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Obesity affects graft function but not graft loss in kidney transplant recipients.

Maria Irene Bellini1, Kostas Koutroutsos2, Hannah Nananpragasam3, Emily Deurloo4, Jack Galliford5, Paul Elliot Herbert3,4.   

Abstract

Entities:  

Keywords:  Obesity; bariatric surgery; body mass index; estimated glomerular filtration rate; kidney function; kidney transplant

Mesh:

Year:  2020        PMID: 31939322      PMCID: PMC7114276          DOI: 10.1177/0300060519895139

Source DB:  PubMed          Journal:  J Int Med Res        ISSN: 0300-0605            Impact factor:   1.671


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Abbreviations

BMI: body mass index KTR: kidney transplant recipient eGFR: estimated glomerular filtration rate

Introduction

No consensus has been established in terms of the waitlist cut-off for a high body mass index (BMI) in kidney transplant candidates worldwide. The latest national guidelines in the United Kingdom[1] no longer recommend considering the BMI as a standalone criteria; however, controversy still exists among various institutions that adopt different immunosuppressive regimens in accepting bariatric patients with end-stage renal disease for transplantation. Aside from an increased perioperative risk for this subcategory of patients undergoing major surgery,[2] the justification of selecting kidney transplant candidates based on the World Health Organization definition of obesity[3] lies on optimisation of those patients who will benefit more from the limited organ donor resource. Some institutions have therefore introduced bariatric surgery as an effective bridge to increase the eligibility of obese kidney transplant candidates.[4] However, there is an argument against weight loss while on the waiting list for deceased-donor kidney transplantation although obesity negatively affects post-transplant outcomes.[5] One important consideration is that the muscle mass and protein storage levels are critical outcome determinants in dialysed patients; additionally, a high BMI cannot properly distinguish between patients with sarcopenia and those with adiposity. Furthermore, patients with a high BMI are often better respondents to the stress of deleterious infections than are other frail and poorly nourished patients; this is commonly called the ‘obesity paradox’.[6] The present study was performed to report our centre’s experience and the mid-term outcomes of a cohort of kidney transplant recipients (KTRs) who underwent treatment with a steroid-sparing immunosuppressive protocol. We compared patient and graft survival between obese and non-obese recipients in a stratified manner.

Methods

This study was performed in accordance with the principles of the Declaration of Helsinki. Data were prospectively collected on consecutive single KTRs who underwent transplantation from January 2014 to March 2016. All patients underwent treatment with a steroid-sparing immunosuppressive regimen (7-day course of steroids) with alemtuzumab induction and tacrolimus monotherapy (trough level, 5–8 ng/mL) or interleukin-2 induction with tacrolimus (trough level, 8–12 ng/mL) and mycophenolate mofetil. If a patient was not already being treated with steroids and mycophenolate mofetil, these drugs were only introduced to treat rejection. The BMI, measured as weight in kilograms divided by the square of height in meters, was grouped according to the World Health Organization classification. The patients were divided into three weight classes according to their BMI: underweight and normal (n = 154, 42%), overweight (n = 146, 39%), and obese (n = 70, 19%). As a measure of allograft function, the estimated glomerular filtration rate (eGFR) calculated with the Modification of Diet in Renal Disease equation[7] was determined at 3, 6, 12, 24, and 36 months post-transplantation. Both in-hospital and outpatient clinic records were considered. Delayed graft function was defined as a need for dialysis within 1 week of transplantation with a perfused graft. Graft survival was measured by the composite endpoint of all-cause graft failure, including failure due to death. Continuous variables are presented as mean ± standard deviation. Analysis of variance and the t test were used to compare continuous variables between groups. Pearson’s χ2 test was performed for nominal or nonparametric variables. The Kaplan–Meier method was applied for survival analysis. The confidence interval was set to 95%, and P was considered significant at <0.05. Analysis was performed using IBM SPSS Version 20.0 (IBM Corp., Armonk, NY, USA).

Results

In total, 370 patients underwent kidney transplantation during the study period. The mean BMI of the overall cohort was 26.2 kg/m2. The study population comprised 148 (40.0%) pre-obese, 47 (12.7%) class I obese, 11 (3.0%) class II obese, and 9 (2.4%) class III obese patients. Table 1 shows the differences in baseline characteristics among the six weight classes. Although there were statistically significant differences in all variables assessed among the groups, only male sex and younger age demonstrated a linear trend from the normal group moving through the progressively heavier groups. Overweight and obese KTRs had a significantly higher incidence of pre-transplant diabetes (p = 0.021). No difference was found in post-transplant new-onset hyperglycaemia among the groups.
Table 1.

Patients’ demographic characteristics.

Underweight (BMI < 18.5)Normal (18.5 ≤ BMI < 25)Overweight (25 ≤ BMI < 30)Class I obesity (30 ≤ BMI < 35)Class II obesity (35 ≤ BMI < 40)Class III obesity (BMI ≥ 40) p
Patients17 (5)137 (37)146 (39)50 (14)11 (3)9 (2)
Mean age, years41.2 ± 16.150.4 ± 13.155.7 ± 11.556.5 ± 9.850.1 ± 9.751.3 ± 11.9 <0.001
Sex
 (Male)5 (28)88 (64)108 (73)30 (64)6 (55)7 (78) 0.006
Recipient ethnicity
 Asian3 (17)48 (35)60 (41)13 (28)4 (36)0 (0)0.081
 Black2 (11)16 (12)9 (6)8 (17)0 (0)1 (11)
 Caucasian7 (39)48 (35)58 (39)19 (40)7 (64)6 (67)
 Mixed6 (33)25 (18)21 (14)7 (15)0 (0)2 (22)
Donor type
 Deceased7 (39)96 (70)99 (67)33 (70)10 (91)7 (78)0.145
 Live related6 (33)22 (16)19 (13)7 (15)0 (0)0 (0)
 Live unrelated5 (28)19 (14)30 (20)7 (15)1 (9)2 (22)
Pre-transplant diabetes1 (6)31 (23)49 (33)20 (43)4 (36)3 (33) 0.021
Induction
 Interleukin-22 (11)12 (9)11 (7)2 (4)0 (0)1 (11)0.791
 Alemtuzumab16 (89)125 (91)137 (93)45 (96)11 (100)8 (89)

BMI is given in kg/m2.

Data are presented as n (%) or mean ± standard deviation.

BMI, body mass index.

Patients’ demographic characteristics. BMI is given in kg/m2. Data are presented as n (%) or mean ± standard deviation. BMI, body mass index. Immunosuppression induction with interleukin-2 versus alemtuzumab did not differ according to BMI class (Table 1). Obesity was a significant risk factor for a lower eGFR at 3 and 6 months post-transplant; interestingly, however, while this was not a persistent finding at the 1-year follow-up, it became significant again at the 2- and 3-year follow-ups (Figure 1). Delayed graft function was not significantly different among the BMI classes. Additionally, no significant difference was found in the hospital length of stay between the non-obese and obese groups (Table 2).
Figure 1.

Kidney function during follow-up.

Table 2.

Transplantation outcomes.

Underweight (BMI < 18.5)Normal (18.5 ≤ BMI < 25)Overweight (25 ≤ BMI < 30)Class I obesity (30 ≤ BMI < 35)Class II obesity (35 ≤ BMI < 40)Class III obesity (BMI ≥ 40) p
Graft function
 Delayed1 (6)27 (20)29 (20)8 (17)2 (18)5 (56)0.27
 Immediate17 (94)109 (80)116 (78)39 (83)9 (82)4 (44)
 Primary dysfunction0 (0)1 (1)3 (2)0 (0)0 (0)0 (0)
Length of stay12.4 ± 6.112.4 ± 10.113.5 ± 10.815.3 ± 12.715.1 ± 14.918.8 ± 14.50.39
Post-treatment hyperglycaemia0 (0)4 (3)11 (7)4 (9)1 (9)0 (0)0.35
Death-censored graft failure0 (0)10 (7)11 (8)5 (10)1 (11)1 (11)0.84
Death1 (6)8 (6)13 (7)3 (6)0 (0)0 (0)0.74
Death with functioning graft0 (0)5 (4)3 (2)2 (4)0 (0)0 (0)0.31
Overall grafts lost1 (6)16 (12)18 (12)8 (16)1 (9)1 (11)0.90

BMI is given in kg/m2.

Data are presented as n (%) or mean ± standard deviation.

BMI, body mass index. Bold values are statistically significant values.

Kidney function during follow-up. Transplantation outcomes. BMI is given in kg/m2. Data are presented as n (%) or mean ± standard deviation. BMI, body mass index. Bold values are statistically significant values. Overall, 28 patients experienced graft loss and 25 patients died during follow-up. Forty-five allografts were lost in total; among these patients, nine died after allograft failure. To examine all-cause allograft loss, the patients were stratified into three groups: underweight and normal (n = 164, 41.3%), overweight (n = 152, 38.3%), and obese (n = 72, 18.1%). As shown in Figure 2, Kaplan–Meier analysis showed no difference in all-cause allograft loss among the different BMI groups during a mean follow-up of 42 months (range, 0–58 months). The allograft survival rate was lower in obese patients, but not significantly. Regression analysis revealed no added risk for graft loss in overweight patients (hazard ratio, 1.261; p = 0.51; 95% confidence interval, 0.63–2.53) and obese patients (hazard ratio, 1.089; p = 0.84; 95% confidence interval, 0.48–2.45) compared with recipients of normal weight when controlled by recipient ethnicity, age, sex, living versus deceased donors, and total number of mismatches.
Figure 2.

Overall graft survival during follow-up.

Overall graft survival during follow-up.

Discussion

In the present study, we investigated the effect of the BMI on kidney transplant outcomes. We previously demonstrated that allograft survival was not affected by the recipient being obese or of normal weight at the 1-year follow-up[8]; we further enhanced the prospective of transplantation rather than dialysis with the results reported herein. Allograft survival was not significantly lower at 2 and 3 years (Figure 2); therefore, obese patients benefit from kidney transplantation to the same extent as patients with a normal BMI. The eGFR was significantly lower in obese patients after the first year, as shown in Figure 1, but this should be interpreted under consideration of the general concept that an elevated BMI, waist circumference, and waist-to-height ratio are independent risk factors for a decline in the eGFR in individuals with a normal or reduced eGFR.[9] The post-transplant scenario is therefore a highly recommended time period during which to encourage weight loss and discuss the pros and cons of different strategies to achieve this.[10] If avoiding steroids is beneficial in the first year after transplant, the outcomes in the mid and long term will be influenced by the other concomitant conditions that obesity induces, namely metabolic syndrome and diabetes, hypertension, and increased risks of cardiovascular and chronic kidney disease.[11] What strategies can be implemented to preserve graft function? In KTRs, lifestyle and nutritional interventions have lower costs and reduced aggressiveness; therefore, all patients are eligible. Dietary advice should be individualised and include meal plans, exercise plans, and specific goals[12]; this is significantly associated with weight loss in the short term, but a high dropout rate and substantial weight regain have been described. Most importantly, no cases of drug malabsorption or complications have been reported to date. This cannot be said for bariatric surgery, which is the best treatment option for severe obesity.[13] Furthermore, the long-term results significantly increase the impact of any dietary interventions, although malabsorptive procedures can impact the KTR’s immunosuppression dose, and there is uncertainty about possible effects on kidney function (e.g., enteric oxalate nephropathy).[14] Although there are surgery-related risks when choosing a weight loss strategy, we believe that bariatric procedures should be more strongly recommended in the post-transplant than pre-transplant scenario for patients with end-stage renal disease.[15,16] We have shown that using a BMI cut-off is not reasonable in terms of transplant survival, and in fact our hospital does not rely on this parameter for the whole kidney transplant program.[17] However, some centres might be reluctant to adopt broader acceptance criteria.[18] Therefore, a possible way to increase transplant eligibility would be the use of robotic kidney transplantation. This technique has been proven to allow surgery in patients with extremely high BMIs with less postoperative pain and fewer wound complications, such as surgical site infections and hernia. This could be particularly advantageous in terms of overall costs and rehospitalisation, although there are initial capital costs associated with this procedure.[19] Finally, we believe that tailored immunosuppression is key. Our centre’s policy is to withdraw steroids early, within the first week after transplantation. This might contribute to ameliorating the outcome in the high-BMI population because in fact there is no difference in the incidence of post-transplant diabetes (Table 2), given that obesity is associated with an increased risk of steroid-induced diabetes.[20] In our view, a possible way forward would be the use of new drugs as belatacept, which has a better metabolic risk profile and may thus reduce drug-induced toxicities such as hypertension and diabetes.[21]

Meeting presentations

Association of Surgeons of Great Britain and Ireland, 7–9 May 2019, Telford, UK[22]; European Society Organ Transplantation Congress, 15–18 September 2019, Copenhagen, DE.[23]
  18 in total

1.  Bariatric Surgery as a Bridge to Renal Transplantation in Patients with End-Stage Renal Disease.

Authors:  Shadi Al-Bahri; Tannous K Fakhry; John Paul Gonzalvo; Michel M Murr
Journal:  Obes Surg       Date:  2017-11       Impact factor: 4.129

2.  Association Between Weight Loss Before Deceased Donor Kidney Transplantation and Posttransplantation Outcomes.

Authors:  Meera Nair Harhay; Karthik Ranganna; Suzanne M Boyle; Antonia M Brown; Thalia Bajakian; Lissa B Levin Mizrahi; Gary Xiao; Stephen Guy; Gregory Malat; Dorry L Segev; David Reich; Mara McAdams-DeMarco
Journal:  Am J Kidney Dis       Date:  2019-05-21       Impact factor: 8.860

3.  A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.

Authors:  A S Levey; J P Bosch; J B Lewis; T Greene; N Rogers; D Roth
Journal:  Ann Intern Med       Date:  1999-03-16       Impact factor: 25.391

Review 4.  Obesity-related glomerulopathy: pathogenesis, pathologic, clinical characteristics and treatment.

Authors:  Tianhua Xu; Zitong Sheng; Li Yao
Journal:  Front Med       Date:  2017-08-08       Impact factor: 4.592

Review 5.  The Role of Bariatric Surgery in Abdominal Organ Transplantation-the Next Big Challenge?

Authors:  Tomasz Dziodzio; Matthias Biebl; Robert Öllinger; Johann Pratschke; Christian Denecke
Journal:  Obes Surg       Date:  2017-10       Impact factor: 4.129

Review 6.  Post-Transplant Diabetes Mellitus: Causes, Treatment, and Impact on Outcomes.

Authors:  Vijay Shivaswamy; Brian Boerner; Jennifer Larsen
Journal:  Endocr Rev       Date:  2015-12-09       Impact factor: 19.871

7.  UK renal transplant outcomes in low and high BMI recipients: the need for a national policy.

Authors:  Ioannis D Kostakis; Theodoros Kassimatis; Valentina Bianchi; Panoraia Paraskeva; Clare Flach; Chris Callaghan; Benedict Lyle Phillips; Nikolaos Karydis; Nicos Kessaris; Francis Calder; Ioannis Loukopoulos
Journal:  J Nephrol       Date:  2019-10-03       Impact factor: 3.902

8.  One-Year Outcomes of a Cohort of Renal Transplant Patients Related to BMI in a Steroid-Sparing Regimen.

Authors:  Maria Irene Bellini; Kostas Koutroutsos; Jack Galliford; Paul E Herbert
Journal:  Transplant Direct       Date:  2017-11-03

9.  Obesity and bariatric intervention in patients with chronic renal disease.

Authors:  Maria Irene Bellini; Filippo Paoletti; Paul Elliot Herbert
Journal:  J Int Med Res       Date:  2019-04-21       Impact factor: 1.671

10.  The Effect of Donors' Demographic Characteristics in Renal Function Post-Living Kidney Donation. Analysis of a UK Single Centre Cohort.

Authors:  Maria Irene Bellini; Sotiris Charalampidis; Ioannis Stratigos; Frank J M F Dor; Vassilios Papalois
Journal:  J Clin Med       Date:  2019-06-20       Impact factor: 4.241

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  3 in total

1.  Impact of sleeve gastrectomy on renal function in patients with morbid obesity: a 1-year prospective cohort study.

Authors:  Delphine Sanchez; Amandine Lebrun; Sosthene Somda; Panagiotis Lainas; Karima Lamouri; Sophie Prevot; Micheline Njike-Nakseu; Hadrien Tranchart; Martin Gaillard; Mohamad Zaidan; Axel Balian; Ibrahim Dagher; Sylvie Naveau; Gabriel Perlemuter; Cosmin Sebastian Voican
Journal:  Langenbecks Arch Surg       Date:  2022-08-09       Impact factor: 2.895

2.  Management of obesity in kidney transplant candidates and recipients: A clinical practice guideline by the DESCARTES Working Group of ERA.

Authors:  Gabriel C Oniscu; Daniel Abramowicz; Davide Bolignano; Ilaria Gandolfini; Rachel Hellemans; Umberto Maggiore; Ionut Nistor; Stephen O'Neill; Mehmet Sukru Sever; Muguet Koobasi; Evi V Nagler
Journal:  Nephrol Dial Transplant       Date:  2021-12-24       Impact factor: 5.992

Review 3.  The Impact of Recipient Demographics on Outcomes from Living Donor Kidneys: Systematic Review and Meta-Analysis.

Authors:  Maria Irene Bellini; Mikhail Nozdrin; Liset Pengel; Simon Knight; Vassilios Papalois
Journal:  J Clin Med       Date:  2021-11-26       Impact factor: 4.241

  3 in total

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