• Medicina · Aug 2024

    Predicting Delayed Postoperative Length of Stay Following Robotic Kidney Transplantation: Development and Simulation of Perioperative Risk Factors.

    • Sang-Wook Lee, Kyoung-Sun Kim, Sung-Hoon Kim, and Ji-Yeon Sim.
    • Brain Korea 21 Project, Department of Anesthesiology and Pain Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea.
    • Medicina (Kaunas). 2024 Aug 1; 60 (8).

    AbstractBackground and Objective: Early discharge following robot-assisted kidney transplantation (RAKT) is a cost-effective strategy for reducing healthcare expenses while maintaining favorable short- and long-term prognoses. This study aims to identify predictors of postoperative delayed discharge in RAKT patients and develop a predictive model to enhance clinical outcomes. Materials and Methods: This retrospective study included 146 patients aged 18 years and older who underwent RAKT at a single tertiary medical center from August 2020 to January 2024. Data were collected on demographics, comorbidities, social and medical histories, preoperative labs, surgical information, intraoperative data, and postoperative outcomes. The primary outcome was delayed postoperative discharge (length of hospital stay > 7 days). Risk factors for delayed discharge were identified through univariate and multivariate regression analyses, leading to the development of a risk scoring system, the effectiveness of which was evaluated through receiver operating characteristic curve analysis. Results: 110 patients (74.8%) were discharged within 7 days post-transplant, while 36 (24.7%) remained hospitalized for 8 days or longer. Univariate and multivariate logistic regression analyses identified ABO incompatibility, BUN levels, anesthesia time, and vasodilator use as risk factors for delayed discharge. The RAKT score, incorporating these factors, demonstrated a predictive performance with a C-statistic of 0.789. Conclusions: This study identified risk factors for delayed discharge after RAKT and developed a promising risk scoring system for real-world clinical application, potentially improving postoperative outcome stratification in RAKT recipients.

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