1
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Kukla A, Sahi SS, Navratil P, Benzo RP, Smith BH, Duffy D, Park WD, Shah M, Shah P, Clark MM, Fipps DC, Denic A, Schinstock CA, Dean PG, Stegall MD, Kudva YC, Diwan TS. Weight Loss Surgery Increases Kidney Transplant Rates in Patients With Renal Failure and Obesity. Mayo Clin Proc 2024; 99:705-715. [PMID: 38702124 DOI: 10.1016/j.mayocp.2024.01.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/23/2023] [Accepted: 01/25/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE To describe the outcomes of kidney transplant (KT) candidates with obesity undergoing sleeve gastrectomy (SG) to meet the criteria for KT. METHODS Retrospective analysis was conducted of electronic medical records of KT candidates with obesity (body mass index >35 kg/m2) who underwent SG in our institution. Weight loss, adverse health events, and the listing and transplant rates were abstracted and compared with the nonsurgical cohort. RESULTS The SG was performed in 54 patients; 50 patients did not have surgery. Baseline demographic characteristics were comparable at the time of evaluation. Mean body mass index ± SD of the SG group was 41.7±3.6 kg/m2 at baseline (vs 41.5±4.3 kg/m2 for nonsurgical controls); at 2 and 12 months after SG, it was 36.4±4.1 kg/m2 and 32.6±4.0 kg/m2 (P<.01 for both). In the median follow-up time of 15.5 months (interquartile range, 6.4 to 23.9 months), SG was followed by active listing (37/54 people), and 20 of 54 received KT during a median follow-up time of 20.9 months (interquartile range, 14.7 to 28.3 months) after SG. In contrast, 14 of 50 patients in the nonsurgical cohort were listed, and 5 received a KT (P<.01). Three patients (5.6%) experienced surgical complications. There was no difference in overall hospitalization rates and adverse health outcomes, but the SG cohort experienced a higher risk of clinically significant functional decline. CONCLUSION In KT candidates with obesity, SG appears to be effective, with 37% of patients undergoing KT during the next 18 months (P<.01). Further research is needed to confirm and to improve the safety and efficacy of SG for patients with obesity seeking a KT.
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Affiliation(s)
- Aleksandra Kukla
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN; Von Liebig Transplant Center, Mayo Clinic, Rochester, MN.
| | - Sukhdeep S Sahi
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Pavel Navratil
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN; Department of Urology, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic; Faculty of Medicine in Hradec Kralove, Charles University, Hradec Kralove, Czech Republic
| | - Roberto P Benzo
- Department of Pulmonary Medicine, Mayo Clinic, Rochester, MN
| | - Byron H Smith
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Dustin Duffy
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Walter D Park
- Department of Cardiovascular Surgery Research, Mayo Clinic, Rochester, MN
| | - Meera Shah
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Pankaj Shah
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Matthew M Clark
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - David C Fipps
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Carrie A Schinstock
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN; Von Liebig Transplant Center, Mayo Clinic, Rochester, MN
| | - Patrick G Dean
- Von Liebig Transplant Center, Mayo Clinic, Rochester, MN; Department of Surgery and Immunology, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- Von Liebig Transplant Center, Mayo Clinic, Rochester, MN; Department of Surgery and Immunology, Mayo Clinic, Rochester, MN
| | - Yogish C Kudva
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Tayyab S Diwan
- Von Liebig Transplant Center, Mayo Clinic, Rochester, MN; Department of Surgery and Immunology, Mayo Clinic, Rochester, MN
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Pencovich N, Smith BH, Attia ZI, Jimenez FL, Bentall AJ, Schinstock CA, Khamash HA, Jadlowiec CC, Jarmi T, Mao SA, Park WD, Diwan TS, Friedman PA, Stegall MD. Electrocardiography-based Artificial Intelligence Algorithms Aid in Prediction of Long-term Mortality After Kidney Transplantation. Transplantation 2024:00007890-990000000-00715. [PMID: 38557657 DOI: 10.1097/tp.0000000000005023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative electrocardiograms (ECGs) in forecasting long-term mortality following KT. METHODS We analyzed preoperative ECGs from KT recipients at three Mayo Clinic sites (Minnesota, Florida, and Arizona) between January 1, 2006, and July 30, 2021. The study involved 6 validated AI algorithms, each trained to predict future development of atrial fibrillation, aortic stenosis, low ejection fraction, hypertrophic cardiomyopathy, amyloid heart disease, and biological age. These algorithms' outputs based on a single preoperative ECG were correlated with patient mortality data. RESULTS Among 6504 KT recipients included in the study, 1764 (27.1%) died within a median follow-up of 5.7 y (interquartile range: 3.00-9.29 y). All AI-ECG algorithms were independently associated with long-term all-cause mortality (P < 0.001). Notably, few patients had a clinical cardiac diagnosis at the time of transplant, indicating that AI-ECG scores were predictive even in asymptomatic patients. When adjusted for multiple clinical factors such as recipient age, diabetes, and pretransplant dialysis, AI algorithms for atrial fibrillation and aortic stenosis remained independently associated with long-term mortality. These algorithms also improved the C-statistic for predicting overall (C = 0.74) and cardiac-related deaths (C = 0.751). CONCLUSIONS The findings suggest that AI-enabled preoperative ECG analysis can be a valuable tool in predicting long-term mortality following KT and could aid in identifying patients who may benefit from enhanced cardiac monitoring because of increased risk.
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Affiliation(s)
- Niv Pencovich
- Departments of Surgery and Immunology, William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
- Department of General Surgery and Transplantation, Sheba Medical Center, Tel Hashomer, Tel-Aviv University, Tel-Aviv, Israel
| | - Byron H Smith
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Zachi I Attia
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | | | - Andrew J Bentall
- Departments of Surgery and Immunology, William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Carrie A Schinstock
- Departments of Surgery and Immunology, William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | | | | | - Tambi Jarmi
- Department of Transplant, Mayo Clinic Florida, Jacksonville, FL
| | - Shennen A Mao
- Division of Transplant Surgery, Department of Surgery, Mayo Clinic, Phoenix, AZ
| | - Walter D Park
- Departments of Surgery and Immunology, William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Tayyab S Diwan
- Departments of Surgery and Immunology, William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Paul A Friedman
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- Departments of Surgery and Immunology, William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
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3
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Alexander MP, Zaidi M, Larson N, Mullan A, Pavelko KD, Stegall MD, Bentall A, Wouters BG, McKee T, Taner T. Exploring the single-cell immune landscape of kidney allograft inflammation using imaging mass cytometry. Am J Transplant 2024; 24:549-563. [PMID: 37979921 DOI: 10.1016/j.ajt.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/01/2023] [Accepted: 11/11/2023] [Indexed: 11/20/2023]
Abstract
Kidney allograft inflammation, mostly attributed to rejection and infection, is an important cause of graft injury and loss. Standard histopathological assessment of allograft inflammation provides limited insights into biological processes and the immune landscape. Here, using imaging mass cytometry with a panel of 28 validated biomarkers, we explored the single-cell landscape of kidney allograft inflammation in 32 kidney transplant biopsies and 247 high-dimensional histopathology images of various phenotypes of allograft inflammation (antibody-mediated rejection, T cell-mediated rejection, BK nephropathy, and chronic pyelonephritis). Using novel analytical tools, for cell segmentation, we segmented over 900 000 cells and developed a tissue-based classifier using over 3000 manually annotated kidney microstructures (glomeruli, tubules, interstitium, and arteries). Using PhenoGraph, we identified 11 immune and 9 nonimmune clusters and found a high prevalence of memory T cell and macrophage-enriched immune populations across phenotypes. Additionally, we trained a machine learning classifier to identify spatial biomarkers that could discriminate between the different allograft inflammatory phenotypes. Further validation of imaging mass cytometry in larger cohorts and with more biomarkers will likely help interrogate kidney allograft inflammation in more depth than has been possible to date.
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Affiliation(s)
- Mariam P Alexander
- Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, Minnesota, USA.
| | - Mark Zaidi
- Department of Medical Biophysics, University of Toronto, Canada
| | - Nicholas Larson
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Aidan Mullan
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Kevin D Pavelko
- Immune Monitoring Core Laboratory, Mayo Clinic, Rochester, Minnesota, USA
| | - Mark D Stegall
- Departments of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andrew Bentall
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Bradly G Wouters
- Department of Medical Biophysics, University of Toronto, Canada; Princess Margaret Cancer Center, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Trevor McKee
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada; Pathomics Inc., Toronto, Ontario, Canada
| | - Timucin Taner
- Departments of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA
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4
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Pencovich N, Long JJ, Smith BH, Kinzelman-Vesely EA, Sudhindran V, Ryan RJ, Stegall MD, Kukla A, Diwan TS. Outcomes of Kidney Transplantation in Patients That Underwent Bariatric Surgery: A Systematic Review and Meta-analysis. Transplantation 2024; 108:346-356. [PMID: 37271882 DOI: 10.1097/tp.0000000000004680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The impact of bariatric surgery (BS) on kidney transplantation (KT) outcomes in patients with obesity remains controversial. We systematically searched MEDLINE, EMBASE, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials for studies reporting outcomes of KT recipients that underwent prior BS. Common/random effects meta-analyses were performed to obtain summary ratios of the postoperative outcomes. Eighteen eligible studies involving 315 patients were identified. Sleeve gastrectomy was the most common BS type (65.7%) followed by Roux-en-Y gastric bypass (27.6%) and gastric banding (4.4%). Across studies that provided the data, the %excess weight loss from BS to KT was 62.79% (95% confidence interval [CI], 52.01-73.56; range, 46.2%-80.3%). The rates of delayed graft function and acute rejection were 16% (95% CI, 7%-28%) and 16% (95% CI, 11%-23%) in 14 and 11 studies that provided this data, respectively. The rates of wound, urinary, and vascular complications following KT were 5% (95% CI, 0%-13%),19% (95% CI, 2%-42%), and 2% (95% CI, 0%-5%), in 12, 9, and 11 studies that provided this data, respectively. Follow-up time after KT was reported in 11 studies (61.1%) and ranged from 16 mo to >5 y. Graft loss was reported in 14 studies with an average of 3% (95% CI, 1%-6%). Four studies that included a comparator group of patients with obesity who did not undergo BS before KT showed comparable outcomes between the groups. We conclude that currently there is a paucity of robust evidence to suggest that pretransplant BS has a major effect on post-KT outcomes. High-quality studies are needed to fully evaluate the impact of BS on KT outcomes.
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Affiliation(s)
- Niv Pencovich
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
| | - Jane J Long
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
| | - Byron H Smith
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
| | | | - Vineeth Sudhindran
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
| | - Randi J Ryan
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
| | - Aleksandra Kukla
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Tayyab S Diwan
- Department of Surgery, Division of Transplantation Surgery, Mayo Clinic, Rochester, MN
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5
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Yoo D, Divard G, Raynaud M, Cohen A, Mone TD, Rosenthal JT, Bentall AJ, Stegall MD, Naesens M, Zhang H, Wang C, Gueguen J, Kamar N, Bouquegneau A, Batal I, Coley SM, Gill JS, Oppenheimer F, De Sousa-Amorim E, Kuypers DRJ, Durrbach A, Seron D, Rabant M, Van Huyen JPD, Campbell P, Shojai S, Mengel M, Bestard O, Basic-Jukic N, Jurić I, Boor P, Cornell LD, Alexander MP, Toby Coates P, Legendre C, Reese PP, Lefaucheur C, Aubert O, Loupy A. A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients. Nat Commun 2024; 15:554. [PMID: 38228634 DOI: 10.1038/s41467-023-44595-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 12/21/2023] [Indexed: 01/18/2024] Open
Abstract
In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.
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Affiliation(s)
- Daniel Yoo
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
| | - Gillian Divard
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
- Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Marc Raynaud
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
| | | | | | | | - Andrew J Bentall
- Division of Nephrology and Hypertension, Mayo Clinic Transplant Center, Rochester, MN, USA
| | | | - Maarten Naesens
- Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
| | - Huanxi Zhang
- Organ Transplant Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Changxi Wang
- Organ Transplant Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Juliette Gueguen
- Néphrologie-Immunologie Clinique, Hôpital Bretonneau, CHU Tours, Tours, France
| | - Nassim Kamar
- Department of Nephrology and Organ Transplantation, Paul Sabatier University, INSERM, Toulouse, France
| | - Antoine Bouquegneau
- Department of Nephrology-Dialysis-Transplantation, Centre hospitalier universitaire de Liège, Liège, Belgium
| | - Ibrahim Batal
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA
| | - Shana M Coley
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA
| | - John S Gill
- Division of Nephrology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Federico Oppenheimer
- Kidney Transplant Department, Hospital Clínic i Provincial de Barcelona, Barcelona, Spain
| | - Erika De Sousa-Amorim
- Kidney Transplant Department, Hospital Clínic i Provincial de Barcelona, Barcelona, Spain
| | - Dirk R J Kuypers
- Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
| | - Antoine Durrbach
- Department of Nephrology, AP-HP Hôpital Henri Mondor, Créteil, Île de France, France
| | - Daniel Seron
- Nephrology Department, Hospital Vall d'Hebrón, Autonomous University of Barcelona, Barcelona, Spain
| | - Marion Rabant
- Department of Pathology, Necker-Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Jean-Paul Duong Van Huyen
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
- Department of Pathology, Necker-Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Patricia Campbell
- Faculty of Medicine & Dentistry - Laboratory Medicine & Pathology Dept, University of Alberta, Edmonton, AB, Canada
| | - Soroush Shojai
- Faculty of Medicine & Dentistry - Laboratory Medicine & Pathology Dept, University of Alberta, Edmonton, AB, Canada
| | - Michael Mengel
- Faculty of Medicine & Dentistry - Laboratory Medicine & Pathology Dept, University of Alberta, Edmonton, AB, Canada
| | - Oriol Bestard
- Nephrology Department, Hospital Vall d'Hebrón, Autonomous University of Barcelona, Barcelona, Spain
| | - Nikolina Basic-Jukic
- Department of nephrology, arterial hypertension, dialysis and transplantation, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Ivana Jurić
- Department of nephrology, arterial hypertension, dialysis and transplantation, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Peter Boor
- Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany
| | - Lynn D Cornell
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Mariam P Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - P Toby Coates
- Department of Renal and Transplantation, University of Adelaide, Royal Adelaide Hospital Campus, Adelaide, SA, Australia
| | - Christophe Legendre
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
- Department of Kidney Transplantation, Necker-Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Peter P Reese
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
- Renal-Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadephia, PA, USA
| | - Carmen Lefaucheur
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
- Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Olivier Aubert
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France
- Department of Kidney Transplantation, Necker-Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Alexandre Loupy
- Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, F-75015, Paris, France.
- Department of Kidney Transplantation, Necker-Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France.
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6
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Long JJ, Motter JD, Jackson KR, Chen J, Orandi BJ, Montgomery RA, Stegall MD, Jordan SC, Benedetti E, Dunn TB, Ratner LE, Kapur S, Pelletier RP, Roberts JP, Melcher ML, Singh P, Sudan DL, Posner MP, El-Amm JM, Shapiro R, Cooper M, Verbesey JE, Lipkowitz GS, Rees MA, Marsh CL, Sankari BR, Gerber DA, Wellen JR, Bozorgzadeh A, Gaber AO, Heher EC, Weng FL, Djamali A, Helderman JH, Concepcion BP, Brayman KL, Oberholzer J, Kozlowski T, Covarrubias K, Massie AB, McAdams-DeMarco MA, Segev DL, Garonzik-Wang JM. Characterizing the risk of human leukocyte antigen-incompatible living donor kidney transplantation in older recipients. Am J Transplant 2023; 23:1980-1989. [PMID: 37748554 PMCID: PMC10767749 DOI: 10.1016/j.ajt.2023.09.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 08/26/2023] [Accepted: 09/18/2023] [Indexed: 09/27/2023]
Abstract
Older compatible living donor kidney transplant (CLDKT) recipients have higher mortality and death-censored graft failure (DCGF) compared to younger recipients. These risks may be amplified in older incompatible living donor kidney transplant (ILDKT) recipients who undergo desensitization and intense immunosuppression. In a 25-center cohort of ILDKT recipients transplanted between September 24, 1997, and December 15, 2016, we compared mortality, DCGF, delayed graft function (DGF), acute rejection (AR), and length of stay (LOS) between 234 older (age ≥60 years) and 1172 younger (age 18-59 years) recipients. To investigate whether the impact of age was different for ILDKT recipients compared to 17 542 CLDKT recipients, we used an interaction term to determine whether the relationship between posttransplant outcomes and transplant type (ILDKT vs CLDKT) was modified by age. Overall, older recipients had higher mortality (hazard ratio: 1.632.072.65, P < .001), lower DCGF (hazard ratio: 0.360.530.77, P = .001), and AR (odds ratio: 0.390.540.74, P < .001), and similar DGF (odds ratio: 0.461.032.33, P = .9) and LOS (incidence rate ratio: 0.880.981.10, P = 0.8) compared to younger recipients. The impact of age on mortality (interaction P = .052), DCGF (interaction P = .7), AR interaction P = .2), DGF (interaction P = .9), and LOS (interaction P = .5) were similar in ILDKT and CLDKT recipients. Age alone should not preclude eligibility for ILDKT.
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Affiliation(s)
- Jane J Long
- Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Jennifer D Motter
- Department of Surgery, New York University Grossman School of Medicine, New York, New York, USA
| | - Kyle R Jackson
- Department of Surgery, Emory University, Atlanta, Georgia, USA
| | - Jennifer Chen
- Department of Surgery, Baylor College of Medicine, Houston, Texas, USA
| | - Babak J Orandi
- Department of Surgery, University of Alabama, Birmingham, Alabama, USA
| | - Robert A Montgomery
- Department of Surgery, New York University Grossman School of Medicine, New York, New York, USA
| | - Mark D Stegall
- Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Stanley C Jordan
- Department of Medicine, Cedars-Sinai Comprehensive Transplant Center, Los Angeles, California, USA
| | - Enrico Benedetti
- Department of Surgery, University of Illinois-Chicago, Chicago, Illinois, USA
| | - Ty B Dunn
- Department of Surgery, University of Pennsylvania, Philadelphia, Philadelphia, USA
| | - Lloyd E Ratner
- Department of Surgery, Columbia University Medical Center, New York, New York, USA
| | - Sandip Kapur
- Department of Surgery, New York Presbyterian/Weill Cornell Medical Center, New York, New York, USA
| | - Ronald P Pelletier
- Department of Surgery, Robert Wood Johnson University Hospital, New Brunswick, New Jersey, USA
| | - John P Roberts
- Department of Surgery, University of California-San Francisco, San Francisco, California, USA
| | - Marc L Melcher
- Department of Surgery, Stanford University, Palo Alto, California, USA
| | - Pooja Singh
- Department of Medicine, Thomas Jefferson University Hospital, Philadelphia, Philadelphia, USA
| | - Debra L Sudan
- Department of Surgery, Duke University Medical Center, Durham, North Carolina, USA
| | - Marc P Posner
- Department of Surgery, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Jose M El-Amm
- Integris Baptist Medical Center, Transplant Division, Oklahoma City, Oklahoma, USA
| | - Ron Shapiro
- Recanati/Miller Transplantation Institute, Mount Sinai Hospital, New York, New York, USA
| | - Matthew Cooper
- Medstar Georgetown Transplant Institute, Washington, District of Columbia, USA
| | - Jennifer E Verbesey
- Medstar Georgetown Transplant Institute, Washington, District of Columbia, USA
| | - George S Lipkowitz
- Department of Surgery, Baystate Medical Center Springfield, Massachusetts, Massachusetts, USA
| | - Michael A Rees
- Department of Urology, University of Toledo Medical Center, Toledo, Ohio, USA
| | - Christopher L Marsh
- Department of Surgery, Scripps Clinic and Green Hospital, La Jolla, California, USA
| | | | - David A Gerber
- Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Jason R Wellen
- Department of Surgery, Barnes-Jewish Hospital, St. Louis, Missouri, USA
| | - Adel Bozorgzadeh
- Department of Surgery, University of Massachusetts Memorial Medical Center, Worcester, Massachusetts, USA
| | - A Osama Gaber
- Department of Surgery, Houston Methodist Hospital, Houston, Texas, USA
| | - Eliot C Heher
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Francis L Weng
- Renal and Pancreas Transplant Division, Cooperman Barnabas Medical Center, Livingston, New Jersey, USA
| | - Arjang Djamali
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - J Harold Helderman
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Beatrice P Concepcion
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kenneth L Brayman
- Department of Surgery, University of Virginia, Charlottesville, Virginia, USA
| | - Jose Oberholzer
- Department of Surgery, University of Virginia, Charlottesville, Virginia, USA
| | - Tomasz Kozlowski
- Department of Surgery, University of Florida, Gainesville, Florida, USA
| | - Karina Covarrubias
- Department of Surgery, University of California San Diego, San Diego, California, USA
| | - Allan B Massie
- Department of Surgery, New York University Grossman School of Medicine, New York, New York, USA; Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Mara A McAdams-DeMarco
- Department of Surgery, New York University Grossman School of Medicine, New York, New York, USA; Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Dorry L Segev
- Department of Surgery, New York University Grossman School of Medicine, New York, New York, USA; Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA; Scientific Registry of Transplant Recipients, Minneapolis, Minnesota, USA
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Asghar MS, Denic A, Mullan AF, Moustafa A, Barisoni L, Alexander MP, Stegall MD, Augustine J, Leibovich BC, Thompson RH, Rule AD. Age-Based Versus Young-Adult Thresholds for Nephrosclerosis on Kidney Biopsy and Prognostic Implications for CKD. J Am Soc Nephrol 2023; 34:1421-1432. [PMID: 37254246 PMCID: PMC10400104 DOI: 10.1681/asn.0000000000000171] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 04/21/2023] [Indexed: 06/01/2023] Open
Abstract
SIGNIFICANCE STATEMENT Nephrosclerosis (glomerulosclerosis, interstitial fibrosis, and tubular atrophy) is the defining pathology of both kidney aging and CKD. Optimal thresholds for nephrosclerosis that identify persons with a progressive disease are unknown. This study determined a young-age threshold (18-29 years) and age-based 95th percentile thresholds for nephrosclerosis on the basis of morphometry of kidney biopsy sections from normotensive living kidney donors. These thresholds were 7.1-fold to 36-fold higher in older (70 years or older) versus younger (aged 18-29 years) normotensive donors. Age-based thresholds, but not young-age threshold, were prognostic for determining risk of progressive CKD among patients who underwent a radical nephrectomy or a for-cause native kidney biopsy, suggesting that age-based thresholds are more useful than a single young-age threshold for identifying CKD on biopsy. BACKGROUND Nephrosclerosis, defined by globally sclerotic glomeruli (GSG) and interstitial fibrosis and tubular atrophy (IFTA), is a pathology of both kidney aging and CKD. A comparison of risk of progressive CKD using aged-based thresholds for nephrosclerosis versus a single young-adult threshold is needed. METHODS We conducted morphometric analyses of kidney biopsy images for %GSG, %IFTA, and IFTA foci density among 3020 living kidney donors, 1363 patients with kidney tumor, and 314 patients with native kidney disease. Using normotensive donors, we defined young-age thresholds (18-29 years) and age-based (roughly by decade) 95th percentile thresholds. We compared age-adjusted risk of progressive CKD (kidney failure or 40% decline in eGFR) between nephrosclerosis that was "normal compared with young," "normal for age but abnormal compared with young," and "abnormal for age" in patients with tumor and patients with kidney disease. RESULTS The 95th percentiles in the youngest group (18-29 years) to the oldest group (70 years or older) ranged from 1.7% to 16% for %GSG, 0.18% to 6.5% for %IFTA, and 8.2 to 59.3 per cm 2 for IFTA foci density. Risk of progressive CKD did not differ between persons with nephrosclerosis "normal compared with young" versus "normal for age but abnormal compared with young." Risk of progressive CKD was significantly higher with %GSG, %IFTA, or IFTA foci density that was abnormal versus normal for age in both cohorts. CONCLUSIONS Given that increased risk of progressive CKD occurs only when nephrosclerosis is abnormal for age, age-based thresholds for nephrosclerosis seem to be better than a single young-age threshold for identifying clinically relevant CKD.
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Affiliation(s)
- Muhammad S. Asghar
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Aidan F. Mullan
- Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, Minnesota
| | - Amr Moustafa
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Laura Barisoni
- Department of Pathology and Medicine, Duke University, Durham, North Carolina
| | - Mariam P. Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Mark D. Stegall
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Andrew D. Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
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Heilman RL, Fleming JN, Mai M, Smith B, Park WD, Holman J, Stegall MD. Multiple abnormal peripheral blood gene expression assay results are correlated with subsequent graft loss after kidney transplantation. Clin Transplant 2023; 37:e14987. [PMID: 37026820 DOI: 10.1111/ctr.14987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 03/16/2023] [Accepted: 03/26/2023] [Indexed: 04/08/2023]
Abstract
BACKGROUND The aim of this study was to correlate peripheral blood gene expression profile (GEP) results during the first post-transplant year with outcomes after kidney transplantation. METHODS We conducted a prospective, multicenter observational study of obtaining peripheral blood at five timepoints during the first post-transplant year to perform a GEP assay. The cohort was stratified based on the pattern of the peripheral blood GEP results: Tx-all GEP results normal, 1 Not-TX had one GEP result abnormal and >1 Not-TX two or more abnormal GEP results. We correlated the GEP results with outcomes after transplantation. RESULTS We enrolled 240 kidney transplant recipients. The cohort was stratified into the three groups: TX n = 117 (47%), 1 Not-TX n = 59 (25%) and >1 Not-TX n = 64 (27%). Compared to the TX group, the >1 Not-TX group had lower eGFR (p < .001) and more chronic changes on 1-year surveillance biopsy (p = .007). Death censored graft survival showed inferior graft survival in the >1 Not-TX group (p < .001) but not in the 1 Not-TX group. All graft losses in the >1 Not-TX group occurred after 1-year post-transplant. CONCLUSIONS We conclude that a pattern of persistently Not-TX GEP assay correlates with inferior graft survival.
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Affiliation(s)
| | - James N Fleming
- Medical Affairs, Transplant Genomics, Inc, Framingham, Massachusetts, USA
| | - Martin Mai
- Department of Medicine, Mayo Clinic, Jacksonville, Florida, USA
| | - Byron Smith
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Walter D Park
- Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - John Holman
- Department of Surgery, University of Utah, Salt Lake City, Utah, USA
| | - Mark D Stegall
- Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA
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Kattah AG, Mullan AF, Denic A, Smith ML, Stegall MD, Moustafa A, Chakkera HA, Garovic VD, Rule AD. Kidney Structure and Reproductive History Among Healthy Female Kidney Donors. Am J Kidney Dis 2023; 82:117-120. [PMID: 36906217 PMCID: PMC10658839 DOI: 10.1053/j.ajkd.2022.12.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 12/27/2022] [Indexed: 03/11/2023]
Affiliation(s)
- Andrea G Kattah
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota.
| | - Aidan F Mullan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Maxwell L Smith
- Department of Laboratory Medicine and Pathology, Division of Anatomic Pathology, Mayo Clinic, Scottsdale, Arizona
| | - Mark D Stegall
- Division of Transplantation Surgery, Mayo Clinic, Rochester, Minnesota
| | - Amr Moustafa
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | | | - Vesna D Garovic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Andrew D Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
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10
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Denic A, Mullan AF, Alexander MP, Wilson LD, Augustine J, Luehrs AC, Stegall MD, Kline TL, Sharma V, Thompson RH, Rule AD. An Improved Method for Estimating Nephron Number and the Association of Resulting Nephron Number Estimates with Chronic Kidney Disease Outcomes. J Am Soc Nephrol 2023; 34:1264-1278. [PMID: 36958059 PMCID: PMC10356139 DOI: 10.1681/asn.0000000000000124] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 02/15/2023] [Indexed: 03/25/2023] Open
Abstract
SIGNIFICANCE STATEMENT Nephron number currently can be estimated only from glomerular density on a kidney biopsy combined with cortical volume from kidney imaging. Because of measurement biases, refinement of this approach and validation across different patient populations have been needed. The prognostic importance of nephron number also has been unclear. The authors present an improved method of estimating nephron number that corrects for several biases, resulting in a 27% higher nephron number estimate for donor kidneys compared with a prior method. After accounting for comorbidities, the new nephron number estimate does not differ between kidney donors and kidney patients with tumor and shows consistent associations with clinical characteristics across these two populations. The findings also indicate that low nephron number predicts CKD independent of biopsy and clinical characteristics in both populations. BACKGROUND Nephron number can be estimated from glomerular density and cortical volume. However, because of measurement biases, this approach needs refinement, comparison between disparate populations, and evaluation as a predictor of CKD outcomes. METHODS We studied 3020 living kidney donors and 1354 patients who underwent radical nephrectomy for tumor. We determined cortex volume of the retained kidney from presurgical imaging and glomerular density by morphometric analysis of needle core biopsy of the donated kidney and wedge sections of the removed kidney. Glomerular density was corrected for missing glomerular tufts, absence of the kidney capsule, and then tissue shrinkage on the basis of analysis of 30 autopsy kidneys. We used logistic regression (in donors) and Cox proportional hazard models (in patients with tumor) to assess the risk of CKD outcomes associated with nephron number. RESULTS Donors had 1.17 million nephrons per kidney; patients with tumor had 0.99 million nephrons per kidney. A lower nephron number was associated with older age, female sex, shorter height, hypertension, family history of ESKD, lower GFR, and proteinuria. After adjusting for these characteristics, nephron number did not differ between donors and patients with tumor. Low nephron number (defined by <5th or <10th percentile by age and sex in a healthy subset) in both populations predicted future risk of CKD outcomes independent of biopsy and clinical characteristics. CONCLUSIONS Compared with an older method for estimating nephron number, a new method that addresses several sources of bias results in nephron number estimates that are 27% higher in donors and 1% higher in patients with tumor and shows consistency between two populations. Low nephron number independently predicts CKD in both populations.
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Affiliation(s)
- Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Aidan F. Mullan
- Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, Minnesota
| | - Mariam P. Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Luke D. Wilson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | | | - Anthony C. Luehrs
- Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, Minnesota
| | - Mark D. Stegall
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | | | - Vidit Sharma
- Department of Urology, Mayo Clinic, Rochester, Minnesota
| | | | - Andrew D. Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
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Raynaud M, Al-Awadhi S, Juric I, Divard G, Lombardi Y, Basic-Jukic N, Aubert O, Dubourg L, Masson I, Mariat C, Prié D, Pernin V, Le Quintrec M, Larson TS, Stegall MD, Bikbov B, Ruggenenti P, Mesnard L, Ibrahim HN, Nielsen MB, Matas AJ, Nankivell BJ, Benjamens S, Pol RA, Bakker SJL, Jouven X, Legendre C, Kamar N, Smith BH, Wadei HM, Durrbach A, Vincenti F, Remuzzi G, Lefaucheur C, Bentall AJ, Loupy A. Race-free estimated glomerular filtration rate equation in kidney transplant recipients: development and validation study. BMJ 2023; 381:e073654. [PMID: 37257905 PMCID: PMC10231444 DOI: 10.1136/bmj-2022-073654] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/17/2023] [Indexed: 06/02/2023]
Abstract
OBJECTIVE To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients. DESIGN Development and validation study SETTING: 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials). PARTICIPANTS 15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021. MAIN OUTCOME MEASURE The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation. RESULTS The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient's creatinine level, age, and sex (https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/). CONCLUSION A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys. TRIAL REGISTRATION ClinicalTrials.gov NCT05229939.
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Affiliation(s)
- Marc Raynaud
- Université de Paris Cité, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, F-75015 Paris, France
| | - Solaf Al-Awadhi
- Université de Paris Cité, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, F-75015 Paris, France
| | - Ivana Juric
- Department of Nephrology, Arterial Hypertension, Dialysis and Transplantation, University Hospital Centre Zagreb, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Gillian Divard
- Université de Paris Cité, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, F-75015 Paris, France
| | - Yannis Lombardi
- Department of Nephrology and Acute Kidney Intensive Care, Tenon Hospital, Paris, France
| | - Nikolina Basic-Jukic
- Department of Nephrology, Arterial Hypertension, Dialysis and Transplantation, University Hospital Centre Zagreb, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Olivier Aubert
- Université de Paris Cité, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, F-75015 Paris, France
- Department of Nephrology and Kidney Transplantation, Necker Hospital, Paris, France
| | - Laurence Dubourg
- Centre de Référence des Maladies Rénales Rares, Service de Néphrologie et Rhumatologie Pédiatriques, Hospices Civils de Lyon, Lyon, France
| | - Ingrid Masson
- Department of Nephrology, Dialysis and Renal Transplantation, Nord Hospital, Jean Monnet University, Saint-Etienne, France
| | - Christophe Mariat
- Department of Nephrology, Dialysis and Renal Transplantation, Nord Hospital, Jean Monnet University, Saint-Etienne, France
| | - Dominique Prié
- Department of Nephrology and Kidney Transplantation, Necker Hospital, Paris, France
| | - Vincent Pernin
- Department of Nephrology, University Hospital Centre, Montpellier, France
| | - Moglie Le Quintrec
- Department of Nephrology, University Hospital Centre, Montpellier, France
| | - Timothy S Larson
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota, USA
| | - Mark D Stegall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota, USA
| | - Boris Bikbov
- Department of Health Policy, Instituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Piero Ruggenenti
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e Cele Daccò": Instituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
- Unit of Nephrology and Dialysis, Azienda Socio-Sanitaria Territoriale Papa Giovanni XXIII, Bergamo, Italy
| | - Laurent Mesnard
- Department of Nephrology and Acute Kidney Intensive Care, Tenon Hospital, Paris, France
| | - Hassan N Ibrahim
- University of Texas Health Sciences Centre at Houston, Texas, USA
| | | | - Arthur J Matas
- Division of Transplantation, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Stan Benjamens
- Department of Surgery, University of Groningen and University Medical Centre Groningen, Groningen, Netherlands
| | - Robert A Pol
- Department of Surgery, University of Groningen and University Medical Centre Groningen, Groningen, Netherlands
| | - Stephan J L Bakker
- Division of Nephrology, Department of Internal Medicine, University of Groningen and University Medical Centre Groningen, Groningen, Netherlands
| | - Xavier Jouven
- Université de Paris Cité, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, F-75015 Paris, France
| | - Christophe Legendre
- Department of Nephrology and Kidney Transplantation, Necker Hospital, Paris, France
| | - Nassim Kamar
- Department of Nephrology and Organ Transplantation, Paul Sabatier University, INSERM, Toulouse, France
| | - Byron H Smith
- Division of Nephrology and Hypertension, Mayo Clinic, Jacksonville, Florida, USA
| | - Hani M Wadei
- Division of Nephrology and Hypertension, Mayo Clinic, Jacksonville, Florida, USA
| | - Antoine Durrbach
- Department of Nephrology and Renal Transplantation, Henri-Mondor Hospital, Paris-Saclay University, Creteil, France
| | - Flavio Vincenti
- Department of Surgery, Kidney Transplant Service, University of California San Francisco, San Francisco, California, USA
| | - Giuseppe Remuzzi
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e Cele Daccò": Instituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | - Carmen Lefaucheur
- Department of Kidney Transplantation, Saint Louis University Hospital, Paris, France
| | - Andrew J Bentall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota, USA
| | - Alexandre Loupy
- Université de Paris Cité, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, F-75015 Paris, France
- Department of Nephrology and Kidney Transplantation, Necker Hospital, Paris, France
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12
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Truchot A, Raynaud M, Kamar N, Naesens M, Legendre C, Delahousse M, Thaunat O, Buchler M, Crespo M, Linhares K, Orandi BJ, Akalin E, Pujol GS, Silva HT, Gupta G, Segev DL, Jouven X, Bentall AJ, Stegall MD, Lefaucheur C, Aubert O, Loupy A. Machine learning does not outperform traditional statistical modelling for kidney allograft failure prediction. Kidney Int 2023; 103:936-948. [PMID: 36572246 DOI: 10.1016/j.kint.2022.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 11/04/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
Machine learning (ML) models have recently shown potential for predicting kidney allograft outcomes. However, their ability to outperform traditional approaches remains poorly investigated. Therefore, using large cohorts of kidney transplant recipients from 14 centers worldwide, we developed ML-based prediction models for kidney allograft survival and compared their prediction performances to those achieved by a validated Cox-Based Prognostication System (CBPS). In a French derivation cohort of 4000 patients, candidate determinants of allograft failure including donor, recipient and transplant-related parameters were used as predictors to develop tree-based models (RSF, RSF-ERT, CIF), Support Vector Machine models (LK-SVM, AK-SVM) and a gradient boosting model (XGBoost). Models were externally validated with cohorts of 2214 patients from Europe, 1537 from North America, and 671 from South America. Among these 8422 kidney transplant recipients, 1081 (12.84%) lost their grafts after a median post-transplant follow-up time of 6.25 years (Inter Quartile Range 4.33-8.73). At seven years post-risk evaluation, the ML models achieved a C-index of 0.788 (95% bootstrap percentile confidence interval 0.736-0.833), 0.779 (0.724-0.825), 0.786 (0.735-0.832), 0.527 (0.456-0.602), 0.704 (0.648-0.759) and 0.767 (0.711-0.815) for RSF, RSF-ERT, CIF, LK-SVM, AK-SVM and XGBoost respectively, compared with 0.808 (0.792-0.829) for the CBPS. In validation cohorts, ML models' discrimination performances were in a similar range of those of the CBPS. Calibrations of the ML models were similar or less accurate than those of the CBPS. Thus, when using a transparent methodological pipeline in validated international cohorts, ML models, despite overall good performances, do not outperform a traditional CBPS in predicting kidney allograft failure. Hence, our current study supports the continued use of traditional statistical approaches for kidney graft prognostication.
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Affiliation(s)
- Agathe Truchot
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France
| | - Marc Raynaud
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France
| | - Nassim Kamar
- Université Paul Sabatier, INSERM, Department of Nephrology and Organ Transplantation, CHU Rangueil and Purpan, Toulouse, France
| | - Maarten Naesens
- Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
| | - Christophe Legendre
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Michel Delahousse
- Department of Transplantation, Nephrology and Clinical Immunology, Foch Hospital, Suresnes, France
| | - Olivier Thaunat
- Department of Transplantation, Nephrology and Clinical Immunology, Hospices Civils de Lyon, Lyon, France
| | - Matthias Buchler
- Nephrology and Immunology Department, Bretonneau Hospital, Tours, France
| | - Marta Crespo
- Department of Nephrology, Hospital del Mar Barcelona, Barcelona, Spain
| | - Kamilla Linhares
- Hospital do Rim, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Babak J Orandi
- University of Alabama at Birmingham Heersink School of Medicine, Birmingham, Alabama, USA
| | - Enver Akalin
- Renal Division, Montefiore Medical Centre, Kidney Transplantation Program, Albert Einstein College of Medicine, New York, New York, USA
| | - Gervacio Soler Pujol
- Unidad de Trasplante Renopancreas, Centro de Educacion Medica e Investigaciones Clinicas Buenos Aires, Buenos Aires, Argentina
| | - Helio Tedesco Silva
- Hospital do Rim, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Gaurav Gupta
- Division of Nephrology, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA
| | - Dorry L Segev
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xavier Jouven
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France; Cardiology Department, European Georges Pompidou Hospital, Paris, France
| | - Andrew J Bentall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota, USA
| | - Mark D Stegall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota, USA
| | - Carmen Lefaucheur
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France; Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Olivier Aubert
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Alexandre Loupy
- Université de Paris, INSERM, PARCC, Paris Translational Research Centre for Organ Transplantation, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France.
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13
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Denic A, Bogojevic M, Subramani R, Park WD, Smith BH, Alexander MP, Grande JP, Kukla A, Schinstock CA, Bentall AJ, Rule AD, Stegall MD. Changes in Glomerular Volume, Sclerosis, and Ischemia at 5 Years after Kidney Transplantation: Incidence and Correlation with Late Graft Failure. J Am Soc Nephrol 2023; 34:346-358. [PMID: 36396330 PMCID: PMC10103088 DOI: 10.1681/asn.2022040418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 10/02/2022] [Indexed: 11/18/2022] Open
Abstract
SIGNIFICANCE STATEMENT Glomerular volume, ischemic glomeruli, and global glomerulosclerosis are not consistently assessed on kidney transplant biopsies. The authors evaluated morphometric measures of glomerular volume, the percentage of global glomerulosclerosis, and the percentage of ischemic glomeruli and assessed changes in these measures over time to determine whether such changes predict late allograft failure. All three features increased from transplant to five-year biopsy. Kidneys with smaller glomeruli at 5 years had more global glomerulosclerosis and a higher percentage of ischemic-appearing glomeruli. Smaller glomeruli and increasing percentages of global glomerulosclerosis and ischemic glomeruli at 5 years predicted allograft failure. Only increased percentage of ischemic glomeruli predicted allograft failure at 5 years independent of all Banff scores. Glomerular changes reflect pathologic processes that predicted allograft loss; measuring them quantitatively might enhance the current Banff system and provide biomarkers for intervention trials. BACKGROUND Histology can provide insight into the biology of renal allograft loss. However, studies are lacking that use quantitative morphometry to simultaneously assess changes in mean glomerular volume and in the percentages of globally sclerosed glomeruli (GSG) and ischemic-appearing glomeruli in surveillance biopsies over time to determine whether such changes are correlated with late graft failure. METHODS We used digital scans of surveillance biopsies (at implantation and at 1 and 5 years after transplantation) to morphometrically quantify glomerular volume and the percentages of GSG and ischemic-appearing glomeruli in a cohort of 835 kidney transplants. Cox proportional hazards models assessed the risk of allograft failure with these three glomerular features. RESULTS From implantation to 5 years, mean glomerular volume increased by nearly 30% (from 2.8×10 6 to 3.6×10 6 µm 3 ), mean percentage of GSG increased from 3.2% to 13.2%, and mean percentage of ischemic-appearing glomeruli increased from 0.8% to 9.5%. Higher percentages of GSG and ischemic-appearing glomeruli at 5-year biopsy predicted allograft loss. The three glomerular features at 5-year biopsy were related; the percentage of GSG and the percentage of ischemic glomeruli were positively correlated, and both were inversely correlated to glomerular volume. At 5 years, only 5.3% of biopsies had ≥40% ischemic glomeruli, but 45% of these grafts failed (versus 11.6% for <40% ischemic glomeruli). Higher Banff scores were more common with increasing percentages of GSG and ischemia, but at 5 years, only the percentage of ischemic glomeruli added to predictive models adjusted for Banff scores. CONCLUSIONS Glomerular changes reflect important pathologic processes that predict graft loss. Measuring glomerular changes quantitatively on surveillance biopsies, especially the proportion of ischemic-appearing glomeruli, may enhance the current Banff system and be a useful surrogate end point for clinical intervention trials. PODCAST This article contains a podcast at.
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Affiliation(s)
- Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Marija Bogojevic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Rashmi Subramani
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Walter D. Park
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | - Byron H. Smith
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Mariam P. Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Joseph P. Grande
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Aleksandra Kukla
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | | | - Andrew J. Bentall
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Andrew D. Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Mark D. Stegall
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
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14
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Hermsen M, Ciompi F, Adefidipe A, Denic A, Dendooven A, Smith BH, van Midden D, Bräsen JH, Kers J, Stegall MD, Bándi P, Nguyen T, Swiderska-Chadaj Z, Smeets B, Hilbrands LB, van der Laak JAWM. Convolutional Neural Networks for the Evaluation of Chronic and Inflammatory Lesions in Kidney Transplant Biopsies. Am J Pathol 2022; 192:1418-1432. [PMID: 35843265 DOI: 10.1016/j.ajpath.2022.06.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 06/13/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
In kidney transplant biopsies, both inflammation and chronic changes are important features that predict long-term graft survival. Quantitative scoring of these features is important for transplant diagnostics and kidney research. However, visual scoring is poorly reproducible and labor intensive. The goal of this study was to investigate the potential of convolutional neural networks (CNNs) to quantify inflammation and chronic features in kidney transplant biopsies. A structure segmentation CNN and a lymphocyte detection CNN were applied on 125 whole-slide image pairs of periodic acid-Schiff- and CD3-stained slides. The CNN results were used to quantify healthy and sclerotic glomeruli, interstitial fibrosis, tubular atrophy, and inflammation within both nonatrophic and atrophic tubuli, and in areas of interstitial fibrosis. The computed tissue features showed high correlation with Banff lesion scores of five pathologists (A.A., A.Dend., J.H.B., J.K., and T.N.). Analyses on a small subset showed a moderate correlation toward higher CD3+ cell density within scarred regions and higher CD3+ cell count inside atrophic tubuli correlated with long-term change of estimated glomerular filtration rate. The presented CNNs are valid tools to yield objective quantitative information on glomeruli number, fibrotic tissue, and inflammation within scarred and non-scarred kidney parenchyma in a reproducible manner. CNNs have the potential to improve kidney transplant diagnostics and will benefit the community as a novel method to generate surrogate end points for large-scale clinical studies.
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Affiliation(s)
- Meyke Hermsen
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Francesco Ciompi
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Adeyemi Adefidipe
- Department of Pathology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Amélie Dendooven
- Department of Pathology, Ghent University Hospital, Ghent, Belgium; Faculty of Medicine, University of Antwerp, Wilrijk, Antwerp, Belgium
| | - Byron H Smith
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota; Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Dominique van Midden
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jan Hinrich Bräsen
- Nephropathology Unit, Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Jesper Kers
- Department of Pathology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands; Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands; Center for Analytical Sciences Amsterdam, Van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Mark D Stegall
- Division of Transplantation Surgery, Mayo Clinic, Rochester, Minnesota
| | - Péter Bándi
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tri Nguyen
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Zaneta Swiderska-Chadaj
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands; Faculty of Electrical Engineering, Warsaw University of Technology, Warsaw, Poland
| | - Bart Smeets
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Luuk B Hilbrands
- Department of Nephrology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jeroen A W M van der Laak
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
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15
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Mujtahedi SS, Yigitbilek F, Benavides X, Merzkani MA, Ozdogan E, Abozied O, Moore NA, Park WD, Stegall MD. Bone marrow derived long-lived plasma cell phenotypes are heterogeneous and can change in culture. Transpl Immunol 2022; 75:101726. [PMID: 36183942 DOI: 10.1016/j.trim.2022.101726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 09/15/2022] [Accepted: 09/25/2022] [Indexed: 11/28/2022]
Abstract
Bone marrow derived long-lived plasma cells (LLPCs) are thought to be a major source of alloantibody in sensitized transplant patients. However, studies of LLPCs have been hampered not only by the fact that they are rare and difficult to isolate and culture but also due to the lack of consensus regarding a definitive cell-surface phenotype. The goal of the current study was to determine if LLPCs have a specific, stable cell-surface phenotype. PCs were isolated from high-volume (120 cc) bone marrow aspirates that were enriched first by negative selection then positive selection using anti-CD38 antibody-coated beads and purified by cell sorting. A typical isolation resulted in >100,000 PCs that were sorted into 4 populations with variable numbers of PCs: CD19+/CD138+/CD38Hi (64.1% of the PCs), CD19-/CD138+/CD38Hi (20.9%), CD19+/CD138-/CD38Hi (10.7%), and CD19-/CD138-/CD38Hi (4.3%). The purity of each subset was 96-99%. Each subset contained PCs secreting IgG and IgA. Measles- and tetanus-specific PCs (i.e. putative IgG secreting, antigen-specific LLPCs). LLPCs were identified in both the CD19+/CD138+/CD38Hi and CD19-/CD138+/CD38Hi subsets and in the smaller CD138- subsets (when pooled). Thus, all CD38Hi subsets contained LLPCs. Cultured PCs maintained viability (>50%) and function and could be retrieved for analyses. During 7 days of culture, cell surface expression changed from baseline in many PCs. For example, approximately 20% of CD19 + CD138+/CD38Hi cells (the largest PC subset) became CD19-. CFSE assays showed no division and only a small percentage of LLPCs were Ki-67 positive suggesting that the cells did not divide in culture and that the antibody detected was not from plasmablasts. We conclude that human bone marrow LLPCs have a heterogeneous expression of CD19 and CD138, which can change during cell culture. The fact that LLPCs were found in all four subsets raises the possibility that a large percentage of PCs in the bone marrow may be LLPCs.
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Affiliation(s)
- Syed S Mujtahedi
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Furkan Yigitbilek
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Xiomara Benavides
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA; Departments of Surgery, Mayo Clinic, Rochester, MN, USA
| | - Massini A Merzkani
- John T. Milliken Department of Medicine, Division of Nephrology, Washington University, St. Louis, MO, USA
| | - Elif Ozdogan
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Omar Abozied
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | | | - Walter D Park
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Mark D Stegall
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA; Division of Transplant Surgery, Departments of Surgery and Immunology, Mayo Clinic, Rochester, MN, USA.
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16
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Kukla A, Diwan T, Smith BH, Collazo-Clavell ML, Lorenz EC, Clark M, Grothe K, Denic A, Park WD, Sahi S, Schinstock CA, Amer H, Issa N, Bentall AJ, Dean PG, Kudva YC, Mundi M, Stegall MD. Guiding Kidney Transplantation Candidates for Effective Weight Loss: A Clinical Cohort Study. Kidney360 2022; 3:1411-1416. [PMID: 36176651 PMCID: PMC9416837 DOI: 10.34067/kid.0001682022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 05/13/2022] [Indexed: 02/08/2023]
Abstract
BACKGROUND Obesity is increasingly common in kidney transplant candidates and may limit access to transplantation. Obesity and diabetes are associated with a high risk for post-transplant complications. The best approach to weight loss to facilitate active transplant listing is unknown, but bariatric surgery is rarely considered due to patient- and physician-related apprehension, among other factors. METHODS We aimed to determine the magnitude of weight loss, listing, and transplant rates in 28 candidates with a mean BMI of 44.4±4.6 kg/m2 and diabetes treated conservatively for 1 year post weight-loss consultations (group 1). Additionally, we evaluated 15 patients (group 2) who met the inclusion criteria but received bariatric intervention within the same time frame. All patients completed a multidisciplinary weight management consultation with at least 1 year of follow-up. RESULTS In the conservatively managed group (group 1), the mean weight at the time of initial consultation was 126.5±18.5 kg, and the mean BMI was 44.4±4.6 kg/m2. At 1 year post weight-loss consultation, the mean weight decreased by 4.4±8.2 kg to 122.9±17 kg, and the mean BMI was 43±4.8 kg/m2, with a total mean body weight decrease of 3% (P=0.01). Eighteen patients (64%) did not progress to become candidates for active listing/transplantation during the follow-up time of 4±2.9 years, with 15 (54%) subsequently developing renal failure/diabetes-related comorbidities prohibitive for transplantation. In contrast, mean total body weight decreased by 19% at 6 months post bariatric surgery, and the mean BMI was 34.2±4 and 32.5±3.7 kg/m2 at 6 and 12 months, respectively. Bariatric surgery was strongly associated with subsequent kidney transplantation (HR=8.39 [95% CI 1.71 to 41.19]; P=0.009). CONCLUSIONS A conservative weight-loss approach involving multidisciplinary consultation was ineffective in most kidney transplant candidates with diabetes, suggesting that a more proactive approach is needed.
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Affiliation(s)
- Aleksandra Kukla
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Tayyab Diwan
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | - Byron H. Smith
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Maria L. Collazo-Clavell
- Department of Medicine, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic Rochester, Minnesota
| | - Elizabeth C. Lorenz
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Matthew Clark
- Department of Medicine, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic Rochester, Minnesota
- Department of Psychiatry and Psychology, Mayo Clinic Rochester, Minnesota
| | - Karen Grothe
- Department of Medicine, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic Rochester, Minnesota
- Department of Psychiatry and Psychology, Mayo Clinic Rochester, Minnesota
| | - Aleksandar Denic
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Walter D. Park
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Sukhdeep Sahi
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Carrie A. Schinstock
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Hatem Amer
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Naim Issa
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Andrew J. Bentall
- Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Patrick G. Dean
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | - Yogish C. Kudva
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
- Department of Medicine, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic Rochester, Minnesota
| | - Manpreet Mundi
- Department of Medicine, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic Rochester, Minnesota
| | - Mark D. Stegall
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
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17
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Benavides X, Rogers RT, Tan EK, Merzkani MA, Thirunavukkarasu S, Yigitbilek F, Smith BH, Rule AD, Kukla A, Chow GK, Heimbach JK, Taner T, Dean PG, Prieto M, Stegall MD. Complications After Hand-Assisted Laparoscopic Living Donor Nephrectomy. Mayo Clin Proc 2022; 97:894-904. [PMID: 35483987 DOI: 10.1016/j.mayocp.2021.11.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 10/12/2021] [Accepted: 11/03/2021] [Indexed: 01/30/2023]
Abstract
OBJECTIVE To study the complications of hand-assisted laparoscopic living donor nephrectomy (HALLDN) with an emphasis on complications occurring early after hospital discharge up to 120 days after surgery. PATIENTS AND METHODS We retrospectively categorized complications using the Clavien-Dindo classification in 3002 HALLDNs performed at 1 center from January 1, 2000, through December 31, 2019. In addition to overall summaries, modeling was used to identify correlates of complications before and after living donation. RESULTS Of these donors, 87% were White, 59% were female, the mean age was 45 years (range, 18-77 years), 30.3% had a body mass index of at least 30, and 36.3% had previous abdominopelvic surgery. There were no deaths related to the surgery. The incidence of major complications (intraoperative complications plus Clavien-Dindo grade ≥III postoperatively) was 2.5% (n=74). The overall complication rate was 12.4% (n=371), including 15 intraoperative, 76 postoperative before discharge, and 280 after discharge to 120 days. Reoperation was required in 1.8% of patients (n=54), and all but 1 of these were incision-related problems. Seventy-six percent of all complications occurred after discharge, including 85% of the reoperations. For major complications, no risk factor was found. Risk factors for any complication included paramedian incision (hazard ratio [HR], 2.54; 95% CI, 1.49 to 4.34; P<.001); a history of abdominopelvic surgery (HR, 1.37; 95% CI, 1.07 to 1.76; P=.01), male sex (HR, 1.37; 95% CI, 1.07 to 1.76; P=.01), non-White race (HR, 1.40; 95% CI, 1.05 to 1.88; P=.02), and early era of the experience. CONCLUSION Most major complications of HALLDN occur after discharge, suggesting that close follow-up is warranted and that the current literature may underestimate the true incidence.
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Affiliation(s)
- Xiomara Benavides
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Richard T Rogers
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Ek Khoon Tan
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital, Singapore
| | - Massini A Merzkani
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | | | - Furkan Yigitbilek
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Byron H Smith
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Andrew D Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Aleksandra Kukla
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | | | - Julie K Heimbach
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Transplantation Surgery, Department of Surgery, Mayo Clinic, Rochester, MN
| | - Timucin Taner
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Transplantation Surgery, Department of Surgery, Mayo Clinic, Rochester, MN
| | - Patrick G Dean
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Transplantation Surgery, Department of Surgery, Mayo Clinic, Rochester, MN
| | - Mikel Prieto
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Transplantation Surgery, Department of Surgery, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN; Division of Transplantation Surgery, Department of Surgery, Mayo Clinic, Rochester, MN.
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18
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Cornell LD, Amer H, Viehman JK, Mehta RA, Lieske JC, Lorenz EC, Heimbach JK, Stegall MD, Milliner DS. Posttransplant recurrence of calcium oxalate crystals in patients with primary hyperoxaluria: Incidence, risk factors, and effect on renal allograft function. Am J Transplant 2022; 22:85-95. [PMID: 34174139 PMCID: PMC8710184 DOI: 10.1111/ajt.16732] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 05/30/2021] [Accepted: 06/19/2021] [Indexed: 01/25/2023]
Abstract
Primary hyperoxaluria (PH) is a metabolic defect that results in oxalate overproduction by the liver and leads to kidney failure due to oxalate nephropathy. As oxalate tissue stores are mobilized after transplantation, the transplanted kidney is at risk of recurrent disease. We evaluated surveillance kidney transplant biopsies for recurrent calcium oxalate (CaOx) deposits in 37 kidney transplants (29 simultaneous kidney and liver [K/L] transplants and eight kidney alone [K]) in 36 PH patients and 62 comparison transplants. Median follow-up posttransplant was 9.2 years (IQR: [5.3, 15.1]). The recurrence of CaOx crystals in surveillance biopsies in PH at any time posttransplant was 46% overall (41% in K/L, 62% in K). Higher CaOx crystal index (which accounted for biopsy sample size) was associated with higher plasma and urine oxalate following transplant (p < .01 and p < .02, respectively). There was a trend toward higher graft failure among PH patients with CaOx crystals on surveillance biopsies compared with those without (HR 4.43 [0.88, 22.35], p = .07). CaOx crystal deposition is frequent in kidney transplants in PH patients. The avoidance of high plasma oxalate and reduction of CaOx crystallization may decrease the risk of recurrent oxalate nephropathy following kidney transplantation in patients with PH. This study was approved by the IRB at Mayo Clinic.
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Affiliation(s)
- Lynn D. Cornell
- Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905
| | - Hatem Amer
- Division of Nephrology, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55905
| | - Jason K. Viehman
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota 55905
| | - Ramila A. Mehta
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota 55905
| | - John C. Lieske
- Division of Nephrology, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55905
| | - Elizabeth C. Lorenz
- Division of Nephrology, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55905
| | - Julie K. Heimbach
- Division of Transplant Surgery, William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota 55905
| | - Mark D. Stegall
- Division of Transplant Surgery, William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota 55905
| | - Dawn S. Milliner
- Division of Nephrology, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55905
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Raynaud M, Aubert O, Divard G, Reese PP, Kamar N, Yoo D, Chin CS, Bailly É, Buchler M, Ladrière M, Le Quintrec M, Delahousse M, Juric I, Basic-Jukic N, Crespo M, Silva HT, Linhares K, Ribeiro de Castro MC, Soler Pujol G, Empana JP, Ulloa C, Akalin E, Böhmig G, Huang E, Stegall MD, Bentall AJ, Montgomery RA, Jordan SC, Oberbauer R, Segev DL, Friedewald JJ, Jouven X, Legendre C, Lefaucheur C, Loupy A. Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study. Lancet Digit Health 2021; 3:e795-e805. [PMID: 34756569 DOI: 10.1016/s2589-7500(21)00209-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 07/22/2021] [Accepted: 08/17/2021] [Indexed: 01/22/2023]
Abstract
BACKGROUND Kidney allograft failure is a common cause of end-stage renal disease. We aimed to develop a dynamic artificial intelligence approach to enhance risk stratification for kidney transplant recipients by generating continuously refined predictions of survival using updates of clinical data. METHODS In this observational study, we used data from adult recipients of kidney transplants from 18 academic transplant centres in Europe, the USA, and South America, and a cohort of patients from six randomised controlled trials. The development cohort comprised patients from four centres in France, with all other patients included in external validation cohorts. To build deeply phenotyped cohorts of transplant recipients, the following data were collected in the development cohort: clinical, histological, immunological variables, and repeated measurements of estimated glomerular filtration rate (eGFR) and proteinuria (measured using the proteinuria to creatininuria ratio). To develop a dynamic prediction system based on these clinical assessments and repeated measurements, we used a Bayesian joint models-an artificial intelligence approach. The prediction performances of the model were assessed via discrimination, through calculation of the area under the receiver operator curve (AUC), and calibration. This study is registered with ClinicalTrials.gov, NCT04258891. FINDINGS 13 608 patients were included (3774 in the development cohort and 9834 in the external validation cohorts) and contributed 89 328 patient-years of data, and 416 510 eGFR and proteinuria measurements. Bayesian joint models showed that recipient immunological profile, allograft interstitial fibrosis and tubular atrophy, allograft inflammation, and repeated measurements of eGFR and proteinuria were independent risk factors for allograft survival. The final model showed accurate calibration and very high discrimination in the development cohort (overall dynamic AUC 0·857 [95% CI 0·847-0·866]) with a persistent improvement in AUCs for each new repeated measurement (from 0·780 [0·768-0·794] to 0·926 [0·917-0·932]; p<0·0001). The predictive performance was confirmed in the external validation cohorts from Europe (overall AUC 0·845 [0·837-0·854]), the USA (overall AUC 0·820 [0·808-0·831]), South America (overall AUC 0·868 [0·856-0·880]), and the cohort of patients from randomised controlled trials (overall AUC 0·857 [0·840-0·875]). INTERPRETATION Because of its dynamic design, this model can be continuously updated and holds value as a bedside tool that could refine the prognostic judgements of clinicians in everyday practice, hence enhancing precision medicine in the transplant setting. FUNDING MSD Avenir, French National Institute for Health and Medical Research, and Bettencourt Schueller Foundation.
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Affiliation(s)
- Marc Raynaud
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France
| | - Olivier Aubert
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Gillian Divard
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Peter P Reese
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Renal Electrolyte and Hypertension Division, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Nassim Kamar
- Université Paul Sabatier, INSERM, Department of Nephrology and Organ Transplantation, CHU Rangueil & Purpan, Toulouse, France
| | - Daniel Yoo
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France
| | - Chen-Shan Chin
- Deep Learning in Medicine and Genomics, DNAnexus, San Francisco, CA, USA
| | - Élodie Bailly
- Nephrology and Immunology Department, Bretonneau Hospital, Tours, France
| | - Matthias Buchler
- Nephrology and Immunology Department, Bretonneau Hospital, Tours, France
| | - Marc Ladrière
- Nephrology Dialysis Transplantation Department, University of Lorraine, Centre Hospitalier Universitaire Nancy, Nancy, France
| | - Moglie Le Quintrec
- Department of Nephrology, Centre Hospitalier Universitaire Montpellier, Montpellier, France
| | - Michel Delahousse
- Department of Transplantation, Nephrology and Clinical Immunology, Foch Hospital, Suresnes, France
| | - Ivana Juric
- Department of Nephrology, Arterial Hypertension, Dialysis and Transplantation, University Hospital Centre Zagreb, School of Medicine University of Zagreb, Zagreb, Croatia
| | - Nikolina Basic-Jukic
- Department of Nephrology, Arterial Hypertension, Dialysis and Transplantation, University Hospital Centre Zagreb, School of Medicine University of Zagreb, Zagreb, Croatia
| | - Marta Crespo
- Department of Nephrology, Hospital del Mar Barcelona, Spain
| | - Helio Tedesco Silva
- Hospital do Rim, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Kamilla Linhares
- Hospital do Rim, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | | | - Gervasio Soler Pujol
- Unidad de Trasplante Renopancreas, Centro de Educacion Medica e Investigaciones Clinicas Buenos Aires, Buenos Aires, Argentina
| | - Jean-Philippe Empana
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France
| | - Camilo Ulloa
- Kidney Transplantation Department, Clinica Alemana de Santiago, Santiago, Chile
| | - Enver Akalin
- Renal Division Montefiore Medical Centre, Kidney Transplantation Program, Albert Einstein College of Medicine, NY, USA
| | - Georg Böhmig
- Division of Nephrology and Dialysis, Department of Medicine III, General Hospital Vienna, Vienna, Austria
| | - Edmund Huang
- Department of Medicine, Division of Nephrology, Comprehensive Transplant Centre, Cedars Sinai Medical Centre, Los Angeles, CA, USA
| | - Mark D Stegall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Andrew J Bentall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | | | - Stanley C Jordan
- Department of Medicine, Division of Nephrology, Comprehensive Transplant Centre, Cedars Sinai Medical Centre, Los Angeles, CA, USA
| | | | - Dorry L Segev
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - John J Friedewald
- Kidney Transplantation Department, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Xavier Jouven
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Cardiology Department, European Georges Pompidou Hospital, Paris, France
| | - Christophe Legendre
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Carmen Lefaucheur
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Alexandre Loupy
- Paris Translational Research Centre for Organ Transplantation, INSERM, PARCC, Université de Paris, Paris, France; Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France.
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Danovitch GM, Bunnapradist S, Cohen D, Hariharan S, McKay D, Ratner L, Stegall MD, Steiner RW, Stock PG, Vincenti F. Tests for the noninvasive diagnosis of kidney transplant rejection should be evaluated by kidney transplant programs. Am J Transplant 2021; 21:3811. [PMID: 34080294 DOI: 10.1111/ajt.16711] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/26/2021] [Accepted: 06/01/2021] [Indexed: 01/25/2023]
Affiliation(s)
- Gabriel M Danovitch
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Suphamai Bunnapradist
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - David Cohen
- Department of Surgery, Columbia University Medical School, New York, New York, USA
| | - Sundaram Hariharan
- Starzl Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Dianne McKay
- Department of Immunology and Microbiology, Scripps Research, San Diego, California, USA
| | - Lloyd Ratner
- Department of Surgery, Columbia University Medical School, New York, New York, USA
| | - Mark D Stegall
- Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Robert W Steiner
- Department of Medicine, University of California at San Diego, San Diego, California, USA
| | - Peter G Stock
- Department of Surgery, University of California at San Francisco, San Francisco, California, USA
| | - Flavio Vincenti
- Department of Surgery, University of California at San Francisco, San Francisco, California, USA
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21
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Park WD, Kim DY, Mai ML, Reddy KS, Gonwa T, Ryan MS, Herrera Hernandez LP, Smith ML, Geiger XJ, Turkevi-Nagy S, Cornell LD, Smith BH, Kremers WK, Stegall MD. Progressive decline of function in renal allografts with normal 1-year biopsies: Gene expression studies fail to identify a classifier. Clin Transplant 2021; 35:e14456. [PMID: 34717009 DOI: 10.1111/ctr.14456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/23/2021] [Accepted: 08/04/2021] [Indexed: 11/29/2022]
Abstract
Histologic findings on 1-year biopsies such as inflammation with fibrosis and transplant glomerulopathy predict renal allograft loss by 5 years. However, almost half of the patients with graft loss have a 1-year biopsy that is either normal or has only interstitial fibrosis. The goal of this study was to determine if there was a gene expression profile in these relatively normal 1-year biopsies that predicted subsequent decline in renal function. Using transcriptome microarrays we measured intragraft mRNA levels in a retrospective Discovery cohort (170 patients with a normal/minimal fibrosis 1-year biopsy, 54 with progressive decline in function/graft loss and 116 with stable function) and developed a nested 10-fold cross-validated gene classifier that predicted progressive decline in renal function (positive predictive value = 38 ± 34%%; negative predictive value = 73 ± 30%, c-statistic = .59). In a prospective, multicenter Validation cohort (270 patients with Normal/Interstitial Fibrosis [IF]), the classifier had a 20% positive predictive value, 85% negative predictive value and .58 c-statistic. Importantly, the majority of patients with graft loss in the prospective study had 1-year biopsies scored as Normal or IF. We conclude predicting graft loss in many renal allograft recipients (i.e., those with a relatively normal 1-year biopsy and eGFR > 40) remains difficult.
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Affiliation(s)
| | - Dean Y Kim
- Henry Ford Hospital, Detroit, Michigan, USA
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22
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Mujtahedi SS, Yigitbilek F, Ozdogan E, Schinstock CA, Stegall MD. Antibody-Mediated Rejection: the Role of Plasma Cells and Memory B Cells. Curr Transpl Rep 2021. [DOI: 10.1007/s40472-021-00342-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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23
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Moreira CL, Hasib Sidiqi M, Buadi FK, Litzow MR, Gertz MA, Dispenzieri A, Russell SJ, Ansell SM, Stegall MD, Prieto M, Dean PG, Nyberg SL, El Ters M, Hogan WJ, Amer H, Cosio FG, Leung N. Long-term Outcomes of Sequential Hematopoietic Stem Cell Transplantation and Kidney Transplantation: Single-center Experience. Transplantation 2021; 105:1615-1624. [PMID: 33031227 DOI: 10.1097/tp.0000000000003477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Experience with sequential hematopoietic stem cell transplant (HSCT) and kidney transplant (KT) is limited. METHODS We conducted a retrospective observational study of adult patients who underwent both HSCT and KT at our center, with a median follow-up of 11 y. RESULTS In our 54 patients cohort (94% autologous HSCT), 36 (67%) patients received HSCT first followed by KT, while 18 (33%) received KT before HSCT. In both groups, AL amyloidosis represented 50% of hematologic diagnosis. Only 4 patients expired due to hematologic disease relapse (2 patients in each group) and only 3 allografts were lost due to hematologic disease recurrence (HSCT first n = 1 and KT first n = 2). Overall 1, 5, and 10 y death-censored graft survival rates were 94%, 94%, and 94%, respectively, for the HSCT first group and 89%, 89%, and 75%, respectively, for the KT first group. Overall 1, 5, and 10 y patients survival rates were 100%, 97% and 90%, respectively, for the HSCT first group and 100%, 76%, and 63%, respectively, for the KT first group. CONCLUSIONS Our study supports safety of sequential KT and HSCT, with improved overall patient survival compared to recipients of HSCT remaining on dialysis and good long-term kidney allograft outcome.
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Affiliation(s)
- Carla Leal Moreira
- Nephrology Department, Centro Hospitalar do Porto, Porto, Portugal
- Nephrology Department, Centro Hospitalar de Vila Nova de Gaia e Espinho, Porto, Portugal
| | | | | | | | | | | | | | | | - Mark D Stegall
- Division of Transplantation Surgery, Mayo Clinic Rochester, Rochester, MN
| | - Mikel Prieto
- Division of Transplantation Surgery, Mayo Clinic Rochester, Rochester, MN
| | - Patrick G Dean
- Division of Transplantation Surgery, Mayo Clinic Rochester, Rochester, MN
| | - Scott L Nyberg
- Division of Transplantation Surgery, Mayo Clinic Rochester, Rochester, MN
| | - Mireille El Ters
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - William J Hogan
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Hatem Amer
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Fernando G Cosio
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Nelson Leung
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
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24
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Kaur RJ, Rizvi SR, Reid C, McCrady-Spitzer SK, Dean P, Kukla A, Stegall MD, Kudva YC. Prospective Longitudinal Study Evaluating Comprehensive Metabolic and Life Style Characteristics of Pancreas Transplantation Recipients. J Endocr Soc 2021. [PMCID: PMC8090499 DOI: 10.1210/jendso/bvab048.941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Introduction: Pancreas Transplantation (PT) improves quality of life in Type 1 Diabetes (T1D) patients but limited longitudinal data are available regarding comprehensive metabolic assessment and lifestyle. Our objective was to comprehensively assess T1D patients who underwent PT (PTA and SPK) ≥ 1 year prior on two separate visits 1 year apart. Methodology: We studied 12 PT recipients ≥1 year post PT. Two assessments 1 year apart included comprehensive assessment of graft function using standard mixed meal tolerance test (MMTT), Continuous Glucose Monitoring (CGM) for 1 week, body composition using DEXA scan, physical activity using ActiGraph for 1 week and dietary assessment by VIOCARE®. Results: PT recipients (9F) were 55.5± 9.7 years old, 91.7 % Caucasian with 34.9 ± 12.3 years of diabetes, 6.7 ± 5.2 years (range-1.3–17.6 years) after PT. Ten participants underwent Pancreas Transplantation alone and two received Simultaneous Pancreas Kidney transplantation. Visit 1(V1) showed HbA1c 5.5 ± 0.7%, Fructosamine 238.4 ± 25.6 mcmol/L, BMI 31.2 ± 6.7 kg/m2, fasting plasma glucose (FPG) 95.2 ± 19.4mg/dL and C-peptide 2.6 ± 1.0 ng/ml and visit 2 (V2) HbA1c 5.5 ± 0.6%, Fructosamine 244.4 ± 41.3 mcmol/L, BMI 29.9 ± 5.1kg/m2, FPG 95.4 ± 27.7mg/dL, and C-peptide 2.5 ± 0.8 ng/ml (p-value not significant). One week CGM (n=9) showed excellent glucose control at both visits with mean glucose 117.8 ± 7.0 vs.112 ± 6.2 mg/dl and 96.3 ± 3.6 vs. 96.9±2.8 % time in target range (70-180mg/dl). Time >180mg/dl and >250mg/dl were 2.7 ± 3.0 vs. 1.3±1.7 % (p=0.0413) and 0.2 ± 0.6 vs. 0.1 ± 0.1 % respectively. Mild CGM hypoglycemia (<70 mg/dl) was observed during both visits (1.0 ± 1.0 vs. 1.7± 2 %). CV was 21.1 ± 5.5 and 20.1 ± 4.8 %. Eight recipients underwent MMTT and showed excellent response to Boost® with no significant difference between visits with exception of insulin concentrations at 60 mins (increased from V1) and 90 mins (decreased from V1) (p=0.0424 and 0.0235). DEXA (n=10) revealed similar total % mean fat, and fat distribution in arms, legs and trunk. ActiGraph (n=10) showed similar physical activity during both visits with 16761 ± 5176 and 14499 ± 4192 average steps/day respectively. Mean MET score was 1.6 ± 0.4 and 1.6 ± 0.2 indicating light intensity activity during both periods. Total mean sedentary bouts increased over 1 year (49.6 ± 39.1 vs. 60.8 ± 43.7, p=0.0038). Dietary assessment in 11 recipients showed no significant difference in dietary intake with calories intake 1.3± 0.4 vs. 1.2±0.5 daily Harris-Benedict and macronutrient intake with fat of 36.7 ± 4.3 % and 36.5 ± 5.7 %, CHO of 45.7 ± 5.5 % and 45.7 ± 5.5 % and Omega-3 of 0.1 ± 0.1 g and 0.05 ± 0.1 g respectively. Conclusion: PT recipients have excellent glucose control and pancreas graft function 1 or more years after PT when assessed over successive 2 years with suboptimal body composition and dietary intake and above average physical activity.
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25
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Motter JD, Jackson KR, Long JJ, Waldram MM, Orandi BJ, Montgomery RA, Stegall MD, Jordan SC, Benedetti E, Dunn TB, Ratner LE, Kapur S, Pelletier RP, Roberts JP, Melcher ML, Singh P, Sudan DL, Posner MP, El-Amm JM, Shapiro R, Cooper M, Verbesey JE, Lipkowitz GS, Rees MA, Marsh CL, Sankari BR, Gerber DA, Wellen JR, Bozorgzadeh A, Gaber AO, Heher EC, Weng FL, Djamali A, Helderman JH, Concepcion BP, Brayman KL, Oberholzer J, Kozlowski T, Covarrubias K, Massie AB, Segev DL, Garonzik-Wang JM. Delayed graft function and acute rejection following HLA-incompatible living donor kidney transplantation. Am J Transplant 2021; 21:1612-1621. [PMID: 33370502 PMCID: PMC8016719 DOI: 10.1111/ajt.16471] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 11/17/2020] [Accepted: 12/08/2020] [Indexed: 02/05/2023]
Abstract
Incompatible living donor kidney transplant recipients (ILDKTr) have pre-existing donor-specific antibody (DSA) that, despite desensitization, may persist or reappear with resulting consequences, including delayed graft function (DGF) and acute rejection (AR). To quantify the risk of DGF and AR in ILDKT and downstream effects, we compared 1406 ILDKTr to 17 542 compatible LDKT recipients (CLDKTr) using a 25-center cohort with novel SRTR linkage. We characterized DSA strength as positive Luminex, negative flow crossmatch (PLNF); positive flow, negative cytotoxic crossmatch (PFNC); or positive cytotoxic crossmatch (PCC). DGF occurred in 3.1% of CLDKT, 3.5% of PLNF, 5.7% of PFNC, and 7.6% of PCC recipients, which translated to higher DGF for PCC recipients (aOR = 1.03 1.682.72 ). However, the impact of DGF on mortality and DCGF risk was no higher for ILDKT than CLDKT (p interaction > .1). AR developed in 8.4% of CLDKT, 18.2% of PLNF, 21.3% of PFNC, and 21.7% of PCC recipients, which translated to higher AR (aOR PLNF = 1.45 2.093.02 ; PFNC = 1.67 2.403.46 ; PCC = 1.48 2.243.37 ). Although the impact of AR on mortality was no higher for ILDKT than CLDKT (p interaction = .1), its impact on DCGF risk was less consequential for ILDKT (aHR = 1.34 1.621.95 ) than CLDKT (aHR = 1.96 2.292.67 ) (p interaction = .004). Providers should consider these risks during preoperative counseling, and strategies to mitigate them should be considered.
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Affiliation(s)
- Jennifer D. Motter
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Kyle R. Jackson
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jane J. Long
- Department of Surgery, Mayo Clinic, Rochester, MN
| | - Madeleine M. Waldram
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Babak J. Orandi
- Department of Surgery, University of Alabama, Birmingham, AL
| | - Robert A. Montgomery
- The NYU Transplant Institute, New York University Langone Medical Center, New York, NY
| | | | - Stanley C. Jordan
- Department of Medicine, Cedars-Sinai Comprehensive Transplant Center, Los Angeles, CA
| | - Enrico Benedetti
- Department of Surgery, University of Illinois-Chicago, Chicago, IL
| | - Ty B. Dunn
- Department of Surgery, University of Pennsylvania, Philadelphia, PA
| | - Lloyd E. Ratner
- Department of Surgery, Columbia University Medical Center, New York, NY
| | - Sandip Kapur
- Department of Surgery, New York Presbyterian/Weill Cornell Medical Center, New York, NY
| | - Ronald P. Pelletier
- Department of Surgery, Robert Wood Johnson University Hospital, New Brunswick, NJ
| | - John P. Roberts
- Department of Surgery, University of California-San Francisco, San Francisco, CA
| | | | - Pooja Singh
- Department of Medicine, Thomas Jefferson University Hospital, Philadelphia. PA
| | - Debra L. Sudan
- Department of Surgery, Duke University Medical Center, Durham, NC
| | - Marc P. Posner
- Department of Surgery, Virginia Commonwealth University, Richmond, VA
| | - Jose M. El-Amm
- Integris Baptist Medical Center, Transplant Division, Oklahoma City, OK
| | - Ron Shapiro
- Recanti Miller Transplantation Institute, Mount Sinai Hospital, New York, NY
| | | | | | | | - Michael A. Rees
- Department of Urology, University of Toledo Medical Center, Toledo, OH
| | | | | | - David A. Gerber
- Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Jason R. Wellen
- Department of Surgery, Barnes-Jewish Hospital, St. Louis, MO
| | - Adel Bozorgzadeh
- Department of Surgery, University of Massachusetts Memorial Medical Center, Worcester, MA
| | - A. Osama Gaber
- Department of Surgery, Houston Methodist Hospital, Houston, TX
| | - Eliot C. Heher
- Department of Medicine, Massachusetts General Hospital, Boston, MA
| | - Francis L. Weng
- Renal and Pancreas Transplant Division, Saint Barnabas Medical Center, Livingston, NJ
| | - Arjang Djamali
- Department of Medicine, University of Wisconsin, Madison, WI
| | | | | | | | - Jose Oberholzer
- Department of Surgery, University of Virginia, Charlottesville, VA
| | | | - Karina Covarrubias
- Department of Surgery, University of California San Diego, San Diego, CA
| | - Allan B. Massie
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Dorry L. Segev
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD
- Scientific Registry of Transplant Recipients, Minneapolis, MN
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26
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Merzkani MA, Mullan A, Denic A, D'Costa M, Iverson R, Kremers W, Alexander MP, Textor SC, Taler SJ, Stegall MD, Augustine J, Issa N, Rule AD. Renal function outcomes and kidney biopsy features of living kidney donors with hypertension. Clin Transplant 2021; 35:e14293. [PMID: 33745214 DOI: 10.1111/ctr.14293] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND The medium- to long-term outcomes of living kidney donors with hypertension compared to normotensive donors are not well understood, especially with the recent changes in hypertension guidelines. METHODS We studied a cohort of 950 living kidney donors using different definitions of hypertension based on either ≥140/90 or ≥130/80 mmHg thresholds and based on either office or ambulatory blood pressure readings. Microstructural features on kidney biopsy at the time of donation were compared using different definitions of hypertension. RESULTS After adjusting for years of follow-up, age, sex, and baseline eGFR, hypertension (by any definition) did not significantly predict an eGFR < 45 ml/min/1.73 m2 at a median follow-up of 10 years postdonation, though there was a borderline association with ambulatory blood pressure ≥ 130/80 mmHg predicting a 40% decline in eGFR (OR = 1.53, 1.00-2.36; p = .051). Proteinuria was predicted by office blood pressure ≥ 140/90 mmHg and by nondipper profile on nocturnal ambulatory blood pressure measurements. At the time of donation, larger glomeruli and arterial hyalinosis on biopsy were associated with hypertension defined by either ≥140/90 or ≥130/80 mmHg (by office or ambulatory measurements). Nocturnal nondipper status was associated with larger glomeruli size but not arteriolar hyalinosis when compared to dippers. CONCLUSIONS In programs that accept donors with controlled hypertension, various definitions of hypertension are associated with histological findings in the donated kidney, but none predict a clinically significant decline in kidney function 10 years after donation. These data support allowing healthy individuals with controlled hypertension to donate a kidney. However, donors with office hypertension (≥140/90 mmHg) and nondippers (regardless of hypertension status) are at greater long-term risk for proteinuria, and particularly for these donors, longer follow-up is warranted.
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Affiliation(s)
- Massini A Merzkani
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA.,William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Aidan Mullan
- Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, USA
| | - Aleksandar Denic
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Matthew D'Costa
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA.,William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Ryan Iverson
- Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, USA
| | - Walter Kremers
- Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, USA
| | | | - Stephen C Textor
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA.,William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Sandra J Taler
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA.,William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Mark D Stegall
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | | | - Naim Issa
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA.,William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Andrew D Rule
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
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27
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Jackson KR, Long J, Motter J, Bowring MG, Chen J, Waldram MM, Orandi BJ, Montgomery RA, Stegall MD, Jordan SC, Benedetti E, Dunn TB, Ratner LE, Kapur S, Pelletier RP, Roberts JP, Melcher ML, Singh P, Sudan DL, Posner MP, El-Amm JM, Shapiro R, Cooper M, Verbesey JE, Lipkowitz GS, Rees MA, Marsh CL, Sankari BR, Gerber DA, Wellen J, Bozorgzadeh A, Gaber AO, Heher E, Weng FL, Djamali A, Helderman JH, Concepcion BP, Brayman KL, Oberholzer J, Kozlowski T, Covarrubias K, Desai N, Massie AB, Segev DL, Garonzik-Wang J. Center-level Variation in HLA-incompatible Living Donor Kidney Transplantation Outcomes. Transplantation 2021; 105:436-442. [PMID: 32235255 PMCID: PMC8080262 DOI: 10.1097/tp.0000000000003254] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Desensitization protocols for HLA-incompatible living donor kidney transplantation (ILDKT) vary across centers. The impact of these, as well as other practice variations, on ILDKT outcomes remains unknown. METHODS We sought to quantify center-level variation in mortality and graft loss following ILDKT using a 25-center cohort of 1358 ILDKT recipients with linkage to Scientific Registry of Transplant Recipients for accurate outcome ascertainment. We used multilevel Cox regression with shared frailty to determine the variation in post-ILDKT outcomes attributable to between-center differences and to identify any center-level characteristics associated with improved post-ILDKT outcomes. RESULTS After adjusting for patient-level characteristics, only 6 centers (24%) had lower mortality and 1 (4%) had higher mortality than average. Similarly, only 5 centers (20%) had higher graft loss and 2 had lower graft loss than average. Only 4.7% of the differences in mortality (P < 0.01) and 4.4% of the differences in graft loss (P < 0.01) were attributable to between-center variation. These translated to a median hazard ratio of 1.36 for mortality and 1.34 of graft loss for similar candidates at different centers. Post-ILDKT outcomes were not associated with the following center-level characteristics: ILDKT volume and transplanting a higher proportion of highly sensitized, prior transplant, preemptive, or minority candidates. CONCLUSIONS Unlike most aspects of transplantation in which center-level variation and volume impact outcomes, we did not find substantial evidence for this in ILDKT. Our findings support the continued practice of ILDKT across these diverse centers.
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Affiliation(s)
- Kyle R. Jackson
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jane Long
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jennifer Motter
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Mary G Bowring
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jennifer Chen
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Madeleine M. Waldram
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Babak J Orandi
- Department of Surgery, University of Alabama, Birmingham, AL
| | - Robert A. Montgomery
- The NYU Transplant Institute, New York University Langone Medical Center, New York, NY
| | | | - Stanley C. Jordan
- Department of Medicine, Cedars-Sinai Comprehensive Transplant Center, Los Angeles, CA
| | - Enrico Benedetti
- Department of Surgery, University of Illinois-Chicago, Chicago, IL
| | - Ty B. Dunn
- Department of Surgery, University of Pennsylvania, Philadelphia, PA
| | - Lloyd E. Ratner
- Department of Surgery, Columbia University Medical Center, New York, NY
| | - Sandip Kapur
- Department of Surgery, New York Presbyterian/Weill Cornell Medical Center, New York, NY
| | - Ronald P. Pelletier
- Department of Surgery, Robert Wood Johnson University Hospital, New Brunswick, NJ
| | - John P. Roberts
- Department of Surgery, University of California-San Francisco, San Francisco, CA
| | | | - Pooja Singh
- Department of Medicine, Thomas Jefferson University Hospital, Philadelphia. PA
| | - Debra L. Sudan
- Department of Surgery, Duke University Medical Center, Durham, NC
| | - Marc P. Posner
- Department of Surgery, Virginia Commonwealth University, Richmond, VA
| | - Jose M. El-Amm
- Integris Baptist Medical Center, Transplant Division, Oklahoma City, OK
| | - Ron Shapiro
- Recanti Miller Transplantation Institute, Mount Sinai Hospital, New York, NY
| | | | | | | | - Michael A. Rees
- Department of Urology, University of Toledo Medical Center, Toledo, OH
| | | | | | - David A. Gerber
- Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Jason Wellen
- Department of Surgery, Barnes-Jewish Hospital, St. Louis, MO
| | - Adel Bozorgzadeh
- Department of Surgery, University of Massachusetts Memorial Medical Center, Worcester, MA
| | - A. Osama Gaber
- Department of Surgery, Houston Methodist Hospital, Houston, TX
| | - Eliot Heher
- Department of Medicine, Massachusetts General Hospital, Boston, MA
| | - Francis L. Weng
- Renal and Pancreas Transplant Division, Saint Barnabas Medical Center, Livingston, NJ
| | - Arjang Djamali
- Department of Medicine, University of Wisconsin, Madison, WI
| | | | | | | | - Jose Oberholzer
- Department of Surgery, University of Virginia, Charlottesville, VA
| | | | - Karina Covarrubias
- Department of Surgery, University of California San Diego, San Diego, CA
| | - Niraj Desai
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Allan B. Massie
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Dorry L. Segev
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD
- Scientific Registry of Transplant Recipients, Minneapolis, MN
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Merzkani MA, Denic A, Narasimhan R, Lopez CL, Larson JJ, Kremers WK, Chakkera HA, Park WD, Taler SJ, Stegall MD, Alexander MP, Issa N, Rule AD. Kidney Microstructural Features at the Time of Donation Predict Long-term Risk of Chronic Kidney Disease in Living Kidney Donors. Mayo Clin Proc 2021; 96:40-51. [PMID: 33097219 PMCID: PMC7796899 DOI: 10.1016/j.mayocp.2020.08.041] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 07/23/2020] [Accepted: 08/24/2020] [Indexed: 12/20/2022]
Abstract
OBJECTIVE To determine whether microstructural features on a kidney biopsy specimen obtained during kidney transplant surgery predict long-term risk of chronic kidney disease in the donor. PATIENTS AND METHODS We studied kidney donors from May 1, 1999, through December 31, 2018, with a follow-up survey for the results of recent blood pressure and kidney function tests (estimated glomerular filtration rate [eGFR] and proteinuria). If not recently available, blood pressure and eGFRs were requested from a local clinic. Microstructural features on kidney biopsy at the time of donation were assessed as predictors of hypertension and kidney function after adjusting for years of follow-up, baseline age, sex, and clinical predictors. RESULTS There were 807 donors surveyed a mean 10.5 years after donation. An eGFR less than 45 mL/min/1.73 m2 in 6.4% (43/673) of donors was predicted by larger glomerular volume per standard deviation (odds ratio [OR], 1.48; 95% CI, 1.08 to 2.04) and nephron number below the age-specific 5th percentile (OR, 3.38; 95% CI, 1.31 to 8.72). An eGFR less than 60 mL/min/1.73 m2 in 42.5% (286/673) of donors was not predicted by any microstructural feature. Residual eGFR (postdonation/predonation eGFR) was predicted by nephron number below the age-specific 5th percentile (difference, -6.07%; 95% CI, -10.24% to -1.89%). Self-reported proteinuria in 5.1% (40/786) of donors was predicted by larger glomerular volume (OR, 1.42; 95% CI, 1.08 to 1.86). Incident hypertension in 18.8% (119/633) of donors was not predicted by any microstructural features. CONCLUSION Low nephron number for age and larger glomeruli are important microstructural predictors for long-term risk of chronic kidney disease after living kidney donation.
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Affiliation(s)
| | - Aleksandar Denic
- Divisions of Nephrology & Hypertension, Mayo Clinic, Rochester, MN
| | - Ramya Narasimhan
- Divisions of Nephrology & Hypertension, Mayo Clinic, Rochester, MN
| | - Camden L Lopez
- Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN
| | - Joseph J Larson
- Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN
| | | | | | - Walter D Park
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Sandra J Taler
- Divisions of Nephrology & Hypertension, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | | | - Naim Issa
- Divisions of Nephrology & Hypertension, Mayo Clinic, Rochester, MN
| | - Andrew D Rule
- Divisions of Nephrology & Hypertension, Mayo Clinic, Rochester, MN.
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Chakkera HA, Denic A, Kremers WK, Stegall MD, Larson JJ, Ravipati H, Taler SJ, Lieske JC, Lerman LO, Augustine JJ, Rule AD. Comparison of high glomerular filtration rate thresholds for identifying hyperfiltration. Nephrol Dial Transplant 2020; 35:1017-1026. [PMID: 30403810 DOI: 10.1093/ndt/gfy332] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 09/11/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND High glomerular filtration rate (GFR) is often used as a surrogate for single-nephron hyperfiltration. Our objective was to determine the definition for high GFR that best reflects clinical and structural characteristics of hyperfiltration. METHODS We studied living kidney donors at the Mayo Clinic and Cleveland Clinic. Potential donors underwent evaluations that included measured GFR (mGFR) by iothalamate clearance and estimated GFR (eGFR) by the serum creatinine-based Chronic Kidney Disease-Epidemiology collaboration (CKD-EPI) equation. High GFR was defined by the 95th percentile for each method (mGFR or eGFR) using either overall or age-specific thresholds. High mGFR was defined as both corrected and uncorrected for body surface area. The association of high GFR by each definition with clinical characteristics and radiologic findings (kidney volume) was assessed. In the subset that donated, the association of high GFR with kidney biopsy findings (nephron number and glomerular volume) and single-nephron GFR was assessed. RESULTS We studied 3317 potential donors, including 2125 actual donors. The overall 95th percentile for corrected mGFR was 134 mL/min/1.73 m2 and for eGFR was 118 mL/min/1.73 m2. The age-based threshold for uncorrected mGFR was 198 mL/min - 0.943×Age, for corrected mGFR it was 164 mL/min/1.73 m2 - 0.730×Age and for eGFR it was 146 mL/min/1.73 m2 - 0.813×Age. High age-based uncorrected mGFR had the strongest associations with higher single-nephron GFR, larger glomerular volume, larger kidney volume, male gender, higher body mass index and higher 24-h urine albumin, but also had the strongest association with high nephron number. A high age-height-gender-based uncorrected mGFR definition performed almost as well but had a weaker association with nephron number and did not associate with male gender. CONCLUSIONS High age-based uncorrected mGFR showed the most consistent associations reflective of hyperfiltration. However, high age-based uncorrected mGFR has limited clinical utility because it does not distinguish between hyperfiltration and high nephron number.
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Affiliation(s)
- Harini A Chakkera
- Division of Nephrology and Hypertension, Mayo Clinic, Scottsdale, AZ, USA
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Walter K Kremers
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | | | - Joseph J Larson
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Harish Ravipati
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Sandra J Taler
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - John C Lieske
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Lilach O Lerman
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | | | - Andrew D Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
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Loupy A, Haas M, Roufosse C, Naesens M, Adam B, Afrouzian M, Akalin E, Alachkar N, Bagnasco S, Becker JU, Cornell LD, Clahsen‐van Groningen MC, Demetris AJ, Dragun D, Duong van Huyen J, Farris AB, Fogo AB, Gibson IW, Glotz D, Gueguen J, Kikic Z, Kozakowski N, Kraus E, Lefaucheur C, Liapis H, Mannon RB, Montgomery RA, Nankivell BJ, Nickeleit V, Nickerson P, Rabant M, Racusen L, Randhawa P, Robin B, Rosales IA, Sapir‐Pichhadze R, Schinstock CA, Seron D, Singh HK, Smith RN, Stegall MD, Zeevi A, Solez K, Colvin RB, Mengel M. The Banff 2019 Kidney Meeting Report (I): Updates on and clarification of criteria for T cell- and antibody-mediated rejection. Am J Transplant 2020; 20:2318-2331. [PMID: 32463180 PMCID: PMC7496245 DOI: 10.1111/ajt.15898] [Citation(s) in RCA: 410] [Impact Index Per Article: 102.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 02/24/2020] [Accepted: 03/10/2020] [Indexed: 01/25/2023]
Abstract
The XV. Banff conference for allograft pathology was held in conjunction with the annual meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh, PA (USA) and focused on refining recent updates to the classification, advances from the Banff working groups, and standardization of molecular diagnostics. This report on kidney transplant pathology details clarifications and refinements to the criteria for chronic active (CA) T cell-mediated rejection (TCMR), borderline, and antibody-mediated rejection (ABMR). The main focus of kidney sessions was on how to address biopsies meeting criteria for CA TCMR plus borderline or acute TCMR. Recent studies on the clinical impact of borderline infiltrates were also presented to clarify whether the threshold for interstitial inflammation in diagnosis of borderline should be i0 or i1. Sessions on ABMR focused on biopsies showing microvascular inflammation in the absence of C4d staining or detectable donor-specific antibodies; the potential value of molecular diagnostics in such cases and recommendations for use of the latter in the setting of solid organ transplantation are presented in the accompanying meeting report. Finally, several speakers discussed the capabilities of artificial intelligence and the potential for use of machine learning algorithms in diagnosis and personalized therapeutics in solid organ transplantation.
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Kaur RJ, Smith BH, Rizvi SR, Batthula S, Kukla A, Dean PG, Kremers WK, Stegall MD, Kudva YC. SUN-624 Low Risk of Major Adverse Cardiovascular Events After Pancreas Transplantation Alone. J Endocr Soc 2020. [PMCID: PMC7207938 DOI: 10.1210/jendso/bvaa046.1791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION: Type 1 Diabetes (T1D) patients have an increased risk for major adverse cardiovascular events (MACE). Pancreas Transplantation Alone (PTA) in patients with T1D achieves near normal glucose control for a prolonged period but limited data are available to date regarding MACE during a 10 year follow up period after the procedure. OBJECTIVE: We studied incidence of MACE after PTA in T1D patients over a 10 year follow-up period. METHODS: Retrospectively, we studied 113 T1D recipients of PTA at Mayo Clinic, Rochester with the procedure performed between January 1998 and August 2018 and follow up of at least 1 year. Data were collected before transplantation and up to 10 year follow up after the first PTA. MACE data were gathered until primary non function, re-transplantation, or complete loss of c-peptide (<0.01ng/ml). We report vascular risk factors including hypertension, hyperlipidemia, smoking and BMI along with MACE (defined as cardiac events as unstable angina, Myocardial Infarction (MI), need for re-vascularization, cardiac death, cerebral events as Transient ischemic attack (TIA), stroke, need for re-vascularization and peripheral arterial disease as need for re-vascularization, gangrene and amputation). RESULTS: Eighteen subjects had pre-transplant MACE. A total of 14 subjects had graft failure within 24 to 36 hours due to thrombosis, with 3 in pre-transplant MACE cohort and 11 in no MACE cohort. Thus, we followed 99 subjects for the development of post-transplant MACE for a period of 6.3 ± 3.6 years. T1D subjects with MACE (n=15) had baseline characteristics: Age 48± 7.8 years, gender F/M 9/6,, duration of diabetes 33 ± 12 years, BMI 26± 3.1(Kg/m2), HbA1c 9.3 ± 1.5% and C-peptide 0.09 ng/ml. 84 T1D patients without MACE were age 42 ± 10.6 years, gender F/M 55/29, duration of diabetes 26.5 ± 10.7 years, BMI 26 ± 5.2(Kg/m2), HbA1c 6.7 ± 2.5 and C-peptide 0.09 ng/ml. There are a total of 584 person-years of follow up to first MACE event and 632 person-years of graft failure, death or last follow-up. Nine patients developed 11 MACE events post-PTA. Therefore, the event rate is 1.5 MACE events per 100 person-years for first MACE event and the total event rate is 1.7 MACE events per 100 person-years of follow-up. Age, smoking (yes), gender, duration of diabetes, HTN and Hyperlipidemia presence did not show any significant impact on post-transplant MACE outcome based on univariate Cox regression but the pre-transplant BMI (HR = 1.14; CI = (1.04, 1.26); p = 0.008) and pre-transplant HbA1c (HR = 1.26; CI = (1.06, 1.51); p = 0.01) showed statistically significant impact. CONCLUSIONS: At our center, MACE is low in PTA recipients. There is no impact of presence of pre-transplant MACE on development of post-transplant MACE but pre-transplant BMI and HbA1c account for risk of MACE.
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Taner T, Abrol N, Park WD, Hansen MJ, Gustafson MP, Lerman LO, van Wijnen AJ, Dietz AB, Gores GJ, Stegall MD. Phenotypic, Transcriptional, and Functional Analysis of Liver Mesenchymal Stromal Cells and Their Immunomodulatory Properties. Liver Transpl 2020; 26:549-563. [PMID: 31950576 DOI: 10.1002/lt.25718] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 01/03/2020] [Indexed: 12/23/2022]
Abstract
The liver is an immunologically active organ with a tolerogenic microenvironment at a quiescent state. The immunoregulatory properties of the liver appear to be retained after transplantation because liver allografts can reduce alloresponses against other organs that are simultaneously transplanted. Mechanisms of this phenomenon remain unknown. Given the known immunomodulatory properties of mesenchymal stromal cells (MSCs), we hypothesized that liver mesenchymal stromal cells (L-MSCs) are superior immunomodulators and contribute to liver-mediated tolerance. L-MSCs, generated from human liver allograft biopsies, were compared with adipose mesenchymal stromal cells (A-MSCs) and bone marrow mesenchymal stromal cells (BM-MSCs). Trilineage differentiation of L-MSCs was confirmed by immunohistochemistry. Comparative phenotypic analyses were done by flow cytometry and transcriptome analyses by RNA sequencing in unaltered cell cultures. The in vitro functional analyses were performed using alloreactive T cell proliferation assays. The transcriptome analysis showed that the L-MSCs are different than the A-MSCs and BM-MSCs, with significant enrichment of genes and gene sets associated with immunoregulation. Compared with the others, L-MSCs were found to express higher cell surface levels of several select immunomodulatory molecules. L-MSCs (versus A-MSCs/BM-MSCs) inhibited alloreactive T cell proliferation (22.7% versus 56.4%/58.7%, respectively; P < 0.05) and reduced the frequency of interferon ɤ-producing T cells better than other MSCs (52.8% versus 94.4%/155.4%; P < 0.05). The antiproliferative impact of L-MSCs was not dependent on cell-to-cell contact, could be reversed incompletely by blocking programmed death ligand 1, and required a higher concentration of the competitive inhibitor of indoleamine 2,3-dioxygenase for complete reversal. In conclusion, L-MSCs appear to be uniquely well-equipped immunomodulatory cells, and they are more potent than A-MSCs and BM-MSCs in that capacity, which suggests that they may contribute to liver-induced systemic tolerance.
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Affiliation(s)
- Timucin Taner
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, MN.,Department of Immunology, Mayo Clinic, Rochester, MN
| | - Nitin Abrol
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, MN
| | - Walter D Park
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, MN
| | | | - Michael P Gustafson
- Immune Progenitor and Cell Therapy (IMPACT), Division of Transfusion Medicine, Mayo Clinic, Rochester, MN
| | - Lilach O Lerman
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | | | - Allan B Dietz
- Immune Progenitor and Cell Therapy (IMPACT), Division of Transfusion Medicine, Mayo Clinic, Rochester, MN
| | - Gregory J Gores
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Mark D Stegall
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, MN.,Department of Immunology, Mayo Clinic, Rochester, MN
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Issa N, Lopez CL, Denic A, Taler SJ, Larson JJ, Kremers WK, Ricaurte L, Merzkani MA, Alexander MP, Chakkera HA, Stegall MD, Augustine JJ, Rule AD. Kidney Structural Features from Living Donors Predict Graft Failure in the Recipient. J Am Soc Nephrol 2020; 31:415-423. [PMID: 31974271 DOI: 10.1681/asn.2019090964] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 11/27/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Nephrosclerosis, nephron size, and nephron number vary among kidneys transplanted from living donors. However, whether these structural features predict kidney transplant recipient outcomes is unclear. METHODS Our study used computed tomography (CT) and implantation biopsy to investigate donated kidney features as predictors of death-censored graft failure at three transplant centers participating in the Aging Kidney Anatomy study. We used global glomerulosclerosis, interstitial fibrosis/tubular atrophy, artery luminal stenosis, and arteriolar hyalinosis to measure nephrosclerosis; mean glomerular volume, cortex volume per glomerulus, and mean cross-sectional tubular area to measure nephron size; and calculations from CT cortical volume and glomerular density on biopsy to assess nephron number. We also determined the death-censored risk of graft failure with each structural feature after adjusting for the predictive clinical characteristics of donor and recipient. RESULTS The analysis involved 2293 donor-recipient pairs. Mean recipient follow-up was 6.3 years, during which 287 death-censored graft failures and 424 deaths occurred. Factors that predicted death-censored graft failure independent of both donor and recipient clinical characteristics included interstitial fibrosis/tubular atrophy, larger cortical nephron size (but not nephron number), and smaller medullary volume. In a subset with 12 biopsy section slides, arteriolar hyalinosis also predicted death-censored graft failure. CONCLUSIONS Subclinical nephrosclerosis, larger cortical nephron size, and smaller medullary volume in healthy donors modestly predict death-censored graft failure in the recipient, independent of donor or recipient clinical characteristics. These findings provide insights into a graft's "intrinsic quality" at the time of donation, and further support the use of intraoperative biopsies to identify kidney grafts that are at higher risk for failure.
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Affiliation(s)
- Naim Issa
- Division of Nephrology and Hypertension.,William J von Liebig Center for Transplantation and Clinical Regeneration
| | | | | | - Sandra J Taler
- Division of Nephrology and Hypertension.,William J von Liebig Center for Transplantation and Clinical Regeneration
| | | | - Walter K Kremers
- William J von Liebig Center for Transplantation and Clinical Regeneration.,Division of Biomedical Statistics and Informatics, and
| | | | | | | | - Harini A Chakkera
- Division of Nephrology, Mayo Clinic Arizona, Scottsdale, Arizona; and
| | - Mark D Stegall
- William J von Liebig Center for Transplantation and Clinical Regeneration
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Stegall MD, Smith B, Bentall A, Schinstock C. The need for novel trial designs, master protocols, and research consortia in transplantation. Clin Transplant 2019; 34:e13759. [PMID: 31889338 DOI: 10.1111/ctr.13759] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 11/16/2019] [Indexed: 12/24/2022]
Abstract
Large multicenter, randomized controlled trials are the paradigm for determining the efficacy and safety of new therapies. However, applying this classical approach to many areas of transplantation is difficult. For most types of organ transplants, the number of transplants performed is too small for such a trial (lung, pancreas, or vascular composite transplantation are examples). In larger populations such as kidney transplantation, the major unmet needs commonly involve small subsets of patients (antibody-mediated rejection, recurrent renal disease, etc). This issue is not unique to transplantation and has been successfully overcome in other areas of medicine. In oncology, for example, novel trial designs such as adaptive trial design and master protocols are now relatively common. In addition, the existence of multicenter, ongoing clinical research consortia have greatly enhanced the successful implementation of these novel trial designs. In this manuscript, we examine how novel trial designs, master protocols, and research consortia might enhance studies in transplantation aimed at the regulatory approval of new agents. Our premise is that more efficient approaches to clinical trials already exist and, through a coordinated effort by researchers, the pharmaceutical industry, and regulatory bodies like the FDA, they can be implemented in transplantation.
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Affiliation(s)
- Mark D Stegall
- Departments of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | - Byron Smith
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Andrew Bentall
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Carrie Schinstock
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
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Affiliation(s)
- Alexandre Loupy
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris 75015, France.
| | - Antoine Bouquegneau
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris 75015, France; Department of Nephrology, Dialysis, Transplantation, University Hospital of Liege, Liege, Belgium
| | - Mark D Stegall
- William J von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
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Schinstock CA, Smith BH, Montgomery RA, Jordan SC, Bentall AJ, Mai M, Khamash HA, Stegall MD. Managing highly sensitized renal transplant candidates in the era of kidney paired donation and the new kidney allocation system: Is there still a role for desensitization? Clin Transplant 2019; 33:e13751. [DOI: 10.1111/ctr.13751] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 10/24/2019] [Accepted: 11/01/2019] [Indexed: 12/15/2022]
Affiliation(s)
- Carrie A. Schinstock
- Division of Nephrology and Hypertension Department of Internal Medicine Mayo Clinic Rochester MN USA
- The William J von Liebig Center for Transplantation and Clinical Regeneration Mayo Clinic Rochester MN USA
| | - Byron H. Smith
- Department of Health Sciences Research Mayo Clinic Rochester MN USA
| | | | | | - Andrew J. Bentall
- Division of Nephrology and Hypertension Department of Internal Medicine Mayo Clinic Rochester MN USA
- The William J von Liebig Center for Transplantation and Clinical Regeneration Mayo Clinic Rochester MN USA
| | - Martin Mai
- Transplant Center Mayo Clinic Jacksonville FL USA
| | - Hasan A. Khamash
- Division of Nephrology and Hypertension Department of Internal Medicine Mayo Clinic Phoenix AZ USA
| | - Mark D. Stegall
- The William J von Liebig Center for Transplantation and Clinical Regeneration Mayo Clinic Rochester MN USA
- Division of Transplantation Surgery Department of Medicine Mayo Clinic Rochester MN USA
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Tan EK, Bentall AJ, Dean PG, Shaheen MF, Stegall MD, Schinstock CA. Use of Eculizumab for Active Antibody-mediated Rejection That Occurs Early Post-kidney Transplantation: A Consecutive Series of 15 Cases. Transplantation 2019; 103:2397-2404. [PMID: 30801549 PMCID: PMC6699919 DOI: 10.1097/tp.0000000000002639] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Active antibody-mediated rejection (AMR) that occurs during the amnestic response within the first month posttransplant is a rare but devastating cause of early allograft loss after kidney transplant. Prior reports of eculizumab treatment for AMR have been in heterogeneous patient groups needing salvage therapy or presenting at varied time points. We investigated the role of eculizumab as primary therapy for active AMR early posttransplant. METHODS We performed a retrospective observational study of a consecutive cohort of solitary kidney transplant recipients who were transplanted between January 1, 2014, and January 31, 2018, and had AMR within the first 30 days posttransplant and treated with eculizumab ± plasmapheresis. RESULTS Fifteen patients had early active AMR at a median (interquartile range [IQR]) of 10 (7-11) days posttransplant and were treated with eculizumab ± plasmapheresis. Thirteen cases were biopsy proven, and 2 cases were presumed on the basis of donor-specific antibody trends and allograft function. Within 1 week of treatment, the median estimated glomerular filtration rate increased from 21 to 34 mL/min (P = 0.001); and persistent active AMR was only found in 16.7% (2/12) of biopsied patients within 4-6 months. No graft losses occurred, and at last follow-up (median [IQR] of 13 [12-19] mo), the median IQR estimated glomerular filtration rate increased to 52 (46-60) mL/min. CONCLUSIONS Prompt eculizumab treatment as primary therapy is safe and effective for early active AMR after kidney transplant or abrupt increases in donor-specific antibodies when biopsy cannot be performed for diagnosis confirmation.
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Affiliation(s)
- Ek Khoon Tan
- Division of Transplantation Surgery, Mayo Clinic, Rochester, Minnesota
| | - Andrew J. Bentall
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- Mayo Clinic William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota
| | - Patrick G. Dean
- Division of Transplantation Surgery, Mayo Clinic, Rochester, Minnesota
- Mayo Clinic William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota
| | | | - Mark D. Stegall
- Division of Transplantation Surgery, Mayo Clinic, Rochester, Minnesota
- Mayo Clinic William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota
| | - Carrie A. Schinstock
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
- Mayo Clinic William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota
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Denic A, Morales MC, Park WD, Smith BH, Kremers WK, Alexander MP, Cosio FG, Rule AD, Stegall MD. Using computer-assisted morphometrics of 5-year biopsies to identify biomarkers of late renal allograft loss. Am J Transplant 2019; 19:2846-2854. [PMID: 30947386 PMCID: PMC8214914 DOI: 10.1111/ajt.15380] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 03/20/2019] [Accepted: 03/28/2019] [Indexed: 01/25/2023]
Abstract
The current Banff scoring system was not developed to predict graft loss and may not be ideal for use in clinical trials aimed at improving allograft survival. We hypothesized that scoring histologic features of digitized renal allograft biopsies using a continuous, more objective, computer-assisted morphometric (CAM) system might be more predictive of graft loss. We performed a nested case-control study in kidney transplant recipients with a surveillance biopsy obtained 5 years after transplantation. Patients that developed death-censored graft loss (n = 67) were 2:1 matched on age, gender, and follow-up time to controls with surviving grafts (n = 134). The risk of graft loss was compared between CAM-based models vs a model based on Banff scores. Both Banff and CAM identified chronic lesions associated with graft loss (chronic glomerulopathy, arteriolar hyalinosis, and mesangial expansion). However, the CAM-based models predicted graft loss better than the Banff-based model, both overall (c-statistic 0.754 vs 0.705, P < .001), and in biopsies without chronic glomerulopathy (c-statistic 0.738 vs 0.661, P < .001) where it identified more features predictive of graft loss (% luminal stenosis and % mesangial expansion). Using 5-year renal allograft surveillance biopsies, CAM-based models predict graft loss better than Banff models and might be developed into biomarkers for future clinical trials.
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Affiliation(s)
- Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Martha C. Morales
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | - Walter D. Park
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
| | - Byron H. Smith
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Walter K. Kremers
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Mariam P. Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Fernando G. Cosio
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Andrew D. Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Mark D. Stegall
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota
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Marks WH, Mamode N, Montgomery RA, Stegall MD, Ratner LE, Cornell LD, Rowshani AT, Colvin RB, Dain B, Boice JA, Glotz D. Safety and efficacy of eculizumab in the prevention of antibody-mediated rejection in living-donor kidney transplant recipients requiring desensitization therapy: A randomized trial. Am J Transplant 2019; 19:2876-2888. [PMID: 30887675 PMCID: PMC6790671 DOI: 10.1111/ajt.15364] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 03/01/2019] [Accepted: 03/10/2019] [Indexed: 01/25/2023]
Abstract
We report results of a phase 2, randomized, multicenter, open-label, two-arm study evaluating the safety and efficacy of eculizumab in preventing acute antibody-mediated rejection (AMR) in sensitized recipients of living-donor kidney transplants requiring pretransplant desensitization (NCT01399593). In total, 102 patients underwent desensitization. Posttransplant, 51 patients received standard of care (SOC) and 51 received eculizumab. The primary end point was week 9 posttransplant treatment failure rate, a composite of: biopsy-proven acute AMR (Banff 2007 grade II or III; assessed by blinded central pathology); graft loss; death; or loss to follow-up. Eculizumab was well tolerated with no new safety concerns. No significant difference in treatment failure rate was observed between eculizumab (9.8%) and SOC (13.7%; P = .760). To determine whether data assessment assumptions affected study outcome, biopsies were reanalyzed by central pathologists using clinical information. The resulting treatment failure rates were 11.8% and 21.6% for the eculizumab and SOC groups, respectively (nominal P = .288). When reassessment included grade I AMR, the treatment failure rates were 11.8% (eculizumab) and 29.4% (SOC; nominal P = .048). This finding suggests a potential benefit for eculizumab compared with SOC in preventing acute AMR in recipients sensitized to their living-donor kidney transplants (EudraCT 2010-019630-28).
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Affiliation(s)
- William H. Marks
- Formerly Alexion PharmaceuticalsBostonMassachusetts,Independent ConsultantBellevueWashington
| | - Nizam Mamode
- Department of Transplant SurgeryGuy's and St Thomas’Evelina London Children's and Great Ormond Street Hospitals NHS TrustLondonUK
| | - Robert A. Montgomery
- NYU Langone Transplant InstituteNew York University Langone Medical CenterNew YorkNew York
| | - Mark D. Stegall
- The William J. von Liebig Center for Transplantation and Clinical Regeneration and Division of Transplantation SurgeryDepartment of SurgeryMayo ClinicRochesterMinnesota
| | | | - Lynn D. Cornell
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesota
| | - Ajda T. Rowshani
- Department of Internal MedicineSection of Nephrology and TransplantationErasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Robert B. Colvin
- Department of PathologyHarvard Medical SchoolMassachusetts General HospitalBostonMassachusetts
| | - Bradley Dain
- Formerly Alexion PharmaceuticalsBostonMassachusetts,Independent statistics consultantGuilfordConnecticut
| | | | - Denis Glotz
- Paris Translational Research Center for Organ TransplantationInstitut National de la Santé et de la Recherche MédicaleUnité Mixte de Recherche‐S970ParisFrance,Department of Nephrology and Organ TransplantationSaint‐Louis HospitalAssistance Publique‐Hôpitaux de ParisInstitut National de la Santé et de la Recherche MédicaleUnité U1160ParisFrance
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40
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Loupy A, Aubert O, Orandi BJ, Naesens M, Bouatou Y, Raynaud M, Divard G, Jackson AM, Viglietti D, Giral M, Kamar N, Thaunat O, Morelon E, Delahousse M, Kuypers D, Hertig A, Rondeau E, Bailly E, Eskandary F, Böhmig G, Gupta G, Glotz D, Legendre C, Montgomery RA, Stegall MD, Empana JP, Jouven X, Segev DL, Lefaucheur C. Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study. BMJ 2019; 366:l4923. [PMID: 31530561 PMCID: PMC6746192 DOI: 10.1136/bmj.l4923] [Citation(s) in RCA: 184] [Impact Index Per Article: 36.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
OBJECTIVE To develop and validate an integrative system to predict long term kidney allograft failure. DESIGN International cohort study. SETTING Three cohorts including kidney transplant recipients from 10 academic medical centres from Europe and the United States. PARTICIPANTS Derivation cohort: 4000 consecutive kidney recipients prospectively recruited in four French centres between 2005 and 2014. Validation cohorts: 2129 kidney recipients from three centres in Europe and 1428 from three centres in North America, recruited between 2002 and 2014. Additional validation in three randomised controlled trials (NCT01079143, EudraCT 2007-003213-13, and NCT01873157). MAIN OUTCOME MEASURE Allograft failure (return to dialysis or pre-emptive retransplantation). 32 candidate prognostic factors for kidney allograft survival were assessed. RESULTS Among the 7557 kidney transplant recipients included, 1067 (14.1%) allografts failed after a median post-transplant follow-up time of 7.12 (interquartile range 3.51-8.77) years. In the derivation cohort, eight functional, histological, and immunological prognostic factors were independently associated with allograft failure and were then combined into a risk prediction score (iBox). This score showed accurate calibration and discrimination (C index 0.81, 95% confidence interval 0.79 to 0.83). The performance of the iBox was also confirmed in the validation cohorts from Europe (C index 0.81, 0.78 to 0.84) and the US (0.80, 0.76 to 0.84). The iBox system showed accuracy when assessed at different times of evaluation post-transplant, was validated in different clinical scenarios including type of immunosuppressive regimen used and response to rejection therapy, and outperformed previous risk prediction scores as well as a risk score based solely on functional parameters including estimated glomerular filtration rate and proteinuria. Finally, the accuracy of the iBox risk score in predicting long term allograft loss was confirmed in the three randomised controlled trials. CONCLUSION An integrative, accurate, and readily implementable risk prediction score for kidney allograft failure has been developed, which shows generalisability across centres worldwide and common clinical scenarios. The iBox risk prediction score may help to guide monitoring of patients and further improve the design and development of a valid and early surrogate endpoint for clinical trials. TRIAL REGISTRATION Clinicaltrials.gov NCT03474003.
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Affiliation(s)
- Alexandre Loupy
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Olivier Aubert
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Babak J Orandi
- Department of Surgery, University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Maarten Naesens
- Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
| | - Yassine Bouatou
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
| | - Marc Raynaud
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
| | - Gillian Divard
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
| | - Annette M Jackson
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Denis Viglietti
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Magali Giral
- Department of Nephrology, Centre Hospitalier Universitaire de Nantes, Nantes, France
| | - Nassim Kamar
- Université Paul Sabatier, INSERM, Department of Nephrology and Organ Transplantation, CHU Rangueil & Purpan, Toulouse, France
| | - Olivier Thaunat
- Department of Transplantation, Nephrology and Clinical Immunology, Hospices Civils de Lyon, France
| | - Emmanuel Morelon
- Department of Transplantation, Nephrology and Clinical Immunology, Hospices Civils de Lyon, France
| | - Michel Delahousse
- Department of Transplantation, Nephrology and Clinical Immunology, Foch Hospital, Suresnes, France
| | - Dirk Kuypers
- Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
| | - Alexandre Hertig
- Kidney transplant department, Tenon Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Eric Rondeau
- Kidney transplant department, Tenon Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Elodie Bailly
- Kidney transplant department, Tenon Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Farsad Eskandary
- Division of Nephrology and Dialysis, Department of Medicine III, General Hospital Vienna, Vienna, Austria
| | - Georg Böhmig
- Division of Nephrology and Dialysis, Department of Medicine III, General Hospital Vienna, Vienna, Austria
| | - Gaurav Gupta
- Division of Nephrology, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Denis Glotz
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Christophe Legendre
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | | | - Mark D Stegall
- William J. von Liebig Centre for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Jean-Philippe Empana
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Cardiology and Heart Transplant department, Pompidou hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Xavier Jouven
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
| | - Dorry L Segev
- Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Carmen Lefaucheur
- Université de Paris, INSERM, Paris Translational Research Centre for Organ Transplantation, Paris, France
- Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
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41
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Hermsen M, de Bel T, den Boer M, Steenbergen EJ, Kers J, Florquin S, Roelofs JJTH, Stegall MD, Alexander MP, Smith BH, Smeets B, Hilbrands LB, van der Laak JAWM. Deep Learning-Based Histopathologic Assessment of Kidney Tissue. J Am Soc Nephrol 2019; 30:1968-1979. [PMID: 31488607 DOI: 10.1681/asn.2019020144] [Citation(s) in RCA: 184] [Impact Index Per Article: 36.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 07/01/2019] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with periodic acid-Schiff (PAS). METHODS We trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network's glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies. RESULTS The weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was "glomeruli" in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by "tubuli combined" and "interstitium." The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures. CONCLUSIONS This study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.
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Affiliation(s)
| | | | | | | | - Jesper Kers
- Department of Pathology, Amsterdam Infection & Immunity, Amsterdam Cardiovascular Sciences, Amsterdam UMC, and.,Center for Analytical Sciences Amsterdam, Van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.,The Ragon Institute of the Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
| | - Sandrine Florquin
- Department of Pathology, Amsterdam Infection & Immunity, Amsterdam Cardiovascular Sciences, Amsterdam UMC, and
| | - Joris J T H Roelofs
- Department of Pathology, Amsterdam Infection & Immunity, Amsterdam Cardiovascular Sciences, Amsterdam UMC, and
| | - Mark D Stegall
- Divisions of Transplantation surgery.,William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota; and
| | - Mariam P Alexander
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota; and.,Pathology, and
| | - Byron H Smith
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, Minnesota; and.,Biomedical Statistics and Informatics, and
| | | | - Luuk B Hilbrands
- Nephrology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jeroen A W M van der Laak
- Departments of Pathology and .,Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
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42
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Abrol N, Kashyap R, Frank RD, Iyer VN, Dean PG, Stegall MD, Prieto M, Kashani KB, Taner T. Preoperative Factors Predicting Admission to the Intensive Care Unit After Kidney Transplantation. Mayo Clin Proc Innov Qual Outcomes 2019; 3:285-293. [PMID: 31485566 PMCID: PMC6713836 DOI: 10.1016/j.mayocpiqo.2019.06.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 05/30/2019] [Accepted: 06/26/2019] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE To identify preoperative factors predicting early admission (within 30 days) of adult kidney transplant recipients to the intensive care unit (ICU). PATIENTS AND METHODS This is a single-center retrospective study of consecutive kidney transplant recipients between January 1, 2007, and December 31, 2016. Children (aged <18 years) and patients who underwent simultaneous multiorgan transplantation were excluded from the analysis. Associations between demographic, transplant-related, and comorbidity variables with ICU admission within 30 days of transplantation were analyzed using univariate and multivariate logistic regression models. RESULTS Of the 1527 eligible patients, 305 (20%) required early ICU admission. In univariate analysis, older age, higher body mass index (BMI), previous transplantation, myocardial infarction, congestive heart failure, obstructive pulmonary disease, longer ischemia time, pretransplant dialysis, and transplantation from a deceased donor were associated with increased odds of ICU admission. After multivariate adjustment, every 10-year increase in recipient age (odds ratio [OR], 1.26; 95% CI, 1.12-1.42; P<.001), 5-unit increase in BMI (OR, 1.11; 95% CI, 1.00-1.22; P=.049), pretransplant dialysis (OR, 1.57; 95% CI, 1.19-2.08; P=.002), and deceased donor transplantation (OR, 1.82; 95% CI, 1.29-2.55; P<.001) were associated with the increased risk of ICU admission. Preemptive transplantation (OR, 0.64; 95% CI, 0.48-0.84; P=.002) and living donor kidney transplantation (OR, 0.55; 95% CI, 0.39-0.77; P<.001) were associated with lower odds of ICU admission after transplantation. CONCLUSION Recipient age, BMI, and the need for pretransplant dialysis are associated with a higher risk of early ICU admission after kidney transplantation, whereas living donor kidney transplantation and preemptive transplantation decrease these odds. Early referral of patients with end-stage renal disease for preemptive transplantation and living donor kidney transplantation can significantly reduce transplant-related ICU admissions.
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Key Words
- ASA, American Society of Anesthesiologists
- BMI, body mass index
- CHF, congestive heart failure
- COPD, chronic obstructive pulmonary disease
- DM, diabetes mellitus
- ESRD, end-stage renal disease
- ICU, intensive care unit
- ILD, interstitial lung disease
- IQR, interquartile range
- MI, myocardial ischemia
- OR, odds ratio
- PVD, peripheral vascular disease
- WIT, warm ischemia time
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Affiliation(s)
- Nitin Abrol
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Rahul Kashyap
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | - Ryan D. Frank
- Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Vivek N. Iyer
- Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN
| | - Patrick G. Dean
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Mark D. Stegall
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Mikel Prieto
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
| | - Kianoush B. Kashani
- Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN
- Department Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Timucin Taner
- William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN
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43
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Bentall A, Smith BH, Gonzales MM, Bonner K, Park WD, Cornell LD, Dean PG, Schinstock CA, Borrows R, Lefaucheur C, Loupy A, Stegall MD. Modeling graft loss in patients with donor-specific antibody at baseline using the Birmingham-Mayo (BirMay) predictor: Implications for clinical trials. Am J Transplant 2019; 19:2274-2283. [PMID: 30768833 DOI: 10.1111/ajt.15312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 12/31/2018] [Accepted: 02/06/2019] [Indexed: 01/25/2023]
Abstract
Predicting which renal allografts will fail and the likely cause of failure is important in clinical trial design to either enrich patient populations to be or as surrogate efficacy endpoints for trials aimed at improving long-term graft survival. This study tests our previous Birmingham-Mayo model (termed the BirMay Predictor) developed in a low-risk kidney transplant population in order to predict the outcome of patients with donor specific alloantibody (DSA) at the time of transplantation and identify new factors to improve graft loss prediction in DSA+ patients. We wanted define ways to enrich the population for future therapeutic intervention trials. The discovery set included 147 patients from Mayo Cohort and the validation set included 111 patients from the Paris Cohort-all of whom had DSA at the time of transplantation. The BirMay predictor performed well predicting 5-year outcome well in DSA+ patients (Mayo C statistic = 0.784 and Paris C statistic = 0.860). Developing a new model did not improve on this performance. A high negative predictive value of greater than 90% in both cohorts excluded allografts not destined to fail within 5 years. We conclude that graft-survival models including histology predict graft loss well, both in DSA+ cohorts as well as DSA- patients.
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Affiliation(s)
- Andrew Bentall
- Department of Renal Medicine, Queen Elizabeth Hospital Birmingham, Birmingham, UK.,William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Byron H Smith
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Manuel Moreno Gonzales
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota.,Servicio de Cirugía General, Americana, Lima, Perú
| | - Keisha Bonner
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Walter D Park
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | - Lynn D Cornell
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Patrick G Dean
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
| | | | - Richard Borrows
- Department of Renal Medicine, Queen Elizabeth Hospital Birmingham, Birmingham, UK
| | - Carmen Lefaucheur
- Department of Nephrology and Kidney Transplantation, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Alexandre Loupy
- Department of Nephrology-Transplantation Necker Hospital, Assistance Publique-Hôpitaux de Paris, University Paris Descartes, Paris, France.,Paris Cardiovascular Research Centre - Biostatistics Unit University Paris Descartes, UMR-S970, Paris, France
| | - Mark D Stegall
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, Minnesota
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44
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Issa N, Vaughan LE, Denic A, Kremers WK, Chakkera HA, Park W, Matas AJ, Taler SJ, Stegall MD, Augustine J, Rule AD. Larger nephron size, low nephron number, and nephrosclerosis on biopsy as predictors of kidney function after donating a kidney. Am J Transplant 2019; 19:1989-1998. [PMID: 30629312 PMCID: PMC6591036 DOI: 10.1111/ajt.15259] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 12/14/2018] [Accepted: 01/06/2019] [Indexed: 01/25/2023]
Abstract
It is unclear whether structural findings in the kidneys of living kidney donors predict postdonation kidney function. We studied living kidney donors who had a kidney biopsy during donation. Nephron size was measured by glomerular volume, cortex volume per glomerulus, and mean cross-sectional tubular area. Age-specific thresholds were defined for low nephron number (calculated from CT and biopsy measures) and nephrosclerosis (global glomerulosclerosis, interstitial fibrosis/tubular atrophy, and arteriosclerosis). These structural measures were assessed as predictors of postdonation measured GFR, 24-hour urine albumin, and hypertension. Analyses were adjusted for baseline age, gender, body mass index, systolic and diastolic blood pressure, hypertension, measured GFR, urine albumin, living related donor status, and time since donation. Of 2673 donors, 1334 returned for a follow-up visit at a median 4.4 months after donation, with measured GFR <60 mL/min/1.73 m2 in 34%, urine albumin >5 mg/24 h in 13%, and hypertension in 5.3%. Larger glomerular volume and interstitial fibrosis/tubular atrophy predicted follow-up measured GFR <60 mL/min/1.73 m2 . Larger cortex volume per glomerulus and low nephron number predicted follow-up urine albumin >5 mg/24 h. Arteriosclerosis predicted hypertension. Microstructural findings predict GFR <60 mL/min/1.73 m2 , modest increases in urine albumin, and hypertension shortly after kidney donation.
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Affiliation(s)
- Naim Issa
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Lisa E. Vaughan
- Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, USA
| | - Aleksandar Denic
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
| | | | | | - Walter Park
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
| | | | - Sandra J. Taler
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
| | | | | | - Andrew D. Rule
- Division of Nephrology & Hypertension, Mayo Clinic, Rochester, MN, USA
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45
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Schinstock CA, Bentall AJ, Smith BH, Cornell LD, Everly M, Gandhi MJ, Stegall MD. Long-term outcomes of eculizumab-treated positive crossmatch recipients: Allograft survival, histologic findings, and natural history of the donor-specific antibodies. Am J Transplant 2019; 19:1671-1683. [PMID: 30412654 PMCID: PMC6509017 DOI: 10.1111/ajt.15175] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 10/30/2018] [Accepted: 11/01/2018] [Indexed: 01/25/2023]
Abstract
We aimed to determine the long-term outcomes of eculizumab-treated, positive crossmatch (+XM) kidney transplant recipients compared with +XM and age-matched negative crossmatch (-XM) controls. We performed an observational retrospective study and examined allograft survival, histologic findings, long-term B-cell flow cytometric XM (BFXM), and allograft-loss-associated factors. The mean (SD) posttransplant follow-up was 6.3 (2.5) years in the eculizumab group; 7.6 (3.5), +XM control group; 7.9 (2.5), -XM control group. The overall and death-censored allograft survival rates were similar in +XM groups (P = .73, P = .48) but reduced compared with -XM control patients (P < .001, P < .001). In the eculizumab-treated group, 57.9% (11/19) of the allografts had chronic antibody-mediated rejection, but death-censored allograft survival was 76.6%, 5 years; 75.4%, 7 years. Baseline IgG3 positivity and BFXM ≥300 were associated with allograft loss. C1q positivity was also associated with allograft loss but did not reach statistical significance. Donor-specific antibodies appeared to decrease in eculizumab-treated patients. After excluding patients with posttransplant plasmapheresis, 42.3% (9/21) had negative BFXMs; 31.8% (7/22), completely negative single-antigen beads 1 year posttransplant. Eculizumab-treated +XM patients had reduced allograft survival compared with -XM controls but similar survival to +XM controls. BFXM and complement-activating donor-specific antibodies (by IgG3 and C1q testing) may be used for risk stratification in +XM transplantation.
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Affiliation(s)
- Carrie A. Schinstock
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA,William J von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Andrew J. Bentall
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA,William J von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA
| | - Byron H. Smith
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Lynn D. Cornell
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Manish J. Gandhi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Mark D. Stegall
- William J von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, Rochester, MN, USA,Division of Transplantation Surgery, Mayo Clinic, Rochester, MN, USA
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46
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Lorenz EC, Cosio FG, Bernard SL, Bogard SD, Bjerke BR, Geissler EN, Hanna SW, Kremers WK, Cheng Y, Stegall MD, Cheville AL, LeBrasseur NK. The Relationship Between Frailty and Decreased Physical Performance With Death on the Kidney Transplant Waiting List. Prog Transplant 2019; 29:108-114. [PMID: 30879429 DOI: 10.1177/1526924819835803] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
INTRODUCTION Frailty and decreased physical performance are associated with poor outcomes after kidney transplant. Less is known about their relationship with pretransplant outcomes. The aim of this study was to characterize associations between frailty and physical performance with death on the kidney transplant waiting list. DESIGN Since December 2014, high-risk kidney transplant candidates at our center (age > 59, diabetic and/or history of >3 years dialysis) have undergone frailty and physical performance testing using Fried Criteria and the Short Physical Performance Battery. RESULTS Between December 2014 and November 2016, 272 high-risk candidates underwent testing and were approved for transplant. Both frailty and physical performance score were significantly associated with death on the waiting list (hazard ratio [HR]: 6.7, confidence interval [CI]: 1.5-30.1; P = .01; HR: 0.8 per 1-point increase, CI: 0.7-1.0; P = .02, respectively). The relationship between frailty, physical performance score, and death on the waiting list appeared to be independent of age, diabetes, or duration of dialysis. DISCUSSION Frailty and decreased physical performance appear to be independently associated with increased mortality on the kidney transplant waiting list. Further studies are needed to determine whether improving frailty and physical performance prior to transplant can decrease waiting list mortality.
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Affiliation(s)
- Elizabeth C Lorenz
- 1 Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Fernando G Cosio
- 1 Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Shari L Bernard
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Steven D Bogard
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Brian R Bjerke
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Elizabeth N Geissler
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Steven W Hanna
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Walter K Kremers
- 3 Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Yijing Cheng
- 3 Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Mark D Stegall
- 4 Department of Surgery, Mayo Clinic, Rochester, MN, USA
| | - Andrea L Cheville
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Nathan K LeBrasseur
- 2 Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
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47
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Stegall MD, Troy Somerville K, Everly MJ, Mannon RB, Gaber AO, First MR, Agashivala N, Perez V, Newell KA, Morris RE, Sudan D, Romero K, Eremenco S, Mattera M, Spear N, Porter AC, O'Doherty I. The importance of drug safety and tolerability in the development of new immunosuppressive therapy for transplant recipients: The Transplant Therapeutics Consortium's position statement. Am J Transplant 2019; 19:625-632. [PMID: 30549395 DOI: 10.1111/ajt.15214] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 11/21/2018] [Accepted: 11/21/2018] [Indexed: 01/25/2023]
Abstract
The Transplant Therapeutics Consortium (TTC) is a public-private partnership between the US Food and Drug Administration and the transplantation community including the transplantation societies and members of the biopharmaceutical industry. The TTC was formed to accelerate the process of developing new medical products for transplant patients. The initial goals of this collaboration are the following: (a) To define which aspects of the kidney transplant drug-development process have clear needs for improvement from an industry and regulatory perspective; (b) to define which of the unmet needs in the process could be positively impacted through the development of specific drug-development tools based on available data; and (c) to determine the most appropriate pathway to achieve regulatory acceptance of the proposed process-accelerating tools. The TTC has identified 2 major areas of emphasis: new biomarkers or endpoints for determining the efficacy of new therapies and new tools to assess the safety or tolerability of new therapies. This article presents the rationale and planned approach to develop new tools to assess safety and tolerability of therapies for transplant patients. We also discuss how similar efforts might support the continued development of patient-reported outcome measures in the future.
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Affiliation(s)
| | | | | | | | | | - M Roy First
- Transplant Genomics Inc., Mansfield, Massachusetts.,Comprehensive Transplant Center, Northwestern University, Chicago, Illinois
| | | | - Vanessa Perez
- Astellas Pharma Global Development, Inc., Northbrook, Illinois
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48
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Schinstock CA, Dadhania DM, Everly MJ, Smith B, Gandhi M, Farkash E, Sharma VK, Samaniego-Picota M, Stegall MD. Factors at de novo donor-specific antibody initial detection associated with allograft loss: a multicenter study. Transpl Int 2019; 32:502-515. [PMID: 30597643 DOI: 10.1111/tri.13395] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2018] [Accepted: 12/23/2018] [Indexed: 12/16/2022]
Abstract
We aimed to evaluate patient factors including nonadherence and viral infection and de novo donor-specific antibody (dnDSA) characteristics [total immunoglobulin G (IgG), C1q, IgG3, and IgG4] as predictors of renal allograft failure in a multicenter cohort with dnDSA. We performed a retrospective observational study of 113 kidney transplant recipients with dnDSA and stored sera for analysis. Predictors of death-censored allograft loss were assessed by Cox proportional modeling. Death-censored allograft survival was 77.0% (87/113) during a median follow-up of 2.2 (IQR 1.2-3.7) years after dnDSA detection. Predictors of allograft failure included medication nonadherence [HR 6.5 (95% CI 2.6-15.9)], prior viral infection requiring immunosuppression reduction [HR 5.3 (95% CI 2.1-13.5)], IgG3 positivity [HR 3.8 (95% CI 1.5, 9.3)], and time post-transplant (years) until donor-specific antibody (DSA) detection [HR 1.2 (95% CI 1.0, 1.3)]. In the 67 patients who were biopsied at dnDSA detection, chronic antibody-mediated rejection [HR 11.4 (95% CI 2.3, 56.0)] and mixed rejection [HR 7.4 (95% CI 2.2, 24.8)] were associated with allograft failure. We conclude that patient factors, including a history of viral infection requiring immunosuppression reduction or medication nonadherence, combined with DSA and histologic parameters must be considered to understand the risk of allograft failure in patients with dnDSA.
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Affiliation(s)
| | - Darshana M Dadhania
- Department of Transplantation Medicine, New-York Presbyterian Hospital Weill NYP-WCM Medical College, New York, NY, USA
| | | | - Byron Smith
- Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Manish Gandhi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Evan Farkash
- Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Vijay K Sharma
- Department of Transplantation Medicine, New-York Presbyterian Hospital Weill NYP-WCM Medical College, New York, NY, USA
| | | | - Mark D Stegall
- William J. von Liebig Transplant Center, Mayo Clinic, Rochester, MN, USA
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49
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Lorenz EC, Egginton JS, Stegall MD, Cheville AL, Heilman RL, Nair SS, Mai ML, Eton DT. Patient experience after kidney transplant: a conceptual framework of treatment burden. J Patient Rep Outcomes 2019; 3:8. [PMID: 30701333 PMCID: PMC6353980 DOI: 10.1186/s41687-019-0095-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 01/15/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Kidney transplant recipients face a lifelong regimen of medications, health monitoring and medical appointments. This work involved in managing one's health and its impact on well-being are referred to as treatment burden. Excessive treatment burden can adversely impact adherence and quality of life. The aim of this study was to develop a conceptual framework of treatment burden after kidney transplantation. Qualitative interviews were conducted with kidney transplant recipients (n = 27) from three Mayo Clinic transplant centers. A semi-structured interview guide originally developed in patients with chronic conditions and tailored to the context of kidney transplantation was utilized. Themes of treatment burden after kidney transplantation were confirmed in two focus groups (n = 16). RESULTS Analyses confirmed three main themes of treatment burden after kidney transplantation: 1) work patients must do to care for their health (e.g., attending medical appointments, taking medications), 2) challenges/stressors that exacerbate felt burden (e.g., financial concerns, health system obstacles) 3) impacts of burden (e.g., role/social activity limitations). CONCLUSIONS Patients describe a significant amount of work involved in caring for their kidney transplants. This work is exacerbated by individual, interpersonal and system-related factors. The framework will be used as a foundation for a patient-reported measure of treatment burden to promote better care after kidney transplantation.
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Affiliation(s)
- Elizabeth C Lorenz
- William J von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA. .,Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, USA.
| | - Jason S Egginton
- Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, USA
| | - Mark D Stegall
- William J von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - Andrea L Cheville
- Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, USA
| | - Raymond L Heilman
- Mayo Clinic Arizona Transplant Center, Mayo Clinic, Phoenix, AZ, USA
| | | | - Martin L Mai
- Department of Transplantation, Mayo Clinic, Jacksonville, FL, USA
| | - David T Eton
- Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, USA.,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
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50
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Abrol N, Dean PG, Prieto M, Stegall MD, Taner T. Routine Stenting of Extravesical Ureteroneocystostomy in Kidney Transplantation: A Systematic Review and Meta-analysis. Transplant Proc 2018; 50:3397-3404. [PMID: 30577212 DOI: 10.1016/j.transproceed.2018.06.041] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 06/27/2018] [Indexed: 01/25/2023]
Abstract
BACKGROUND Although rare, major urologic complications (MUC) in kidney transplantation can cause significant morbidity, increased cost, and may even lead to graft loss. Ureteric stents are routinely used to prevent MUC, although complications related to their use have been reported. Here, we systematically reviewed the role of routine stenting in preventing MUC in kidney transplantation with extravesical ureteric implantation and performed a meta-analysis of 6 randomized controlled trials. METHODS A PubMed search was performed for studies on MUC and stents in kidney transplant recipients. Randomized controlled trials were shortlisted for the review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RevMan 5 was used for statistical analysis, and outcome analysis was done with Cochran-Mantel-Haenszel test using random effect model. RESULTS Six trials meeting the criteria were identified. Although stent use did not decrease the incidence of urinary leak (odds ratio [OR], 0.39; 95% CI, 0.14-1.11; P = .08) or obstruction (OR, 0.41; 95% CI, 0.13-1.24; P = .11), it was associated with a higher incidence of urinary tract infection (OR, 3.59; 95% CI, 1.33-9.75; P = .01). CONCLUSION In the present era of extravesical ureterovesical anastomosis, routine stenting has a limited role in decreasing major urologic complications and may be associated with higher incidence of urinary tract infections.
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Affiliation(s)
- N Abrol
- William J. von Liebig Center for Transplantation, Mayo Clinic, Rochester, MN
| | - P G Dean
- William J. von Liebig Center for Transplantation, Mayo Clinic, Rochester, MN
| | - M Prieto
- William J. von Liebig Center for Transplantation, Mayo Clinic, Rochester, MN
| | - M D Stegall
- William J. von Liebig Center for Transplantation, Mayo Clinic, Rochester, MN
| | - T Taner
- William J. von Liebig Center for Transplantation, Mayo Clinic, Rochester, MN.
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