Rana Abbas, Witte Ellen D, Halazun Karim J, Sood Gagan K, Mindikoglu Ayse L, Sussman Norman L, Vierling John M, Kueht Michael L, Galvan Nhu Thao N, Cotton Ronald T, O'Mahony Christine A, Goss John A
Michael E. DeBakey Department of Surgery, Division of Abdominal Transplantation and Division of Hepatobiliary Surgery, Baylor College of Medicine, Houston, TX, USA.
Department of Surgery, Division of Liver Transplantation and Hepatobiliary Surgery, New York-Presbyterian/Weill Cornell Medical Center, New York, NY, USA.
Clin Transplant. 2017 Dec;31(12). doi: 10.1111/ctr.13141. Epub 2017 Nov 13.
An index to predict hospital length of stay after liver transplantation could address unmet clinical needs. Length of stay is an important surrogate for hospital costs and efforts to limit stays can preserve our healthcare resources. Here, we devised a scoring system that predicts hospital length of stay following liver transplantation. We used univariate and multivariate analyses on 73 635 adult liver transplant recipient data and identified independent recipient and donor risk factors for prolonged hospital stay (>30 days). Multiple imputation was used to account for missing variables. We identified 22 factors as significant predictors of prolonged hospital stay, including the most significant risk factors: intensive care unit (ICU) admission (OR 1.75, CI 1.58-1.95) and previous transplant (OR 1.60, CI 1.47-1.75). The length of stay (LOS) index assigns weighted risk points to each significant factor in a scoring system to predict prolonged hospital stay after liver transplantation with a c-statistic of 0.75. The LOS index demonstrated good discrimination across the entire population, dividing the cohort into tertiles, which had odds ratios of 2.25 (CI 2.06-2.46) and 7.90 (7.29-8.56) for prolonged hospital stay (>30 days). The LOS index utilizes 22 significant donor and recipient factors to accurately predict hospital length of stay following liver transplantation. The index further demonstrates the basis for a clear clinical recommendation to mitigate risk of long hospitalization by minimizing cold ischemia time.
一个预测肝移植后住院时间的指标可以满足未被满足的临床需求。住院时间是医院成本的重要替代指标，限制住院时间的努力可以保护我们的医疗资源。在此，我们设计了一个评分系统来预测肝移植后的住院时间。我们对73635例成年肝移植受者的数据进行了单因素和多因素分析，确定了延长住院时间（>30天）的独立受者和供者风险因素。采用多重填补法处理缺失变量。我们确定了22个因素为延长住院时间的显著预测因素，其中最显著的风险因素包括：入住重症监护病房（ICU）（比值比1.75，可信区间1.58 - 1.95）和既往移植（比值比1.60，可信区间1.47 - 1.75）。住院时间（LOS）指数在评分系统中为每个显著因素赋予加权风险点，以预测肝移植后延长的住院时间，c统计量为0.75。LOS指数在整个人口中显示出良好的区分度，将队列分为三个三分位数，延长住院时间（>30天）的比值比分别为2.25（可信区间2.06 - 2.46）和7.90（7.29 - 8.56）。LOS指数利用22个显著的供者和受者因素准确预测肝移植后的住院时间。该指数进一步证明了通过尽量缩短冷缺血时间来降低长期住院风险的明确临床建议的依据。
