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Background: There have been concerns regarding increased perioperative mortality, length of hospital stay, and rates of graft loss in kidney transplant recipients with functional limitations. The application of machine learning consensus clustering approach may provide a novel understanding of unique phenotypes of functionally limited kidney transplant recipients with distinct outcomes in order to identify strategies to improve outcomes. Methods: Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 3205 functionally limited kidney transplant recipients (Karnofsky Performance Scale (KPS) < 40% at transplant) in the OPTN/UNOS database from 2010 to 2019. Each cluster's key characteristics were identified using the standardized mean difference. Posttransplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection were compared among the clusters Results: Consensus cluster analysis identified two distinct clusters that best represented the clinical characteristics of kidney transplant recipients with limited functional status prior to transplant. Cluster 1 patients were older in age and were more likely to receive deceased donor kidney transplant with a higher number of HLA mismatches. In contrast, cluster 2 patients were younger, had shorter dialysis duration, were more likely to be retransplants, and were more likely to receive living donor kidney transplants from HLA mismatched donors. As such, cluster 2 recipients had a higher PRA, less cold ischemia time, and lower proportion of machine-perfused kidneys. Despite having a low KPS, 5-year patient survival was 79.1 and 83.9% for clusters 1 and 2; 5-year death-censored graft survival was 86.9 and 91.9%. Cluster 1 had lower death-censored graft survival and patient survival but higher acute rejection, compared to cluster 2. Conclusion: Our study used an unsupervised machine learning approach to characterize kidney transplant recipients with limited functional status into two clinically distinct clusters with differing posttransplant outcomes. [ABSTRACT FROM AUTHOR]

(1) Background: Virtual reality (VR) technology is a widely used training tool in medical education. The present study aimed to evaluate the effectiveness of VR training of oral hygiene students on providing oral healthcare to disabled elderly persons. (2) Methods: A randomized controlled trial was conducted. In 2021, oral hygiene students were randomly assigned to a VR experimental group (EG; n = 11) and a control group (CG; n = 12). The EG received two-hour, thrice-repeated VR-based training interventions at 2-week, 4-week, and 6-week follow-ups. The CG received no VR-based interventions. Data were collected using a self-administered questionnaire before and immediately after each intervention. We performed generalized estimating equations to compare the responses. (3) Results: The EG exhibited a more significant improvement in oral care-related knowledge, attitude, self-efficacy, and intention at the 6-week follow-up than the CG. The students' intention to assist the elderly in using interdental brushes (β = 0.91), with soft tissue cleaning (β = 0.53), and with oral desensitization (β = 0.53), and to have regular dental visits (β = 0.61) improved significantly at the 6-week follow-up. (4) Conclusions: VR training positively affected students' knowledge, attitude, self-efficacy, and intentions on providing oral healthcare to disabled elderly persons. [ABSTRACT FROM AUTHOR]