Oral sub-chronic toxicity of fingerroot (Boesenbergia rotunda) rhizome extract formulation in Wistar rats

Background

Boesenbergia rotunda (fingerroot) rhizome extract contains two major bioactive components, panduratin A and pinostrobin. In our previous study, we found the anti-inflammatory effects of the fingerroot extract against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in golden Syrian hamsters. In the present study, we evaluated the sub-chronic toxicity of a fingerroot extract formulation over 90 consecutive days of oral administration.

Methods

We enhanced the water solubility of a fingerroot extract by formulating it with cyclodextrin, containing panduratin A (29% w/w) and pinostrobin (32% w/w). This formulation was administered to male and female Wistar rats at doses of 25, 50, or 100 mg/kg/day for a duration of 90 days. Additionally, two recovery groups, comprising a control group and a high-dose group, were designated for a 14-day observation period to assess the persistence and reversibility of potential adverse effects. Throughout the experiment, we performed clinical and health observations, followed by hematological testing, clinical biochemistry analysis, necropsy examination, and histopathological evaluation at the end of the experiment.

Results

The administration of the fingerroot extract formulation at doses of 25, 50, or 100 mg/kg/day did not result in mortality or clinical signs of toxicity. No clinically significant findings were associated with the oral administration of the fingerroot extract formulation.

Conclusion

The fingerroot extract formulation showed no serious adverse effects at doses up to 100 mg/kg/day in Wistar rats under the experimental condition. Consequently, the No Observed Adverse Effect Level (NOAEL) was considered to be 100 mg/kg/day. This finding contributes significance for future developments involving fingerroot extract in herbal medicinal products targeting chronic inflammation.

Association of Proton Pump Inhibitor Use and Immune Checkpoint Inhibitor Mediated Acute Kidney Injury: A Meta-Analysis and a Review of Related Outcomes

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, they pose the risk of immune-related adverse events, including ICI-mediated acute kidney injury (ICI-AKI). Recent studies have implicated proton pump inhibitors (PPIs) as potential contributors to ICI-AKI development. This meta-analysis examines the association between PPI use and ICI-AKI, exploring a potential modifiable risk factor in ICI therapy, while also reviewing the possible outcomes of ICI-AKI.

METHODS

We conducted a comprehensive systematic review and meta-analysis of observational studies, assessing the risk of ICI-AKI in cancer patients concurrently using PPIs and potential outcomes. Odds ratios (ORs) were pooled using random-effects models. Subgroup analyses and sensitivity analyses were performed to evaluate heterogeneity and potential biases.

RESULTS

A total of 14 studies involving 12,694 patients were included. In total, we analyzed 639 patients with all-cause AKI and 779 patients with ICI-AKI. The pooled OR for the overall incidence of AKI from all-cause was 1.57 (95% Confidence Interval (CI), 1.02 to 2.40) among patients on PPIs. Specifically, the risk of ICI-AKI associated with PPI use was significantly higher, with a pooled OR of 1.84 (95% CI 1.16 to 2.90). This indicates approximately 84% higher likelihood of developing ICI-AKI with concurrent use of PPIs. Additionally, among patients with ICI-AKI, 67% had complete or partial recovery of renal function, 32% progressed to chronic kidney disease (CKD) and about 36% died during a follow-up period of at least 3 months.

CONCLUSION

This meta-analysis highlights the importance of cautious PPI prescription in cancer patients undergoing ICI therapy. Clinicians are advised to evaluate the risks and benefits of PPI use and consider alternative therapies when feasible.

Sub-chronic oral toxicity of a water-soluble extract of Centella asiatica (Centell-S) in Wistar rats

BACKGROUND

Centell-S, a water-soluble extract from Centella asiatica, is predominantly composed of madecassoside and asiaticoside, exceeding 80% w/w. Pursuing its development as an herbal medicinal product, Centell-S underwent sub-chronic toxicity assessment adhering to OECD GLP 408 standards.

METHODS

In a study involving 100 Wistar rats, varying doses of Centell-S (50, 200, or 800 mg/kg/day) or a vehicle control were administered orally over 90 days. To evaluate Centell-S's safety profile, assessments included clinical observations, health examinations, clinical biochemistry analyses, and detailed anatomical pathology evaluations were conducted.

RESULTS

Over the 90 days of treatment, the administration of Centell-S did not lead to any fatalities in the test animals. Clinical observations did not reveal any signs indicative of toxic effects. Notably, an increase in total white blood cell and lymphocyte counts was observed in both sexes, yet these levels returned to normal following a two-week discontinuation period post-treatment.

CONCLUSIONS

Under the specific conditions of the OECD GLP 408, Repeated Dose 90-day Oral Toxicity Study in Rodents, the no observed adverse effect level (NOAEL) of Centell-S was 800 mg/kg/day. These findings are promising for the continued development of Centell-S as a phytopharmaceutical for clinical applications.

Safety and efficacy of glucagon-like peptide-1 receptor agonists among kidney transplant recipients: a systematic review and meta-analysis

Background

Evidence supporting glucagon-like peptide-1 receptor agonists (GLP-1RAs) in kidney transplant recipients (KTRs) remains scarce. This systematic review and meta-analysis aims to evaluate the safety and efficacy of GLP-1RAs in this population.

Methods

A comprehensive literature search was conducted in the MEDLINE, Embase and Cochrane databases from inception through May 2023. Clinical trials and observational studies that reported on the safety or efficacy outcomes of GLP-1RAs in adult KTRs were included. Kidney graft function, glycaemic and metabolic parameters, weight, cardiovascular outcomes and adverse events were evaluated. Outcome measures used for analysis included pooled odds ratios (ORs) with 95% confidence intervals (CIs) for dichotomous outcomes and standardized mean difference (SMD) or mean difference (MD) with 95% CI for continuous outcomes. The protocol was registered in the International Prospective Register of Systematic Reviews (CRD 42023426190).

Results

Nine cohort studies with a total of 338 KTRs were included. The median follow-up was 12 months (interquartile range 6-23). While treatment with GLP-1RAs did not yield a significant change in estimated glomerular filtration rate [SMD -0.07 ml/min/1.73 m2 (95% CI -0.64-0.50)] or creatinine [SMD -0.08 mg/dl (95% CI -0.44-0.28)], they were associated with a significant decrease in urine protein:creatinine ratio [SMD -0.47 (95% CI -0.77 to -0.18)] and haemoglobin A1c levels [MD -0.85% (95% CI -1.41 to -0.28)]. Total daily insulin dose, weight and body mass index also decreased significantly. Tacrolimus levels remained stable [MD -0.43 ng/ml (95% CI -0.99 to 0.13)]. Side effects were primarily nausea and vomiting (17.6%), diarrhoea (7.6%) and injection site pain (5.4%).

Conclusions

GLP-1RAs are effective in reducing proteinuria, improving glycaemic control and supporting weight loss in KTRs, without altering tacrolimus levels. Gastrointestinal symptoms are the main side effects.

Phenotypic subtypes of fibrotic hypersensitivity pneumonitis identified by machine learning consensus clustering analysis

BACKGROUND

Patients with fibrotic hypersensitivity pneumonitis (f-HP) have varied clinical and radiologic presentations whose associated phenotypic outcomes have not been previously described. We conducted a study to evaluate mortality and lung transplant (LT) outcomes among clinical clusters of f-HP as characterized by an unsupervised machine learning approach.

METHODS

Consensus cluster analysis was performed on a retrospective cohort of f-HP patients diagnosed according to recent international guideline. Demographics, antigen exposure, radiologic, histopathologic, and pulmonary function findings along with comorbidities were included in the cluster analysis. Cox proportional-hazards regression was used to assess mortality or LT risk as a combined outcome for each cluster.

RESULTS

Three distinct clusters were identified among 336 f-HP patients. Cluster 1 (n = 158, 47%) was characterized by mild restriction on pulmonary function testing (PFT). Cluster 2 (n = 46, 14%) was characterized by younger age, lower BMI, and a higher proportion of identifiable causative antigens with baseline obstructive physiology. Cluster 3 (n = 132, 39%) was characterized by moderate to severe restriction. When compared to cluster 1, mortality or LT risk was lower in cluster 2 (hazard ratio (HR) of 0.42; 95% CI, 0.21-0.82; P = 0.01) and higher in cluster 3 (HR of 1.76; 95% CI, 1.24-2.48; P = 0.001).

CONCLUSIONS

Three distinct phenotypes of f-HP with unique mortality or transplant outcomes were found using unsupervised cluster analysis, highlighting improved mortality in fibrotic patients with obstructive physiology and identifiable antigens.

Safety and Efficacy of GLP-1 Receptor Agonists in Type 2 Diabetes Mellitus with Advanced and End-Stage Kidney Disease: A Systematic Review and Meta-Analysis

Background and Objectives: Limited evidence exists regarding the safety and efficacy of glucagon-like peptide-1 receptor agonists (GLP-1RAs) in type 2 diabetes mellitus (T2DM) patients with advanced chronic kidney disease (CKD) or end-stage kidney disease (ESKD). Thus, we conducted a systematic review and meta-analysis to assess the safety and efficacy of GLP-1RAs in T2DM patients with advanced CKD and ESKD. Materials and Methods: We performed a systematic literature search in MEDLINE, EMBASE, and Cochrane database until 25 October 2023. Included were clinical trials and cohort studies reporting outcomes of GLP-1RAs in adult patients with T2DM and advanced CKD. Outcome measures encompassed mortality, cardiovascular parameters, blood glucose, and weight. Safety was assessed for adverse events. The differences in effects were expressed as odds ratios with 95% confidence intervals (CIs) for dichotomous outcomes and the weighted mean difference or standardized mean difference (SMD) with 95% confidence intervals for continuous outcomes. The Risk of Bias In Non-randomized Studies-of Interventions (ROBIN-I) tool was used in cohort and non-randomized controlled studies, and the Cochrane Risk of Bias (RoB 2) tool was used in randomized controlled trials (RCTs). The review protocol was registered in the International Prospective Register of Systematic Reviews (CRD 42023398452) and received no external funding. Results: Eight studies (five trials and three cohort studies) consisting of 27,639 patients were included in this meta-analysis. No difference was observed in one-year mortality. However, GLP-1RAs significantly reduced cardiothoracic ratio (SMD of -1.2%; 95% CI -2.0, -0.4) and pro-BNP (SMD -335.9 pmol/L; 95% CI -438.9, -232.8). There was no significant decrease in systolic blood pressure. Moreover, GLP-1RAs significantly reduced mean blood glucose (SMD -1.1 mg/dL; 95% CI -1.8, -0.3) and increased weight loss (SMD -2.2 kg; 95% CI -2.9, -1.5). In terms of safety, GLP-1RAs were associated with a 3.8- and 35.7-time higher risk of nausea and vomiting, respectively, but were not significantly associated with a higher risk of hypoglycemia. Conclusions: Despite the limited number of studies in each analysis, our study provides evidence supporting the safety and efficacy of GLP-1RAs among T2DM patients with advanced CKD and ESKD. While gastrointestinal side effects may occur, GLP-1RAs demonstrate significant improvements in blood glucose control, weight reduction, and potential benefit in cardiovascular outcomes.

Re-assessing prolonged cold ischemia time in kidney transplantation through machine learning consensus clustering

BACKGROUND

We aimed to cluster deceased donor kidney transplant recipients with prolonged cold ischemia time (CIT) using an unsupervised machine learning approach.

METHODS

We performed consensus cluster analysis on 11 615 deceased donor kidney transplant patients with CIT exceeding 24 h using OPTN/UNOS data from 2015 to 2019. Cluster characteristics of clinical significance were identified, and post-transplant outcomes were compared.

RESULTS

Consensus cluster analysis identified two clinically distinct clusters. Cluster 1 was characterized by young, non-diabetic patients who received kidney transplants from young, non-hypertensive, non-ECD deceased donors with lower KDPI scores. In contrast, the patients in cluster 2 were older and more likely to have diabetes. Cluster 2 recipients were more likely to receive transplants from older donors with a higher KDPI. There was lower use of machine perfusion in Cluster 1 and incrementally longer CIT in Cluster 2. Cluster 2 had a higher incidence of delayed graft function (42% vs. 29%), and lower 1-year patient (95% vs. 98%) and death-censored (95% vs. 97%) graft survival compared to Cluster 1.

CONCLUSIONS

Unsupervised machine learning characterized deceased donor kidney transplant recipients with prolonged CIT into two clusters with differing outcomes. Although Cluster 1 had more favorable recipient and donor characteristics and better survival, the outcomes observed in Cluster 2 were also satisfactory. Overall, both clusters demonstrated good survival suggesting opportunities for transplant centers to incrementally increase CIT.

Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering

BACKGROUND

Educational attainment significantly influences post-transplant outcomes in kidney transplant patients. However, research on specific attributes of lower-educated subgroups remains underexplored. This study utilized unsupervised machine learning to segment kidney transplant recipients based on education, further analyzing the relationship between these segments and post-transplant results.

METHODS

Using the OPTN/UNOS 2017-2019 data, consensus clustering was applied to 20,474 kidney transplant recipients, all below a college/university educational threshold. The analysis concentrated on recipient, donor, and transplant features, aiming to discern pivotal attributes for each cluster and compare post-transplant results.

RESULTS

Four distinct clusters emerged. Cluster 1 comprised younger, non-diabetic, first-time recipients from non-hypertensive younger donors. Cluster 2 predominantly included white patients receiving their first-time kidney transplant either preemptively or within three years, mainly from living donors. Cluster 3 included younger re-transplant recipients, marked by elevated PRA, fewer HLA mismatches. In contrast, Cluster 4 captured older, diabetic patients transplanted after prolonged dialysis duration, primarily from lower-grade donors. Interestingly, Cluster 2 showcased the most favorable post-transplant outcomes. Conversely, Clusters 1, 3, and 4 revealed heightened risks for graft failure and mortality in comparison.

CONCLUSIONS

Through unsupervised machine learning, this study proficiently categorized kidney recipients with lesser education into four distinct clusters. Notably, the standout performance of Cluster 2 provides invaluable insights, underscoring the necessity for adept risk assessment and tailored transplant strategies, potentially elevating care standards for this patient cohort.

Efficacy of extracorporeal plasma therapy for adult native kidney patients with Primary FSGS: a Systematic review

PURPOSE

This study aimed to assess efficacy of extracorporeal plasma therapy (EPT), including plasmapheresis (PE), immunoadsorption (IA), low-density lipoprotein apheresis (LDL-A), and lymphocytapheresis (LCAP) for adult native kidney patients with primary focal segmental glomerulosclerosis (FSGS).

METHODS

A literature search was conducted using MEDLINE, EMBASE and Cochrane Databases through August 2022. Studies that reported outcomes of EPT in adult native kidneys with primary FSGS were enrolled.

RESULTS

18 studies with 104 therapy-resistant or refractory primary native FSGS patients were identified. Overall EPT response rate was 56%, with long-term benefit of 46%. Of the 101 non-hemodialysis (HD) patients, 54% achieved remission, with 30% complete remission (CR) and 23% partial remission (PR). Of 31 patients with PE, response rate was 65%; CR and PR rates were 27% and 37% in 30 non-HD patients. Of 61 patients with LDL-A, the response rate was 54%; CR and PR rates were 41% and 3% in 29 non-HD patients. Of 10 patients with IA, response rate was 40%. Of 2 patients with LCAP, 1 achieved CR, and one developed renal failure. All 3 HD patients showed increase in urine output and gradual decrease in urine protein excretion following PE (n = 1) or LDL-A (n = 2). 2 of 3 HD patients ultimately discontinued dialysis.

CONCLUSION

EPT with immunosuppressive therapy showed benefit in some patients with refractory primary FSGS, and PE appeared to have a higher response rate.

Potential drug-drug interactions of frequently prescribed medications in long COVID detected by two electronic databases

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to a wide range of acute and chronic complications including long COVID, a well-known chronic sequela. Long COVID often necessitates long-term treatment, which may lead to an increased potential for drug-drug interactions (DDIs). The objective of this study was to assess potential DDIs among frequently prescribed medications in long COVID by using two electronic databases. Sixty frequently prescribed agents were selected from Thailand's National List of Essential Medicine 2022 for potential DDI analysis by Micromedex and Drugs.com. From these databases, 488 potential DDIs were identified. There were 271 and 434 DDI pairs based on Micromedex and Drugs.com, respectively. Among these DDIs, 77 pairs were labeled as contraindicated or major by both databases. The most common mechanisms for these serious interactions are cytochrome P450 (CYP) inhibition (45%), CYP induction (19%), and QT interval prolongation (7.8%). Based on Fleiss' kappa (0.073), there was only slight agreement of the DDI severity classifications between these two databases. In conclusion, a large number of potential DDIs were detected among frequently prescribed medications for long COVID. Health care providers should be aware of these DDIs, particularly those that are deemed as contraindicated or major. These DDIs are most likely to cause significant adverse events in patients with long COVID because polypharmacy is common.

Efficacy of Therapeutic Apheresis for Cryoglobulinemic Vasculitis Patients with Renal Involvement: A Systematic Review

INTRODUCTION

Therapeutic apheresis (TA) is commonly used for cryoglobulinemic vasculitis (CV) patients, but its efficacy remains uncertain. This systematic review aimed to assess the efficacy of different TA modalities, such as plasma exchange (PE), plasmapheresis (PP), and cryofiltration (CF), in treating CV patients with renal involvement.

METHODS

Literature search of MEDLINE, EMBASE, and Cochrane Databases was conducted up to December 2022. Studies that reported the outcomes of TA in adult CV patients with renal involvement were assessed. The protocol for this systematic review has been registered with PROSPERO (No. CRD42023417727). The quality of each study was evaluated by the investigators using the validated methodological index for non-randomized studies (minors) quality score.

RESULTS

154 patients who encountered 170 episodes of serious events necessitating TA were evaluated across 76 studies. Among them, 51% were males, with a mean age ranging from 49 to 58 years. The CV types included 15 type I, 97 type II, and 13 type III, while the remaining patients exhibited mixed (n = 17) or undetermined CV types (n = 12). Among the treatment modalities, PE, PP, and CF were performed in 85 (56%), 52 (34%), and 17 patients (11%), respectively, with no identical protocol for TA treatment. The overall response rate for TA was 78%, with response rates of 84%, 77%, and 75% observed in type I, II, and III patients respectively. Most patients received steroids, immunosuppressants, and treatment targeting the underlying causative disease. The overall long-term renal outcome rate was 77%, with type I, II, and III patients experiencing response rates of 89%, 76%, and 90%, respectively. The renal outcomes in patients receiving PE, PP, and CF were comparable, with rates of 78%, 76%, and 81%, respectively.

CONCLUSIONS

This study presents compelling evidence that combination of TA with other treatments, especially immunosuppressive therapy, is a successful strategy for effectively managing severe renal involvement in CV patients. Among the TA modalities studied, including PE, PP, and CF, all demonstrated efficacy, with PE being the most frequently employed approach.

AI-Powered Renal Diet Support: Performance of ChatGPT, Bard AI, and Bing Chat

Patients with chronic kidney disease (CKD) necessitate specialized renal diets to prevent complications such as hyperkalemia and hyperphosphatemia. A comprehensive assessment of food components is pivotal, yet burdensome for healthcare providers. With evolving artificial intelligence (AI) technology, models such as ChatGPT, Bard AI, and Bing Chat can be instrumental in educating patients and assisting professionals. To gauge the efficacy of different AI models in discerning potassium and phosphorus content in foods, four AI models-ChatGPT 3.5, ChatGPT 4, Bard AI, and Bing Chat-were evaluated. A total of 240 food items, curated from the Mayo Clinic Renal Diet Handbook for CKD patients, were input into each model. These items were characterized by their potassium (149 items) and phosphorus (91 items) content. Each model was tasked to categorize the items into high or low potassium and high phosphorus content. The results were juxtaposed with the Mayo Clinic Renal Diet Handbook's recommendations. The concordance between repeated sessions was also evaluated to assess model consistency. Among the models tested, ChatGPT 4 displayed superior performance in identifying potassium content, correctly classifying 81% of the foods. It accurately discerned 60% of low potassium and 99% of high potassium foods. In comparison, ChatGPT 3.5 exhibited a 66% accuracy rate. Bard AI and Bing Chat models had an accuracy rate of 79% and 81%, respectively. Regarding phosphorus content, Bard AI stood out with a flawless 100% accuracy rate. ChatGPT 3.5 and Bing Chat recognized 85% and 89% of the high phosphorus foods correctly, while ChatGPT 4 registered a 77% accuracy rate. Emerging AI models manifest a diverse range of accuracy in discerning potassium and phosphorus content in foods suitable for CKD patients. ChatGPT 4, in particular, showed a marked improvement over its predecessor, especially in detecting potassium content. The Bard AI model exhibited exceptional precision for phosphorus identification. This study underscores the potential of AI models as efficient tools in renal dietary planning, though refinements are warranted for optimal utility.

Ethical Implications of Chatbot Utilization in Nephrology

This comprehensive critical review critically examines the ethical implications associated with integrating chatbots into nephrology, aiming to identify concerns, propose policies, and offer potential solutions. Acknowledging the transformative potential of chatbots in healthcare, responsible implementation guided by ethical considerations is of the utmost importance. The review underscores the significance of establishing robust guidelines for data collection, storage, and sharing to safeguard privacy and ensure data security. Future research should prioritize defining appropriate levels of data access, exploring anonymization techniques, and implementing encryption methods. Transparent data usage practices and obtaining informed consent are fundamental ethical considerations. Effective security measures, including encryption technologies and secure data transmission protocols, are indispensable for maintaining the confidentiality and integrity of patient data. To address potential biases and discrimination, the review suggests regular algorithm reviews, diversity strategies, and ongoing monitoring. Enhancing the clarity of chatbot capabilities, developing user-friendly interfaces, and establishing explicit consent procedures are essential for informed consent. Striking a balance between automation and human intervention is vital to preserve the doctor-patient relationship. Cultural sensitivity and multilingual support should be considered through chatbot training. To ensure ethical chatbot utilization in nephrology, it is imperative to prioritize the development of comprehensive ethical frameworks encompassing data handling, security, bias mitigation, informed consent, and collaboration. Continuous research and innovation in this field are crucial for maximizing the potential of chatbot technology and ultimately improving patient outcomes.

Examining the Validity of ChatGPT in Identifying Relevant Nephrology Literature: Findings and Implications

Literature reviews are valuable for summarizing and evaluating the available evidence in various medical fields, including nephrology. However, identifying and exploring the potential sources requires focus and time devoted to literature searching for clinicians and researchers. ChatGPT is a novel artificial intelligence (AI) large language model (LLM) renowned for its exceptional ability to generate human-like responses across various tasks. However, whether ChatGPT can effectively assist medical professionals in identifying relevant literature is unclear. Therefore, this study aimed to assess the effectiveness of ChatGPT in identifying references to literature reviews in nephrology. We keyed the prompt "Please provide the references in Vancouver style and their links in recent literature on… name of the topic" into ChatGPT-3.5 (03/23 Version). We selected all the results provided by ChatGPT and assessed them for existence, relevance, and author/link correctness. We recorded each resource's citations, authors, title, journal name, publication year, digital object identifier (DOI), and link. The relevance and correctness of each resource were verified by searching on Google Scholar. Of the total 610 references in the nephrology literature, only 378 (62%) of the references provided by ChatGPT existed, while 31% were fabricated, and 7% of citations were incomplete references. Notably, only 122 (20%) of references were authentic. Additionally, 256 (68%) of the links in the references were found to be incorrect, and the DOI was inaccurate in 206 (54%) of the references. Moreover, among those with a link provided, the link was correct in only 20% of cases, and 3% of the references were irrelevant. Notably, an analysis of specific topics in electrolyte, hemodialysis, and kidney stones found that >60% of the references were inaccurate or misleading, with less reliable authorship and links provided by ChatGPT. Based on our findings, the use of ChatGPT as a sole resource for identifying references to literature reviews in nephrology is not recommended. Future studies could explore ways to improve AI language models' performance in identifying relevant nephrology literature.

Safety and Efficacy of Vaptans in the Treatment of Hyponatremia from Syndrome of Inappropriate Antidiuretic Hormone Secretion (SIADH): A Systematic Review and Meta-Analysis

The utilization of vasopressin receptor antagonists, known as vaptans, in the management of hyponatremia among patients afflicted with the syndrome of inappropriate antidiuretic hormone (SIADH) remains a contentious subject. This meta-analysis aimed to evaluate the safety and efficacy of vaptans for treating chronic hyponatremia in adult SIADH patients. Clinical trials and observational studies were identified by a systematic search using MEDLINE, EMBASE, and Cochrane Database from inception through September 2022. The inclusion criteria were the studies that reported vaptans' safety or efficacy outcomes compared to placebo or standard therapies. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD 42022357307). Five studies were identified, comprising three RCTs and two cohort studies, enrolling a total of 1840 participants. Regarding short-term efficacy on days 4-5, vaptans exhibited a significant increase in serum sodium concentration from the baseline in comparison to the control group, with a weighted mean difference of 4.77 mmol/L (95% CI, 3.57, 5.96; I2 = 34%). In terms of safety outcomes, the pooled incidence rates of overcorrection were 13.1% (95% CI 4.3, 33.6; I2 = 92%) in the vaptans group and 3.3% (95% CI 1.6, 6.6; I2 = 27%) in the control group. Despite the higher correction rate linked to vaptans, with an OR of 5.72 (95% CI 3.38, 9.70; I2 = 0%), no cases of osmotic demyelination syndrome were observed. Our meta-analysis comprehensively summarizes the efficacy and effect size of vaptans in managing SIADH. While vaptans effectively raise the serum sodium concentration compared to placebo/fluid restriction, clinicians should exercise caution regarding the potential for overcorrection.

Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care

Longer pre-transplant dialysis duration is known to be associated with worse post-transplant outcomes. Our study aimed to cluster kidney transplant recipients with prolonged dialysis duration before transplant using an unsupervised machine learning approach to better assess heterogeneity within this cohort. We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 5092 kidney transplant recipients who had been on dialysis ≥ 10 years prior to transplant in the OPTN/UNOS database from 2010 to 2019. We characterized each assigned cluster and compared the posttransplant outcomes. Overall, the majority of patients with ≥10 years of dialysis duration were black (52%) or Hispanic (25%), with only a small number (17.6%) being moderately sensitized. Within this cohort, three clinically distinct clusters were identified. Cluster 1 patients were younger, non-diabetic and non-sensitized, had a lower body mass index (BMI) and received a kidney transplant from younger donors. Cluster 2 recipients were older, unsensitized and had a higher BMI; they received kidney transplant from older donors. Cluster 3 recipients were more likely to be female with a higher PRA. Compared to cluster 1, cluster 2 had lower 5-year death-censored graft (HR 1.40; 95% CI 1.16-1.71) and patient survival (HR 2.98; 95% CI 2.43-3.68). Clusters 1 and 3 had comparable death-censored graft and patient survival. Unsupervised machine learning was used to characterize kidney transplant recipients with prolonged pre-transplant dialysis into three clinically distinct clusters with variable but good post-transplant outcomes. Despite a dialysis duration ≥ 10 years, excellent outcomes were observed in most recipients, including those with moderate sensitization. A disproportionate number of minority recipients were observed within this cohort, suggesting multifactorial delays in accessing kidney transplantation.

Contrast-Induced Encephalopathy in Patients with Chronic Kidney Disease and End-Stage Kidney Disease: A Systematic Review and Meta-Analysis

Background: Contrast-induced encephalopathy (CIE) is an infrequent but serious neurological condition that occurs shortly after the administration of contrast during endovascular and angiography procedures. Patients suffering from chronic kidney disease (CKD) or end-stage kidney disease (ESKD) are considered to be at a higher risk of contrast medium neurotoxicity, due to the delayed elimination of the contrast medium. However, the occurrence and characteristics of CIE in CKD/ESKD patients have not been extensively investigated. Methods: We conducted a comprehensive literature search, utilizing databases such as MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews, up to September 2022. The purpose was to identify documented cases of CIE among patients with CKD or ESKD. Employing a random-effects model, we calculated the pooled incidence and odds ratio (OR) of CIE in CKD/ESKD patients. Results: Our search yielded a total of eleven articles, comprising nine case reports and two observational studies. Among these studies, 2 CKD patients and 12 ESKD patients with CIE were identified. The majority of the CKD/ESKD patients with CIE (93%) had undergone intra-arterial contrast media and/or endovascular procedures to diagnose acute cerebrovascular disease, coronary artery disease, and peripheral artery disease. The male-to-female ratio was 64%, and the median age was 63 years (with an interquartile range of 55 to 68 years). In the two observational studies, the incidence of CIE was found to be 6.8% in CKD patients and 37.5% in ESKD patients, resulting in a pooled incidence of 16.4% (95% CI, 2.4%-60.7%) among the CKD/ESKD patients. Notably, CKD and ESKD were significantly associated with an increased risk of CIE, with ORs of 5.77 (95% CI, 1.37-24.3) and 223.5 (95% CI, 30.44-1641.01), respectively. The overall pooled OR for CIE in CKD/ESKD patients was 32.9 (95% CI, 0.89-1226.44). Although dialysis prior to contrast exposure did not prevent CIE, approximately 92% of CIE cases experienced recovery after undergoing dialysis following contrast exposure. However, the effectiveness of dialysis on CIE recovery remained uncertain, as there was no control group for comparison. Conclusions: In summary, our study indicates an association between CIE and CKD/ESKD. While patients with CIE showed signs of recovery after dialysis, further investigations are necessary, especially considering the lack of a control group, which made the effects of dialysis on CIE recovery uncertain.

Sodium Thiosulfate for Calciphylaxis Treatment in Patients on Peritoneal Dialysis: A Systematic Review

Limited data are available on the utilization of sodium thiosulfate (STS) treatment for calciphylaxis in peritoneal dialysis (PD) patients, while it is well-studied in hemodialysis (HD) patients. A systematic literature search was conducted using Ovid MEDLINE, EBM Reviews-Cochrane Central Register of Controlled Trials, and EBM Reviews-Cochrane Database of Systematic Reviews to identify reported cases of PD patients with calciphylaxis who received STS. The search covered the inception of the databases through August 2022. Across 19 articles, this review identified 30 PD patients with calciphylaxis who received STS. These included 15 case reports, 2 case series, and 2 cohort studies. The administration routes and doses varied depending on the study. For intravenous (IV) administration (n = 18), STS doses ranged from 3.2 g twice daily to 25 g three times weekly for 5 weeks to 8 months. Outcomes included 44% of patients experiencing successful wound healing, 6% discontinuing STS due to adverse effects, 67% transitioning to HD, and 50% dying from calciphylaxis complications. For intraperitoneal (IP) administration (n = 5), STS doses ranged from 12.5 to 25 g three to four times weekly for 12 h to 3 months. Results showed 80% of patients achieving successful wound healing, 80% discontinuing STS due to adverse effects, 40% transitioning to HD, and 20% dying from IP STS-related chemical peritonitis. In cases where patients switched from IV to IP STS (n = 3), doses ranged from 12.5 to 25 g two to three times weekly for 2.5 to 5 months. Among them, 67% experienced successful wound healing, while 33% died from sepsis. Two cases utilized oral STS at a dose of 1500 mg twice daily for 6 and 11 months, resulting in successful wound healing without adverse effects or need for HD. However, one patient (50%) died due to small bowel obstruction. This systematic review provides an overview of STS treatment for PD patients with calciphylaxis. Although successful treatment cases exist, adverse effects were significant. Further research, including larger clinical studies and pharmacokinetic data, is necessary to establish the optimal route, dose, and efficacy of STS in PD patients.

Differences between Kidney Transplant Recipients from Deceased Donors with Diabetes Mellitus as Identified by Machine Learning Consensus Clustering

Clinical outcomes of deceased donor kidney transplants coming from diabetic donors currently remain inconsistent, possibly due to high heterogeneities in this population. Our study aimed to cluster recipients of diabetic deceased donor kidney transplants using an unsupervised machine learning approach in order to identify subgroups with high risk of inferior outcomes and potential variables associated with these outcomes. Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 7876 recipients of diabetic deceased donor kidney transplants from 2010 to 2019 in the OPTN/UNOS database. We determined the important characteristics of each assigned cluster and compared the post-transplant outcomes between the clusters. Consensus cluster analysis identified three clinically distinct clusters. Recipients in cluster 1 (n = 2903) were characterized by oldest age (64 ± 8 years), highest rate of comorbid diabetes mellitus (55%). They were more likely to receive kidney allografts from donors that were older (58 ± 6.3 years), had hypertension (89%), met expanded criteria donor (ECD) status (78%), had a high rate of cerebrovascular death (63%), and carried a high kidney donor profile index (KDPI). Recipients in cluster 2 (n = 687) were younger (49 ± 13 years) and all were re-transplant patients with higher panel reactive antibodies (PRA) (88 [IQR 46, 98]) who received kidneys from younger (44 ± 11 years), non-ECD deceased donors (88%) with low numbers of HLA mismatch (4 [IQR 2, 5]). The cluster 3 cohort was characterized by first-time kidney transplant recipients (100%) who received kidney allografts from younger (42 ± 11 years), non-ECD deceased donors (98%). Compared to cluster 3, cluster 1 had higher incidence of primary non-function, delayed graft function, patient death and death-censored graft failure, whereas cluster 2 had higher incidence of delayed graft function and death-censored graft failure but comparable primary non-function and patient death. An unsupervised machine learning approach characterized diabetic donor kidney transplant patients into three clinically distinct clusters with differing outcomes. Our data highlight opportunities to improve utilization of high KDPI kidneys coming from diabetic donors in recipients with survival-limiting comorbidities such as those observed in cluster 1.

The use of continuous positive airway pressure in COPD-OSA overlap syndrome: A systematic review

BACKGROUND

The co-occurrence of obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD), known as COPD-OSA overlap syndrome, increases morbidity and mortality. The effectiveness of continuous positive airway pressure (CPAP) therapy, a commonly used treatment for OSA, in this patient population remains uncertain. Therefore, we conducted a systematic review to evaluate the efficacy of CPAP therapy in improving clinical outcomes.

METHODS

We conducted a comprehensive systematic review to identify studies that evaluated the impact of CPAP therapy on COPD exacerbation, hospitalization, and mortality in patients with COPD-OSA overlap syndrome. We followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Statement and assessed the quality of each study using the Newcastle-Ottawa quality scale.

RESULTS

From the initial 3184 articles identified, we reviewed 365 and included five in the systematic review. Our findings revealed that CPAP therapy improved clinical outcomes, including COPD exacerbation, COPD related hospitalization, and mortality in patients with COPD-OSA overlap syndrome. However, the definition of COPD and OSA varied across studies, and the definition of CPAP usage was not consistent.

CONCLUSION

Our systematic review suggests that CPAP therapy is effective in improving outcomes in patients with COPD-OSA overlap syndrome. Nonetheless, further research is required to establish the efficacy of CPAP therapy by standardizing the definition of COPD, OSA, and CPAP usage.

Differences between Very Highly Sensitized Kidney Transplant Recipients as Identified by Machine Learning Consensus Clustering

Background and Objectives: The aim of our study was to categorize very highly sensitized kidney transplant recipients with pre-transplant panel reactive antibody (PRA) ≥ 98% using an unsupervised machine learning approach as clinical outcomes for this population are inferior, despite receiving increased allocation priority. Identifying subgroups with higher risks for inferior outcomes is essential to guide individualized management strategies for these vulnerable recipients. Materials and Methods: To achieve this, we analyzed the Organ Procurement and Transplantation Network (OPTN)/United Network for Organ Sharing (UNOS) database from 2010 to 2019 and performed consensus cluster analysis based on the recipient-, donor-, and transplant-related characteristics in 7458 kidney transplant patients with pre-transplant PRA ≥ 98%. The key characteristics of each cluster were identified by calculating the standardized mean difference. The post-transplant outcomes were compared between the assigned clusters. Results: We identified two distinct clusters and compared the post-transplant outcomes among the assigned clusters of very highly sensitized kidney transplant patients. Cluster 1 patients were younger (median age 45 years), male predominant, and more likely to have previously undergone a kidney transplant, but had less diabetic kidney disease. Cluster 2 recipients were older (median 54 years), female predominant, and more likely to be undergoing a first-time transplant. While patient survival was comparable between the two clusters, cluster 1 had lower death-censored graft survival and higher acute rejection compared to cluster 2. Conclusions: The unsupervised machine learning approach categorized very highly sensitized kidney transplant patients into two clinically distinct clusters with differing post-transplant outcomes. A better understanding of these clinically distinct subgroups may assist the transplant community in developing individualized care strategies and improving the outcomes for very highly sensitized kidney transplant patients.

Revolutionizing Chronic Kidney Disease Management with Machine Learning and Artificial Intelligence

Chronic kidney disease (CKD) poses a significant public health challenge, affecting approximately 11% to 13% of the global population [...].

Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering

BACKGROUND

Better understanding of the different phenotypes/subgroups of non-U.S. citizen kidney transplant recipients may help the transplant community to identify strategies that improve outcomes among non-U.S. citizen kidney transplant recipients. This study aimed to cluster non-U.S. citizen kidney transplant recipients using an unsupervised machine learning approach; Methods: We conducted a consensus cluster analysis based on recipient-, donor-, and transplant- related characteristics in non-U.S. citizen kidney transplant recipients in the United States from 2010 to 2019 in the OPTN/UNOS database using recipient, donor, and transplant-related characteristics. Each cluster's key characteristics were identified using the standardized mean difference. Post-transplant outcomes were compared among the clusters; Results: Consensus cluster analysis was performed in 11,300 non-U.S. citizen kidney transplant recipients and identified two distinct clusters best representing clinical characteristics. Cluster 1 patients were notable for young age, preemptive kidney transplant or dialysis duration of less than 1 year, working income, private insurance, non-hypertensive donors, and Hispanic living donors with a low number of HLA mismatch. In contrast, cluster 2 patients were characterized by non-ECD deceased donors with KDPI <85%. Consequently, cluster 1 patients had reduced cold ischemia time, lower proportion of machine-perfused kidneys, and lower incidence of delayed graft function after kidney transplant. Cluster 2 had higher 5-year death-censored graft failure (5.2% vs. 9.8%; p < 0.001), patient death (3.4% vs. 11.4%; p < 0.001), but similar one-year acute rejection (4.7% vs. 4.9%; p = 0.63), compared to cluster 1; Conclusions: Machine learning clustering approach successfully identified two clusters among non-U.S. citizen kidney transplant recipients with distinct phenotypes that were associated with different outcomes, including allograft loss and patient survival. These findings underscore the need for individualized care for non-U.S. citizen kidney transplant recipients.

Differences between kidney retransplant recipients as identified by machine learning consensus clustering

BACKGROUND

Our study aimed to characterize kidney retransplant recipients using an unsupervised machine-learning approach.

METHODS

We performed consensus cluster analysis based on the recipient-, donor-, and transplant-related characteristics in 17 443 kidney retransplant recipients in the OPTN/UNOS database from 2010 to 2019. We identified each cluster's key characteristics using the standardized mean difference of >.3. We compared the posttransplant outcomes, including death-censored graft failure and patient death among the assigned clusters RESULTS: Consensus cluster analysis identified three distinct clusters of kidney retransplant recipients. Cluster 1 recipients were predominantly white and were less sensitized. They were most likely to receive a living donor kidney transplant and more likely to be preemptive (30%) or need ≤1 year of dialysis (32%). In contrast, cluster 2 recipients were the most sensitized (median PRA 95%). They were more likely to have been on dialysis >1 year, and receive a nationally allocated, low HLA mismatch, standard KDPI deceased donor kidney. Recipients in cluster 3 were more likely to be minorities (37% Black; 15% Hispanic). They were moderately sensitized with a median PRA of 87% and were also most likely to have been on dialysis >1 year. They received locally allocated high HLA mismatch kidneys from standard KDPI deceased donors. Thymoglobulin was the most commonly used induction agent for all three clusters. Cluster 1 had the most favorable patient and graft survival, while cluster 3 had the worst patient and graft survival.

CONCLUSION

The use of an unsupervised machine learning approach characterized kidney retransplant recipients into three clinically distinct clusters with differing posttransplant outcomes. Recipients with moderate allosensitization, such as those represented in cluster 3, are perhaps more disadvantaged in the kidney retransplantation process. Potential opportunities for improvement specific to these re-transplant recipients include working to improve opportunities to improve access to living donor kidney transplantation, living donor paired exchange and identifying strategies for better HLA matching.

Efficacy and Safety of Plasma Exchange as an Adjunctive Therapy for Rapidly Progressive IgA Nephropathy and Henoch-Schönlein Purpura Nephritis: A Systematic Review

Patients with IgA nephropathy (IgAN), including Henoch-Schönlein purpura nephritis (HSP), who present with rapidly progressive glomerulonephritis (RPGN) have a poor prognosis despite aggressive immunosuppressive therapy. The utility of plasmapheresis/plasma exchange (PLEX) for IgAN/HSP is not well established. This systematic review aims to assess the efficacy of PLEX for IgAN and HSP patients with RPGN. A literature search was conducted using MEDLINE, EMBASE, and through Cochrane Database from inception through September 2022. Studies that reported outcomes of PLEX in IgAN or HSP patients with RPGN were enrolled. The protocol for this systematic review is registered with PROSPERO (no. CRD42022356411). The researchers systematically reviewed 38 articles (29 case reports and 9 case series articles) with a total of 102 RPGN patients (64 (62.8%) had IgAN and 38 (37.2%) had HSP). The mean age was 25 years and 69% were males. There was no specific PLEX regimen utilized in these studies, but most patients received at least 3 PLEX sessions that were titrated based on the patient's response/kidney recovery. The number of PLEX sessions ranged from 3 to 18, and patients additionally received steroids and immunosuppressive treatment (61.6% of patients received cyclophosphamide). Follow-up time ranged from 1 to 120 months, with the majority being followed for at least 2 months after PLEX. Among IgAN patients treated with PLEX, 42.1% (n = 27/64) achieved remission; 20.3% (n = 13/64) achieved complete remission (CR) and 18.7% (n = 12/64) partial remission (PR). 60.9% (n = 39/64) progressed to end-stage kidney disease (ESKD). Among HSP patients treated with PLEX, 76.3% (n = 29/38) achieved remission; of these, 68.4% (n = 26/38) achieved CR and 7.8% achieved (n = 3/38) PR. 23.6% (n = 9/38) progressed to ESKD. Among kidney transplant patients, 20% (n = 1/5) achieved remission and 80% (n = 4/5) progressed to ESKD. Adjunctive plasmapheresis/plasma exchange with immunosuppressive therapy showed benefits in some HSP patients with RPGN and possible benefits in IgAN patients with RPGN. Future prospective, multi-center, randomized clinical studies are needed to corroborate this systematic review's findings.

Periodic limb movements during sleep and risk of hypertension: A systematic review

BACKGROUND

Several studies suggest an association between periodic limb movements during sleep (PLMS) and hypertension; however, a systematic evaluation of this relationship is lacking.

METHODS

We conducted a systematic review and meta-analysis of observational studies that reported odds ratio, relative risk, hazard ratio, or standardized incidence ratio, comparing the risk of hypertension in persons with PLMS (defined by the level of periodic limb movements per hour of sleep depended on individual studies) versus those without PLMS. After assessing heterogeneity and bias, the pooled risk ratio and 95% confidence intervals (CIs) were determined using a random-effect, generic inverse variance method of DerSimonian and Laird.

RESULTS

Out of 572 potentially relevant articles, six eligible studies were included in the data analysis. Studies (6 cross-sectional) included 8949 participants. The statistical heterogeneity of this study was insignificant, with an I² of 0%. A funnel plot and Egger's regression asymmetry test showed no publication bias with P-value ≥0.05. The pooled risk ratio of hypertension in patients with PLMS was 1.26 (95% CI, 1.12-1.41).

CONCLUSIONS

Our analysis demonstrates an increased hypertension risk among patients with PLMS. Prospective or interventional studies are needed to confirm this association.

Effects of Mediterranean Diet, DASH Diet, and Plant-Based Diet on Outcomes among End Stage Kidney Disease Patients: A Systematic Review and Meta-Analysis

BACKGROUND

The Mediterranean, Dietary Approach to Stop Hypertension (DASH), and plant-based diets may provide cardiovascular benefit to the general population. However, data on their effect on end stage kidney disease (ESKD) patients are limited. This systematic review aims to assess the impact of Mediterranean, DASH, and plant-based diets on outcomes among ESKD patients.

METHODS

A literature review was conducted in EMBASE, MEDLINE, and Cochrane databases from inception through September 2022 to identify studies that assess the clinical outcomes of Mediterranean, DASH, or plant-based diets on ESKD patients on hemodialysis (HD) or peritoneal dialysis (PD). Effect estimates from the individual studies were derived utilizing the random-effect, generic inverse variance approach of DerSimonian and Laird.

RESULTS

Seven studies with 9400 ESKD patients (8395 HD and 1005 PD) met the eligibility criteria and were included in the data analysis. Pooled odds ratios (ORs) of mortality for ESKD patients who adhered to the Mediterranean versus plant-based diet were 0.49 (95% CI: 0.07-3.54; two studies, I² = 67%) and 0.87 (95% CI: 0.75-1.01; two studies, I² = 0%), respectively. Data on mortality for ESKD patients on a DASH diet were limited to one study with an OR of 1.00 (95% CI: 0.89-1.12). The pooled OR of cardiovascular mortality among ESKD patients who adhered to a plant-based diet was 0.86 (95% CI: 0.68-1.08; two studies, I² = 0%), compared to those who did not. Data on cardiovascular mortality among those with Mediterranean and DASH diet were limited to one study with ORs of 1.14 (95% CI: 0.90-1.43) and 1.19 (95% CI: 0.99-1.43), respectively. Mediterranean diet adherence was found to be associated with reduced risk of left ventricular hypertrophy (LVH) with an OR of 0.82 (95% CI: 0.68-0.99) in a study including 127 ESKD patients. The risk of hyperkalemia was not significant among those with a plant-based diet with an OR of 1.00 (95% CI: 0.94-1.07) in a study including 150 ESKD patients.

CONCLUSIONS

While our systematic review demonstrated no significant associations of Mediterranean, DASH, and plant-based diets with reduced all-cause mortality or cardiovascular mortality, there was also no evidence that suggested harmful effects of these diets to ESKD patients.

Explainable Preoperative Automated Machine Learning Prediction Model for Cardiac Surgery-Associated Acute Kidney Injury

BACKGROUND

We aimed to develop and validate an automated machine learning (autoML) prediction model for cardiac surgery-associated acute kidney injury (CSA-AKI).

METHODS

Using 69 preoperative variables, we developed several models to predict post-operative AKI in adult patients undergoing cardiac surgery. Models included autoML and non-autoML types, including decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and artificial neural network (ANN), as well as a logistic regression prediction model. We then compared model performance using area under the receiver operating characteristic curve (AUROC) and assessed model calibration using Brier score on the independent testing dataset.

RESULTS

The incidence of CSA-AKI was 36%. Stacked ensemble autoML had the highest predictive performance among autoML models, and was chosen for comparison with other non-autoML and multivariable logistic regression models. The autoML had the highest AUROC (0.79), followed by RF (0.78), XGBoost (0.77), multivariable logistic regression (0.77), ANN (0.75), and DT (0.64). The autoML had comparable AUROC with RF and outperformed the other models. The autoML was well-calibrated. The Brier score for autoML, RF, DT, XGBoost, ANN, and multivariable logistic regression was 0.18, 0.18, 0.21, 0.19, 0.19, and 0.18, respectively. We applied SHAP and LIME algorithms to our autoML prediction model to extract an explanation of the variables that drive patient-specific predictions of CSA-AKI.

CONCLUSION

We were able to present a preoperative autoML prediction model for CSA-AKI that provided high predictive performance that was comparable to RF and superior to other ML and multivariable logistic regression models. The novel approaches of the proposed explainable preoperative autoML prediction model for CSA-AKI may guide clinicians in advancing individualized medicine plans for patients under cardiac surgery.

Machine Learning Consensus Clustering of Morbidly Obese Kidney Transplant Recipients in the United States

Background: This study aimed to better characterize morbidly obese kidney transplant recipients, their clinical characteristics, and outcomes by using an unsupervised machine learning approach. Methods: Consensus cluster analysis was applied to OPTN/UNOS data from 2010 to 2019 based on recipient, donor, and transplant characteristics in kidney transplant recipients with a pre-transplant BMI ≥ 40 kg/m2. Key cluster characteristics were identified using the standardized mean difference. Post-transplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection, were compared among the clusters. Results: Consensus clustering analysis identified 3204 kidney transplant recipients with a BMI ≥ 40 kg/m2. In this cohort, five clinically distinct clusters were identified. Cluster 1 recipients were predominantly white and non-sensitized, had a short dialysis time or were preemptive, and were more likely to receive living donor kidney transplants. Cluster 2 recipients were older and diabetic. They were likely to have been on dialysis >3 years and receive a standard KDPI deceased donor kidney. Cluster 3 recipients were young, black, and had kidney disease secondary to hypertension or glomerular disease. Cluster 3 recipients had >3 years of dialysis and received non-ECD, young, deceased donor kidney transplants with a KDPI < 85%. Cluster 4 recipients were diabetic with variable dialysis duration who either received non-ECD standard KDPI kidneys or living donor kidney transplants. Cluster 5 recipients were young retransplants that were sensitized. One-year patient survival in clusters 1, 2, 3, 4, and 5 was 98.0%, 94.4%, 98.5%, 98.7%, and 97%, and one-year death-censored graft survival was 98.1%, 93.0%, 96.1%, 98.8%, and 93.0%, respectively. Cluster 2 had the worst one-year patient survival. Clusters 2 and 5 had the worst one-year death-censored graft survival. Conclusions: With the application of unsupervised machine learning, variable post-transplant outcomes are observed among morbidly obese kidney transplant recipients. Recipients with earlier access to transplant and living donation show superior outcomes. Unexpectedly, reduced graft survival in cluster 3 recipients perhaps underscores socioeconomic access to post-transplant support and minorities being disadvantaged in access to preemptive and living donor transplants. Despite obesity-related concerns, one-year patient and graft survival were favorable in all clusters, and obesity itself should be reconsidered as a hard barrier to kidney transplantation.