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):1255. doi: 10.3390/medicina60081255.
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. 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. 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. 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.
机器人辅助肾移植(RAKT)术后早期出院是降低医疗费用的一种具有成本效益的策略,同时保持良好的短期和长期预后。本研究旨在确定 RAKT 患者术后延迟出院的预测因素,并开发预测模型以改善临床结局。 这项回顾性研究纳入了 2020 年 8 月至 2024 年 1 月在一家三级医学中心接受 RAKT 的 146 名年龄在 18 岁及以上的患者。收集了人口统计学、合并症、社会和医疗史、术前实验室检查、手术信息、术中数据和术后结局等数据。主要结局是术后延迟出院(住院时间>7 天)。通过单因素和多因素回归分析确定延迟出院的危险因素,进而开发风险评分系统,并通过接受者操作特征曲线分析评估其有效性。 110 名患者(74.8%)在移植后 7 天内出院,36 名患者(24.7%)住院时间为 8 天或更长。单因素和多因素逻辑回归分析确定 ABO 不相容、BUN 水平、麻醉时间和血管扩张剂使用是延迟出院的危险因素。包含这些因素的 RAKT 评分具有预测性能,C 统计量为 0.789。 本研究确定了 RAKT 后延迟出院的危险因素,并开发了一种有前途的风险评分系统,用于真实世界的临床应用,可能改善 RAKT 受者的术后结局分层。