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Advances in Kidney Transplantation: 2nd Edition
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Advances in Kidney Transplantation: 2nd Edition

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nephrology & Urology".

Deadline for manuscript submissions: 25 May 2026 | Viewed by 501

Special Issue Editors

Dr. Pedro Ruiz-Esteban

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Guest Editor
Nephrology Department, Hospital Regional Universitario de Málaga, E-29010 Malaga, Spain
Interests: kidney transplantation; immunosuppression; acute rejection; subclinical inflammation; cardiovascular complications; metabolic complications; graft survival
Special Issues, Collections and Topics in MDPI journals
Dr. Domingo Hernández-Marrero

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Guest Editor
Nephrology Department, Hospital Universitario de Canarias, Instituto de Tecnologías Biomédicas-Universidad La Laguna, RICORS2040-renal (RD24/0004/0025), E-38320 Tenerife, Spain
Interests: kidney transplant; immunosuppression; acute rejection; subclinical inflammation; cardiovascular complications; metabolic complications; graft survival
Special Issues, Collections and Topics in MDPI journals
Dr. Verónica López-Jiménez

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Guest Editor
Nephrology Department, Hospital Regional Universitario de Málaga, E-29010 Malaga, Spain
Interests: kidney transplant; immunosuppression; acute rejection; subclinical inflammation; cardiovascular complications; metabolic complications; graft survival
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of renal transplantation continues its transformation toward precision medicine, propelled by rapid advancements in our understanding of graft rejection, post-transplant complications, and the integration of innovative technologies such as artificial intelligence and nanotechnology.

Building on the foundation established in our previous volume, recent research has further refined the clinical application of biomarkers for graft monitoring, enabling earlier detection of rejection, subclinical inflammation, and new risk stratification strategies for transplant recipients. These biomarkers are increasingly used not only as diagnostic tools but also as therapeutic targets, contributing to improved post-transplant outcomes and personalized care.

The clinical integration of artificial intelligence and big data analytics is revolutionizing renal transplantation by enhancing the prediction of graft survival, optimizing donor–recipient matching, and personalizing immunosuppressive therapies. At the same time, advances in nanotechnology are opening new avenues for organ preservation, targeted drug delivery, and immune modulation, further raising the standards of transplant medicine.

All these efforts continue to advance the clinician’s approach to diagnosis, treatment, and prognosis prediction and offer new perspectives for long-term outcome improvement in renal transplantation. The aim of this second Special Issue volume is to showcase the latest scientific achievements in diagnosis, treatment, and prognosis innovation, emphasizing emerging technologies and translational research that are shaping the future of renal transplantation.

Dr. Pedro Ruiz-Esteban
Dr. Domingo Hernández-Marrero
Dr. Verónica López-Jiménez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • kidney transplant
  • acute rejection
  • biomarkers
  • artificial intelligence
  • post-transplant complications
  • graft survival

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Published Papers (1 paper)

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Research

30 pages, 2445 KB  
Article
Insulin Resistance and Atherogenic Dyslipidemia Drive Cardiac Remodeling and Cardiovascular Events After Kidney Transplantation
by Ioana Adela Ratiu, Cristina Mihaela Brisc, Alina Daciana Elec, Corina Moisa, Anamaria Ratiu, Edy Hagi-Islai, Cristian Adrian Ratiu, Ioana Paula Blaj-Tunduc, Victor Vlad Babeș and Emilia Elena Babeș
J. Clin. Med. 2026, 15(8), 2915; https://doi.org/10.3390/jcm15082915 - 11 Apr 2026
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Abstract
Background: Cardiovascular disease remains a leading cause of morbidity and mortality after kidney transplantation. The relative contribution of metabolic abnormalities and inflammatory burden to cardiac remodeling and subsequent clinical outcomes in kidney transplant recipients (KTRs) remains incompletely understood. Methods: In this [...] Read more.
Background: Cardiovascular disease remains a leading cause of morbidity and mortality after kidney transplantation. The relative contribution of metabolic abnormalities and inflammatory burden to cardiac remodeling and subsequent clinical outcomes in kidney transplant recipients (KTRs) remains incompletely understood. Methods: In this retrospective cohort study, 152 KTRs underwent comprehensive cardiovascular evaluation at a stable post-transplant time point (12 ± 4 months after transplantation). Metabolic phenotype was assessed using metabolic syndrome and indices of insulin resistance and atherogenic dyslipidemia (TyG index, TG/HDL ratio, and atherogenic index of plasma [AIP]). Inflammatory status was evaluated using hs-CRP and complete blood count-derived indices. Echocardiographic damage composite (EDC) was defined as the presence of left ventricular hypertrophy, diastolic dysfunction, or left atrial enlargement. Patients were followed for major adverse clinical outcome (MACO), defined as cardiovascular event, graft failure, or death, and major adverse cardiovascular and cerebrovascular events (MACCE). Results: At baseline, 78 patients (51.3%) met criteria for EDC. EDC was strongly associated with higher TyG, AIP, TG/HDL, LDL/HDL ratio, and metabolic syndrome, whereas inflammatory markers showed no association. In multivariable logistic regression adjusted for age, sex, eGFR, and proteinuria, TyG remained independently associated with EDC (OR 1.13 per 0.1 increase, 95% CI 1.05–1.21; p = 0.001), independent of hs-CRP. Similar results were observed when AIP was evaluated in place of TyG (OR 10.39, 95% CI 2.22–48.71; p = 0.003). During follow-up, 78 patients developed MACO and 49 developed MACCE. In Cox regression analysis, graft dysfunction and inflammatory markers independently predicted MACO, whereas TyG was no longer significant. In contrast, TyG remained an independent predictor of MACCE after adjustment for confounders and inflammatory markers (HR 1.10 per 0.1 increase, 95% CI 1.04–1.16; p < 0.001). Similar results were observed when AIP was tested in place of TyG (HR 10.8, 95% CI 3.06–38.11; p < 0.001). Echocardiographic damage did not independently predict outcomes after adjustment. Conclusions: In KTRs, metabolic abnormalities reflecting insulin resistance and atherogenic dyslipidemia are closely associated with cardiac remodeling one year after transplantation and remain specifically linked to subsequent cardiovascular events. In contrast, systemic inflammation and graft dysfunction are the primary determinants of overall adverse clinical outcomes. Simple metabolic indices such as TyG and AIP may provide practical tools for cardiovascular risk stratification in this population. In Cox proportional hazards models, TyG (HR 1.102, 95% CI 1.043–1.164, p = 0.001) and AIP (HR 10.8, 95% CI 3.06–38.11, p < 0.001) were independently associated with cardiovascular events during follow-up, underscoring the role of atherogenic dyslipidemia in cardiovascular risk. Full article
(This article belongs to the Special Issue Advances in Kidney Transplantation: 2nd Edition)
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