i EVALUATION OF POTENTIAL KIDNEY DONORS AND OUTCOMES POST-DONATION AT CHARLOTTE MAXEKE JOHANNESBURG ACADEMIC HOSPITAL (1983 – 2015) Chandni Dayal A research report submitted to the Faculty of Health Sciences, University of Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Medicine in the branch of Internal Medicine Johannesburg, 2019 ii DECLARATION I, Chandni Dayal, hereby declare that this research report is my own unaided work. It is being submitted for the degree of Master of Medicine in the branch of Internal Medicine. This research report is submitted in the publishable format as recognised by the Faculty of Health Sciences. I further declare that this work has not been submitted before for any degree or examination at this or any other University. _____________________________ 3rd day of June, 2019 iii For my parents, Prakash and Nirmal Dayal iv PUBLICATIONS AND PRESENTATIONS ARISING FROM THIS RESEARCH 1. Awarded best poster presentation at the South African Renal Society Congress, Cape Town, 11 September 2016 Published abstract resulting: Dayal C, Diana N, Davies M, Meyers AM, Paget G. Failure to launch: Exclusion from living kidney donation at Charlotte Maxeke Johannesburg Academic Hospital (1983-2015). African Journal of Nephrology 2016;19:48. 2. Oral presentation at the South African Renal Society Congress, Cape Town, 9-11 September 2016 Published abstract resulting: Dayal C, Diana N, Davies M, Meyers AM, Paget G. Long-term outcomes in accepted living kidney donors at Charlotte Maxeke Johannesburg Academic Hospital (1983-2015). African Journal of Nephrology 2016;19:35. 3. Oral presentation to the Wits Donald Gordon Medical Centre Renal unit, Johannesburg, 13 October 2016 4. Oral presentation to the Charlotte Maxeke Johannesburg Academic Hospital Department of Internal Medicine, Johannesburg, 10 February 2017 v ETHICAL CONSIDERATIONS Permission for this retrospective study was obtained from Prof. G. Paget (Head of Nephrology, Department of Internal Medicine, Charlotte Maxeke Johannesburg Academic Hospital), Ms. G. Bogoshi (Chief Executive Officer, Charlotte Maxeke Johannesburg Academic Hospital), and the Human Research Ethics Committee of the University of Witwatersrand (Clearance number M150923). vi ABSTRACT Background Living kidney donation has emerged as a key therapeutic modality for end-stage kidney disease due to the global chronic shortage of renal allografts. However, the potential benefits to the recipient of a living donor kidney must be balanced against donor safety. In demographically diverse populations, there is a paucity of data regarding the living donor evaluation process and outcomes following donation. Objectives This study was undertaken to describe donation patterns, characterise reasons for non- donation and evaluate long-term morbidity and mortality following living kidney donation in the South African context. Methods A retrospective analysis of all Potential Living Donors (PLDs) evaluated at a single centre over a 32-year period was conducted. Of the total cohort of 1208 PLDs, 298 were Accepted Living Donors (ALDs), resulting in 910 Failed Living Donors (FLDs). Data collected included donor demographics. In addition, in the ALD group, clinical and laboratory parameters at various points in donor follow-up, as well as mortality data was noted. In the FLD group reason for donor exclusion was documented. vii Results Of the 1208 PLDs, 697 (58%) were female. The majority (559; 46%) were of Black African descent, and related to the intended recipient (991; 82%). Outcome of PLD evaluation varied significantly by race (p<0.001), with only a third of Black PLDs being accepted for donation. Black vs. Caucasian PLDs were more likely to fail work- up (52.1% vs. 39.3%; p<0.001) and be excluded for medical reasons (44% vs. 35%; p<0.001). Leading medical exclusions included hypertension, HIV and obesity. In the ALD cohort, median follow-up time was 44 months (IQR 13.8 – 93.5 months). Hypertension was documented in 12.8% of ALDs at most recent follow-up compared to 4.7% of ALDs pre-donation (p=0.06). There was a significant increase in Albumin Excretion Rate (AER) following donation (p<0.001). There was a significant decline in the CKD-EPI eGFR between pre-donation (91.7 ± 19.1 ml /min/1.73 m2) and the most recent visit post- donation (72.5 ± 20 ml/min/1.73 m2; p<0.001). 27% of ALDs had a CKD-EPI eGFR<60 ml/min/1.73 m2 at most recent visit, however none required renal replacement therapy. There were 5 documented deaths, all unrelated to the development of renal dysfunction. Black ethnicity was not associated with increased risk of adverse outcome following donation. Conclusions There is a high exclusion rate for PLDs. Black PLDs are more likely to be excluded than Caucasian counterparts due to significant comorbidity. Although limited by high rates of viii donors lost to follow-up, it is concerning that a quarter of ALDs developed an eGFR<60 ml/min/1.73 m2 at last follow-up, with a significant increase in AER. ix ACKNOWLEDGEMENTS I wish to acknowledge the following people for the roles they have played in the completion of this report: Dr. Nina Diana and Dr. Malcolm Davies – for assistance as supervisors of this study, review of the prepared manuscript, and constant support. Professor Anthony Meyers and Professor Graham Paget – for encouragement and guidance. Dr. Avinash Dayal, Dr. Sunaina Paima, Dr. Nida Siddiqui and Sr. Anne Morolo – for invaluable aid with record gathering. x TABLE OF CONTENTS DECLARATION ................................................................................................................... ii PUBLICATIONS AND PRESENTATIONS ARISING FROM THIS RESEARCH ............... iv ETHICAL CONSIDERATIONS ............................................................................................ v ABSTRACT .......................................................................................................................... vi ACKNOWLEDGEMENTS .................................................................................................... ix LIST OF TABLES ................................................................................................................ xiii ABBREVIATIONS / NOMENCLATURE ........................................................................... xiv CHAPTER 1: PROTOCOL AND EXTENTED REVIEW OF THE LITERATURE ................. 1 1. BACKGROUND ................................................................................................... 1 1.1. Introduction ....................................................................................................... 1 1.2. Physiology of uninephrectomy ....................................................................... 2 1.3. Clinical context .................................................................................................. 3 1.4. An overview of Failed Living Donors ............................................................. 5 1.4.1. Medical reasons for donor exclusion ................................................................... 5 1.4.2. Non-medical reasons for donor exclusion .......................................................... 6 1.4.2.1. Immunological factors ......................................................................................... 6 1.4.2.2. Psychosocial factors ............................................................................................. 6 1.4.3. Outcome of donor evaluation by ethnicity ......................................................... 7 1.5. An overview of Accepted Living Donors ....................................................... 8 1.5.1. A pre-2014 perspective ........................................................................................ 8 1.5.1.1. Renal outcomes ................................................................................................... 8 1.5.1.2. Non-renal outcomes ............................................................................................ 9 1.5.2. Critical analysis of pre-2014 data ....................................................................... 9 1.5.3. Current data on living donation ....................................................................... 10 1.5.3.1. Renal outcomes ................................................................................................. 10 1.5.3.2. Donor Mortality ................................................................................................. 11 1.5.4. Medically complex donors ................................................................................. 12 1.5.5. Effect of race on donor outcome........................................................................ 12 1.5.6. Donor ESKD risk projection ................................................................................ 13 1.5.7. Measurement of renal outcomes post donation: eGFR ..................................... 15 xi 1.5.8. Donor follow-up ................................................................................................. 15 1.5.8.1. Barriers to donor follow-up ............................................................................... 16 1.5.8.2. Improving donor follow-up ............................................................................... 16 1.6. The South African context ............................................................................. 17 1.7. Summary ........................................................................................................... 18 2. OBJECTIVES ...................................................................................................... 20 2.1. Primary Objective ............................................................................................ 20 2.2. Secondary Objectives ...................................................................................... 20 3. METHODOLOGY .............................................................................................. 21 3.1. Study design ..................................................................................................... 21 3.2 Data collection ................................................................................................. 21 3.2.1 Data collection for failed living donors ........................................................... 21 3.2.2 Data collection for accepted living donors ...................................................... 22 3.3 Definition of variables.................................................................................... 24 3.3.1 Classification of donors .................................................................................... 24 3.3.2 Hypertension ..................................................................................................... 24 3.3.3 Albuminuria ....................................................................................................... 25 3.3.4 Glomerular filtration rate .................................................................................. 25 3.3.5 Chronic kidney disease ..................................................................................... 26 3.3.6 Body mass index ............................................................................................... 27 3.3.7 Isolated medical abnormalities ........................................................................ 28 4. STATISTICAL ANALYSIS ................................................................................. 29 5. ETHICS ............................................................................................................... 30 6. TIMING .............................................................................................................. 30 7. FUNDING .......................................................................................................... 30 8. POTENTIAL LIMITATIONS .............................................................................. 31 9. REFERENCES ..................................................................................................... 32 CHAPTER 2: PROPOSED MANUSCRIPT ....................................................................... 44 ABSTRACT ........................................................................................................................ 44 INTRODUCTION .............................................................................................................. 45 RESULTS ............................................................................................................................ 47 DISCUSSION ..................................................................................................................... 56 xii MATERIALS AND METHODS ......................................................................................... 63 DISCLOSURE ..................................................................................................................... 65 ACKNOWLEDGEMENTS .................................................................................................. 65 REFERENCES ..................................................................................................................... 66 CHAPTER 3: APPENDICES .............................................................................................. 74 APPENDIX A: Data collection sheets ............................................................................ 74 i. Data collection sheet for failed living donors .................................................. 74 ii. Data collection sheet for accepted living donors ........................................... 76 APPENDIX B: Ethics clearance certificate .................................................................... 80 APPENDIX C: Plagiarism report .................................................................................... 81 xiii LIST OF TABLES Chapter Table Title Page 1 1.1 Revised KDOQI classification for chronic kidney disease 27 1 1.2 WHO international classification of BMI 28 2 2.1 Donor demographics 51 2 2.2 Reasons for non-donation 52 2 2.3 Donor exclusion stratified by ethnicity 53 2 2.4 Comparative clinical parameters in accepted living donors 53 2 2.5 Logistic regression analysis of variables associated with an eGFR<60 ml/min/1.73m2 at most recent follow-up 54 2 2.6 Accepted donor ethnicity and parameters at most recent follow up visit 55 2 2.7 Parameters associated with defaulting post-donation follow-up 55 xiv ABBREVIATIONS / NOMENCLATURE 51Cr-EDTA Chromium-51-ethylene-diamine-tetra-acetic-acid ACS Acute coronary syndrome AER Albumin excretion rate ALD Accepted living donor APOL1 Apolipoprotein L1 BMI Body mass index CI Confidence interval CKD Chronic kidney disease CKD-EPI Chronic Kidney Disease Epidemiology Collaboration CMJAH Charlotte Maxeke Johannesburg Academic Hospital CMV Cytomegalovirus COPD Chronic obstructive pulmonary disease CrCl Creatinine clearance CTA Computed tomography angiogram EBV Epstein-Barr virus eGFR Estimated glomerular filtration rate ESKD End-stage kidney disease FLD Failed living donor GFR Glomerular filtration rate HepBsAg Hepatitis B surface antigen HepCAb Hepatitis C antibody HIV Human immunodeficiency virus xv HLA Human Leukocyte Antigen HR Hazard ratio IHD Ischemic heart disease IMA Isolated medical abnormality KDIGO Kidney Disease Improving Global Outcomes KDOQI Kidney Disease Outcomes Quality Initiative NSAIDs Non-steroidal anti-inflammatory drugs PLD Potential living donor PSA Prostate-specific antigen RLD Related living donor RRT Renal replacement therapy SA South Africa sCr Serum creatinine TB Tuberculosis UTIs Urinary tract infections 1 CHAPTER 1: PROTOCOL AND EXTENTED REVIEW OF THE LITERATURE 1. BACKGROUND 1.1. Introduction As the burden of end-stage kidney disease (ESKD) escalates globally, the growing demand for renal allografts cannot be met by deceased donors alone. [1, 2] This escalation is of particular concern in developing countries, as it is estimated that by the year 2030 in excess of 70% of patients with ESKD will reside in middle- and low-income countries, such as those in sub-Saharan Africa. [3, 4] Transplantation is the preferred modality of renal replacement therapy (RRT), having significantly better morbidity and mortality rates compared to long term dialysis. [5] Living donor transplants are known to offer improved allograft survival rates over deceased donor grafts. [5] In addition, living kidney donation offers the potential to significantly expand the kidney donor pool. [2] Rates of living kidney donation are increasing globally, with a twofold rise in the number of living donor transplants reported over the last decade in countries where registry data is available. [6] Living donation necessitates healthy individuals to undergo major surgery without any direct self-benefit. [7] The advantages of living donor transplantation for the recipient must therefore be balanced against ensuring donor safety, both in the selection process of potential living donors (PLDs) and the post-donation care of accepted living donors (ALDs). [8-11] 2 To date, the outcome of living donation for donors has largely been assessed in the developed world. [6] Emerging studies now suggest that the risk of adverse outcomes amongst ALDs may have been underestimated. [12-14] There is a paucity of data amongst demographically diverse populations in the developing world. [15] 1.2. Physiology of uninephrectomy Micro-puncture animal studies have informed much of what is understood about the pathophysiological sequelae of nephron mass reduction resulting from donor harvesting. [16, 17] Uninephrectomy induces a series of both structural and functional adaptations at a glomerular level. [16] An increase in renal plasma flow in the remaining kidney results in sustained single nephron hyperfiltration, which is accompanied by a rise in intraglomerular pressure. [17] The release of various growth factors and cytokines mediates glomerular hypertrophy which is reflected by an increase in the renal volume. [16, 17] These compensatory mechanisms facilitate the maintenance of a post-donation estimated filtration rate (eGFR) that is comparable to normal renal function, despite a loss of half the renal mass. [16] Delanaye et al. reported that the average post-donation eGFR reaches 65- 70% of the pre-donation value (in donors ≤ 60 years of age) and that the progressive decline in eGFR following donation mirrors that which occurs with normal senescence. [18] 3 However, long-term sustained hyperfiltration may cause maladaptive alterations to remnant glomeruli which in turn lead to progressive renal injury. [16, 17] In animal models, hyperfiltrating glomeruli undergo morphological changes ultimately resulting in focal and segmental glomerulosclerosis. [17] This is postulated to be the pathophysiological mechanism accounting for the long-term complications arising post uninephrectomy, including the development of proteinuria, hypertension and progression to ESKD. [16] A key consideration with regard to the animal model is that a 5/6 reduction in nephron mass of the experimental rat is not physiologically equivalent to a loss of half the nephron mass in an otherwise healthy individual. [19] A recent study by Lenihan et al. analysed glomerular dynamics following donation and suggested that single nephron hyperfiltration occurs largely independent of maladaptive glomerular hypertension. [20] This is thought to account for the observation that adverse renal outcomes occur relatively infrequently amongst living kidney donors. [21] An additional concern is the adverse impact of nephron mass reduction on cardiovascular health. Numerous human studies have demonstrated an elevation in biomarkers associated with endothelial dysfunction and atherosclerosis following uninephrectomy. [22 – 25] 1.3. Clinical context The practice of living kidney donation has evolved considerably since the first successful live donor transplant over sixty years ago. [26] Advances in therapy have led to renal 4 transplantation emerging as the preferred treatment modality for ESKD, with live donor pools accounting for a significant number of kidney transplants worldwide. [2, 6] Living donation encompasses both related and unrelated donors. Unrelated donors may either be directed or purely altruistic. [11] Living donor paired exchanges and donor chains offer the potential to increase the utilisation of living donors in otherwise incompatible donor-recipient pairs. [27, 28] As guided by the Kidney Disease Improving Global Outcomes (KDIGO) organization which developed an international standard of care for the live kidney donor, PLDs undergo an extensive multidisciplinary assessment prior to being accepted for living donation. [29] It is not uncommon for this rigorous work-up to detect occult disease in the prospective donor. [29] PLDs who are not accepted for donation are called failed living donors (FLDs). Multiple studies report similarly high rates of FLDs, ranging between 47-62%, with prospective Black donors most likely to be excluded. [30-34] Regarding outcomes in ALDs, older data appeared to show no difference in the long-term medical outcomes in living kidney donors as compared to the general population with some studies even suggesting that kidney donors ‘live longer’. [35, 36]. More recent studies, which have compared outcomes in ALDs to appropriately matched controls, have been less reassuring. [12-14] African-American donors were consistently under-represented in these studies, although the estimated risk of adverse outcome is believed to be highest in this population group. [15, 37, 38] 5 1.4. An overview of Failed Living Donors Characterising the reasons for donor exclusion may identify modifiable factors that can be addressed in order to safely expand living donor pools. [33, 39] 1.4.1. Medical reasons for donor exclusion Medical contraindications prevail universally as the most common reason for donor exclusion. [30-34] Enhanced pre-donation screening highlights the declining health of the aging general population, as well as the growing burden of non-communicable disease globally. [4, 39, 40] It is estimated that roughly 10% of the world’s population has chronic kidney disease (CKD), most of which is asymptomatic. [4, 41] Given this estimation, it can be extrapolated that roughly five million South Africans have underlying CKD. [42] Hypertension and diabetes constitute the main causes, mirroring global trends. [40, 42-44] Underlying both these disorders is the worldwide epidemic of obesity. The South African population’s obesity rate is 49%, double the global rate. [44, 45] Numerous studies have found obesity, hypertension and diabetes to be the most prevalent medical reasons for potential donors failing to ultimately donate a kidney. [30-34] In addition, sub-Saharan Africa has a high prevalence of human immunodeficiency virus (HIV). [4] The potential for donor exclusion due to communicable disease is therefore greater in this region. [4, 39, 42] 6 1.4.2. Non-medical reasons for donor exclusion 1.4.2.1. Immunological factors ABO and cross-match incompatibility amongst donor-recipient pairs have historically been major limiting factors in living kidney donation. [30-32, 34] Previously, immunological factors resulted in the exclusion of at least one-third of otherwise suitable donors. [46] In recent years, however, novel approaches have emerged to circumvent these immunological barriers. [47, 48] These include the use of immune modulatory therapy to allow HLA-desensitisation and ABO incompatible transplantation. [46-48] In addition, kidney exchange and domino-paired anonymous donation programs offer a cost effective alternative, without the added risk of complications arising from the use of additional intense immunosuppression needed to overcome immunological factors. [27, 48] The outcomes of these strategies have thus far been reassuring, with similar graft survival rates being demonstrated as compared to standard living donor transplants. [27, 28, 46, 47] This further highlights their importance in sustaining an expansion in living donor pools. [48] 1.4.2.2. Psychosocial factors All PLDs undergo mandatory evaluation to determine psychosocial suitability for donation. [39] During this process, motive for donation, socioeconomic support structures, and 7 general psychosocial wellbeing are assessed. [39] Aside from cultural factors, an increasingly common phenomenon is non-donation among medically suitable candidates who voluntarily withdraw from donation due to concerns regarding their prognosis following donation as well as fear of the potential complications of the surgical procedure itself. [30, 31, 33] Targeted donor education programs which can address such concerns early on in the evaluation process could potentially enhance living donor transplant rates by at least 10%. [33] 1.4.3. Outcome of donor evaluation by ethnicity Weng et al. highlighted that Black (vs. non-Black) potential donors were more likely to be excluded for medical reasons, most notably hypertension and obesity. [34] Furthermore, a prospective cohort study determined the overall odds of donation to be 52% lower in African Americans as compared to Caucasians (OR 0.48; p<0.001), with similarly high rates of exclusion for diseases of lifestyle. [50] African American donors are more likely to decide against donation. [33, 34, 50, 51] Reasons for this disparity in willingness to donate among African Americans were outlined in a study by Purnell et al. [52] Key issues highlighted include medical mistrust and cultural beliefs pertaining to bodily integrity. Gill et al. found socioeconomic inequality to be a significant barrier. [53] The incidence of living donation was lower amongst African American populations in the lowest income quintile (incidence rate ratio 0.84; 95% CI [0.78-0.90]). 8 In view of the above, various strategies have been proposed to enhance living donation rates in the African American population. [51, 54, 55] These include improved preventative medical care and educational programs to address unique concerns related to living donation in this subgroup. [51, 55] 1.5. An overview of Accepted Living Donors 1.5.1. A pre-2014 perspective Older reports of long-term donor follow-up suggested that the risks of uninephrectomy were of limited clinical significance, with outcomes amongst living donors being comparable (if not superior) to that of the general population. [18, 35, 36, 58, 59, 64-66] 1.5.1.1. Renal outcomes In a large longitudinal study by Ibrahim et al. 85% of a predominantly Caucasian cohort of donors were found to have a preserved GFR of greater than 60 ml/min/1.73 m2 at a mean of 12 years following donation. [35] When compared to the general population, no additional risk of accelerated decline in GFR, hypertension or albuminuria was demonstrated post-donation. The incidence of ESKD was found to be significantly lower than that of the general American population, at a rate of 180 cases per million per year, as compared to 268 cases per million per year respectively (p<0.001). [35] These findings were consistent with numerous other studies that reported relatively benign renal outcomes following donation. [56-64] 9 1.5.1.2. Non-renal outcomes A number of reports have compared long-term donor survival to population-based estimates. One such study by Fehrman-Ekholm et al. conducted over a 30-year follow up period found that donor longevity exceeded that of the general Swedish population, as survival rates were found to be superior in the donor group by 29% (p<0.001). [36] In addition, a Norwegian study reported that cardiovascular and overall mortality amongst donors were similar to demographically matched controls. [65] Major cardiovascular event rates were also found to be lower in donors compared to non-donors (2.8 vs. 4.1 events per 1000 person years, HR 0.66, 95% CI [0.48-0.90]). [66] 1.5.2. Critical analysis of pre-2014 data Numerous concerns have been raised regarding study methodologies used in the reports prior to 2014, which favoured the interpretation of better outcomes amongst donors. [64, 67] A primary concern has been that of selection bias generated by the use of the general population as a control group, as it represents a high risk comparator to live donors who are thoroughly screened and thus intrinsically healthier at baseline. [67] Additional concerns include the reliability of the data due to restrictive sample sizes, short follow-up durations and limited ethnic diversity amongst donor cohorts. [64, 67] 10 These shortcomings underscore the need to undertake studies that determine attributable risk by comparing donors to appropriate controls, namely matched, healthy non-donor population groups with large cohort numbers and long duration of follow-up. [68] 1.5.3. Current data on living donation Few studies have compared long-term outcomes between donors and healthy matched non-donors. These studies highlight evolving concerns pertaining to morbidity and mortality following kidney donation. [68] Moreover, emerging prospective data on long- term donor follow-up has provided valuable new insight into donor nephrectomy outcomes. [69] 1.5.3.1. Renal outcomes In the first prospective study conducted on living donors to date, Janki et al. assessed 100 donors over a median follow-up time of 10 years at two Dutch transplant centres. [70] There was a significant decline in the eGFR of 12.9 ml/min/1.73 m2 (p<0.001) at follow-up. One- fifth of the cohort had an eGFR between 30-60 ml/min/1.73 m2 at the study end-point. [70] In a report subsequently published by the same primary investigator, variables associated with an accelerated decline in renal function following donation were evaluated in a prospective cohort of 190 donors. [71] Over a 5-year follow-up period, a 33.6% decline in mean eGFR was noted following donor nephrectomy, with longitudinal analysis revealing a lower eGFR among male donors and older age (p<0.001). In this cohort, renal function had stabilized after an expected initial decrement immediately following nephrectomy and no donor required the institution of RRT. 11 Conversely, two reports suggest that living donors are at increased risk of developing ESKD as compared to matched controls. Mjøen et al. studied a large cohort of Caucasian living donors in Norway and found an eleven-fold increase in the relative risk of ESKD after donor nephrectomy. [12] The second, a US-based study by Muzalle et al. included 96214 donors with a median follow-up of 8 years. [14] Here, the estimated risk of ESKD was found to be 7.9-fold higher in living donors. Importantly however, the absolute 15-year incidence of ESKD in both these studies remained low at less than 1%. [68] Although an uncommon occurrence, prior living donors who require RRT have favourable post-transplant outcomes, particularly in the US where waiting times for kidney transplant are brief as national policy allocates priority to these patients. [72] Event rates for acute dialysis following donation are also low. [60, 73] 1.5.3.2. Donor Mortality In a retrospective cohort, Mjøen et al. showed that all-cause mortality in the first decade following donation remained comparable to healthy matched non-donor groups. [12] However, at 25 years, survival curves diverged, with the cumulative all-cause mortality increasing by 5% amongst donors. Over a median follow-up of fifteen years, the same study also found an increased risk of cardiovascular mortality amongst donors (HR 1.4; p<0.001). In contrast, prospective studies by Janki et al. report reassuring donor survival over mean follow-up periods of between 5 and 10 years, with mortality being due to causes unrelated to donation. [70, 71] 12 1.5.4. Medically complex donors Critical organ shortages have led to the emergence of expanded criteria for donor eligibility, in order to augment living donor pools. [74] Previously published data reported uncertainty in the long-term outcomes of donors with preceding isolated medical abnormalities (IMAs), including those who were older (≥ 65 years of age) or had pre-existing risk factors for CKD such as obesity (BMI 30-35 kg/m2) and pre-existing hypertension (stage 1 controlled on a single agent with no end-organ damage). [75] However, recent literature in this regard has largely been reassuring. A 2014 systematic review including studies using appropriately matched cohorts reported favourable outcomes with the use of older donors (up to the age of 70), as well as obese donors (irrespective of body mass index). [74] Despite concerns around a greater degree of pre- existing glomerulopaenia in hypertensive donors, outcomes in this subgroup have been comparable to that of normotensive donors. [71, 76-79] These findings are supported physiologically by the demonstration of similar compensatory changes in the remaining kidney of medically complex donors as compared to standard donors. [80] 1.5.5. Effect of race on donor outcome Comparative studies are limited but have highlighted that Black donors have an increased risk of adverse post-donation outcomes as compared to Caucasian donors. [15, 37, 38, 59] 13 Over a median follow-up of 6.3 years, the risk of peri-operative mortality was reported to be threefold greater amongst Black donors. [64] Following donation, the all cause risk of re- hospitalisation also greater amongst this subgroup (HR 2.6, 95% CI [1.54-3.03]). [81] There was however no statistically significant cause to account for these findings among black donors. [64, 81] At 7 year follow-up, the incidence of renal disease, including proteinuria and nephrotic syndrome, was higher amongst black donors as compared to Caucasian counterparts. [38] Lentine et al. showed that Black donors have a greater post-nephrectomy risk of developing hypertension (HR 1.52; 95% CI [1.23-1.88]) and diabetes (HR 2.31; 95% CI [1.33-3.62]). [15] In addition, Black donors were twice as likely to develop CKD. [15] The absolute risk of ESKD has consistently been shown to be greater in Black donors. [14, 59] A study of donation patterns revealed that Black donors are more likely to be related to the recipient than Caucasian donors (88% vs. 74%; p=0.007). [82] Genetic factors, including the identification of coding variants in the Apolipoprotein L1 (APOL1) gene, are thought to underlie the elevated risk for adverse renal outcomes amongst Black patients, although this association is yet to be proven amongst Black living kidney donors. [83-87] 1.5.6. Donor ESKD risk projection In order to inform donor counselling and selection, various models have been developed to estimate the projected long-term risk of ESKD following uninephrectomy. [13, 88-91] 14 The first extrapolated data is from the Mjøen et al. cohort of 1901 Caucasian donors. [12] In this model, with the assumption that all donors live to 80 years of age and that the incidence of ESKD remains constant with time, the estimated risk of a 60-year old PLD developing ESKD is predicted to be 1 in 150. With a younger age at donation, the estimated risk of ESKD incrementally increases, being 1 in 75 for a 40-year old PLD, and 1 in 50 in a 20-year old PLD. [13] Furthermore, a risk calculator developed by Ibrahim et al. to assess renal outcomes that portend ESKD in Caucasian donors found that the development of post- donation diabetes and hypertension was associated with a two-fold higher risk of ESKD. [88] The only model that included risk projection amongst racially diverse donors was generated using US population based data. [89] In this report, the projected risk of ESKD amongst PLDs over a 15-year time period was found to be 3.5 - 5.3 times greater than the projected risk in the absence of donation. Furthermore, the risk of ESKD was identified as being highest amongst young Black PLDs – an average 40 year old Black donor had a 3.9 times higher 15-year risk of developing ESKD as compared to a Caucasian donor of the same age and baseline characteristics. [89] Recent studies highlight a strong genetic component to the ESKD risk profile in living kidney donors; donors who are first-degree relatives to the recipient have consistently been shown to have a significantly greater predicted risk for ESKD following donation. [90, 91] 15 1.5.7. Measurement of renal outcomes post donation: eGFR Post uninephrectomy, the assessment of renal function in donors requires a reliable method for the determination of GFR. This allows for the timeous identification of a possible decline in renal function following donation. [92, 93] Ideally, GFR should be accurately measured in donors as concerns have been expressed regarding the use of creatinine-based equations to estimate renal function in individuals with a single kidney. [93] In practise however, calculated estimates of GFR are cost effective, and are therefore of particular relevance in resource limited settings. [92] Although many studies have applied the Cockroft-Gault or Modification of Diet in Renal Diseases formulas, the estimate now recommended for use in the assessment of renal function in living donors following uninephrectomy is the Chronic Kidney Disease Epidemiological Collaboration (CKD-EPI) equation. [92,93] This formula has been shown to closely approximate measured GFRs in living donors and has superior precision and accuracy as compared to other creatinine-based equations. [94] 1.5.8. Donor follow-up The need for structured donor follow-up is critical – particularly in an era where medically complex donors are frequently utilised and longitudinal data reveal a risk of comorbidity following donation. [74, 95] Monitoring of donors facilitates the early diagnosis and timeous institution of therapy where indicated, thus minimising the risk of potential complications. [96] Nevertheless, donor follow-up rates remain universally low. [97-99] In a 2015 report, Keshvani et al. noted that, by two years following donation, 40% of all transplant centres 16 lose contact with more than two-thirds of their donors. [100] This underscores the likelihood that potential adverse donor outcomes are substantially underreported. [67] 1.5.8.1. Barriers to donor follow-up Incomplete donor follow-up can be attributed to both donor and transplant centre factors. [100, 101] Schold et al. highlighted that younger age at donation, Black race, poor health literacy and distance of domicile in relation to follow-up centre were all independent risk factors for low follow-up rates. [101] This is consistent with Weng et al.’s report which identified similar risk factors. [102] Weng et al. also noted that amongst donors who had pursued follow-up, only 8% had been assessed by a nephrologist following donation. [102] In addition, higher rates of donor defaulting are reported amongst transplant centres with a higher volume of living donor transplants per year, as well as those with limited resources to trace patients following donation. [101] 1.5.8.2. Improving donor follow-up The institution of targeted strategies to augment donor follow-up has led to improved donor compliance at many transplant centres. [100-103] In the Keshvani et al. cohort, increased efforts to telephonically contact donors for follow-up, patient education classes conducted by a dedicated transplant nurse as well as reimbursement of donors for transport costs incurred by follow-up visits were all shown to significantly improve donor follow-up at 2 years (p<0.001). [100] Dedicated initiatives to improve follow-up in particular at-risk 17 subgroups such as younger donors and those with lower educational attainment have also been of benefit. [101] 1.6. The South African context The lack of access to RRT in developing countries has been well documented. [4] In South Africa (SA), the burgeoning HIV/AIDS epidemic has demanded a disproportionate quantum of healthcare resources, further limiting the provision of RRT. [44,104,105] As a result, a significant number of South Africans are at risk of premature death due to ESKD. [3] Living kidney donation thus offers a cost-effective measurement to facilitate definitive RRT in the South African setting. [104] Living donor transplant rates are however low across many centres in SA, with only 93 performed in the year 2014 despite the rapidly growing demand for donor organs. [104,105] Of further concern is that the risks associated with living donation have historically been poorly defined in demographically diverse populations. [15] To date, only four studies relating to living kidney donation in South Africa have been undertaken. The first, conducted in Johannesburg in 1986 by O’ Donnell et al. studied 33 living related donors over a mean follow-up period of 5.8 years. [106] Donors were found to have substantial rise in diastolic blood pressure (p<0.001), as well as inclination towards a significant decline in creatinine clearance following donation (p 0.0558). In a series by Naicker et al. 135 related living donors were reviewed over a ten year period. [107] The 18 majority of donors in this cohort were female (63%) and of Indian origin (58%), with a mean age of 34 years. Here, blood pressure post nephrectomy remained essentially unchanged, although three donors demonstrated clinically significant proteinuria following donation. The post-donation serum creatinine was found to be within normal limits, despite a mean rise of 33.4% over the follow-up period. The findings of the third study by Abdu et al. highlighted the need to encourage living donation and facilitate donor follow-up, which was noted to be poor in roughly 40% of the cohort. [108] The final report described reasons for donor exclusion in 117 prospective donors at a Cape Town centre. [109] In this study, only 17% of donors ultimately donated, with the remainder excluded for predominantly immunological and medical reasons such as obesity, hypertension and CKD. 1.7. Summary Living kidney donation has emerged as the preferred strategy to ameliorate the growing demand for renal allografts worldwide. [6] It is thus essential that the transplant community investigates methods to sustain living donor pools without compromising donor safety. [29, 39] This is particularly relevant as recent data highlights a substantial risk for adverse outcomes amongst prior living donors, although outcomes in racially diverse populations have been poorly characterised. [15, 35, 36] In order to tailor the informed consent process, attention to long-term outcomes amongst diverse living kidney donors is needed. [37, 67] The present study was undertaken in an effort to evaluate living kidney donation in the South African context with a view to identifying reasons for donor exclusion which may in 19 future facilitate the assessment of potentially modifiable barriers to donation, and in an attempt to characterise long-term morbidity and mortality following donation which may better inform the consent process for prospective donors in this setting. 20 2. OBJECTIVES 2.1. Primary Objective To determine donor morbidity and mortality after donation. Analysis of morbidity will focus on the development of a. New onset hypertension following donation (BP ≥140/90) b. Chronic kidney disease following donation, defined as the development of either of the following i. New onset proteinuria (AER >300mg/day) ii. An eGFR <60 ml/min/1.73 m² (using the CKD-EPI formula) 2.2. Secondary Objectives To determine the reasons for exclusion of potential donors from living kidney donation To determine the prevalence of ESKD following donation (eGFR <15 ml/min/1.73 m² using the CKD-EPI formula) To determine potential risk factors associated with proteinuria and/or a reduced eGFR post kidney donation, by evaluating – a. donor demographics b. the presence of isolated medical abnormalities prior to donation, defined by: - a borderline pre-donation 51Cr-EDTA GFR (<80 ml/min/1.73 m²) - pre-existing hypertension (well controlled on a single agent with no end- organ damage) - class I obesity (BMI 30-35 kg/m²) To determine the proportion of patients lost to follow-up post donation 21 3. METHODOLOGY 3.1. Study design A single centre retrospective observational study will be conducted of all patients attending the Living Donor Clinic in the Renal Unit at CMJAH over a 32-year period between 01 January 1983 and 31 July 2015. The closing date for sampling reflects the period of protocol submission for this study. The cohort will be comprised of 1208 potential living donors, of which: 910 are failed living donors, assessed between 01 January 1990 and 31 July 2015 298 are accepted living donors, assessed between 01 January 1983 and 31 July 2015 3.2 Data collection 3.2.1 Data collection for failed living donors Data collection for failed living donors will comprise the following parameters: Demographic data – age at assessment, gender and ethnicity Family history of the donor Relation to the intended recipient – whether related, unrelated or altruistic The outcome of eligibility evaluation 22 If excluded from living donation, reasons for non-donation will be documented, which will be categorised as: - donor-recipient related, - donor-related, - recipient-related, or - miscellaneous. The indications and findings of any renal biopsy undertaken on a donor will be recorded 3.2.2 Data collection for accepted living donors Data collection for accepted living donors will comprise the following parameters: Demographic information – gender, ethnicity, age at donation (as well as age at each follow-up point) Family history of the accepted donor Details pertaining to the donation, specifically: - relation to the recipient, as well as cause of renal failure in the recipient - the date of donation - the graft outcome (if known) The last follow-up date at the Living Donor Clinic and the approximate number of post- donation follow-up visits Domicile in relation to the Living Donor Clinic (in kilometres from transplant centre) The reason for lost to follow-up (if known) Baseline characteristics at donation, including: 23 - Body mass index - Urine albumin : creatinine ratio - Systolic blood pressure - Diastolic blood pressure - Baseline serum creatinine - eGFR as defined by an isotope study, the chromium-51-ethylene-diamine-tetra- aceticacid scan (51Cr EDTA scan) as well as the CKD-EPI formula - Habits, including smoking status and history of alcohol consumption - History of pre-existing medical condition(s) Characteristics at follow-up (correlated with time after donation), including: - Body mass index - Urine albumin : creatinine ratio - Systolic blood pressure - Diastolic blood pressure - Serum creatinine - eGFR as defined by the CKD-EPI formula - Habits, including smoking status and alcohol consumption - Development of co-morbid disease - History of nephrotoxic drug intake The above variables will be retrospectively collected from data recorded at the patients’ first follow-up visit post-donation, one-year post-donation visit, and at the most recent follow- up visit. 24 Mortality data will be collected in accepted living donors that demised during the study period, and will include: - age at death - the time from donation to mortality - cause of death, whether related to renal disease, a cardiovascular event or other cause 3.3 Definition of variables 3.3.1 Classification of donors Potential living donors (PLDs) – refer to all donors assessed at the CMJAH Living Donor Clinic Failed living donors (FLDs) – refer to the sub-group of PLDs excluded from living kidney donation Accepted living donors (ALDs) – refer to the subgroup of PLDs that ultimately donated a kidney 3.3.2 Hypertension Defined as per the Eighth Joint National Committee (JNC8) guidelines for blood pressure targets: 25 For donors with a current age of more than sixty years: - a systolic blood pressure of more than 150mmHg, with - a diastolic blood pressure of more than 90mmHg For donors with a current age of less than sixty years: - a systolic blood pressure of more than 140mmHg, with - a diastolic blood pressure of more than 90mmHg 3.3.3 Albuminuria Quantified as per the revised Kidney Disease Improving Global Outcomes (KDIGO) chronic kidney disease classification into three stages of albuminuria based on the albumin excretion rate (AER) in milligrams per day (mg/day): A1: Normal or mildly increased (AER <30 mg/day) A2: Moderately increased (AER between 30 - 300 mg/day) A3: Severely increased (AER >300 mg/day, with nephrotic range proteinuria defined as >3500 mg/day) 3.3.4 Glomerular filtration rate Pre-donation GFR will be defined: - as per isotope study: 51Cr EDTA scan - as calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula, expressed as: 26 GFR = 141 × min (Scr /κ, 1) α × max (Scr /κ, 1)-1.209 × 0.993Age × 1.018 [if female] × 1.159 [if black] where: GFR = glomerular filtration rate in ml/min/1,73m2 Scr = serum creatinine in mg/dL κ = 0.7 for females and 0.9 for males α = -0.329 for females and -0.411 for males min indicates the minimum of Scr /κ or 1, and max indicates the maximum of Scr /κ or 1. Post-donation GFR will be calculated by the CKD-EPI formula, as expressed above. 3.3.5 Chronic kidney disease Defined as per the revised Kidney Disease Outcomes Quality Initiative (KDOQI) as either kidney damage or GFR<60 ml/min/1.73 m² for ≥ 3 months. Kidney damage encompasses pathological abnormalities or markers of damage, including biochemical or radiological abnormalities. GFR is further classified into stages (table 1.1). 27 Table 1.1 | Revised KDOQI classification for chronic kidney disease GFR Stages GFR (ml/min/1,73 m2) Classification 1 >90 Normal 2 60 – 89 Mildly decreased 3a 45 – 59 Mildly to moderately decreased 3b 30 – 44 Moderately to severely decreased 4 15 – 29 Severely decreased 5 <15 ESKD 3.3.6 Body mass index BMI will be calculated as weight (in kilograms) divided by height (in meters) squared. It will then be sub-classified as per the World Health Organisation (WHO) international BMI classification (table 1.2). 28 Table 1.2 | WHO international classification of BMI Classification BMI (kg/m2) Underweight < 18.5 Normal Range 18.5 to 24.99 Overweight Pre-obese Obese - Obese Class I - Obese Class II - Obese Class III ≥ 25 25 to 29.99 ≥ 30 30 to 34.99 35 to 39.99 ≥ 40 3.3.7 Isolated medical abnormalities Refers to donors with any of the following characteristics prior to donation: A borderline 51Cr-EDTA GFR <80 ml/min/1.73 m2 Pre-existing hypertension well-controlled on a single agent with no end- organ damage Class I obesity (BMI 30 - 35 kg/m2 ) 29 4. STATISTICAL ANALYSIS Data analysis will be conducted using STATISTICA 12, a software package developed by StatSoft All data will be tabulated in a Microsoft Excel spreadsheet The distribution of continuous variables will be analysed using the Shapiro Wilk W test and by visual inspection of the histogram plot. The central measurement will be indicated by the mean for normally distributed variables and by the median for non- parametric data; dispersion will be presented as standard deviation and interquartile range, respectively. The categorical variables will be presented as percentages Statistical comparisons will be performed with the Student’s t-test for continuous normally distributed variables and the chi-squared test for categorical variables. Where appropriate, the one-way ANOVA and Wilcoxon matched pairs testing will be applied. For the accepted donor cohort, a multiple linear regression analysis will be performed to identify independent factors associated with a reduced eGFR of <60 ml/min/1.73 m2 at last follow-up. The Cox proportional hazard model will be applied to assess variables which impact on donor follow-up. If last follow-up is more than six months before the study end-point, donor defaulting will be assumed. A p-value of less than 0.05 will be considered to indicate statistical significance. 30 5. ETHICS Permission for this study was obtained from the Human Research Ethics Committee (Medical) – Clearance Certificate Number: M150923 (Chapter 3 – Appendix B). Permission to access patient records was obtained from the Head of Nephrology at CMJAH, as well as the Clinical Director and CEO of the institution. Patient confidentiality will be maintained by randomly allocating each patient record to a study number, allowing patient data to be kept strictly anonymous. All collected data and inferences thereof will then be analysed collectively. 6. TIMING Gantt chart showing the timeline of the study: 7. FUNDING All funding for this study will be borne by the author. 31 8. POTENTIAL LIMITATIONS Information bias may occur as a result of poor record keeping or incomplete data in the records Patients lost to follow-up may underpower the capacity of the study to assess certain outcomes 32 9. 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Comorbidity burden and perioperative complications for living kidney donors in the United States. Clin J Am Soc Nephrol 2013;8:1773-1782. 96. Kwapisz M, Kieszek R, Jedrzejko K, Domagala P, Bieniasz M, Gozdowska J, et al. Pathologies in living kidney donors diagnosed in the long-term care system. Transplant Proc 2016;48:1439-1445. 97. Kim SH, Hwang HS, Yoon HE, Kim YK, Choi BS, Moon IS, et al. Long-term risk of hypertension and chronic kidney disease in living kidney donors. Transplant Proc 2012;44:632-635. 42 98. von Zur-Mühlen B, Berglund D, Yamamoto S, Wadström J. Single-centre long-term follow-up of live kidney donors demonstrates preserved kidney function but the necessity of a structured lifelong follow-up. Ups J Med Sci 2014;119:236-241. 99. Khatami MR, Nikravan N, Alimohammadi F. Quality and quantity of health evaluation and the follow-up of Iranian living donors. Transplant Proc 2015;47:1092-1095. 100. Keshvani N, Feurer ID, Rumbaugh E, Dreher A, Zavala E, Stanley M, et al. Evaluating the impact of performance improvement initiatives on transplant center reporting compliance and patient follow-up after living kidney donation. Am J Transplant 2015;15:2126-2135. 101. Schold JD, Buccini LD, Rodrigue JR, Mandelbrot D, Goldfarb DA, Flechner SM, et al. Critical factors associated with missing follow-up data for living kidney donors in the United States. Am J Transplant 2015;15:2394-2403. 102. Weng FL, Reese PP, Waterman AD, Soto AG, Demissie K, Mulgaonkar S. Health care follow-up by live kidney donors more than three years post-nephrectomy. Clin Transplant 2012;26:E300-E306. 103. Mandelbrot D, Pavlakis M, Karp SJ, Johnson SR, Hanto DW, Rodrigue JR. Practices and barriers in long term living kidney donor follow-up: A survey of US transplant centres. Transplantation 2009;88:855-860. 104. Moosa MR, Meyers AM, Gottlich E, Naicker S. An effective approach to chronic kidney disease in South Africa. S Afr Med J 2016;106:156-159. 105. Davids MR, Balbir Singh GK, Marais N, Jacobs JC. South African Renal Registry Annual Report 2014. South African Renal Society, Cape Town 2016. 106. O'Donnell D, Seggie J, Levinson I, Meyers AM, Botha JR, Myburgh JA, et al. Renal function after nephrectomy for donor organs. S Afr Med J 1986;69:177-179. 107. Naicker S, Azor M, Sukool A, Holmes I, Muranda A, Haffejee AA. Follow-up of kidney donors at a single center in South Africa. AJN 1998;2:18-20. 43 108. Abdu A, Morolo N, Meyers AM, Wadee S, Britz R, Naicker S. Living kidney donor transplants over a 16-year period in South Africa: A single center experience. Ann Afr Med 2011;10:127-131. 109. McCurdie FJ, Pascoe MD, Broomberg CJ, Kahn D. Outcome of assessment of potential donors for live donor kidney transplants. Transplant Proc 2005;37:605-606. 44 CHAPTER 2: PROPOSED MANUSCRIPT Living kidney donation in a developing country Chandni Dayal 1, Malcolm Davies 1, 2, Nina Diana 1, 2 1 Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand; 2 Division of Nephrology, Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa ABSTRACT Living kidney donation is increasing in global significance as the preferred therapeutic modality to ameliorate the widening demand for renal allografts. There is limited data evaluating living donation in developing countries. We assessed reasons for non-donation and outcomes following donation amongst a cohort of 1208 ethnically diverse potential living donors over a 32-year period at a transplant centre in South Africa. Medical contraindications were the commonest reason for donor exclusion. These included hypertension, human immunodeficiency virus and obesity. Black donors were more likely to be excluded from donation (52.1% vs. 39.3%; p<0.001) particularly for medical reasons (44% vs. 35%; p<0.001). Amongst 298 accepted live donors, estimated glomerular filtration rate dropped below 60 ml/min/1.73m2 in 27% of patients at median follow-up of 3.7 years, although none required the initiation of renal replacement therapy. Following nephrectomy, severely increased albuminuria of >300 mg/day was noted in 4% of donors and 12.8% developed new-onset hypertension. Five donors demised of causes unrelated to renal outcomes. Black ethnicity was not associated with an increased risk of adverse post-donation outcome. This study shows a 45 substantial donor exclusion rate with considerable racial variation in the outcome of donor evaluation. A proportion of donors demonstrated a significant decline in renal function following nephrectomy, highlighting the need for close long-term donor follow-up. KEYWORDS: living kidney donation, developing country, potential living donors, donor exclusion, donor outcomes Correspondence: C Dayal, Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand; Charlotte Maxeke Johannesburg Academic Hospital Area 551; 7 York Road, Parktown, Johannesburg, 2193, South Africa. E-mail: chandnidayal@gmail.com INTRODUCTION The prevalence of end-stage kidney disease (ESKD) continues to rise globally1 and contributes significantly to the burden of chronic disease in developing countries.2 It is estimated that by the year 2030, in excess of 70% of patients with ESKD will reside in middle and low income countries, such as those in sub-Saharan Africa.3 Historically, renal replacement therapy (RRT) has been limited in these settings, with access being lowest in Africa, where less than one-fifth of individuals needing RRT receive it.4 South Africa faces a unique set of challenges in addressing this RRT gap.5 With the rising scourge of communicable diseases including human immunodeficiency virus (HIV) and tuberculosis demanding a disproportionate quantum of healthcare resources,6 the provision of expensive therapies such as RRT has the potential to exert significant strain on its emerging 46 economy.7 Due to pre-existing disparities in the provision of renal care, RRT in South Africa is at present largely concentrated in the privately funded sector; 8-10 whilst in the state sector, which serves more than 80% of the population, dialysis treatment is rationed with only those patients who are eligible for renal transplant being accepted. 7, 9 The present national transplant rate of 4.6 per million population in South Africa is on a downward trend,8 well below the transplant rates of other middle income countries.2, 8, 11 Without emergent intervention to expand the availability of transplantation in the South African population, already strained dialysis programs are at risk of collapse.7 The majority of renal transplants in the local state sector program are from deceased donors; living donation, whether altruistic or donor-directed, offers a mechanism to increase transplantation rates. Indeed, living kidney donation has been shown to be a cost-effective therapeutic modality to ameliorate the growing demand for sustainable RRT in the developing world.1, 2, 9, 12 Living donation does, however, require that healthy individuals endure a major surgical procedure devoid of any direct self-benefit.12 The numerous advantages of pre-emptive transplantation for the recipient must therefore be carefully balanced against maintaining immediate and long-term donor safety.13-16 Data suggests that up to two-thirds of potential living donors fail to complete the donation process.17-21 Understanding the reasons for non-donation is required to identify possible modifiable barriers for intervention in order to augment living donation rates.17,20 Furthermore, obtaining informed consent for donation is a challenge as consensus regarding the risks to the accepted donor following nephrectomy remain unclear,22 particularly amongst donors of black ethnicity who seem to bear the greatest risk of adverse outcomes.23-26 Older reports of 47 long-term donor follow-up suggested that the risks of uninephrectomy were of limited clinical significance, with donor outcomes largely comparable to that of the general population.27-30 In contrast, emerging data, with appropriately matched control groups, highlight poorer long term survival and an elevated risk of ESKD amongst living donor cohorts. 31-33 There is a paucity of data on the living donor selection process and outcomes at post-donation follow-up amongst demographically diverse populations in the developing world. The present study was undertaken to evaluate living donation in the South African context. The aim was to characterise reasons for non-donation, examine morbidity and mortality following donation, and to identify if any differences exist in outcomes among demographic subgroups in this setting. RESULTS Between January 1983 and July 2015, 1208 potential living donors were assessed at Charlotte Maxeke Johannesburg Academic Hospital (CMJAH), a transplant centre in South Africa. Only a quarter (n=298) of assessed patients were accepted for living donation, resulting in 910 failed living donors (FLDs). The demographic characteristics of the potential donor population are presented in Table 2.1. The most represented age group was that of 30-39 years (428; 35.4%). The majority of potential donors were female (697; 58%), of Black African descent (559; 46%) and biologically related to the intended or eventual recipient (991; 82%). 48 Medical contraindications to donation were the most common cause for donor disqualification (363; 39.9%); of which obesity, hypertension and HIV were most prevalent. Immunological barriers resulted in the exclusion of a further 19% of potential donors (n=173). A significant proportion (222; 25%) of donors were medically suitable but ultimately did not proceed to donation. This subgroup encompassed exclusions for recipient-related factors (120; 13.2%) and prospective donors who voluntarily withdrew from donation due to lack of further interest (102; 11.2%). Eighty-five (9.3%) of referred donors were lost to follow-up during the process of evaluation (Table 2.2). Outcome of donor evaluation varied significantly by race (Table 2.3). Black donors were more likely to fail work-up (51.2% vs. 39.3%; p<0.001) and be excluded for medical reasons (44% vs. 35%; p<0.001). In addition, forty-eight (49.5%) of medically suitable donors who voluntarily withdrew were of Black ethnicity. Median follow-up of the accepted donors was 3.7 years after donation (IQR 1.2-7.8 years). Clinical and laboratory parameters for this subgroup at baseline and at three successive post- donation follow-up points (at first visit, at one-year and at most recent visit) are shown in Table 2.4. Thirty-eight donors (12.8%) developed hypertension at follow-up, although the frequency of new-onset hypertension was not significantly different as compared to baseline (p=0.06). Statistically significant increase in both systolic and diastolic blood pressure was detected at one-year follow-up (p<0.001). There was a significant increase in albuminuria over time between the pre-donation and post-donation (most recent visit) (p<0.001), however the albumin excretion rate (AER) remained within normal limits. Thirteen donors (4%) developed 49 the primary endpoint of AER>300 mg/day, one of which was a living-unrelated donor that developed biopsy-proven membranous glomerulonephritis following donation. At most recent follow-up, estimated glomerular filtration rate (eGFR), determined using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula, was significantly lower compared to baseline measurements (72.5 vs. 91.7 ml/min/1.73 m2 respectively, p<0.001), representing a decrease in GFR of 21%. Eighty accepted donors (27%) developed a CKD-EPI- eGFR of less than 60 ml/min/1.73 m2 at most recent follow-up. Regression analysis identified multiple risk factors associated with this outcome (Table 2.5). These included Caucasian ethnicity, a lower eGFR at baseline and preceding visits, and an elevated blood pressure at the one year visit. However, none of the donors developed ESKD or required the institution of RRT. Black African ethnicity did not portend an increased risk of adverse outcome at most recent follow-up (Table 2.6). Over a longer median follow-up duration post donation, Black donors had better serum creatinine levels and calculated eGFR. However, donors of Black African origin had higher mean systolic blood pressures at last follow-up, although still within normal limits. Sixty-seven donors (22.5%) had an isolated medical abnormality (IMA) prior to donation. This subgroup included donors with a pre-donation body mass index (BMI) of between 30-35 kg/m2 (n=32); donors with a baseline isotope GFR of less than 80 ml/min/1.73 m2 (n=21) and those with pre-existing hypertension, well controlled on a single agent with no end-organ damage (n=14). A third of donors with an IMA were of Black African ethnicity. Class I obesity at baseline was not associated with an increased risk of developing hypertension (p=0.09) or an eGFR of 50 less than 60 ml/min/1.73 m2 (p=0.71) at follow-up. A pre-donation isotope GFR of less than 80 ml/min/1.73 m2 was associated with an eGFR less than 60 ml/min/1.73 m2 at most recent follow-up (p=0.02); the incidence of new onset hypertension was not significantly greater in this subgroup (p=0.27). With respect to non-renal outcomes, in the perioperative period sixteen donors (5.4%) suffered from complications including an iatrogenic pneumothorax (n=1); hospital acquired infections (n=3); and prolonged pain at the site of the nephrectomy scar (n=11). During the study period there were a total of 5 deaths (1.7%), one of which occurred in the immediate post-operative period. The remaining four deaths resulted from trauma and were thus unrelated to donation. Four donors (1.3%) required psychological support for major depressive disorder (n=2) and substance abuse (n=2). Caucasian donors were more likely to default follow-up (Table 2.7). Donors who resided more than 100 kilometres from the transplant centre had significantly shorter durations of post- donation follow-up. In addition, all donors aged 18-21 years (n=9) at the time of donation were lost to follow-up; donors over the age of twenty-one were at significantly lower risk of defaulting follow-up. Gender and degree of relationship to the recipient were not associated with poorer follow-up. 51 Table 2.1 | Donor demographics Characteristic Donors excluded n=910 (75.3%) Donors accepted n=298 (24.7%) Total evaluated n=1208 Age (in years) 18-21 22-29 30-39 40-49 50-59 ≥60 54 (5.9) ª 213 (23.4) 315 (34.6) 221 (24.2) 93 (10.2) 14 (1.53) 9 (3.0) 71 (23.8) 113 (37.9) 85 (28.5) 19 (6.4) 1 (0.3) 63 (5.2) 284 (23.5) 428 (35.4) 306 (25.3) 112 (9.3) 15 (1.2) Gender Female Male 522 (57.4) 388 (42.6) 175 (58.7) 123 (41.3) 697 (57.7) 511 (42.3) Ethnicity Black Caucasian Indian/Asian Coloured 474 (52.1) 358 (39.3) 38 (4.2) 40 (4.4) 85 (28.5) 175 (58.7) 26 (8.7) 12 (4.1) 559 (46.2) 533 (44.1) 64 (5.3) 52 (4.3) Relation to recipient Biological First degree relative Other relative Non-biological Directed Non-directed 722 (79.0) 631 (69.0) 91 (10.0) 188 (21.0) 180 (19.7) 8 (0.9) 269 (90.3) 256 (85.9) 13 (4.7) 29 (9.73) 29 (9.73) 0 991 (82) 887 (73.4) 104 (8.6) 217 (18.0) 209 (17.3) 8 (0.7) ª Values are expressed as n (%) 52 Table 2.2 | Reasons for non-donation n % n % DONOR RELATED FACTORS MEDICAL Hypertension 90 9.9 363 39.9 Human Immunodeficiency Virus 45 4.9 Obese class I (BMI 30-34) 40 4.4 Obese class II (BMI 35-39) 40 4.4 Chronic kidney disease (eGFR <70) 37 4.1 Hypertension and obesity 29 3.2 Obese class III (BMI ≥40) 9 1 Persistent iron deficiency anaemia 8 0.9 Diabetes 5 0.5 Persistent microalbuminuria 5 0.5 Hepatitis B 5 0.5 Hepatitis C 5 0.5 Hypertension and chronic kidney disease 4 0.4 Metabolic syndrome 4 0.4 Recurrent urinary tract infections 4 0.4 Tuberculosis 4 0.4 Familial hypercholesterolemia with atherosclerosis 3 0.3 Ischaemic heart disease 2 0.2 Valvular heart disease 2 0.2 Chronic obstructive pulmonary disease 2 0.2 Poorly controlled epilepsy 2 0.2 Von Willebrand Disease 2 0.2 Primary hyperparathyroidism 2 0.2 Systemic lupus erythematosus 2 0.2 Syphilis 2 0.2 Glomerulonephritis 1 0.1 Autosomal dominant polycystic kidney disease 1 0.1 Alport syndrome 1 0.1 Hashimoto's thyroiditis 1 0.1 Grave's disease 1 0.1 Ankylosing spondylitis 1 0.1 Incidental malignancy 1 0.1 UROLOGICAL Nephrolithiasis 6 0.6 8 0.9 Obstructive uropathy 2 0.2 ANATOMICAL Multiple renal arteries bilaterally 14 1.5 28 3.1 Congenital renal anomaly 8 0.8 Fibromuscular dysplasia 5 0.5 Renal artery stenosis 1 0.1 PSYCHOSOCIAL Withdrew voluntarily 102 11.2 208 22.9 Lost to follow-up 85 9.3 Psychiatric disorder 14 1.5 Polysubstance abuse 7 0.8 RECIPIENT RELATED FACTORS Transplant candidate demised 47 5.2 120 13.2 Alternate donation received (from alternate living donor) 32 3.5 Transplant candidate became medically ineligible 21 2.3 Alternate donation received (from deceased donor) 20 2.2 DONOR-RECIPIENT RELATED FACTORS ABO incompatibility 96 10.5 173 19 Positive cytotoxic antibody cross-match 77 8.5 MISCELLANEOUS Otherª 10 1.1 10 1.1 Abbreviations: BMI, Body mass index; eGFR, estimated glomerular filtration rate ª Includes donors disqualified for age >70 years, pregnancy and incarceration 53 Table 2.3 | Donor exclusion stratified by ethnicity Caucasian Black p-value Donor-related factors Medical Urological Anatomical Psychosocial 125 (34.9) ª 6 (1.7) 23 (6.4) 77 (21.5) 210 (44.3) 1 (0.2) 5 (1.1) 109 (23.0) <0.001 <0.001 <0.001 <0.001 Donor-recipient related factors Immunological 70 (19.6) 95 (20.0) <0.001 ª Values are expressed as n (%) Table 2.4 | Comparative clinical parameters in accepted living donors Pre- donation Post-donation p-value First Visit One Year Visit Most Recent Visit Systolic BP (mmHg) a Diastolic BP (mmHg) a Albuminuria (AER in mg/day) b Serum Creatinine (µmol/L) a CKD-EPI eGFR (ml/min/1.73m2)a 119 (11.8) 73 (9.1) 6 (3-12) 85 (14.6) 91.7 (19.1) 121 (17.3) 75 (11.7) 10 (3-28) 114 (21.0) 70.6 (19.4) 126 (17.1) 78 (12.9) 13 (3-77) 104 (15.7) 86.1 (19.7) 125 (16.0) 79 (10.7) 7 (3-29) 103 (24.3) 72.5 (20.0) <0.001 c <0.001 c <0.001 <0.001 <0.001 Abbreviations: BP, blood pressure; AER, albumin excretion rate; CKD-EPI eGFR, estimated glomerular filtration rate by Chronic Kidney Disease Epidemiology Collaboration equation ª Values are mean (± SD) b Values are median (± IQR) c Applies to analysis commencing at one-year follow-up 54 Table 2.5 | Logistic regression analysis of variables associated with an eGFR<60 ml/min/1.73m2 at most recent follow-up Coefficient Wald test p-value Age at donation -0.023 0.11 0.73 Gender Female 0.212 0.15 0.70 Ethnicity Caucasian Black 8.165 0.511 95 (20.0) 0.58 <0.001 0.44 BMI (kg/m2) Pre-donation First visit One-year visit 0.218 0.025 0.054 0.40 0.01 0.04 0.53 0.95 0.80 CKD-EPI eGFR (ml/min/1.73m2) Pre-donation First visit One-year visit -0.114 -0.270 -0.172 3.96 6.58 4.58 0.04 0.01 0.03 AER (mg/day) Pre-donation First visit One-year visit -0.018 0.022 -0.063 0.56 1.95 3.54 0.45 0.16 0.06 Systolic BP (mmHg) Pre-donation First visit One-year visit -0.024 -0.021 0.550 0.15 0.12 6.94 0.70 0.73 0.008 Diastolic BP (mmHg) Pre-donation First visit One-year visit 0.126 -0.111 -0.433 1.33 2.67 4.81 0.25 0.10 0.03 Abbreviations: BMI, body mass index; CKD-EPI eGFR, estimated glomerular filtration rate by Chronic Kidney Disease Epidemiology Collaboration equation; AER, albumin excretion rate; BP, blood pressure; 51 Cr-EDTA GFR, Chromium-51-ethylene-diamine-tetra-acetic-acid glomerular filtration rate 55 Table 2.6 | Accepted donor ethnicity and parameters at most recent follow-up visit Caucasian Black p-value Follow-up in years ª 2.29 (0.56-6.93) 5.54 (1.75-8.84) 0.0028 Parameter at most recent follow-up b Systolic BP (mmHg) Diastolic BP (mmHg) Albuminuria (AER in mg/day) Serum Creatinine (µmol/L) CKD-EPI eGFR (ml/min/1.73m2) 115.01 (17.53) 88.75 (13.41) 98.40 (446.22) 104.77 (18.95) 64.44 (15.51) 121.21 (18.04) 84.64 (13.07) 47.66 (64.85) 99.07 (21.99) 84.53 (21.33) 0.008 0.199 0.298 0.031 <0.0001 Abbreviations: BP, Blood Pressure; AER, albumin excretion rate; CKD-EPI eGFR, estimated glomerular filtration rate by Chronic Kidney Disease Epidemiology Collaboration equation a values are median (± IQR) b values are mean (± SD) Table 2.7 | Parameters associated with defaulting post-donation follow-up Parameter Hazard ratio 95% CI p-value Age at donation (in years) Age <21 0.2 0.1-0.5 0.001 Gender Female Male 0.7 1.1 0.6-1.0 0.4-2.9 0.1 0.6 Ethnicity Black Caucasian 0.8 2.4 0.4-2.0 1.2-4.7 0.06 0.008 Degree of relationship First Second Third 2.0 5.9 0.3 0.7-5.9 1.1-31.5 0.1-1.5 0.8 0.1 0.01 Domicile from hospital >100 kilometres 1.4 0.8-1.5 0.04 Abbreviations: CI, confidence interval 56 DISCUSSION Published data on living donation in Africa is limited, relying on small cohort studies.34-37 In an analysis of 117 potential donors at a single centre in the Western Cape province of South Africa, the donor exclusion rate was 83%. 34 In the first South African study assessing outcomes of 33 Caucasian related living donors over thirty years ago, 35 a rise in mean diastolic blood pressure with an inclination towards significant decline in creatinine clearance was noted at 5-year follow-up. In a later series by Naicker et al.36, 135 donors with a similar demographic profile to the present study were assessed over a 10-year period. Although limited by 10% of donors being lost to follow-up, no significant difference in blood pressure or proteinuria was noted following donation, with a normal mean serum creatinine level over the follow-up period. Findings of a subsequent study by Abdu et al. 37 were similarly reassuring. This study describes living kidney donation in the context of a developing country. Key findings include: 1. A substantial donor exclusion rate, predominately due to medical contraindications. 2. A significant decline in eGFR amongst a quarter of donors at most recent follow-up (median 3.7 years, IQR 1.2-7.8 years), although none required RRT. 3. Mortality in this series was low and unrelated to the development of renal dysfunction. 4. There was variation in outcomes amongst demographic subgroups, both in the donor evaluation process and in the decline in renal function following donor nephrectomy. Exclusion rates were highest amongst prospective donors of Black African origin. However, no greater risk to Black donors was demonstrated following nephrectomy. 57 The screening of prospective donors frequently results in the incidental diagnosis of occult disorders. Consistent with previous studies, 17-20 medical contraindications were the most common reason for non-donation in the present cohort, of which undiagnosed hypertension (14%) and obesity (10%) were most prevalent. This reflects the current spectrum of non-communicable disease burden in the local population where hypertension and obesity rates are amongst the highest in sub-Saharan Africa, 38, 39 at 45% and 49% respectively.40 In addition, epidemiological studies attribute the greatest proportion of disability adjusted life years lost in South Africa to these conditions.6 The high rates of hypertension and obesity in the failed donor group may partly be due to genetics; numerous studies support the role of distinct heritable factors that contribute to the increased development of these disorders, particularly in populations of black African ancestry. 41-43 In contrast to developed settings, 17, 20 the present study shows a significant donor exclusion rate due to communicable diseases (6.7%), primarily HIV infection (n=45; 4.9%). The prevalence of HIV amongst potential donors in this cohort is however lower than the general South African population prevalence of HIV infection. In 2016, the estimated adult (aged 15-49 years) seroprevalence rate of HIV in South Africa was 16.6%.8 A reduction in donor disqualification rates for medical reasons can be facilitated by improved quality of preventative care provided in primary health care systems.44 This is of particular relevance with non-communicable diseases, where enhanced screening at a 58 primary healthcare level may aid the timeous institution of therapy, prior to the development of complications that limit the use of prospective donors. As in our cohort, donors with isolated medical abnormalities including obesity (body mass index 30-35 kg/m2) and pre-existing hypertension, well controlled on a single agent with no end-organ damage, have been accepted in order to expand living donor pools; recent evidence supports favourable post donation outcomes amongst these subgroups as compared to appropriately matched cohorts. 45, 46 Immunological barriers resulted in the exclusion of 19% of donor candidates. This represents an important subgroup where novel modalities including paired donor exchanges, potential desensitisation of cross-match positive pairs and ABO-incompatible transplantation may be applied to augment living donation rates.47, 48 In developed settings, these approaches have increased the utilisation of living donors in otherwise incompatible donor-recipient pairs.49-51 Medically suitable donors who voluntarily withdrew accounted for the exclusion of 11.2% of failed donors in this study. Similarly high rates have been reported in multiple centres across the United States.20, 21 These rep