Mejia, Mateo Velasquez

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.

Key Points Morphometry allows for a more prognostic multidimensional quantification of interstitial fibrosis and tubular atrophy (IFTA) in kidneys than does visual inspection. The density of IFTA foci is determined by dividing the number of contiguous IFTA patches in the kidney cortex by the area of cortex. Higher density of IFTA foci significantly predicted renal allograft failure beyond %IFTA and other biopsy and clinical characteristics. Background Contraction of interstitial fibrosis and tubular atrophy (IFTA) may cause %IFTA to under-represent the severity of nephron loss. Higher density of IFTA foci is an important predictor of progressive CKD in native kidneys independent of %IFTA. Methods We studied kidney transplant recipients transplanted between 2000 and 2013 who had a 5-year surveillance kidney biopsy and subsequent follow-up. Banff ci score (interstitial fibrosis) was obtained from the pathology reports. After digitizing the biopsies, we traced cortex area and each distinct IFTA focus on a single trichrome-stained section. Percent IFTA area and IFTA foci density (count of IFTA foci/cortex area) were calculated. Cox models assessed the risk of death-censored graft failure after the 5-year biopsy with Banff ci score, morphometric %IFTA, and IFTA foci density. Results There were 58 death-censored allograft failures among 835 kidney recipients during the 5 years of follow-up. Biopsies from grafts that failed had higher mean Banff ci score (1.5 versus 0.7, P < 0.0001), %IFTA (22.6% versus 7.0%, P < 0.0001), and IFTA foci density (1.3/mm 2 versus 0.4/mm 2 , P < 0.0001). After adjusting for other Banff scores or clinical variables, Banff ci did not correlate with allograft failure, but both higher %IFTA (hazard ratio = 1.56, P < 0.0001) and higher IFTA foci density (hazard ratio = 2.34, P < 0.0001) did. All but four allograft failures by 10 years had biopsies in the top quartile of either %IFTA or IFTA foci density at 5 years. A model using just these two morphometric measures without clinical characteristics resulted in a c-statistic of 0.891 with respect to allograft failure. Conclusions Morphometric characterization of IFTA foci density is a strong predictor of death-censored allograft failure not captured in current Banff classification for grading of kidney fibrosis.

Background. Mesangial expansion (ME) is an understudied histologic lesion in renal allografts. The current Banff mm score is not reproducible and may miss important ME features. The study aimed to improve the quantification of ME using morphometry, assess changes over time, and determine its association with allograft loss. Methods. We studied ME in 1-y and 5-y surveillance biopsies in 835 kidney transplants performed between January 2000 and December 2013. ME was assessed using the Banff mm score by a central pathologist and by morphometry. We derived 3 different morphometric measures: (1) %ME mm (%glomeruli with ME in ≥2 lobules, like Banff mm); (2) %MEany (%glomeruli with any ME lesion); and (3) %ME area (sum of all ME areas/all glomerular tuft areas). Unadjusted and adjusted Cox models assessed the risk of death-censored allograft loss. Results. From 1- to 5-y biopsies, the mean Banff mm score increased from 0.18 to 0.34, whereas %ME mm increased from 2.5% to 13.3%. Banff mm score had modest correlations with morphometric ME measures. Moderate-severe %ME mm was present in 20.1% of 5-y biopsies, whereas only 6.6% of Banff mm scores were. In general, higher ME on both 1- and 5-y biopsies was associated with a deceased donor, older recipient age, recipient diabetes/obesity (present in >50% of severely affected biopsies), higher hemoglobin A1c at 5 y posttransplant, and recurrent kidney disease. Higher ME on 5-y biopsies was associated with delayed graft function. A higher Banff mm score at 1-y biopsy and morphometry ME measures at 5-y biopsy were associated with rejection during the first year posttransplant. Morphometric ME measures were associated with allograft loss independent of Banff scores and all clinical characteristics, including kidney function and recurrent disease. The model with %MEany had the highest c-statistic (0.872). Conclusions. Banff mm score underestimates the pervasiveness of ME in 5-y biopsies. ME is common and associated with alloimmune and nonalloimmune causes of graft loss.