DNA methylation has been shown to be associated with kidney function and diabetic kidney disease (DKD), but prospective studies are scarce. Therefore, we conducted epigenome-wide association studies (EWASs) on early- and late-stage DKD progression using DNA methylation data obtained by analysing baseline blood samples from participants in the Finnish Diabetic Nephropathy Study type 1 diabetes cohort. We included 403 individuals with normal AER (early-stage progression group) and 372 individuals with severe albuminuria (late-stage progression group), and followed up DKD progression, defined as a decrease in eGFR to <60 ml/min per 1.73 m2 in the early-stage progression group, and end-stage kidney disease (ESKD) in the late-stage group. Replication was conducted in two type 1 diabetes cohorts in addition to publicly available EWAS summary statistics from diabetes and general population cohorts. Significant loci were further characterised by integration with genetic and proteomic data. We identified 11 methylation sites associated with DKD progression (p<9.4 × 10−8). Methylation at cg01730944 near the podocyte-specific gene CDKN1C and three other CpGs associated with early-stage DKD progression were independent of baseline eGFR, whereas late-stage progression CpGs were strongly associated with eGFR. The identified lead ESKD risk locus cg17944885 (chr19p13.2, p=2.6 × 10−17) and several novel methylation sites associated with late-stage DKD progression were supported by the results of previous studies. Proteomic analysis of cis proteins identified potential target genes for two CpGs: cg14999724 methylation was associated with PRG3 and PRG2, and cg12272104 was associated with BSG, FSTL3 and PALM. Furthermore, UK Biobank data show associations between these proteins and severe kidney endpoints. Finally, survival models that included methylation markers in addition to clinical risk factors significantly improved the identification of individuals at risk of early-stage DKD progression. The current study detected 11 loci associated with DKD progression, identifying methylation changes predictive of early-stage DKD progression in type 1 diabetes for the first time. Future research is needed to establish prognostic DNA methylation markers for DKD progression.

INTRODUCTION:Telomeres, which protect chromosome ends, are important in cell replication and are altered by ageing. In the realm of organ transplantation, telomere length has emerged as a potential biomarker for predicting both graft survival and recipient longevity. This study explores the correlation of telomere length with transplant outcomes to assess whether longer telomere length is associated with better long-term graft function and patient survival. METHODS:Telomere length (TL) was analysed in 274 European renal transplant pairs (donors/recipients). Recipient DNA was collected before and after kidney transplantation, and donor DNA just prior to transplant surgery. RESULTS:Donor TL was not significantly associated with graft survival. Donor age was a significant predictor of graft failure (1.02, 95% CI: 1.01-1.03, p < 0.01). Post-transplant recipient TL had a significant association with graft survival. Longer TL was associated with an up to 90% reduction in risk of graft failure (HR = 0.10, 95% CI: 0.015-0.71, p = 0.02). CONCLUSIONS:In this study, kidney transplant recipients with longer telomere length demonstrated significantly better long-term graft survival. If validated in additional kidney transplant cohorts, recipient telomere length could serve as a valuable biomarker for improving graft failure risk stratification and enhancing the long-term care of transplant recipients.

Abstract Background Post-transplant Immunoglobulin A Nephropathy (IgAN) is an important cause of premature graft loss. Management strategies are often extrapolated from native IgAN, with available evidence limited to heterogeneous, predominantly small retrospective studies. Objectives To characterise diagnostic criteria, map management strategies, and summarise associated clinical outcomes in post-transplant IgAN. Methods A literature search was performed in MEDLINE, Embase, Web of Science, and Scopus (1st January 2000–11th December 2025) following Joanna Briggs Institute (JBI) and PRISMA-ScR guidelines. English-language studies of adult kidney transplant recipients with biopsy-proven post-transplant IgAN and documented management strategies were included. Data on study design, cohorts, diagnostic criteria, interventions, and outcomes were charted and narratively described. Results Twenty-seven studies met the inclusion criteria. Most were single-centre retrospective cohorts. Diagnostic criteria varied, but typically histological evidence of IgA deposition alone was sufficient. IgAN was often clinically relevant, with proteinuria > 1 g/day frequently reported. Reported treatments included renin-angiotensin-aldosterone system (RAAS)-blockade, immunosuppression adjustment, rituximab, tonsillectomy and pulsed corticosteroids. Several small case series explored emerging therapies (iptacopan, budesonide, telitacicept). Study heterogeneity precluded quantitative data synthesis. Conclusions RAAS-blockade was the most commonly used intervention and was associated with benefit in several studies. Tonsillectomy was associated with improved outcomes but reported only in Japanese cohorts. Other interventions (rituximab, pulsed steroids, emerging therapies) warrant prospective clinical trials. Amid evolving paradigms in native IgAN management, this review highlights heterogeneity in diagnostic criteria, outcome reporting, and interventions for the management of post-transplant IgAN. Robust prospective, multicentre studies are urgently required to define optimal management in this high-risk population.

Abstract Background Currently there is insufficient evidence to inform the co-design of an exercise intervention as part of a multimodal intervention for renal cachexia. Co-design is an effective approach in collaborating with service users, carers and healthcare professionals to identify acceptable methods of improving delivery of care. The aim of this study was to use a co-design process to adapt an exercise intervention for patients with or at risk of renal cachexia as part of a cRCT for a multimodal intervention (NCT07107087) Methods The objectives were as follows: (1) To co-design a strategy to promote optimal recruitment and adherence to an exercise intervention for those with or at risk of renal cachexia receiving HD, (2) To produce a conceptual model in relation to the implementation of an exercise intervention for this group. Using Bird and colleagues generative co-design framework for healthcare innovation, we adopted three stages of pre-design, co-design, and post-design. Accordingly, three workshops were conducted to correspond to each stage and the operational decisions recorded in seven steps to report the iterative design of the exercise intervention. The co-design workshops took place in November 2023 (n = 10), June 2024 (n = 11) and February 2025 (n = 6). Public co-design partners from Northern Ireland and England representing Kidney Care UK, Northern Ireland Kidney Patients Association and Northern Ireland Kidney Research Fund, participated in the workshops. Results Contexts, intervention factors, mechanisms and outcomes which influence the uptake of, and adherence to, an exercise intervention within this patient population were identified. These included: the exercise intervention with an individualised and flexible approach; ensuring the exercise programme is manageable for patients receiving HD (session duration, timing and fistula awareness); ensuring the content of the exercise booklets is relatable and achievable (using household items rather than traditional exercise equipment and accrediting everyday activities as part of exercise log); providing support during the intervention (weekly telephone calls and progress tracking); and invitation to patients receiving HD considered most promising to encourage recruitment, sustain involvement and maximise impact from trusted healthcare professionals. Conclusion Using the generative co-design framework for healthcare innovation, a conceptual model has been produced to promote optimal recruitment and adherence to an exercise intervention as part of a multimodal intervention for renal cachexia management in practice. This has informed component design, the wider implementation plan and evaluation design of a multimodal intervention for renal cachexia.

Background: The 2020 KDIGO ‘Clinical Practice Guideline on Evaluation and Management of Candidates for Kidney Transplantation’ suggests frailty is measured when assessing a candidate’s suitability to be waitlisted for a kidney transplant. However, the optimal method of frailty assessment is not clear. There are numerous frailty assessment tools, but it is uncertain if these instruments are capturing the same cohort of frail candidates or whether they are measuring different constructs. This study investigated frailty prevalence in a cohort of waitlisted kidney transplant candidates from the United Kingdom and Ireland, described factors associated with frailty and explored agreement between different frailty assessment tools. Methods: FRAILKT is a single-region observational cohort study of adult waitlisted kidney transplant candidates who had transplant procedures in Northern Ireland. Frailty was assessed in all candidates using four frailty assessment tools. Correlations were analysed using Spearman’s test. Agreement between frailty classifications was analysed using Cohen’s kappa. Results: 190 participants were recruited. Frailty prevalence was measured by each of the tools (14.7% by Fried Frailty Phenotype, 16.8% by Edmonton Frail Scale, 9.5% by FRAIL scale and 11.0% by Clinical Frailty Scale). Factors associated with frailty depended on the tool used to measure it. Agreement between frailty assessment tools on a candidate’s frailty status was limited. Fifty participants were classified as frail using the frailty assessment tools however only three participants were classified as frail by all four frailty instruments. Conclusions: Frailty prevalence in waitlisted kidney transplant candidates varies depending on the measurement tool used. The limited agreement between assessment tools suggests that they may be capturing different constructs. Establishing the optimal tool for assessing frailty in waitlisted kidney transplant candidates remains challenging.

Abstract Hyperglycaemia is a hallmark of diabetes and a major risk factor for diabetic kidney disease (DKD). However, the molecular consequences of long-term cumulative hyperglycaemia (CH) remain unclear. As a stable epigenetic modification, DNA methylation may capture past glycaemic exposure. Here, we assessed CH-associated DNA methylation in 1,245 participants with type 1 diabetes (T1D) from Finland and the United Kingdom-Republic of Ireland cohorts. We identified 17 CH-associated CpGs, with the strongest association at cg19693031 ( TXNIP ). Longitudinal analyses demonstrate that these CH-associated DNA methylation levels remain stable despite short-term glycaemic fluctuations, suggesting lasting epigenetic imprints of earlier metabolic control. Integrative analyses combining genomic, epigenetic, and proteomic data characterized these CpGs and potential target proteins. Mendelian randomization suggested a causal association between cg20853880 ( KLF11 ) and DKD, supported by chromatin accessibility and kidney KLF11 expression. Our findings suggest that epigenetic changes contribute to metabolic memory and may mediate the effects of hyperglycaemia on DKD.

INTRODUCTION:Evidence on the anti-inflammatory effects and safety of omega-3 fatty acid supplementation in haemodialysis (HD) patients remains limited, particularly regarding the influence of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) dose, composition, and source. METHODS:We searched PubMed (n = 345), CENTRAL (n = 148) and EMBASE (n = 706) to July 2025. Studies were screened using Covidence, risk of bias was assessed using the Cochrane ROB 1 tool, and analyses were conducted in Review Manager 9.5.1. Only trials reporting C-reactive protein (CRP) were included. Pre-planned subgroup analyses examined formulation type, total daily dose, active ingredient dose, and DHA:EPA composition. Random-effects models were used to generate pooled standardised mean differences (SMDs), with heterogeneity assessed using I2. A sensitivity analysis excluded studies at high risk of bias. The protocol is registered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/JCBHN). RESULTS:Thirteen studies (n = 678) were included (12 in meta-analyses). Two studies were judged high risk of bias, one unclear, and the remainder low risk. Adverse events were poorly reported: eight trials did not report any events, while five described only mild, transient effects (e.g., diarrhoea). Omega-3 fatty acids reduced CRP more than comparators across triglyceride formulations (SMD -0.62, 95 % CI -1.22 to -0.03; P = 0.04, I2 = 74 %); in the <2000 mg/day total dose subgroup (SMD -0.32, 95 % CI -0.61 to -0.04; P = 0.02, I2 = 29 %); and in the <2000 mg/day active ingredient subgroup (SMD -0.36, 95 % CI -0.59 to -0.13; P = 0.003, I2 = 31 %). No statistically significant differences were observed between subgroups. Sensitivity analyses did not materially change the results. CONCLUSION:A daily dose <2000 mg of omega-3 fatty acids in natural triglyceride form appears more effective than synthetic ethyl ester formulations for lowering CRP in HD patients. Larger, high-quality trials are required to confirm therapeutic benefit, determine optimal dosing, and clarify the ideal EPA:DHA composition for this population.

Kidney cachexia is a debilitating and under-recognised complication of advanced chronic kidney disease (CKD), characterised by unintentional weight loss, muscle wasting, inflammation, and reduced functional capacity. Its profound impact on morbidity, quality of life, and healthcare utilisation underscores the need for targeted, implementable interventions. The multicomponent implementation strategy for a multi-modal, integrated, exercise, anti-inflammatory, and dietary advice (MMIEAD) intervention seeks to address this gap. Guided by the practical, robust implementation, and sustainability model (PRISM), which incorporates reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) outcomes, this study aims to ensure strong intervention–context alignment to support future scalability. The MMIEAD model will be evaluated by determining patient eligibility and recruitment rates, identifying intervention retention and adherence, assessing key statistical and methodological considerations to inform optimal study design and data collection burden, conducting a qualitative process evaluation to examine intervention acceptability and practicality, and determining the feasibility of undertaking a definitive economic evaluation. This mixed-methods study consists of three phases. Phase 1 will deliver and evaluate a 12-week multimodal intervention using a feasibility cluster randomised controlled trial (cRCT) design. Phase 2 will undertake a qualitative process evaluation with healthcare practitioners (HCPs) and patients. Phase 3 will assess the feasibility of conducting a full economic evaluation. Patients will be eligible if they have haemodialysis-dependent CKD stage 5 for more than 3 months, have experienced unintentional weight loss of at least 5

MicroRNAs may act as diagnostic and prognostic biomarkers of chronic kidney disease and are functionally important in disease pathogenesis. To identify novel microRNA biomarkers, we performed small RNA-sequencing on plasma from individuals with type 2 diabetes, with and without chronic kidney disease. MiR-190a-5p abundance was significantly lower in the circulation of type 2 diabetic patients with reduced function compared to those with normal kidney function. In an independent cohort of patients with chronic kidney disease of diverse aetiology, miR-190a-5p abundance predicted disease progression in individuals with no or moderate albuminuria ( < 300 mg/mmol). miR-190a-5p expression in kidney biopsy tissue correlated with the level of miR-190a-5p in the circulation and with estimated glomerular filtration rate, tubular mass and negatively with histological fibrosis. Administration of a miR-190a-5p mimic in a murine ischaemia-reperfusion injury model in male mice reduced tubular injury and fibrosis and increased expression of genes associated with tubular health. Our analyses suggest that miR-190a-5p is a biomarker of tubular cell health, low circulating levels may predict chronic kidney disease progression independent of existing risk factors and strategies to preserve miR-190a-5p may be an effective treatment for restoring tubular cell health following kidney injury.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis in the world and is an important cause of chronic kidney disease (CKD) and kidney failure. Outcomes are heterogeneous, and accurate risk stratification is important to identify the highest risk individuals for treatment and to help prevent disease progression. The Oxford classification (OC) is an internationally adopted standard for renal biopsy reporting in IgAN, which measures the degree of histological abnormalities and predicts prognosis. The kidney failure risk equation (KFRE) was developed to predict kidney failure in all causes of CKD and has been shown to be highly accurate across diverse etiologies. This review aimed to compare the KFRE with formulae incorporating the OC in accurately determining the risk of kidney failure in IgAN. A systematic review was conducted in accordance with the Cochrane library guidelines and PRISMA statement for reporting of systematic reviews. Studies comparing the accuracy of the KFRE with the OC in predicting disease progression and kidney failure in IgAN were evaluated. The search strategy and analysis were performed independently by two reviewers. Studies that were eligible for inclusion compared the KFRE with any tool incorporating the OC in a cohort of individuals with IgAN. Eligible outcomes were reduction of estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD), and prognostic tools were required to assess the accuracy of these formulae by discrimination and/or calibration. After searching several databases, only one study was eligible for inclusion in the review. This study of 2300 Chinese individuals with IgAN had a median follow-up of 2.5 years. Two-hundred eighty-eight individuals had a composite outcome of 50

Background:Artificial intelligence (AI) and large language models (LLMs) are increasing in sophistication and are being integrated into many disciplines. The potential for LLMs to augment clinical decision-making is an evolving area of research. Objective:This study compared the responses of over 1000 kidney specialist physicians (nephrologists) with the outputs of commonly used LLMs using a questionnaire determining when a kidney biopsy should be performed. Methods:This research group completed a large online questionnaire for nephrologists to determine when a kidney biopsy should be performed. The questionnaire was co-designed with patient input, refined through multiple iterations, and piloted locally before international dissemination. It was the largest international study in the field and demonstrated variation among human clinicians in biopsy propensity relating to human factors such as sex and age, as well as systemic factors such as country, job seniority, and technical proficiency. The same questions were put to both human doctors and LLMs in an identical order in a single session. Eight commonly used LLMs were interrogated: ChatGPT-3.5, Mistral Hugging Face, Perplexity, Microsoft Copilot, Llama 2, GPT-4, MedLM, and Claude 3. The most common response given by clinicians (human mode) for each question was taken as the baseline for comparison. Questionnaire responses on the indications and contraindications for biopsy generated a score (0-44) reflecting biopsy propensity, in which a higher score was used as a surrogate marker for an increased tolerance of potential associated risks. Results:The ability of LLMs to reproduce human expert consensus varied widely with some models demonstrating a balanced approach to risk in a similar manner to humans, while other models reported outputs at either end of the spectrum for risk tolerance. In terms of agreement with the human mode, ChatGPT-3.5 and GPT-4 (OpenAI) had the highest levels of alignment, agreeing with the human mode on 6 out of 11 questions. The total biopsy propensity score generated from the human mode was 23 out of 44. Both OpenAI models produced similar propensity scores between 22 and 24. However, Llama 2 and MS Copilot also scored within this range but with poorer response alignment to the human consensus at only 2 out of 11 questions. The most risk-averse model in this study was MedLM, with a propensity score of 11, and the least risk-averse model was Claude 3, with a score of 34. Conclusions:The outputs of LLMs demonstrated a modest ability to replicate human clinical decision-making in this study; however, performance varied widely between LLM models. Questions with more uniform human responses produced LLM outputs with higher alignment, whereas questions with lower human consensus showed poorer output alignment. This may limit the practical use of LLMs in real-world clinical practice.

Background Diabetic kidney disease (DKD) is a serious diabetes complication caused by both environmental and genetic risk factors. Previous genome-wide association studies (GWAS) have identified several loci associated with kidney function and kidney disease in the general population and, to a lesser extent, in diabetes. Methods To uncover the genetic factors driving diabetes-induced kidney function, we conducted a series of GWAS meta-analyses of eGFR in 17,267 individuals with type 1 diabetes and 35,264 with type 2 diabetes (52,531 total), using multiple well-characterized cohorts of type 1 diabetes DKD and data from the UK Biobank and SUrrogate markers for Micro- and Macrovascular hard end points for Innovative diabetes Tools (SUMMIT) consortium. We further accounted for DKD case/control status, diabetes duration and subtype, body mass index, glycated hemoglobin levels, and the relationship between eGFR and albuminuria. Results GWAS identified 13 loci associated with eGFR (P < 5x10(-8)), with five loci (candidate genes: HIPK3, TRIM5, RORA, ERBB4, and BCL6/LPP) not associated with or were in opposite directions as compared with eGFR in the general population. Four candidate genes (HIPK3, BCL6, LPP, and RORA) demonstrated evidence of differential expression in kidney compartments and cells among subgroups with DKD or diabetes versus controls. Lead single-nucleotide polymorphisms rs8027829 (RORA) and rs76300256 (BCL6/LPP) were methylation quantitative trait loci in whole blood and kidney tissue, respectively, and rs76300256 and its related CpGs all cluster in a kidney enhancer. Conclusions Our integrated approach identified candidate genes with diabetes-specific effects on kidney function.

Rationale & Objective:There is substantial variation in kidney biopsy practices within and between countries; however, the reasons for this are unclear due to limited research among large diverse populations. The aim of this study was to explore variations in attitude to the indications and contraindications for native kidney biopsy in the United States (US). Study Design:A case-vignette questionnaire was developed. A propensity-to-biopsy score (0-44) was generated from responses to indications and contraindications, with a higher score indicating an increased likelihood to recommend biopsy. Dissemination of the questionnaire occurred by email, social media, and the National Kidney Foundation. Setting & Participants:A total of 295 nephrologists/fellows from 43 states within the US participated. Exposure:All participants completed an identical questionnaire on kidney biopsy practice. Outcomes:Responses were collected on indications, contraindications, and attitudes to biopsy. Analytical Approach:Anonymized IP addresses were collected for comparison between US states. Data were also collected on the demographics of the individual and the type of institution in which the doctor was based. Results:In an adjusted multiple linear regression analysis, higher propensity-to-biopsy scores were demonstrated in US clinicians who were male, younger and more frequent performers of kidney biopsy (P = 0.05). There were significant differences between the 18 US states with 5 or more participants (P < 0.001) with the mean propensity-to-biopsy score ranging from 20.3 (Wisconsin) to 29.2 (New Jersey and Virginia). Increased biopsy propensity was also observed in US states with higher nephrologist density and lower statewide deprivation (P = 0.006). Limitations:The condensed clinical scenarios may not accurately replicate real-world cases, and clinicians opted in often using social media, so generalizability is limited. Conclusions:Attitudes to kidney biopsy practice in the US are highly variable, and clinician or institutional characteristics do not fully explain these discrepancies. Further research is required to understand the factors that influence clinical decision making.

Artificial intelligence (AI) and Large Language models (LLMs) are increasing in sophistication and have become integrated into many industries. The potential for LLMs to augment clinical decisions is an evolving area of research. This study compared the responses of over 1000 kidney specialist physicians (nephrologists) to outputs of commonly used LLMs using a questionnaire determining when a kidney biopsy should be performed. This research group completed a large online questionnaire for nephrologists to determine when a kidney biopsy should be performed. The same questions were put to both human doctors and LLMs in an identical order. Eight LLMs were interrogated: Chat GPT 3.5, Mistral Hugging Face, Perplexity, Microsoft Co-pilot, Llama 2, GPT 4.0, MedLM and Claude 3. The most common response given by clinicians (human mode) to each question was taken as the baseline for comparison. Questionnaire responses generated a score reflecting biopsy propensity. Chat GPT 3.5 and GPT 4.0 had the highest levels of agreement, with the human mode selected in 6/11 questions and a similar propensity score to the human mode. Llama 2 and Microsoft Co-pilot produced similar propensity scores, but with lower levels of agreement with the human mode. LLM outputs were able to replicate human clinical decision making in this study, however the performance varied widely between LLM models. Questions with more uniform human responses produced LLM outputs with greater alignment, whereas in questions with low levels of human consensus there was poor output alignment. This may limit the practical use of LLMs in real world clinical practice.

Background. While socioeconomic status (SES) is an established determinant of kidney transplant access and outcomes, less is known about how these disparities vary within universal healthcare systems. This study hypothesized that, despite shared healthcare and organ allocation systems, regional differences would be observed in the magnitude and pattern of the association between SES and transplant access and outcomes between England and Northern Ireland (NI). Methods. We conducted a retrospective cohort study using national transplant registry data from England (n = 42 220) and NI (n = 1615) from 2000 to 2020. SES was measured using national deprivation indices. Outcomes included transplant incidence, preemptive and living donor transplantation, graft survival, and patient survival. Statistical analyses included Poisson regression, Cox proportional hazards models, and concentration indices to assess equity. Results. In England, lower SES was significantly associated with reduced transplant access (incidence rate ratio for most versus least deprived quintile, 0.71; 95% confidence interval [CI], 0.69-0.73), lower rates of preemptive and living donor transplantation, and poorer graft (hazard ratio, 1.41; 95% CI, 1.32-1.50) and patient survival (hazard ratio, 1.49; 95% CI, 1.39-1.59). These disparities persisted across ethnic groups. In contrast, NI showed no significant SES-related differences in transplant access, despite a more deprived population overall. Conclusions. SES remains strongly associated with transplant access in England but not in NI, suggesting that regional models of healthcare delivery may mitigate or exacerbate inequities.These findings suggest a role of system design in promoting equity.

The genetic architecture of chronic kidney disease (CKD) is complex, including monogenic and polygenic contributions. CKD progression to kidney failure is influenced by factors including male sex, baseline estimated glomerular filtration rate (eGFR), hypertension, diabetes, proteinuria, and the underlying kidney disease. These traits all have strong genetic components, which can be partially quantified using polygenic risk scores. This paper examines the association between polygenic risk scores for CKD-related traits and age at kidney failure development. Genome-wide genotype data from 10,586 patients with kidney failure were compiled from 12 cohorts. Polygenic risk scores for hypertension, albuminuria, rapid decline in eGFR, decreased total kidney volume, and decreased eGFR were calculated using weights from published independent population-scale genome-wide association studies. The association between each polygenic risk score and age at kidney failure was investigated using logistic regression models. The association between polygenic risk score and age at kidney failure was also investigated separately for each primary kidney disease. Individuals in the highest 10

Reduced functional capacity increases the risk of adverse outcomes after kidney transplantation. The Duke Activity Status Index is a measurement of physical function, previously reported as being predictive of adverse outcomes after major non-cardiac surgery. This study assessed the ability of the Duke Activity Status Index to predict adverse outcomes for patients undergoing kidney transplantation. Adult kidney transplant recipients with a Duke Activity Status Index calculated at time of listing for transplantation in Northern Ireland between 2019 and 2024 were analysed. Dichotomous outcomes (delayed graft function, unplanned critical care admission, 30-day hospital re-admission, 30-day severe postoperative complication, 30-day cardiovascular complication) were analysed using multivariate logistic regression. Post-transplant length of stay was assessed using multivariate linear regression. All-cause mortality and death-censored graft loss were evaluated using Cox proportional hazard regression models. Data was available for 408 kidney transplant recipients. Duke Activity Status Index was not predictive of delayed graft function (aOR 0.99 (95