2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:T6e8,The renin-angiotensin-aldosterone system (RAAS) plays a central role in regulating renal hemodynamics, sodium and water balance, and cardiovascular homeostasis. Chronic RAAS activation contributes to hypertension, proteinuria, inflammation, fluid overload, and fibrosis, making RAAS blockade (RAASb) a cornerstone therapy across the kidney life cycle. Over the past decades, ACE inhibitors, angiotensin receptor blockers, direct renin inhibitors, and mineralocorticoid receptor antagonists have demonstrated substantial benefits in slowing chronic kidney disease (CKD) progression, reducing proteinuria, and lowering cardiovascular risk. However, the efficacy and safety of RAASb vary according to the kidney life cycle. Evidence supports its use in proteinuric CKD and even in advanced stages, whereas the benefit in non-proteinuric disease remains limited. Novel non-steroidal mineralocorticoid receptor antagonists such as finerenone further enhance renal and cardiovascular protection, particularly in persons with diabetes and CKD. In dialysis populations, RAASb may preserve residual kidney function improve cardiac structure/function, although the benefit of steroidal MRAs remains uncertain. In kidney transplantation, RAASb appears safe and may improve long-term graft and patient survival, particularly when initiated early. The emergence of SGLT2 inhibitors and GLP-1 receptor agonists has reshaped therapeutic strategies, with accumulating evidence supporting complementary rather than competing roles with RAASb. This review synthesizes current evidence on RAAS modulation across the kidney life cycle from primary prevention to advanced CKD, dialysis, and transplantation, highlighting both established benefits and areas of current clinical uncertainty.31:T72c,ABSTRACT The renin–angiotensin–aldosterone system (RAAS) plays a central role in regulating renal hemodynamics, sodium and water balance, and cardiovascular homeostasis. Chronic RAAS activation contributes to hypertension, proteinuria, inflammation, fluid overload, and fibrosis, making RAAS blockade (RAASb) a cornerstone therapy across the kidney life cycle. Over the past decades, ACE inhibitors, angiotensin receptor blockers, direct renin inhibitors, and mineralocorticoid receptor antagonists (MRAs) have demonstrated substantial benefits in slowing chronic kidney disease (CKD) progression, reducing proteinuria, and lowering cardiovascular risk. However, the efficacy and safety of RAASb vary according to the kidney life cycle. Evidence supports its use in proteinuric CKD and even in advanced stages, whereas the benefit in non-proteinuric disease remains limited. Novel non-steroidal MRAs such as finerenone further enhance renal and cardiovascular protection, particularly in persons with diabetes and CKD. In dialysis populations, RAASb may preserve residual kidney function and improve cardiac structure/function, although the benefit of steroidal MRAs remains uncertain. In kidney transplantation, RAASb appears safe and may improve long-term graft and patient survival, particularly when initiated early. The emergence of SGLT2 inhibitors and glucagon-like peptide-1 receptor agonists has reshaped therapeutic strategies, with accumulating evidence supporting complementary rather than competing roles with RAASb. This review synthesizes current evidence on RAAS modulation across the kidney life cycle from primary prevention to advanced CKD, dialysis, and transplantation, highlighting both established benefits and areas of current clinical uncertainty.32:T7d8,Sarcopenia remains a significant concern among kidney transplant recipients even after renal function improves. However, the predictors of impaired muscle recovery are not well established. We retrospectively analyzed 40 adults who underwent living-donor kidney transplantation at Kansai Medical University Hospital between January 2018 and December 2020. Preoperative cardiopulmonary exercise testing (CPX) was used to stratify patients into low-tolerance (anaerobic threshold VO₂ < 11 mL/kg/min and peak VO₂ < 20 mL/kg/min) and normal groups. The skeletal muscle index (SMI) was measured using dual-energy x-ray absorptiometry from baseline to 3 years post-transplantation. Multivariable linear regression and correlation analyses were performed to identify predictors of long-term SMI improvement. Forty recipients were analyzed, including 12 (30%) in the low-tolerance group. Following transplantation, the median SMI in both groups decreased at 6 months and improved thereafter. However, from 1 year after transplantation onwards, the normal group demonstrated a significant increase in SMI compared with the low-tolerance group. Three years after transplantation, the median SMI in the normal group exceeded pretransplant levels and steadily increased, whereas in the low-tolerance group, there was little improvement and no return to baseline (P ≤ .05). Multivariable analysis identified low preoperative exercise tolerance as an independent predictor of reduced SMI recovery (P ≤ .05). Correlation analysis revealed that preoperative anaerobic threshold VO₂ and peak VO₂ were moderately and significantly associated with 3-year SMI improvement (r = 0.427 and r = 0.607, respectively). Low exercise tolerance before kidney transplantation strongly predicts impaired long-term skeletal muscle recovery. Cardiopulmonary exercise testing-based risk assessment may help identify candidates who could benefit from tailored perioperative rehabilitation strategies to enhance functional outcomes.33:T8da,Abstract Artificial intelligence (AI), encompassing machine learning, deep learning, and generative AI, is poised to redefine nephrology by enabling earlier detection, more precise risk stratification, and workflow-integrated clinical decision support across the spectrum of kidney disease. This state-of-the-art review synthesizes emerging applications of AI in acute kidney injury (AKI), chronic kidney disease (CKD), dialysis, and kidney transplantation, with attention to clinical integration, real-world validation, workflow implementation, and translational challenges. In AKI, predictive models trained on high-frequency EHR data and ICU telemetry have demonstrated strong performance in forecasting critical events, yet translation into routine clinical workflows remains limited. In CKD, machine learning tools support progression risk stratification and phenotype clustering, with the potential to inform individualized surveillance and therapy. AI-enabled dialysis management systems optimize ultrafiltration, anemia control, and vascular access surveillance, while generative AI and large language models (LLMs) offer novel capabilities for clinical documentation, triage, and patient education. In transplantation, AI applications span organ allocation, dynamic graft monitoring, and digital pathology-assisted rejection classification, with validated tools such as the iBox system gaining regulatory recognition. Implementation challenges include data heterogeneity, bias, interpretability, regulatory uncertainty, and workflow integration. Looking ahead, multimodal integration of imaging, pathology, and multi-omics data may support biologically informed precision nephrology. Reinforcement learning, digital twins, and ambient intelligence are emerging as adaptive decision-support paradigms rather than autonomous care systems. Regulatory frameworks are evolving to accommodate adaptive algorithms, underscoring the need for clinician engagement in model development, validation, and deployment. As AI matures from pilot to practice, nephrologists who embrace and help shape these tools will lead the transition toward a more personalized, efficient, and equitable future for kidney care.25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Kidney Transplantation: condition Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Kidney Transplantation (condition). Clinician-written summaries and actionable practice insights. Updated daily.\",\"url\":\"https://www.reachrx.ai/hub/tag/condition/Kidney%20Transplantation\",\"breadcrumb\":{\"@type\":\"BreadcrumbList\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https://www.reachrx.ai\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Research Hub\",\"item\":\"https://www.reachrx.ai/hub\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Conditions\",\"item\":\"https://www.reachrx.ai/hub/tag/condition\"},{\"@type\":\"ListItem\",\"position\":4,\"name\":\"Kidney Transplantation\",\"item\":\"https://www.reachrx.ai/hub/tag/condition/Kidney%20Transplantation\"}]}}"}}]],["$","$L2f",null,{"title":"Kidney Transplantation: Research & Clinical Takeaways","description":"Discover peer-reviewed research on Kidney Transplantation with concise clinician summaries and next-step guidance.","papers":[{"doi":"10.1053/j.ajkd.2026.06.008","pmid":"42726032","title":"Complement in Kidney Disease: Core Curriculum 2026","journal_title":"American Journal of Kidney Diseases","journal_issn":"0272-6386","published_at":"2026-09-11T00:00:00.000Z","url":"https://doi.org/10.1053/j.ajkd.2026.06.008","source_score":25,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-09-14T06:23:17.694Z","updated_at":"2026-09-14T06:23:17.694Z","tags":[{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"brand","value":"Soliris","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"category","value":"Urology & Nephrology","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"ANCA-Associated Vasculitis","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Atypical Hemolytic Uremic Syndrome","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"C3 Glomerulopathy","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Diabetic Kidney Disease","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"IgA Nephropathy","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Immune-Complex Membranoproliferative Glomerulonephritis","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Kidney Transplantation","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Lupus Nephritis","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Membranous Nephropathy","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"condition","value":"Thrombotic Microangiopathy","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"generic","value":"avacopan","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"generic","value":"eculizumab","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"generic","value":"iptacopan","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"generic","value":"pegcetacoplan","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"generic","value":"ravulizumab","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"level_of_evidence","value":"7","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"modality","value":"C3 Inhibitor","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"modality","value":"C5a Receptor Antagonist","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"modality","value":"C5 Inhibitor","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"modality","value":"Complement Inhibitor","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"modality","value":"Factor B Inhibitor","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"study_design","value":"Narrative Review / Core Curriculum","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"warning","value":"Avacopan's FDA approval for ANCA-associated vasculitis is under active reconsideration due to data integrity concerns in the ADVOCATE trial; clinical use should be reassessed pending regulatory decision.","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"warning","value":"Several sample sizes cited (e.g., VALIANT n=124, APPEAR-C3G n=74, APPLAUSE-IgAN n=250) are from interim analyses, not final trial results — effect sizes may change.","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"warning","value":"Study design tag reflects that this is a narrative Core Curriculum review, not a primary study; level of evidence is assigned accordingly.","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.06.008","tag_type":"warning","value":"The ADVOCATE trial data was retracted; the vasculitis section reflects a rapidly evolving regulatory situation as of publication date (September 2026).","value_numeric":null}],"summaries":{"what_studied":"This Core Curriculum review covers the role of complement activation in kidney disease, including the biology of the complement cascade, FDA-approved complement inhibitory drugs for 5 renal indications, complement diagnostics (plasma biomarkers, genetic testing, immunofluorescence), infection risks, and emerging therapeutic targets.","key_result":"FDA-approved complement inhibitors now cover 5 kidney diseases: aHUS (eculizumab, ravulizumab), C3 glomerulopathy (iptacopan, pegcetacoplan), IC-MPGN (pegcetacoplan), IgA nephropathy (iptacopan, accelerated approval August 2024), and ANCA-associated vasculitis (avacopan — FDA withdrawal under consideration). In aHUS, C5 inhibition reduced 5-year ESKD or death from ~60% to ~15%. In C3G, 6-month iptacopan (APPEAR-C3G, n=74) and pegcetacoplan (VALIANT interim, n=124) both significantly reduced proteinuria and stabilized kidney function.","limitations":"- Review article (Core Curriculum); not a systematic review or meta-analysis — evidence synthesis is narrative.\n- Avacopan's approval for AAV is under active FDA reconsideration due to data integrity concerns in the ADVOCATE trial.\n- Complement biomarkers (plasma/urine fragments) remain investigational and lack standardized normal ranges.","practice_takeaway":"Before starting any complement inhibitor, vaccinate patients against meningococcus (A, C, W, Y, B), *S. pneumoniae*, and *H. influenzae* type B at least 2 weeks prior; consider ongoing antibiotic prophylaxis for C5 blockers (Neisserial risk remains ~0.5%/year even after vaccination). Use kidney biopsy immunofluorescence for C3 fragments as the most accurate indicator of ongoing glomerular complement activation, and follow CH50/AH50 to confirm therapeutic suppression."}},{"doi":"10.1681/asn.0000001162","pmid":"42322663","title":"Evaluating Barriers to Kidney Transplantation in the United States","journal_title":"Journal of the American Society of Nephrology","journal_issn":"1046-6673","published_at":"2026-06-20T00:00:00.000Z","url":"https://doi.org/10.1681/asn.0000001162","source_score":116,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-25T13:25:28.344Z","updated_at":"2026-06-25T13:25:28.344Z","tags":[{"paper_doi":"10.1681/asn.0000001162","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"category","value":"Urology & Nephrology","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"condition","value":"Kidney Failure","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"condition","value":"Kidney Transplantation","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"modality","value":"Organ Transplantation","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"sample_size","value":"n=720348","value_numeric":720348},{"paper_doi":"10.1681/asn.0000001162","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"study_design","value":"Cohort Study","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"warning","value":"Impact flag 'practice_changing' is applied given the large national sample and clear identification of actionable center-level and patient-level barriers, but the observational design means causality is not established.","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"warning","value":"The full text pages extracted from the PDF appear to contain an ASN Media Kit (advertising rate card), not the clinical study body — only the abstract and results sections contain study data. Summaries and tags are based solely on the abstract and results as provided.","value_numeric":null},{"paper_doi":"10.1681/asn.0000001162","tag_type":"warning","value":"The published date is listed as 2026-06-20, which is consistent with today's date; this is an early/recent publication and may not yet have broad external validation.","value_numeric":null}],"summaries":{"what_studied":"This cohort study used Epic Cosmos EHR data to evaluate stage-specific progression and attrition from referral through evaluation, waitlisting, and kidney transplantation among 720,348 U.S. adults referred from 2014 to 2025. Individual (marital status, obesity, rural residence), center-level, and geographic factors were assessed using modified Poisson regression.","key_result":"Of 720,348 referred candidates, only 48% initiated evaluation, 19% were waitlisted, and 10% underwent transplantation. Severe obesity (RR 0.70; 95% CI, 0.69–0.72), never-married status (RR 0.94; 95% CI, 0.93–0.94), and rural zip code (RR 0.98; 95% CI, 0.97–1.00) were associated with lower rates of evaluation initiation. Low-volume centers had lower transplantation rates (RR 0.92; 95% CI, 0.88–0.96). Top reasons for non-progression included not meeting criteria (18%), patient decision (13%), and inability to contact the patient (12%).","limitations":"- EHR-based data (Epic Cosmos) may not capture all referred patients or centers, limiting generalizability.\n- Reasons for non-progression to evaluation were only documented at a subset of centers, introducing selection bias in that analysis.\n- Observational design precludes causal inference about identified barriers.","practice_takeaway":"Clinicians and transplant centers should proactively address high attrition between referral and evaluation—particularly for patients with severe obesity, those who are unmarried, or those in rural areas. Low-volume centers should benchmark against national rates and consider process improvements to close the gap in waitlisting and transplantation."}},{"doi":"10.1016/j.ajt.2026.06.004","pmid":"42269874","title":"Improving diagnostic performance of kidney allograft rejection with a model combining relative fraction and absolute copies of donor-derived cell-free DNA - results from five independent cohorts","journal_title":"American Journal of Transplantation","journal_issn":"1600-6135","published_at":"2026-06-10T00:00:00.000Z","url":"https://doi.org/10.1016/j.ajt.2026.06.004","source_score":105,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-15T13:21:51.377Z","updated_at":"2026-06-15T13:21:51.377Z","tags":[{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"category","value":"Surgery","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"condition","value":"Kidney Allograft Rejection","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"condition","value":"Kidney Transplantation","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"modality","value":"Liquid Biopsy / Cell-Free DNA Biomarker","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"sample_size","value":"n=361","value_numeric":361},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"study_design","value":"Multicohort Diagnostic Accuracy Study","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"warning","value":"Study design label 'Multicohort Diagnostic Accuracy Study' is an approximation; the paper is not a standard RCT or systematic review. The use of a 'random discovery set' introduces some ambiguity about the analytic approach.","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"warning","value":"The discovery set was small (n=51 total), which may have influenced CM-Score derivation; the composite score formula is not detailed in the abstract and may require supplementary review before clinical implementation.","value_numeric":null},{"paper_doi":"10.1016/j.ajt.2026.06.004","tag_type":"warning","value":"The 'practice_changing' impact flag is applied cautiously — the improvement in PPV is striking, but the CM-Score has not yet been validated in a prospective interventional trial.","value_numeric":null}],"summaries":{"what_studied":"This study evaluated whether combining dd-cfDNA percentage and copies/mL into a composite score (CM-Score) improves diagnostic accuracy for kidney allograft rejection, using 443 measurements from 361 patients across five independent cohorts, with validation in 81 rejections and 282 non-rejections.","key_result":"The CM-Score outperformed both individual metrics: NPV 91% (89–93%) and PPV 81% (72–89%) at 25% prevalence — a major improvement over published weighted-average PPV of 54% (52–55%) from 11 cohorts (N=6,536). Decision curve analysis showed significantly higher net benefit for the CM-Score (P<0.003).","limitations":"Discovery set was small (25 rejections, 26 non-rejections); results depend on having both percentage and copies/mL available simultaneously, which is not standard in all labs; external validation used published cohort data rather than individual patient-level data.","practice_takeaway":"When both dd-cfDNA % and copies/mL are available, using the CM-Score instead of either metric alone can substantially improve rule-in accuracy for rejection (PPV ~81% vs ~54%) while maintaining strong rule-out performance. Clinicians should request both metrics from their testing lab to leverage this composite approach."}},{"doi":"10.1007/s00467-026-07391-7","pmid":"42249203","title":"Perioperative severe hemorrhage in pediatric kidney transplantation: frequency, risk factors, and outcomes","journal_title":"Pediatric Nephrology","journal_issn":"0931-041X","published_at":"2026-06-06T00:00:00.000Z","url":"https://doi.org/10.1007/s00467-026-07391-7","source_score":7,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-17T13:29:43.646Z","updated_at":"2026-06-17T13:29:43.646Z","tags":[{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"age_group","value":"pediatric","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"category","value":"Pediatrics","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"category","value":"Urology & Nephrology","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"condition","value":"Chronic Kidney Disease","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"condition","value":"Kidney Transplantation","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"condition","value":"Perioperative Hemorrhage","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"generic","value":"fibrinogen concentrate","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"generic","value":"recombinant activated factor VII","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"modality","value":"Solid Organ Transplantation","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"sample_size","value":"n=218","value_numeric":218},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"study_design","value":"Retrospective Cohort Study","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"warning","value":"Living donor association with hemorrhage may reflect donor-recipient size disparity rather than living donation per se, as acknowledged by the authors.","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"warning","value":"Multivariable analysis was not performed due to the small number of events; reported risk factors are from unadjusted logistic regression only and may be confounded.","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"warning","value":"The severe hemorrhage definition was developed data-driven (k-means clustering) within this single cohort and has not been externally validated — comparisons to other studies using standard criteria (e.g., ISTH) should be made cautiously.","value_numeric":null},{"paper_doi":"10.1007/s00467-026-07391-7","tag_type":"warning","value":"The study period (2008–2015) predates current immunosuppression and surgical protocols; applicability to contemporary practice is uncertain.","value_numeric":null}],"summaries":{"what_studied":"Single-center retrospective cohort of 218 children undergoing first kidney transplant (2008–2015) to define severe perioperative hemorrhage using cluster analysis plus clinical criteria, then identify risk factors and outcomes including 5-year graft survival.","key_result":"Severe hemorrhage occurred in 16/218 cases (7.3%). Key risk factors included younger/smaller recipients, older donors, living donors, and higher graft-to-recipient size ratio. Five-year graft survival was markedly lower in the hemorrhage group (62.5% vs. 91.5%, p < 0.001); hospital stay was longer (10 vs. 7 days, p = 0.003). Patient mortality did not differ between groups.","limitations":"- Retrospective, single-center design (2008–2015) limits causal inference and generalizability.\n- Small number of events (n=16) prevented multivariable logistic regression, so independent risk factors could not be confirmed.\n- Data are relatively old; institutional changes in 2016 precluded extending the dataset.","practice_takeaway":"In small pediatric kidney transplant recipients receiving large grafts—especially from living or older donors—monitor closely for bleeding in the first 24 hours post-op, as this group faces significantly lower 5-year graft survival when severe hemorrhage occurs. Early use of plasma, cryoprecipitate, or platelets (even at low volumes) may signal clinically relevant hemorrhage requiring prompt escalation."}},{"doi":"10.1053/j.ajkd.2026.01.011","pmid":"42167833","title":"Malignancy and Kidney Transplant: Core Curriculum 2026","journal_title":"American Journal of Kidney Diseases","journal_issn":"0272-6386","published_at":"2026-05-20T00:00:00.000Z","url":"https://doi.org/10.1053/j.ajkd.2026.01.011","source_score":24,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-03T13:44:31.911Z","updated_at":"2026-06-03T13:44:31.911Z","tags":[{"paper_doi":"10.1053/j.ajkd.2026.01.011","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.01.011","tag_type":"brand","value":"Opdivo","value_numeric":null},{"paper_doi":"10.1053/j.ajkd.2026.01.011","tag_type":"category","value":"Urology & 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novel non-steroidal MRAs (e.g., finerenone) add renal and cardiovascular protection in diabetic CKD; benefit in non-proteinuric disease is limited; in dialysis, RAASb may preserve residual kidney function and improve cardiac structure; in transplantation, early RAASb appears safe and may improve graft and patient survival.","limitations":"- Review article (not a meta-analysis or RCT); conclusions are synthesis-level and inherit the limitations of underlying studies.\n- Efficacy and safety data in dialysis populations and transplant recipients remain uncertain, particularly for steroidal MRAs in dialysis.\n- Evidence on optimal timing, agent selection, and combination with newer agents (SGLT2i, GLP-1 RA) across all lifecycle stages is still evolving.","practice_takeaway":"Use RAASb as first-line therapy in proteinuric CKD and consider adding finerenone in patients with diabetes and CKD for added renal and cardiovascular protection. In transplant recipients, early initiation of RAASb appears safe and may improve long-term outcomes; SGLT2 inhibitors and GLP-1 receptor agonists play a complementary — not competing — role alongside RAASb."}},{"doi":"10.1016/j.transproceed.2025.11.013","pmid":"41513523","title":"Low Preoperative Exercise Tolerance Predicts Impaired Skeletal Muscle Recovery After Kidney Transplantation","journal_title":"Transplantation Proceedings","journal_issn":"0041-1345","published_at":"2026-01-10T00:00:00.000Z","url":"https://doi.org/10.1016/j.transproceed.2025.11.013","source_score":15,"is_retracted":false,"is_open_access":false,"raw_metadata":{"ooir":{"day":"2026-01-12","doi":"10.1016/j.transproceed.2025.11.013","days":"7","issn":"0041-1345","rank":"9","field":"Clinical Medicine","score":"15","category":"Surgery","categories":["Surgery"],"_categories":["Surgery"]},"pubmed":{"doi":"10.1016/j.transproceed.2025.11.013","title":"Low Preoperative Exercise Tolerance Predicts Impaired Skeletal Muscle Recovery After Kidney Transplantation.","journal":"Transplantation proceedings","methods":"","results":"Forty recipients were analyzed, including 12 (30%) in the low-tolerance group. Following transplantation, the median SMI in both groups decreased at 6 months and improved thereafter. However, from 1 year after transplantation onwards, the normal group demonstrated a significant increase in SMI compared with the low-tolerance group. Three years after transplantation, the median SMI in the normal group exceeded pretransplant levels and steadily increased, whereas in the low-tolerance group, there was little improvement and no return to baseline (P ≤ .05). Multivariable analysis identified low preoperative exercise tolerance as an independent predictor of reduced SMI recovery (P ≤ .05). Correlation analysis revealed that preoperative anaerobic threshold VO₂ and peak VO₂ were moderately and significantly associated with 3-year SMI improvement (r = 0.427 and r = 0.607, respectively).","abstract":"$32","keywords":[],"pubmed_id":"41513523","conclusions":"","publication_date":"2026-01-10T00:00:00"},"crossref":{"DOI":"10.1016/j.transproceed.2025.11.013","URL":"https://doi.org/10.1016/j.transproceed.2025.11.013","ISSN":["0041-1345"],"link":[{"URL":"https://api.elsevier.com/content/article/PII:S0041134525005949?httpAccept=text/xml","content-type":"text/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https://api.elsevier.com/content/article/PII:S0041134525005949?httpAccept=text/plain","content-type":"text/plain","content-version":"vor","intended-application":"text-mining"}],"page":null,"type":"journal-article","issue":null,"score":1,"title":["Low Preoperative Exercise Tolerance Predicts Impaired Skeletal Muscle Recovery After Kidney Transplantation"],"author":[{"given":"Masaaki","family":"Yanishi","sequence":"first","affiliation":[]},{"given":"Yutaka","family":"Kimura","sequence":"additional","affiliation":[]},{"given":"Yuya","family":"Koito","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Matsushita","sequence":"additional","affiliation":[]},{"given":"Ryuichi","family":"Yoshida","sequence":"additional","affiliation":[]},{"given":"Hiroyasu","family":"Tsukaguchi","sequence":"additional","affiliation":[]},{"given":"Yoshihiro","family":"Taniyama","sequence":"additional","affiliation":[]},{"given":"Hidefumi","family":"Kinoshita","sequence":"additional","affiliation":[]}],"issued":{"date-parts":[[2026,1]]},"member":"78","prefix":"10.1016","source":"Crossref","volume":null,"created":{"date-time":"2026-01-09T04:45:13Z","timestamp":1767933913000,"date-parts":[[2026,1,9]]},"indexed":{"date-time":"2026-01-09T06:27:41Z","timestamp":1767940061794,"date-parts":[[2026,1,9]]},"license":[{"URL":"https://www.elsevier.com/tdm/userlicense/1.0/","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"tdm"},{"URL":"https://www.elsevier.com/legal/tdmrep-license","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"tdm"},{"URL":"https://doi.org/10.15223/policy-017","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"stm-asf"},{"URL":"https://doi.org/10.15223/policy-037","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"stm-asf"},{"URL":"https://doi.org/10.15223/policy-012","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"stm-asf"},{"URL":"https://doi.org/10.15223/policy-029","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"stm-asf"},{"URL":"https://doi.org/10.15223/policy-004","start":{"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000,"date-parts":[[2026,1,1]]},"delay-in-days":0,"content-version":"stm-asf"}],"subject":[],"abstract":null,"language":"en","relation":{},"resource":{"primary":{"URL":"https://linkinghub.elsevier.com/retrieve/pii/S0041134525005949"}},"subtitle":[],"assertion":[{"name":"publisher","label":"This article is maintained by","value":"Elsevier"},{"name":"articletitle","label":"Article Title","value":"Low Preoperative Exercise Tolerance Predicts Impaired Skeletal Muscle Recovery After Kidney Transplantation"},{"name":"journaltitle","label":"Journal Title","value":"Transplantation Proceedings"},{"name":"articlelink","label":"CrossRef DOI link to publisher maintained version","value":"https://doi.org/10.1016/j.transproceed.2025.11.013"},{"name":"content_type","label":"Content Type","value":"article"},{"name":"copyright","label":"Copyright","value":"© 2025 Elsevier Inc. 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detailed.","value_numeric":null},{"paper_doi":"10.1016/j.transproceed.2025.11.013","tag_type":"warning","value":"Single‑center, living‑donor cohort; generalizability to other settings (e.g., deceased‑donor) is uncertain.","value_numeric":null}],"summaries":{"what_studied":"A retrospective cohort of 40 adults undergoing living‑donor kidney transplantation (2018–2020) was stratified by preoperative CPX into low‑tolerance (anaerobic threshold VO₂ <11 mL/kg/min and peak VO₂ <20 mL/kg/min; n=12) versus normal groups, with skeletal muscle index (SMI) by DXA tracked from baseline to 3 years. Multivariable regression and correlation analyses examined predictors of long‑term SMI improvement.","key_result":"From 1 year onward, the normal group showed greater SMI gains than the low‑tolerance group; at 3 years, the normal group’s median SMI exceeded pretransplant levels while the low‑tolerance group did not return to baseline (P ≤ .05). Low preoperative exercise tolerance independently predicted reduced SMI recovery (P ≤ .05), and preoperative anaerobic threshold VO₂ and peak VO₂ correlated with 3‑year SMI improvement (r=0.427 and r=0.607).","limitations":"Single‑center, retrospective study with a small sample (n=40) of living‑donor recipients limits generalizability. The abstract reports significance without absolute SMI values or effect sizes.","practice_takeaway":"Preoperative CPX can identify kidney transplant candidates at risk for poor long‑term muscle recovery. Patients with low exercise tolerance may warrant targeted perioperative rehabilitation and closer follow‑up."}},{"doi":"10.1093/ckj/sfag004","pmid":null,"title":"Transforming Nephrology Through Artificial Intelligence: A State-of-the-Art Roadmap for Clinical Integration","journal_title":"Clinical Kidney Journal","journal_issn":"2048-8505","published_at":"2026-01-08T00:00:00.000Z","url":"https://doi.org/10.1093/ckj/sfag004","source_score":30,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-01-10","doi":"10.1093/ckj/sfag004","days":"14","issn":"2048-8505","rank":"2","field":"Clinical Medicine","score":"30","category":"Urology & Nephrology","categories":["Urology & Nephrology"],"_categories":["Urology & 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classification is based on a state-of-the-art narrative review; it is not presented as a systematic review.","value_numeric":null},{"paper_doi":"10.1093/ckj/sfag004","tag_type":"warning","value":"The abstract provides no numeric performance metrics or comparative outcomes; full text may contain details not captured here.","value_numeric":null},{"paper_doi":"10.1093/ckj/sfag004","tag_type":"warning","value":"This review spans multiple kidney conditions; tags reflect this breadth rather than a single disease focus.","value_numeric":null}],"summaries":{"what_studied":"State-of-the-art review of artificial intelligence across nephrology—AKI, CKD, dialysis, and kidney transplantation—with focus on clinical integration, real-world validation, workflow implementation, and translational challenges, including regulatory context and the iBox transplant tool.","limitations":"Narrative review with no quantitative performance metrics or comparative outcomes reported in the abstract. Many applications described have limited translation into routine workflows, constraining real-world applicability.","practice_takeaway":"Adopt AI tools selectively where validated (e.g., iBox in transplantation) and plan for bias mitigation, interpretability, and seamless workflow integration. Clinician involvement in model development, validation, and deployment is essential as regulatory frameworks evolve."}}],"initialOffset":9,"fetchConfig":{"kind":"tags","tags":[{"tag_type":"condition","value":"Kidney Transplantation"}]},"breadcrumbItems":[{"name":"Home","href":"/"},{"name":"Research Hub","href":"/hub"},{"name":"Conditions","href":"/hub/tag/condition"},{"name":"Kidney Transplantation"}],"hrefConfig":{"basePath":"/hub/papers","webViewQueryParams":{"hub_ctx":"tag","hub_tag_type":"condition","hub_tag_value":"Kidney Transplantation"}}}]]

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