Clinical Journal of the American Society of Nephrology

Out-of-sequence (OOS) allocation, the process by which organ procurement organizations (OPOs) can deviate from standard rank lists of potential recipients to expeditiously allocate deceased-donor kidneys, is rising in the U.S. We aimed to determine whether current OPO reporting practices obscure the extent of OOS allocation. Using match-run data for all U.S. deceased-donor kidney transplants from 2021-2023, we defined "miscoded" OOS (mOOS) allocation transplants as those with use of the 799 or 898 OPO- initiated refusal codes ("other, specify") with free text responses clearly indicating OOS allocation, and compared these to "explicit" OOS (eOOS) allocation, wherein OOS transplants are appropriately coded using refusal codes 861-863. We found that the prevalence of mOOS allocation increased from 2021 (122 transplants) to 2023 (430 transplants) and accounted for 12% of all OOS transplants by 2023. Organs allocated via mOOS had a lower median KDPI than those allocated via eOOS (51% vs 55%, p <0.01). While an increasing number of OPOs used mOOS throughout the study period, the practice remained concentrated overall, with 5 "outlier" OPOs performing 66% of mOOS allocations in 2023. These findings highlight the need for stricter oversight of organ allocation and underscore the responsibility of the OPTN to ensure proper data reporting.

BackgroundAfrican Americans are at increased risk for chronic kidney disease (CKD) in part due to Apolipoprotein L1 gene (APOL1) high-risk genotypes. Recently, a study from West Africa reported an association between monoallelic genotypes and risk of CKD and focal segmental glomerulosclerosis (FSGS). We here study the association of biallelic and monoallelic genotypes with CKD, proteinuria, and FSGS in participants in a hospital-based cohort in the Southeastern United States. MethodsWe conducted a case-control study of African Ancestry participants from the Vanderbilt University Medical Center Biobank (n=23, 857). The primary outcome was CKD defined as: persistent GFR < 60 ml/min, end stage kidney disease (ESKD), biopsy-proven FSGS or urine protein-to-creatinine ratio of >700 mg/g or albumin-to-creatinine ratio of >420 mg/g. Secondary outcomes were proteinuria and FSGS outcomes separately. The primary exposure was APOL1 monoallelic genotype (1 copy of a risk allele versus none). APOL1 biallelic genotypes was studied as a secondary exposure. Sequential logistic regression models were performed adjusting for potential confounders. ResultsAmong 23,857 participants, 5,784 had CKD, 1,533 had proteinuria, and 80 had biopsy-proven FSGS, 44.5% had one risk allele (monoallelic) and 13.6% had two risk alleles (biallelic). Biallelic carriers had higher odds of CKD than those with one or no risk alleles (adjusted odds ratio (aOR), 1.72; 95% confidence interval [CI], 1.57-1.89), proteinuria aOR = 2.02 (95% CI, 1.77-2.31), and FSGS aOR = 17.48 (95%CI 10.53-29.02). Monoallelic carriers (G0/G1 or G0/G2) had a small increase in odds of CKD (aOR = 1.08, 95% CI 1.00-1.16, p=0.04), which was driven by the G0/G2 genotype (aOR = 1.11, 95% CI 1.01-1.23, p=0.03). Monoallelic carriers (G0/G1 or G0/G2) had higher odds of proteinuria (aOR = 1.23; 95% CI, 1.09-1.39) and G0/G1 had higher odds of FSGS (14 cases) (aOR = 2.83; 95% CI, 1.18-6.79). ConclusionsIn our study, monoallelic APOL1 genotypes were associated with 23% higher odds of proteinuria and 3-fold higher odds of FSGS for G0/G1. A modest increase odd for CKD of 8%, which may reflect CKD phenotypic heterogeneity. Our study supports the observations from a West Africa cohort in a US based cohort and adds the association of APOL1 monoallelic genotypes with proteinuria.

ObjectiveDetermine whether urine biomarkers of kidney tubule dysfunction and injury are associated with future-term risk of post-CABG AKI. DesignNested cohort study using data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. SettingA national, population-based, longitudinal cohort study of 30,239 U.S. adults aged [&ge;]45 years. ParticipantsWe included all 760 participants who underwent CABG surgery. The final cohort included 394 participants after exclusion for a history of dialysis or kidney transplant at admission (n=3), illegible chart data (n=346), missing laboratory data (n=15) or underwent a cardiac procedure mislabeled as CABG (n=2). ExposuresUsing spot urine obtained at enrollment, an average of 5.5 years before CABG surgery, we measured biomarkers of kidney tubule dysfunction (urine alpha-1 microglobulin [A1M], uromodulin [UMOD] and epidermal growth factor [EGF]) and injury (kidney injury molecule-1 [KIM-1]). Main OutcomesAKI development following surgery, defined as an increase in serum creatinine [&ge;]0.3 mg/dL from 48 hours prior to CABG to end of hospitalization. ResultsOf 394 eligible participants who underwent CABG (mean age 66, 29% female, 20% Black), 176 (45%) experienced post-operative AKI. Higher baseline urine A1M was associated with higher odds of AKI (adjusted OR 1.34 per 2-fold higher A1M, 95% Confidence Interval (CI): 1.00-1.80). Higher urine UMOD was associated with lower odds of AKI (adjusted OR 0.77 per 2-fold higher UMOD, 95% CI 0.62-0.95). Higher EGF showed a non-significant tendency towards lower odds of AKI (adjusted OR 0.79 per 2-fold higher EGF, 95% CI 0.59-1.05). KIM-1 was not associated with AKI (adjusted OR 0.92 per 2-fold higher KIM-1, 95% CI 0.77- 1.10). ConclusionsSelect biomarkers of tubule dysfunction, but not injury, measured when patients were at a stable baseline, are associated with future AKI after CABG. These markers of kidney dysfunction may offer a strategy for identifying individuals vulnerable to AKI after CABG.

Introduction: APOL1 high-risk variants markedly increase susceptibility to kidney disease among individuals of African ancestry; however, only a subset of carriers develops clinically significant CKD or ESKD. This discrepancy highlights a gap between genetic risk and clinical trajectory. Current prognostic tools rely primarily on eGFR and albuminuria, which incompletely reflect the underlying biological processes driving APOL1-associated kidney injury. We hypothesized that plasma biomarkers reflecting inflammatory and tubular injury pathways could identify biologically active disease states within this genetically high-risk population and improve prognostic stratification. Methods: Participants from the Mount Sinai BioMe Biobank carrying two APOL1 high-risk alleles (G1, G1; G1, G2; or G2 G2) were followed for a median of 6 years. Baseline plasma biomarkers of inflammation and tubular injury (TNFR1, TNFR2, KIM-1, MCP-1, YKL-40, IL-18, suPAR) were measured. The composite outcome was sustained 40% decline in eGFR or ESKD. Multivariable Cox models assessed associations between biomarkers and outcomes. A weighted biomarker risk score was derived from tertile-based hazard ratios and categorized into low-, moderate-, and high-risk groups. Results: Among 498 participants (median eGFR 83 ml/min/1.73 m2), 80 (16.1%) reached the composite outcome. Higher concentrations of TNFR1, TNFR2, suPAR, KIM-1, and IL-18 were independently associated with kidney events after multivariable adjustment. Event rates were 7% in the low-risk group, 16% in the moderate-risk group, and 36% in the high-risk group. Conclusions: Plasma biomarkers reflecting inflammatory and tubular injury pathways reveal marked heterogeneity in kidney outcomes among individuals with high-risk APOL1 genotypes. Integration of these signals into a biology-weighted score identifies distinct prognostic phenotypes beyond genotype and traditional clinical measures, supporting multidomain biomarker frameworks for risk stratification and potential trial enrichment in APOL1-associated kidney disease.

IntroductionChronic kidney disease (CKD) is a highly prevalent disease with disparities in diagnosis and treatment. Until recently, primary diagnosis for CKD was based on equations that incorporated race and have demonstrated racial bias. This study had two aims comparing outcomes for Black patients and their counterparts: 1) whether using the new 2021 CKD-EPI equation led to decreased disparity with time to diagnosis; and 2) whether there was discordance in the staging between the two equations at potential diagnosis point. MethodsWe evaluated patients aged 18 and over with non-hospitalization related serum creatinine laboratory results between January 1, 2016 and September 30, 2023. We estimated the GFR for each patient using the 2009 and 2021 CKD-EPI creatinine equations. We assessed stage discordance for stages 3a, 3b, 4, and 5 using chi-square tests and the Cochran-Mantel-Haenszel. We used multivariate logistic regression to assess a change in staging based on the equation used. Results15.5% of the 8,080,889 patients included in this study were Black. The median age was 57 years and 15.3% of patients met the criteria for stage 3a CKD or higher using either equation. Discordance in staging by equation and by race existed, especially for Black patients at stages 3a and 3b. 40% of Black patients identified as stage 4 using the 2021 equation were 3b or lower using the 2009 equation. DiscussionWell established medical algorithms with race components are being re-examined. We found more disparity with the initial staging of the disease. The disconnect in the timing of staging by equation for Black patients means a number of these patients may not have received the appropriate treatment. Future work should elucidate the impact of the change in CKD staging with the 2021 CKD-EPI creatinine equation on treatment. ConclusionSignificant disparity exists in the timing and staging of CKD by CKD-EPI equation and by race.

BackgroundWe did this study to develop and validate a risk score for new chronic kidney disease (CKD), focusing on predictors that are typically available in Canadian administrative health datasets. MethodsThis was a retrospective population-based cohort study using data from the Alberta Kidney Disease Network database: 3,558,192 adult participants were followed from April 1, 2007 to March 31, 2019. We developed a simple score to predict reduced glomerular filtration rate using bootstrapping (100 iterations with replacement) and internally validated the score using the original dataset. FindingsThe final score had a maximum total of 9 points: age 50-70 years, moderate albuminuria, hypertension, diabetes and heart failure all received a single point, and age >70 years and severe albuminuria received three points. The C-statistic of the score for incident CKD was 0.9272 and the Brier score was 0.0053, indicating excellent discrimination. Graphical analysis demonstrated that predicted risk closely aligned with the observed risk of developing CKD, indicating a well-calibrated model. InterpretationWe have derived and internally validated a risk score for new CKD which is suitable for application to routinely collected Canadian administrative health data. FundingDavid Freeze chair in health services research

BackgroundRising kidney discard rates and uncertainty around accepting higher risk donor kidneys highlight the need for decision support tools that integrate donor and recipient factors and communicate risk in ways that are understandable and usable at the time of offer. Conventional indices (e.g., KDPI/KDRI) provide population level signals but do not deliver individualized, cognitively accessible information aligned with real time clinical workflows. ObjectiveTo describe how key transplant stakeholders (patients, coordinators, and providers) interpret and evaluate a prototype Kidney Risk Calculator app that generates donor-recipient specific survival projections and to identify the content, format and features, and functionality needed for clinically meaningful, patient-centered decision support. DesignQualitative study using focus groups and individual interviews. SettingUniversity of New Mexico Hospital (UNMH) Kidney Transplant Center. ParticipantsFive patients (four transplant candidates and one patient advocate), three transplant coordinators, and five transplant providers (3 attending physicians and 2 advanced practice practitioners). MethodsSemi-structured sessions (45 to 60 minutes) with 13 stakeholders (patients, coordinators, and providers) included a live app demonstration and explored usability, interpretability, contextual information needs, perceived clinical utility, and anticipated barriers/facilitators. Data were collected via one coordinator focus group, one patient focus group, and five provider interviews; sessions were recorded, transcribed, de-identified, and analyzed using inductive reflexive thematic analysis. ResultsStakeholders affirmed the value of personalized projections as an adjunct to clinical judgment, particularly for higher risk offers. Participants prioritized: 1) Content: clear education on hepatitis C virus (HCV) positive donors and Public Health Service (PHS) risk criteria; plain explanations of Calculated Panel Reactive Antibody (CPRA); and framing that makes time on dialysis and tradeoffs salient; 2) Format & Features: plain language narratives, percentages rather than decimals, simple visuals, minimized acronyms, U.S. customary units, and a stepwise (TurboTax-like) input flow preferred by patients; and 3) Functionality: attention to cognitive load and workflow alignment, given phone based time pressure and digital access constraints. Stakeholders emphasized that the value of the tool hinges on clarity, context, and workflow fit, not predictive accuracy alone. LimitationsSingle center, formative prototype study with a modest sample; findings are illustrative and may have limited transferability. Participants reacted to a demonstration rather than using the app during real time offer calls; convenience/email recruitment and Zoom only English sessions may introduce selection bias; team involvement in app development may contribute residual confirmation bias despite mitigation. ConclusionsEarly stakeholder input suggests that a kidney offer decision support tool should integrate individualized predictions with plain language explanations, contextual information that addresses common misconceptions, workflow aligned functionality, and accessible outputs. Tools designed and implemented with these features may support acceptance of medically complex kidneys and may help reduce offer bypass and organ discard. These inferences reflect stakeholder perceptions in a formative qualitative study and warrant prospective evaluation.

In kidney transplantation, obtaining early information about the risk of graft failure helps physicians and patients anticipate a potential return to dialysis or retransplantation. Clinical prediction models are commonly used to obtain such risk estimation, but their performance needs to be continuously evaluated in various contexts. We propose an external validation study of the Kidney Transplant Failure Score in a pooled sample of 3,144 patients transplanted between 2010 and 2015 in France, Belgium, Norway and Canada. This score is used at the first transplantation anniversary to predict the probability of graft failure over the following seven years. The target population was defined as adult recipients of a kidney from a neurologically deceased donor without graft failure in the first year post-transplantation. Graft failure was defined as a return to dialysis. Around 10% of patients returned to dialysis, and 12.6% died during the seven-year follow-up. The KTFS authors fitted a Cox model and then adjusted its coefficients to maximize the discrimination, yielding the KTFS final version. We evaluated the performance of the initial and final versions of the KTFS, as well as the performance of another model we developed to consider death as a competing event. All KTFS versions yielded similarly good discrimination (area under the time-dependant receiver operating curve around from 0.79 [0.76-0.82] to 0.80 [0.77-0.84]), while the discrimination-optimized one presented important miscalibration. Clinical utility, assessed through net benefit, was also the lowest for the discrimination-optimized version. Our results warn against using the current KTFS version and recommend using either the initial coefficients or the competing risk-based ones instead. Lay summaryFrench nephrologists have used the Kidney Transplant Failure Score (KTFS) for nearly fifteen years to predict kidney graft failure eight years after the transplantation. Because predictive performance decreases over time, we first verified that the score could still predict correctly in France and also in other countries. Then, we compared the different KTFS formulas to find that the one currently used is suboptimal and should be avoided. Our findings show that the KTFS is still a reliable source of information for both kidney recipients and nephrologists when using its first version.

BackgroundAcute rejection threatens kidney allograft longevity. Cell-free DNA (cfDNA) is a real-time marker of organ injury and immune response. Donor-derived cfDNA (dd-cfDNA) has been leveraged as a biomarker of rejection, however, its reliability as a screening tool is unclear. DNA methylation is an epigenetic marker that informs regulatory element activity. We aim to elucidate differential methylation of total plasma cfDNA derived from pediatric kidney transplant recipients in the presence compared to absence of acute rejection. In doing so, we hope to exploit the property of cfDNA as a real-time biomarker and build on available testing to identify genes and processes participating in acute rejection pathophysiology in kidney transplantation. MethodsTwenty plasma cfDNA samples from pediatric kidney transplant recipients were collected at the time of allograft biopsy. Using whole genome bisulfite sequencing, differentially methylated CpG residues ([&ge;]20% difference in methylation rate, q-value <0.05) were identified in presence (N = 7) vs absence (N = 9) of acute rejection. Separate analyses were performed comparing those with borderline rejection (N = 4) to those with rejection, and to those without rejection. Differentially methylated cytosines were then assessed for gene associations and pathway enrichments. ResultsIn the comparison of acute rejection to non-rejection samples, there were 34,356 differentially methylated cytosines corresponding to 1,269 associated genes, and 533 enriched pathways. These numbers were all substantially greater (4-13x) than the comparisons made between acute rejection against those with borderline rejection, and between non-rejection against borderline rejection. Prominently enriched pathways between samples of individuals with and without acute rejection were related to immune cell regulation, inflammatory response, lipid metabolism, and tryptophan-kynurenine metabolism. ConclusionsOur data suggest methylation plays a role in development of or response to acute kidney allograft rejection. Specifically, differentially methylated pathways associated with acute rejection include those related to immune and inflammatory responses.

BackgroundSoluble tumor necrosis factor receptor (sTNFR)1, sTNFR2, and plasma kidney injury molecule-1 (KIM-1) are associated with kidney events in patients with and without diabetes. However, their associations with clinical outcomes when obtained pre-operatively have not been explored. MethodsThe TRIBE-AKI cohort study is a prospective, multicenter, cohort study of high-risk adults undergoing cardiac surgery. We assessed the associations between pre-operative concentrations of plasma sTNFR1, sTNFR2, and KIM-1 and post-operative long-term outcomes including mortality, cardiovascular events, and chronic kidney disease (CKD) incidence or progression, ascertained after discharge. ResultsAmong 1378 participants included in the analysis with a median follow-up period was 6.7 (IQR 4.0-7.9), 434 (31%) patients died, 256 (19%) experienced cardiovascular events and out of 837 with available long-term kidney function data, 30% developed CKD. After adjustment for clinical covariates, each log increase in biomarker concentration was independently associated with mortality with 95%CI adjusted hazard ratios (aHRs) of 3.0 (2.3-4.0), 2.3 (1.8-2.9) and 2.0 (CI 1.6-2.4) for sTNFR1, sTNFR2 and KIM-1, respectively. For cardiovascular events, the 95%CI aHRs were 2.1 (1.5 - 3.1), 1.9 (1.4 - 2.6) and 1.6 (1.2 - 2.1) for sTNFR1, sTNFR2 and KIM-1, respectively. For CKD events, the aHRs were 2.2 (1.5 - 3.1) for sTNFR1, 1.9 (1.3 - 2.7) for sTNFR2, and 1.7 (1.3 - 2.3) for KIM-1. Despite the associations, each of the biomarkers alone or in combination failed to result in robust discrimination on an absolute basis or compared to a clinical model. ConclusionsTNFR1, sTNFR2, and KIM-1 were independently associated with longitudinal outcomes after discharge from a cardiac surgery hospitalization including death, cardiovascular and CKD events when obtained pre-operatively in high-risk individuals. Pre-operative plasma biomarkers could serve to assist during the evaluation of patients in whom cardiac surgery is planned.

Sodium-glucose co-transporter 2 (SGLT2) inhibitors are recommended for use in adults with chronic kidney disease (CKD) and are widely prescribed. SGLT2 inhibition markedly increases urine glucose excretion, which could interfere with laboratory assays. We assessed whether assays for several key urine tubular biomarkers (alpha-1 microglobulin [1M], dickkopf-3 [DKK-3], epidermal growth factor [EGF], interleukin-18 [IL-18], kidney injury molecule-1 [KIM-1], monocyte chemoattractant protein-1 [MCP-1], neutrophil gelatinase-associated lipocalin [NGAL], uromodulin [UMOD], and human cartilage glycoprotein-40 [YKL-40]) are affected by glycosuria using urine samples from participants with CKD. Each urine sample was divided into three aliquots, with one serving as control and the other two being spiked with glucose to reach effective concentrations of 28 mmol/l and 111 mmol/l. There was large positive mean bias [95% CI] observed at 28 mmol/l glucose concentration for IL-18 (0.10 [0.01, 0.23]) and YKL-40 (0.40 [0.32, 0.49]). The limits of agreement (LOA) for both biomarkers were wide, spanning >1 unit difference in log-transformed biomarker values. The rest of the biomarkers had narrow LOA. Modest negative mean bias at 28 mmol/l glucose concentration was observed for DKK-3 (-0.02 [-0.04, 0]), KIM-1 (-0.04 [-0.06, -0.02]), and UMOD (-0.08 [-0.11, -0.06]), with similar values observed at 111 mmol/l glucose concentration. There was no evidence of any bias in measurements of 1M, EGF, MCP-1, and NGAL. Glycosuria substantially interferes with IL-18 and YKL-40 measurements, without importantly affecting 1M, DKK-3, EGF, KIM-1, MCP-1, NGAL or UMOD.

Secondary hyperparathyroidism persists in the majority of kidney transplant recipients and is associated with adverse graft and cardiovascular outcomes. The immunosuppressive drug class used post-transplant may modulate parathyroid hormone (PTH) levels through distinct mechanisms: calcineurin inhibitors (CNI) stabilize PTH mRNA, while mTOR inhibitors (mTORi) suppress parathyroid cell proliferation in experimental models. We report supporting evidence from two independent analyses. In a multinational real-world database analysis (TriNetX Global Collaborative Network), kidney transplant recipients with documented mTORi use and eGFR in the target range had lower PTH than those on CNI across eGFR strata examined (15-30, 30-45, 45-60, 60-75, >75 mL/min/1.73 m2), with risk ratios for PTH >130 pg/mL ranging from 0.47 to 0.67 in propensity-matched analyses (all p < 0.05). The known confounders - calcium (higher in CNI) and phosphate (higher in mTORi) - both act to oppose this pattern, strengthening the possibility of a drug effect. In a longitudinal single-center cohort (n = 118; 796 PTH measurements), a linear mixed-effects model with time-varying mTORi exposure confirmed a 42% lower PTH during on-mTORi periods after adjustment for eGFR, transplant vintage, diabetes, age, and sex (fold-change 0.58 [95% CI 0.50-0.68]; p < 0.0001). These findings suggest a direct PTH-lowering effect of mTORi. Immunosuppression choice may be considered in the management of post-transplant hyperparathyroidism in selected patients.

ImportanceObesity-related glomerulopathy (ORG), part of the cardio-renal spectrum, has an early reversible stage of hyperfiltration. Early identification in the obese adolescent population provides an opportunity to reverse the damage. ObjectiveAge-appropriate formulae for estimated glomerular filtration rate (eGFR), are standardized to ideal body surface area (BSA) and provide assessment of renal function in mL/min/1.73 m2 units, may underestimate prevalence of early ORG. We investigated whether adjusting eGFR to actual BSA more readily identifies early ORG. DesignCross sectional cohort study. Data were collected between 2011-2015 and analysis was performed between January-November 2020. SettingElectronic health records clinical data base from 12 academic health centers and community health centers in the New York metropolitan area. Participants22,417 women and girls ages 12-21 years for whom data of body measurements and renal function were available. Main Outcome and measuresThe hypothesis was generated using previously collected health record data. eGFR was calculated in two ways: BSA-standardized eGFR according to KDIGO recommended formula; and Absolute eGFR adjusted to individual BSA. Hyperfiltration was defined above a threshold of 135mL/min/1.73 m2 or 135 mL/min, respectively. The prevalence of hyperfiltration according to each formula was assessed in parallel to 24-hour urine creatinine. Results22,417 female adolescents mean age 17 with high prevalence of underrepresented populations (32.6% African American, 12.8% Caucasians and 40.4% Hispanic) were evaluated. Serum creatinine values and hyperfiltration rates according to BSA-standardized eGFR were similar,13.4-15.3%, across Body Mass Index (BMI) groups. Prevalence of hyperfiltration determined by Absolute eGFR differed across groups: Underweight - 2.3%; Normal 6.1%; Overweight - 17.4%; Obese - 31.4%. This trend paralleled the rise in 24-hour urine creatinine across BMI groups. Conclusions and relevanceAbsolute eGFR more readily identifies early ORG compared to currently used formulae, which are adjusted to an archaic value of a BSA, not representative of current population BMI measures. The high proportion of underrepresented populations in this study accounts for the higher-than-expected obesity rates and should raise awareness for missed opportunities for screening, early diagnosis, and intervention particularly in young Black adults. Key pointsO_ST_ABSQuestionC_ST_ABSDo the currently recommended formulae estimating GFR reliably predict hyperfiltration due to Obesity Related Glomerulopathy (ORG)? FindingsRenal function in relation to BMI was evaluated in a cohort of 22,417 adolescents from the New York metropolitan. Serum creatinine values and BSA-standardized eGFR (mL/min/1.73m2) were similar across BMI groups, and as a result, hyperfiltration rates were also similar. However, Absolute eGFR (mL/min) adjusted to individual BSA, created a positive trend across BMI groups similar to urine creatinine. MeaningAbsolute eGFR better reflects the prevalence of hyperfiltration due to Obesity Related Glomerulopathy providing an opportunity for early intervention and damage reversal.

Rationale and ObjectiveThe NKF-ASN Task Force recommends accurate kidney function estimation avoiding biases through racial adjustments. We explored the use of multiple kidney function biomarkers and hence estimated glomerular filtration rate (eGFR) equations to improve kidney function calculations in an ethnically diverse patient population. Study designProspective community cohort study. Setting and ParticipantsRural New Mexico clinic with patients > 18 yo. MethodsMarkers of kidney function, IDMS-Creatinine (SCr), chemiluminescence Beta-2 Microglobulin (B2M), Nephelometry-calibrated ELISA Cystatin C (CysC), inflammation, glucose tolerance, demographics, BUN/UACR from the baseline visit of the COMPASS cohort, were analyzed by Kernel-based Virtual Machine learning methods. ResultsAmong 205 participants, the mean age was 50.1, 62% were female, 54.1% Hispanic American and 30.2% Native American. Average kidney function biomarkers were: SCr 0.9 mg/dl, B2M 1.8 mg/L, and CysC 0.7 mg/dl. The highest agreement was observed between SCr and B2M-based eGFR equations [mean difference in eGFRs: (4.48 ml/min/1.73m2], and the lowest agreement between B2M and CysC-based eGFR equations (-24.75 ml/min/1.73m2). There was no pattern of association between the differences in eGFR measures and gender. In the continuous analyses, the absolute eGFR value (p<2 x 10-16) and serum albumin (p =6.4 x 10-5) predicted the difference between B2M- and SCr-based e-GFR. The absolute eGFR value (p<2 x 10-16) and age (p =7.6 x 10-5) predicted the difference between CysC- and SCr-based e-GFR. LimitationsRelatively small sample size, elevated inflammatory state in majority of study participants and no inulin excretion rate measurements. ConclusionB2M should be strongly considered as a kidney function biomarker fulfilling the criteria for the NKF-ASN. B2Ms eGFR equation does not need adjustment for gender or race and showed the highest agreement with SCr-based eGFR equations.

Gabapentin and pregabalin are renally cleared gabapentinoids with markedly different pharmacokinetic profiles in chronic kidney disease: gabapentin half-life extends from 5-7 hours to 52-132 hours in advanced chronic kidney disease, while pregabalin accumulation is more predictable. In an active comparator new-user cohort of 33,791 adults aged [&ge;]40 years with hypertension initiating gabapentinoids (2018-2024) from the Rutgers Clinical Research Data Warehouse, chronic kidney disease substantially amplified gabapentin-associated dementia risk (hazard ratio 7.39, 95% confidence interval 3.43 to 15.92, P<0.001), whereas patients without chronic kidney disease showed near-null effect (hazard ratio 1.09, 95% confidence interval 0.89 to 1.34; P=0.41; interaction P<0.001). This effect was independent of prescribed dose: within the low-dose stratum, chronic kidney disease patients showed hazard ratio 5.06 versus 1.27 in patients without chronic kidney disease. Pre-existing chronic kidney disease conferred significantly elevated risk (hazard ratio 1.78; P=0.001), while incident chronic kidney disease showed a nonsignificant trend (hazard ratio 1.32; P=0.16), consistent with cumulative pharmacokinetic burden. Independent replication in the NIH All of Us Research Program Controlled Tier (N=47,079; hazard ratio 1.593, 95% confidence interval 1.349 to 1.882; P<0.001) confirmed the overall gabapentin-pregabalin signal; eGFR-staged analysis showed the expected pharmacokinetic pattern (mild CKD [eGFR [&ge;]45]: hazard ratio 1.15, not significant; severe CKD [eGFR <45]: hazard ratio 1.77, directionally elevated but underpowered with 51 events). Food and Drug Administration Adverse Event Reporting System data corroborated the renal mechanism (odds ratio 1.642 for renal events in elderly co-exposed patients). These converging findings suggest that chronic kidney disease is a clinically important modifier of gabapentin-associated cognitive risk, and that gabapentinoid selection in chronic kidney disease patients should integrate renal function status into prescribing decisions. Significance StatementGabapentin is the most prescribed gabapentinoid in the United States, with approximately 59 million annual prescriptions, and is entirely dependent on renal clearance. In this active comparator cohort study of 33,791 gabapentinoid initiators, chronic kidney disease amplified gabapentin-associated dementia risk nearly 7-fold compared with pregabalin, an effect that was independent of prescribed dose and persisted even among patients receiving low-dose gabapentin. External replication in the NIH All of Us Research Program and FDA pharmacovigilance data corroborated the signal. These findings suggest that current dose-adjustment guidelines for gabapentin in CKD may be insufficient to prevent cognitive harm, and that renal function status should be incorporated into gabapentinoid selection decisions.

BackgroundThe appropriate use and the implications of using variables that attempt to encode a patients race in clinical predictive algorithms remain unclear. The clinical algorithm for estimating glomerular filtration rate (GFR) adjusts for race, but the observed difference between Black and non-Black participants lacks biologically substantiated evidence. We investigated the impact of using a race variable on GFR prediction by race-stratified error analysis. MethodsWe implemented three predictive algorithms with varied amount of input information from an electronic health record database to estimate GFR. We compared the prediction error of the estimated GFR with and without the variable race between Black patients and White patients. ResultsThe prediction error for patients coded as Black was higher than that for patients coded as White across all three algorithms. Removing race from the prediction algorithm did not lower the prediction error for patients coded as Black, neither did it decrease the difference in error between the two groups. The algorithm that included the most information with thousands of variables but excluding race produced the most accurate estimate for both groups and minimized the difference in performance between the two groups. ConclusionThe prediction error for patients coded as Black was higher compared to those coded as White, regardless of inclusion of race as a variable. Using a large amount of information represented in electronic health record variables achieved a more accurate prediction of GFR and the least difference in prediction error across racial groups.

PurposeCreatinine-based estimated glomerular filtration rate (eGFRCRE) may overestimate kidney function in patients with sarcopenia. While Cystatin C-based eGFR (eGFRCYS) is less affected by muscle mass, it may underestimate kidney function in patients with obesity. We sought to evaluate the relationship between body composition and discrepancies between creatinine and eGFRCRE and eGFRCYS in patients with cancer. MethodsWe conducted a cross-sectional study of consecutive adults with cancer who had an abdominal CT scan performed within 90 days of simultaneous eGFRCRE and eGFRCYS measurements between May 2010-January 2022. Sarcopenia was defined using independent sex-specific cutoffs for skeletal muscle index (SMI) at the level of the third lumbar vertebral body (<39 cm2/m2 for women,<55 cm2/m2 for men). High adiposity was defined as the highest sex-specific quartile of total (visceral plus subcutaneous) adiposity index in the cohort. The primary outcome was eGFR discrepancy, defined by eGFRCYS >30% lower than eGFRCRE. We estimated the odds of eGFR discrepancy using multivariable logistic regression modeling. ResultsOf 545 included patients (mean age 63 {+/-}14 years, 300 [55%] females, 440 [80.7%] non-Hispanic white), 320 (58.7%) met the criteria for sarcopenia and 136 (25%) had high adiposity. After adjustment for potential confounders, sarcopenia and high adiposity were both associated with >30% eGFR discrepancy (adjusted odds ratio [aOR] 1.90, 95% confidence interval [CI] 1.12-3.24; aOR 2.01, 95% CI 1.15-3.52, respectively). ConclusionDiscrepancies in eGFRCRE and eGFRCYS are common in adult patients with cancer, and sarcopenia and high adiposity are both independently associated with large eGFR discrepancies. Significance statementSerum creatinine may overestimate glomerular filtration rate (GFR) in patients with muscle loss, which is particularly common among patients with cancer. Serum cystatin C may perform better than creatinine in such patients, but its accuracy is affected by obesity. We performed body composition analysis using computed tomography scans in 545 adult patients with cancer and found that both sarcopenia and high adiposity were independently associated with greater discrepancies in serum creatinine-vs. cystatin C-based estimated GFR. These findings highlight the need for future studies to improve and personalize GFR assessment in patients with cancer, particularly in those who will receive renally cleared medications and anti-neoplastic therapies with a narrow therapeutic index.

IntroductionGenomic testing is reshaping nephrology practice, yet the structure, outcomes, and implementation of kidney genetics services remain poorly characterized. MethodsWe conducted a two-part scoping study comprising (i) a literature review (JBI methodology, PRISMA-ScR compliant; OSF registration doi.org/10.17605/OSF.IO/N32VA) of English-language publications (2000-2025) describing kidney genetics services and outcomes, and (ii) an international stakeholder consultation of clinic leads to capture real-world service and implementation experiences. ResultsSixty studies were included, predominantly from North America (n=23), followed by United Kingdom/Ireland (n=5), Europe (n=17), Australia/New Zealand (n=10), and Asia (n=5). Among the 25 studies describing clinic models, four types were identified: multidisciplinary integrated (n=12), nephrologist-led (n=9), mainstreaming (n=2), and traditional genetics referral (n=2). Clinic structure varied by region. Outcome reporting focused on diagnostic yield (92%), with limited data on timeliness (16%), patient-reported outcomes (12%), or implementation outcomes (4%). Test penetration was high across regions and models, while diagnostic yield varied. Nephrologist-led clinics demonstrated comparable performance to multidisciplinary models when adequately supported. International stakeholder consultation data (n=48) revealed diversification of clinic models across regions. In Australia/New Zealand, multidisciplinary clinics predominated, supported by public funding and in-house or hybrid laboratory. United Kingdom/Ireland clinics used public funding and a national laboratory. North American clinics show greater heterogeneity, with higher prevalence of nephrologist-led models, reliance on commercial laboratories, and mixed or private funding. Asian clinics reported nephrologist-led models, with resource constraints, and hybrid testing and funding arrangements. Comprehensive sequencing with virtual panels predominated in Australia/New Zealand, United Kingdom, and Europe; phenotype-driven panels {+/-} reflex testing were more common in North America. ConclusionsKidney genetics care is expanding but remains unevenly implemented. Nephrologist-led and multidisciplinary models can be effective with appropriate support. Patient selection may influence diagnostic yield more than testing modality. Standardized outcome reporting and theory-driven implementation evaluation are essential for delivering equitable, sustainable genomic services. Lay SummaryThis study examined how kidney genetics services are delivered across the globe. We reviewed 60 studies (2000-2025) and consulted 48 clinic leaders globally. Four service models were identified--multidisciplinary integrated, nephrologist-led, mainstreaming, and traditional genetics referral--and mapped variation in care teams, test strategies, test laboratories, and funding. Most studies reported diagnostic yield, but few assessed patient experience or how well services were implemented. European programs showed the highest performance, attributed to clear referral criteria, deep phenotyping, detailed family histories, multidisciplinary review, and strong public funding. Clinics led by nephrologists performed comparably to multidisciplinary teams when adequately supported. Across all settings, patient selection was more important than the specific type of genetic test used in determining diagnostic success. Kidney genetics services are expanding but remain uneven. This study highlights the need for context-specific, theory-informed, and determinants-targeted strategies to support scalable, equitable, and sustainable genomic care worldwide.

The response of the immune system to COVID-19 in end stage kidney disease patients who undergo kidney transplantation has yet to be described. We report data on 72 patients who underwent SARS-CoV-2 antibody testing both before and after kidney transplantation and were followed for a median of 186 days (range 83, 277). Of the 25 patients with a positive antibody test at the time of transplant, 17 (68%) remained positive after transplantation. Patients were significantly more likely to have a persistently positive test if they reported a symptomatic COVID-19 infection prior to transplant (p=0.01). SARS-CoV-2 IgG index values were measured in a subset of kidney transplant recipients and compared to wait -listed dialysis patients. These assays demonstrated a more significant decline in IgG (58% versus 14% p = 0.008) in transplant recipients when compared to dialysis patients tested during the same time period. Additional analysis of the quality of the immune response measuring the binding of SARS-CoV-2 antibodies to the receptor-binding domain (RBD binding), the antibody neutralizing capability, and the antibody avidity demonstrated a more pronounced effect when comparing pre-transplant values to post-induction therapy/post transplant values. The attenuated IgG response seen in transplant patients compared to dialysis patients after induction therapy requires further study. These data have important implications for post-transplant management of vaccinated dialysis patients.

Background and hypothesis: Sodium-glucose cotransporter-2 inhibitors (SGLT2-inhibitors) slow chronic kidney disease progression, but evidence in non-diabetic kidney transplant recipients is limited. We evaluated associations between SGLT2-inhibitor use and major adverse kidney events (MAKE), major adverse cardiovascular events (MACE), and all-cause mortality. Methods: In this retrospective cohort study using the TriNetX federated research network, adult non-diabetic kidney transplant recipients transplanted between January 2015 and January 2022 were identified. SGLT2-inhibitor users initiating therapy [&ge;]1000 days post-transplant were compared with non-users after 1:1 propensity score matching. The primary outcome was MAKE, defined as dialysis initiation or death. Secondary outcomes included all-cause mortality and MACE. Results: Propensity score matching yielded 867 pairs of SGLT2-inhibitor users and non-users. SGLT2-inhibitor use was associated with lower risks of MAKE (adjusted hazard ratio [aHR] 0.64, 95% CI 0.45-0.91) and all-cause mortality (aHR 0.55, 95% CI 0.36-0.85). No significant association was observed for MACE (aHR 0.86, 95% CI 0.64-1.17). No increased risk of urinary tract infections was observed among SGLT2-inhibitor users. Conclusion: SGLT2-inhibitor use was associated with lower risks of MAKE and all-cause mortality in non-diabetic kidney transplant recipients.