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Background: Accurate diagnosis of acute tubulointerstitial nephritis (AIN) often requires a kidney biopsy. We previously developed a diagnostic statistical model for predicting biopsy-confirmed AIN by combining four laboratory tests after evaluating over 150 potential predictors from the electronic health record. Here, we validate this diagnostic model in two biopsy-based cohorts at Johns Hopkins Hospital (JHH) and Yale, which were geographically and temporally distinct from the development cohort, respectively., Methods: We analyzed patients who underwent kidney biopsy at JHH and Yale University (2019-2023). We assessed discrimination (AUC) and calibration using previously derived model coefficients and recalibrated the model using an intercept correction factor that accounted for differences in baseline prevalence of AIN between development and validation cohorts., Results: We included 1982 participants: 1454 at JHH and 528 at Yale. JHH (5%) and Yale (17%) had lower proportions of biopsies with AIN than the development set (23%). The AUC was 0.73 (0.66-0.79) at JHH and 0.73 (0.67-0.78) at Yale, similar to the development set (0.73 (0.64-0.81)). Calibration was imperfect in validation cohorts, particularly at JHH, but improved with application of an intercept correction factor. The model increased AUC of clinicians' prebiopsy suspicion for AIN by 0.10 to 0.77 (0.71-0.82)., Conclusions: An AIN diagnostic model retained discrimination in two validation cohorts but needed recalibration to account for local AIN prevalence. The model improved clinicians' ability to predict AIN., (Copyright © 2024 by the American Society of Nephrology.)

Importance: Recipient outcomes after kidney transplant from deceased donors who received dialysis prior to kidney donation are not well described., Objective: To compare outcomes of transplant recipients who received kidneys from deceased donors who underwent dialysis prior to kidney donation vs recipients of kidneys from deceased donors who did not undergo dialysis., Design, Setting, and Participants: A retrospective cohort study was conducted including data from 58 US organ procurement organizations on deceased kidney donors and kidney transplant recipients. From 2010 to 2018, 805 donors who underwent dialysis prior to kidney donation were identified. The donors who underwent dialysis prior to kidney donation were matched 1:1 with donors who did not undergo dialysis using a rank-based distance matrix algorithm; 1944 kidney transplant recipients were evaluated., Exposure: Kidney transplants from deceased donors who underwent dialysis prior to kidney donation compared with kidney transplants from deceased donors who did not undergo dialysis., Main Outcomes and Measures: The 4 study outcomes were delayed graft function (defined as receipt of dialysis by the kidney recipient ≤1 week after transplant), all-cause graft failure, death-censored graft failure, and death., Results: From 2010 to 2018, 1.4% of deceased kidney donors (805 of 58 155) underwent dialysis prior to kidney donation. Of these 805 individuals, 523 (65%) donated at least 1 kidney. A total of 969 kidneys (60%) were transplanted and 641 kidneys (40%) were discarded. Among the donors with kidneys transplanted, 514 (mean age, 33 years [SD, 10.8 years]; 98 had hypertension [19.1%] and 36 had diabetes [7%]) underwent dialysis prior to donation and were matched with 514 (mean age, 33 years [SD, 10.9 years]; 98 had hypertension [19.1%] and 36 had diabetes [7%]) who did not undergo dialysis. Kidney transplants from donors who received dialysis prior to donation (n = 954 kidney recipients) were associated with a higher risk of delayed graft function compared with kidney transplants from donors who did not receive dialysis (n = 990 kidney recipients) (59.2% vs 24.6%, respectively; adjusted odds ratio, 4.17 [95% CI, 3.28-5.29]). The incidence rates did not significantly differ at a median follow-up of 34.1 months for all-cause graft failure (43.1 kidney transplants per 1000 person-years from donors who received dialysis prior to donation vs 46.9 kidney transplants per 1000 person-years from donors who did not receive dialysis; adjusted hazard ratio [HR], 0.90 [95% CI, 0.70-1.15]), for death-censored graft failure (22.5 vs 20.6 per 1000 person-years, respectively; adjusted HR, 1.18 [95% CI, 0.83-1.69]), or for death (24.6 vs 30.8 per 1000 person-years; adjusted HR, 0.76 [95% CI, 0.55-1.04])., Conclusions and Relevance: Compared with receiving a kidney from a deceased donor who did not undergo dialysis, receiving a kidney from a deceased donor who underwent dialysis prior to kidney donation was associated with a significantly higher incidence of delayed graft function, but no significant difference in graft failure or death at follow-up.

Experimental models suggest an important role for mitochondrial dysfunction in the pathogenesis of chronic kidney disease (CKD) and acute kidney injury (AKI), but little is known regarding the impact of common mitochondrial genetic variation on kidney health. We sought to evaluate associations of inherited mitochondrial DNA (mtDNA) variation with risk of CKD and AKI in a large population-based cohort. We categorized UK Biobank participants who self-identified as white into eight distinct mtDNA haplotypes, which were previously identified based on their associations with phenotypes associated with mitochondrial DNA copy number, a measure of mitochondrial function. We used linear and logistic regression models to evaluate associations of these mtDNA haplotypes with estimated glomerular filtration rate by serum creatinine and cystatin C (eGFR Cr-CysC , N = 362,802), prevalent (N = 416 cases) and incident (N = 405 cases) end-stage kidney disease (ESKD), AKI defined by diagnostic codes (N = 14,170 cases), and urine albumin/creatinine ratio (ACR, N = 114,662). The mean age was 57 ± 8 years and the mean eGFR was 90 ± 14 ml/min/1.73 m 2 . MtDNA haplotype was significantly associated with eGFR (p = 2.8E-12), but not with prevalent ESKD (p = 5.9E-2), incident ESKD (p = 0.93), AKI (p = 0.26), or urine ACR (p = 0.54). The association of mtDNA haplotype with eGFR remained significant after adjustment for diabetes mellitus and hypertension (p = 1.2E-10). When compared to the reference haplotype, mtDNA haplotypes I (β = 0.402, standard error (SE) = 0.111; p = 2.7E-4), IV (β = 0.430, SE = 0.073; p = 4.2E-9), and V (β = 0.233, SE = 0.050; p = 2.7E-6) were each associated with higher eGFR. Among self-identified white UK Biobank participants, mtDNA haplotype was associated with eGFR, but not with ESKD, AKI or albuminuria., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)