Stegall, Mark D

ABSTRACT Predicting delayed graft function (DGF) relies on donor, recipient, and perioperative factors. Despite the growing recognition that DGF duration strongly influences patient outcomes, no models currently address or predict its impact—highlighting an important gap in current research and clinical practice. This study aimed to develop an ensemble‐based machine learning model using perioperative data to predict DGF occurrence and duration. The gradient‐boosted decision trees model was trained and validated on 2725 patients, with k‐fold cross‐validation in an external cohort of 284 patients. Model performance was evaluated based on accuracy, ROC‐AUC, and other metrics using R and Python libraries. The binary DGF prediction model achieved a ROC‐AUC of 0.77, while the DGF duration classification model had an accuracy of 79.2%. DGF duration AUC values by time interval were 0.76 for 0–1 weeks, 0.81 for >1–2 weeks, 0.80 for >2–3 weeks, and 0.87 for >3 weeks; the overall macro‐averaged AUC was 0.81. The mean Brier score for multi‐class predictions was 0.14. External validation showed a 78% accuracy for DGF duration prediction. Acute kidney injury (AKI) and donor donation after circulatory death (DCD) status were key DGF predictors. The use of gradient‐boosted decision trees (GBDT) improves the prediction of both the likelihood and duration of DGF, addressing a current gap in kidney transplant patient care. By facilitating personalized transplant care, this model supports more effective perioperative planning and timely interventions, which may contribute to better patient outcomes.

ABSTRACT Background Abdominal arterial calcification (AAC) is a common comorbidity in patients with end‐stage kidney disease (ESKD) and a predictor of cardiovascular events post‐kidney transplant. However, prior studies lacked a standardized approach to evaluate AAC and its impact on post‐transplant outcomes. This study aimed to correlate AAC score values with post‐kidney transplant outcomes using a modified scoring system traditionally applied to coronary artery calcification. Methods This retrospective study included 14 339 adult patients listed for kidney transplant between 2002 and 2023 at three transplant centers. Among them, 3683 patients met the criteria of undergoing a kidney transplant and an abdominal computed tomography (CT) scan pre‐transplant. We modified the coronary calcium score software by adjusting intake data points to quantify calcification in the abdominal aorta, common iliac, external iliac, and internal iliac arteries. Outcomes focused on post‐transplant mortality. Results In 3683 kidney transplant recipients, higher AAC scores were significantly associated with increased mortality. Each 1000‐unit increase in AAC score elevated hazard ratios (HRs) across arterial regions, including 1.116 for the aorta and 1.389 for the internal iliac (all p < 0.001). Adjusted analyses confirmed AAC as an independent risk factor for mortality. Kaplan–Meier curves demonstrated lower survival with increasing AAC quartiles. Conclusions AAC, measured by a standardized score, is a significant mortality risk factor in kidney transplant recipients. Integrating AAC scores into pre‐transplant evaluations could enhance risk stratification and improve outcomes. Prospective studies are needed to validate these findings and explore interventions to reduce AAC and improve survival.

ABSTRACT Background Ureteral stents are commonly placed during kidney transplantation (KT) to mitigate urologic complications. The objective of this study was to compare clinical outcomes in KT recipients with either early stent removal when attached to the Foley catheter or late removal via cystoscopy when unattached. Methods We conducted a multi‐center retrospective analysis of consecutive living donor KT patients (8/18/21‐4/21/23) stratified into Foley‐attached and unattached stent groups. Outcomes assessed were ureteral stricture, urine leaks, UTIs at 90 days and allograft failure and BKV DNAemia (BK virus DNAemia) at 1 year. Data are reported as mean and standard deviation. Results Among 247 patients with attached and 260 with unattached stents, baseline demographics (age, sex, diabetes) were similar between groups. There was a difference in race (87.9% vs. 77.8% Caucasian; p = 0.004). Foley catheters remained longer in the attached group (3.7 ± 1.8 vs. 3.0 ± 2.0 days; p < 0.001), but stents were removed earlier (3.7 ± 1.8 vs. 21.9 ± 4.7 days; p < 0.001). Comparing attached versus unattached, there were no differences in ureteral stricture (0.4% vs. 1.5%; p = 0.197), urine leak (0.8% vs. 0.4%; p = 0.533), BKV DNAemia (17.7% vs. 16.9%; p = 0.616), or allograft failure (0% vs. 0.8%; p = 0.167). However, UTI incidence by 90 days was lower in the attached group (5.7% vs. 11.9% p = 0.013). Induction therapy differed significantly between groups, with Alemtuzumab more common in the unattached group (58.1% vs. 19.4%, p < 0.001), Basiliximab more common in the attached group (43.3% vs. 35.0%, p < 0.001), and Thymoglobulin more common in the attached group (36.0% vs. 6.9%, p < 0.001). Baseline steroid use was higher in the unattached group (81.9% vs. 57.9%, p < 0.001). Conclusion Early stent removal via connection to the Foley catheter had similarly low rates of ureteral complications while reducing urinary tract infections and avoiding cystoscopic removal.

ABSTRACTIntroductionThe incidence of mortality late in the pandemic, particularly after widespread vaccine availability, is not well understood. Herein, we elucidate the effect of this impact of the COVID pandemic as well as risk factors for mortality during it.MethodsThe primary end point was death with a functioning graft with secondary endpoints of mortality rates in subgroups and at different time intervals during the pandemic.ResultsDespite widespread vaccination, mortality rates for kidney transplant (KTx) recipients almost doubled during the COVID‐19 era (6.40 deaths per 100 person years vs. 3.54 pre‐COVID). Mortality increased in all racial/ethnic groups but increased more in Native Americans, Hispanics, and African Americans compared to non‐Hispanic Caucasians. The highest mortality rate occurred during the Delta and Omicron time frames. In contrast to the general population, mortality was more evenly spread across age groups in KTx recipients.ConclusionsMortality rates during the COVID‐19 era were extremely high, more than doubling in some racial/ethnic groups. We conclude that the KTx population was a particularly vulnerable group during the COVID‐19 era and suggests the need for further research into the management of variants in the future.

AbstractPancreas transplantation alone (PTA) is a β cell replacement option for selected patients with type 1 diabetes mellitus; concerns have been raised regarding deterioration in kidney function (KF) after PTA. This retrospective multicenter study assessed actual impact of transplantation and immunosuppression on KF in PTA recipients at three Transplant Centers. The primary composite endpoint 10 years after PTA was >50% eGFR decline, eGFR < 30 mL/min/1.73 m2, and/or receiving a kidney transplant (KT). Overall, 822 PTA recipients met eligibility. Median baseline and 10‐year eGFR (mL/min/1.73 m2) were 76.3 (58.1–100.8) and 51.3 (35.3–65.9), respectively. Primary composite endpoint occurred in 98 patients (53.5%) with 45 experiencing a >50% decrease in eGFR by 10 years post‐transplant, 38 eGFR < 30 mL/min/1.73 m2 and 49 requiring KT. KF declined most significantly within 6 months post‐PTA, more often in females and patients with better preserved GFR up to 5 years with 11.6% kidney failure at 10 years. Patient survival and death‐censored graft survival were both 68% at 10 years with overall graft thrombosis rate 8%. KF declined initially after PTA but stabilized with further slow progression. In conclusion, prospective intervention studies are needed to test renal sparing interventions while gathering more granular data.

AbstractKidney transplantation is the preferred treatment for individuals with end‐stage kidney disease. From a modeling perspective, our understanding of kidney function trajectories after transplantation remains limited. Current modeling of kidney function post‐transplantation is focused on linear slopes or percent decline and often excludes the highly variable early timepoints post‐transplantation, where kidney function recovers and then stabilizes. Using estimated glomerular filtration rate (eGFR), a well‐known biomarker of kidney function, from an aggregated dataset of 4904 kidney transplant patients including both observational studies and clinical trials, we developed a longitudinal model of kidney function trajectories from time of transplant to 6 years post‐transplant. Our model is a nonlinear, mixed‐effects model built in NONMEM that captured both the recovery phase after kidney transplantation, where the graft recovers function, and the long‐term phase of stabilization and slow decline. Model fit was assessed using diagnostic plots and individual fits. Model performance, assessed via visual predictive checks, suggests accurate model predictions of eGFR at the median and lower 95% quantiles of eGFR, ranges which are of critical clinical importance for assessing loss of kidney function. Various clinically relevant covariates were also explored and found to improve the model. For example, transplant recipients of deceased donors recover function more slowly after transplantation and calcineurin inhibitor use promotes faster long‐term decay. Our work provides a generalizable, nonlinear model of kidney allograft function that will be useful for estimating eGFR up to 6 years post‐transplant in various clinically relevant populations.

AbstractBackgroundThe aim of this study was to correlate peripheral blood gene expression profile (GEP) results during the first post‐transplant year with outcomes after kidney transplantation.MethodsWe conducted a prospective, multicenter observational study of obtaining peripheral blood at five timepoints during the first post‐transplant year to perform a GEP assay. The cohort was stratified based on the pattern of the peripheral blood GEP results: Tx‐all GEP results normal, 1 Not‐TX had one GEP result abnormal and >1 Not‐TX two or more abnormal GEP results. We correlated the GEP results with outcomes after transplantation.ResultsWe enrolled 240 kidney transplant recipients. The cohort was stratified into the three groups: TX n = 117 (47%), 1 Not‐TX n = 59 (25%) and >1 Not‐TX n = 64 (27%). Compared to the TX group, the >1 Not‐TX group had lower eGFR (p < .001) and more chronic changes on 1‐year surveillance biopsy (p = .007). Death censored graft survival showed inferior graft survival in the >1 Not‐TX group (p < .001) but not in the 1 Not‐TX group. All graft losses in the >1 Not‐TX group occurred after 1‐year post‐transplant.ConclusionsWe conclude that a pattern of persistently Not‐TX GEP assay correlates with inferior graft survival.

Significance Statement Nephron number currently can be estimated only from glomerular density on a kidney biopsy combined with cortical volume from kidney imaging. Because of measurement biases, refinement of this approach and validation across different patient populations have been needed. The prognostic importance of nephron number also has been unclear. The authors present an improved method of estimating nephron number that corrects for several biases, resulting in a 27% higher nephron number estimate for donor kidneys compared with a prior method. After accounting for comorbidities, the new nephron number estimate does not differ between kidney donors and kidney patients with tumor and shows consistent associations with clinical characteristics across these two populations. The findings also indicate that low nephron number predicts CKD independent of biopsy and clinical characteristics in both populations. Background Nephron number can be estimated from glomerular density and cortical volume. However, because of measurement biases, this approach needs refinement, comparison between disparate populations, and evaluation as a predictor of CKD outcomes. Methods We studied 3020 living kidney donors and 1354 patients who underwent radical nephrectomy for tumor. We determined cortex volume of the retained kidney from presurgical imaging and glomerular density by morphometric analysis of needle core biopsy of the donated kidney and wedge sections of the removed kidney. Glomerular density was corrected for missing glomerular tufts, absence of the kidney capsule, and then tissue shrinkage on the basis of analysis of 30 autopsy kidneys. We used logistic regression (in donors) and Cox proportional hazard models (in patients with tumor) to assess the risk of CKD outcomes associated with nephron number. Results Donors had 1.17 million nephrons per kidney; patients with tumor had 0.99 million nephrons per kidney. A lower nephron number was associated with older age, female sex, shorter height, hypertension, family history of ESKD, lower GFR, and proteinuria. After adjusting for these characteristics, nephron number did not differ between donors and patients with tumor. Low nephron number (defined by <5th or <10th percentile by age and sex in a healthy subset) in both populations predicted future risk of CKD outcomes independent of biopsy and clinical characteristics. Conclusions Compared with an older method for estimating nephron number, a new method that addresses several sources of bias results in nephron number estimates that are 27% higher in donors and 1% higher in patients with tumor and shows consistency between two populations. Low nephron number independently predicts CKD in both populations. Podcast This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/JASN/2023_06_22_JASN0000000000000124.mp3

AbstractBackgroundComputer‐assisted scoring is gaining prominence in the evaluation of renal histology; however, much of the focus has been on identifying larger objects such as glomeruli. Total inflammation impacts graft outcome, and its quantification requires tools to identify objects at the cellular level or smaller. The goal of the current study was to use CD45 stained slides coupled with image analysis tools to quantify the amount of non‐glomerular inflammation within the cortex.MethodsSixty renal transplant whole slide images were used for digital image analysis. Multiple thresholding methods using pixel intensity and object size were used to identify inflammation in the cortex. Additionally, convolutional neural networks were used to separate glomeruli from other objects in the cortex. This combined measure of inflammation was then correlated with rescored Banff total inflammation classification and outcomes.ResultsIdentification of glomeruli on biopsies had high fidelity (mean pixelwise dice coefficient of .858). Continuous total inflammation scores correlated well with Banff rescoring (maximum Pearson correlation .824). A separate set of thresholds resulted in a significant correlation with alloimmune graft loss.ConclusionsAutomated scoring of inflammation showed a high correlation with Banff scoring. Digital image analysis provides a powerful tool for analysis of renal pathology, not only because it is reproducible and can be automated, but also because it provides much more granular data for studies.

Background Obesity is increasingly common in kidney transplant candidates and may limit access to transplantation. Obesity and diabetes are associated with a high risk for post-transplant complications. The best approach to weight loss to facilitate active transplant listing is unknown, but bariatric surgery is rarely considered due to patient- and physician-related apprehension, among other factors. Methods We aimed to determine the magnitude of weight loss, listing, and transplant rates in 28 candidates with a mean BMI of 44.4±4.6 kg/m 2 and diabetes treated conservatively for 1 year post weight-loss consultations (group 1). Additionally, we evaluated 15 patients (group 2) who met the inclusion criteria but received bariatric intervention within the same time frame. All patients completed a multidisciplinary weight management consultation with at least 1 year of follow-up. Results In the conservatively managed group (group 1), the mean weight at the time of initial consultation was 126.5±18.5 kg, and the mean BMI was 44.4±4.6 kg/m 2 . At 1 year post weight-loss consultation, the mean weight decreased by 4.4±8.2 kg to 122.9±17 kg, and the mean BMI was 43±4.8 kg/m 2 , with a total mean body weight decrease of 3% ( P =0.01). Eighteen patients (64%) did not progress to become candidates for active listing/transplantation during the follow-up time of 4±2.9 years, with 15 (54%) subsequently developing renal failure/diabetes-related comorbidities prohibitive for transplantation. In contrast, mean total body weight decreased by 19% at 6 months post bariatric surgery, and the mean BMI was 34.2±4 and 32.5±3.7 kg/m 2 at 6 and 12 months, respectively. Bariatric surgery was strongly associated with subsequent kidney transplantation (HR=8.39 [95% CI 1.71 to 41.19]; P =0.009). Conclusions A conservative weight-loss approach involving multidisciplinary consultation was ineffective in most kidney transplant candidates with diabetes, suggesting that a more proactive approach is needed.