (i.e. standard deviation) within each group. To clarify this variability, we considered the influence of perioperative complications on costs of cadaveric renal transplantation (Table 6). The following complications were observed in this cohort of 67 patients from group 1: DGF, 21; Table 5: Functional and financial outcome after cadaveric renal transplantation stratified by donor renal score (group 1, n Ω 67) Donor score (points) No. D30CL (ml/min) LOS1 (d) $$T30 ($) p p 0.01 NS p p 0.05 NS D30CL, recipient clearance 30 d after transplantation; LOS1, length of stay during initial hospitalization for renal transplantation; NS, p 0.05; $$T30, total cost of medical services during 30 d after transplantation. Table 6: Influence of perioperative complications on functional and financial outcome after cadaveric renal transplantation (group 1, n Ω 67) Outcome measure or Perioperative complication p end-point Yes (n Ω 33) No (n Ω 34) D30CL (ml/min) LOS1 (d) Hospital cost ($) Other costs, 30 d ($) Total cost, 30 d ($) Donor score, points D30CL, recipient renal clearance determined 30 d after transplantation; LOS1, length of stay during initial hospitalization. American Journal of Transplantation 2001; 1:

7 Nyberg et al. Table 7: Representative grade D cadaveric kidneys from group 1 Donor Summary of donor variables a Recipient end-points Age DCL f HTN DM Preserv. COD Plaque Score D30CL HD (years) (ml/min) (year) (h) severity (points) (ml/min) (runs) 1 59 (2) 39 (6) 0 (0) No (0) 19 (1) ICH (6) Moderate (2) (3) 104 (0) 20 (6) Yes (3) 20 (1) ICH (6) None (0) (1) 75 (2) 30 (6) No (0) 17 (1) Ischemic (6) Severe (3) 19 HD b (3) 104 (0) 20 (6) Yes (3) 33 (2) ICH (6) None (0) (5) 53 (4) 9 (3) No (0) 25 (2) ICH (6) Moderate (2) (5) 68 (3) 15 (6) No (0) 18 (1) ICH (6) Moderate (2) 23 HD b 12 COD, cause of death; DCL f, final donor creatinine clearance; D30CL, iothalamate or creatinine clearance determined 30 d after transplantation; DM, history of diabetes; HD, hemodialysis; HTN, history of hypertension; ICH, intracranial hemorrhage; Ischemic, ischemic cerebrovascular accident; Preserv., cold preservation time. a Numbers in parentheses are points. b Prolonged delayed graft function requiring hemodialysis beyond day 30 after transplantation. acute rejection, 11; lymphocele, five; wound infection, three; and ureteral leak, two. Multiple complications were observed in 14 recipients. Occurrence of a complication during the 30 d after transplantation had a strong adverse effect on functional outcome (D30CL), length of initial hospital stay, and financial outcome after cadaveric renal transplantation. The difference was highly significant (P 0.001) in each case. The complication rates were 65% in recipients of grade C/D kidneys and 40% in recipients of grade A/B kidneys. For this reason, a financial analysis of donor score in recipients of uncomplicated renal transplants was not performed. Discussion We report a scoring system based on seven donor variables available at the time of organ procurement. This system was found useful in the prediction of early renal function after cadaveric renal transplantation. The seven variables were selected from a list of established risk factors for DGF (Table 1). Selection of variables and allocation of points were based on results of combined univariate and multivariate analyses. Three categories (COD, final creatinine clearance, and history of hypertension) received a maximum of six points because of their high level of significance in the multivariate analysis (Table 2). Donor age was shown to have intermediate predictive value of early renal function and therefore was given a maximum of five points. The remaining three categories (history of diabetes, preservation time, severity of renal artery plaque) were given a maximum of three points on the basis of their significance in the univariate analysis. This scoring system, which can be summarized as the donor scorecard for cadaveric renal transplantation (Table 3), was useful in predicting early renal function. Information on long-term graft survival was not available for these cadaveric grafts transplanted between 1997 and 1999; however, a direct association between early renal function and long-term graft survival is well established (14). Data from six patients in group 1 who received grade D kidneys (16 points or more) are summarized in Table 7. Prolonged graft failure developed in two patients in this group, and they never achieved independence from hemodialysis. These patients received kidneys from 52- and 72-year-old donors who had scores of 19 and 23 points, respectively. These two cases exemplify the importance of a donor scoring system. Namely, the synergism of all seven risk factors provided a better prediction of early renal function than one variable (i.e. age). Some caution must be exercised when using a scoring system such as this, however, because excluding kidneys from donors on the basis of score could result in discarding potentially acceptable kidneys and maintaining prolonged dialysis for the intended recipients. Three of the six kidneys with 16 or more points in the initial cohort provided fair early renal function (D30CL 20 ml/min). The long-term results for grade C and grade D cadaveric kidneys will be an important focus in follow-up studies. Follow-up studies should also include recipients of dual renal transplantation (17 19). In the two dual cadaveric renal transplantations we have performed, the scoring system held: 10 points (D30CL, 48 ml/min) and 23 points (hemodialysis-dependent). Also, 14 recipients of combined kidney pancreas (nω 10) or combined kidney liver (n Ω 4) allografts were included in the group 1 analysis. These combined organ transplants were included because each had received a kidney from a cadaveric donor. Because of the nature of pancreas and liver transplantation, these organs had shorter preservation times, fewer risk factors for delayed graft function, and relatively low donor scores (mean Ω3.1 points). As expected, mean D30CL for this group of patients was high (53.3 ml/ min). Because only one patient received organs from a donor with a score greater than 10 (donor age, 65 years), we must be cautious in recommending our scoring system for cases of multi-organ transplantation involving cadaver kidneys. Application of this proposed scoring system in clinical practice will depend on each transplant program s philosophy to- 168 American Journal of Transplantation 2001;1:

8 Donor Scoring System for Renal Transplantation ward marginal donors and the program s reliance on cadaveric organs for renal transplantation. Reliance on cadaveric kidneys may be relieved somewhat by living donation and laparoscopic donor nephrectomy (20). However, many patients are not fortunate enough to have a living donor available, as reflected by the growing number of patients on the United Network for Organ Sharing Organ Procurement and Transplantation Network waiting list (21). For patients doing reasonably well on dialysis, it seems appropriate to wait for a cadaveric kidney with a high probability of good early renal function. Our scoring system and the results summarized in Table 5 suggest that grade A to grade C cadaveric kidneys (0 15 points) should provide good function in at least 70% of recipients and poor function in fewer than 10%. The likelihood of DGF and multiple hemodialysis treatments in these patients is less than 25%. For patients with difficult dialysis access or high panel reactive antibody status, grade D cadaver kidneys ( 15 points) may be considered cautiously. However, many grade D organs function poorly (15% in group 2) and require multiple hemodialysis runs ( 60% in group 2). Kidneys with high scores were also shown to prolong the length of initial hospitalization in our study and were associated with increased medical costs. Our scoring system did not predict which patients were likely to have a perioperative complication, however. In addition, although there were no technical graft losses in this study, the system would not be expected to predict technical graft loss. Other limitations of our scorecard deserve discussion. For example, small pediatric donors ( 40 kg, 12 years) were excluded from our analysis because estimation of creatinine clearance in these small donors was not thought to be reliable by the Cockcroft Gault equation. Donors in whom hemodynamic instability develops after collection of the final creatinine sample and before aortic cross-clamping should be given special consideration, because they have a significant risk of graft dysfunction even though their final creatinine clearance (i.e. DCL f ) may have been normal. Similarly, the system has not yet been tested on kidneys from non-heart-beating donors or on machine-perfused cadaveric kidneys (22). Modifications to the proposed scoring system may be needed when long-term end-points are considered. For example, HLA matching was not found to influence early renal function in the current study. However, HLA matching has been associated with long-term graft survival in other studies (4). Donor renal biopsy data (namely, percentage of glomerulosclerosis) did not predict early renal function in our study but may be predictive of long-term graft survival. The insignificance of biopsy material in the prediction of early renal function may be explained, in part, by the fact that cadaveric kidneys with greater than 30% glomerulosclerosis on procurement biopsy were not considered for renal transplantation. For this reason, future applications of this scoring system must consider that group 1 patients did not receive kidneys with advanced nephrosclerosis. Of note, biopsy results were important for establishing a tumor or other renal pathology in some cases. Acute rejection is a confounding factor American Journal of Transplantation 2001; 1: that may have weakened the predictive value of our scoring system. Namely, the scoring system was not able to predict episodes of acute rejection in the first 30 d after transplantation. This was unfortunate, since acute rejection was associated with lower than expected D30CL, especially in grade A and grade B kidneys after an episode of acute rejection. On the other hand, the variables that determined this scoring system show the relevance of nonalloimmune factors on the outcome of renal allograft function. In summary, we have proposed a common-sense scoring system with practical applications. All data needed to determine a donor score should be available at the time of organ procurement. Cold ischemia time may be somewhat uncertain, but estimation to within 12 h increments should be possible at the time of offering. Application of this scoring system depends on institutional policies on use of marginal organs and reliance on cadaveric organs for renal transplantation. The proposed system is intended for patients who do not have access to a suitable living donor and therefore require cadaveric transplantation. The proposed scoring system may improve informed consent by allowing a discussion of issues, such as the likelihood of success, with the patient before cadaveric transplantation. We strongly recommend that each transplant center consider its own multifactorial donor analysis or consider incorporating our scoring system into its practice. Acknowledgments The authors thank the staff of LifeSource, Upper Midwest Organ Procurement Organization, for their assistance in gathering data for this project. Pamela Dahle is thanked for professional assistance with the preparation of this manuscript. References 1. Lee CM, Scandling JD, Shen GK, Salvatierra O, Dafoe DC, Alfrey EJ. The kidneys that nobody wanted: support for the utilization of expanded criteria donors. Transplantation 1996; 62: Hariharan S, McBride MA, Bennett LE, Cohen EP. Risk factors for renal allograft survival from older cadaver donors. Transplantation 1997; 64: Pfaff WW, Howard RJ, Patton PR, Adams VR, Rosen CB, Reed AI. Delayed graft function after renal transplantation. Transplantation 1998; 65: Morris PJ, Johnson RJ, Fuggle SV, Belger MA, Briggs JD. Analysis of factors that affect outcome of primary cadaveric renal transplantation in the UK. HLA Task Force of the Kidney Advisory Group of the United Kingdom Transplant Support Service Authority (UKTSSA). Lancet 1999; 354: Matas AJ, Gillingham KJ, Elick BA et al. Risk factors for prolonged hospitalization after kidney transplants. Clin Transplant 1997; 11: McLaren AJ, Jassem W, Gray DW, Fuggle SV, Welsh KI, Morris PJ. Delayed graft function: risk factors and the relative effects of early function and acute rejection on long-term survival in cadaveric renal transplantation. Clin Transplant 1999; 13: Terasaki PI, Gjertson DW, Cecka JM, Takemoto S, Cho YW. Significance of the donor age effect on kidney transplants. Clin Transplant 1997; 11:

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