Xu Jianping, Ge Yipeng, Hu Shengshou, Song Yunhu, Sun Hansong, Liu Ping
Cardiovascular Institute and Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Bei Jing, China.
J Heart Valve Dis. 2007 Mar;16(2):109-15.
The study aim was to construct a simple model (the Fuwai risk score) to predict prolonged intensive care unit (ICU) stay after surgery to treat acquired heart valve disease.
Data were collected retrospectively from 2,218 consecutive patients who underwent surgery for acquired heart valve disease. Prolonged ICU stay was defined as > or =5 days. A simple logistic score was calculated using the logistic coefficient, and the additive score by odds ratio. The Fuwai risk score, EuroSCORE and Parsonnet score were applied to predict a prolonged ICU stay and mortality. A C statistic (receiver operating characteristic curve) was used to test discrimination of the models. Calibration was assessed with a Hosmer-Lemeshow goodness-of-fit statistic.
The simple logistic model of the Fuwai risk score showed very good discriminatory ability (C statistic 0.76) and calibration (Hosmer-Lemeshow, p = 0.25) in predicting prolonged ICU stay, while the additive algorithm had good discriminatory ability (C statistic 0.75) but poor calibration (p <0.001). The additive algorithm greatly underestimated the risk for high-risk patients. The Fuwai risk score showed good discriminatory ability, but poor calibration in predicting mortality. Neither the EuroSCORE nor Parsonnet score was superior to the Fuwai risk score.
The logistic algorithm of the Fuwai risk score is a simple, objective, convenient and accurate scoring system which may be used to predict prolonged ICU stay after surgery to treat acquired heart valve disease.
本研究旨在构建一个简单模型（阜外风险评分），以预测后天性心脏瓣膜病手术后重症监护病房（ICU）的延长住院时间。
回顾性收集2218例连续接受后天性心脏瓣膜病手术患者的数据。ICU延长住院时间定义为≥5天。使用逻辑系数计算简单逻辑评分，并通过比值比计算相加评分。应用阜外风险评分、欧洲心脏手术风险评估系统（EuroSCORE）和Parsonnet评分来预测ICU延长住院时间和死亡率。使用C统计量（受试者工作特征曲线）来检验模型的辨别能力。用Hosmer-Lemeshow拟合优度统计量评估校准情况。
阜外风险评分的简单逻辑模型在预测ICU延长住院时间方面显示出非常好的辨别能力（C统计量0.76）和校准情况（Hosmer-Lemeshow，p = 0.25），而相加算法具有良好的辨别能力（C统计量0.75）但校准情况较差（p <0.001）。相加算法大大低估了高危患者的风险。阜外风险评分在预测死亡率方面显示出良好的辨别能力，但校准情况较差。EuroSCORE和Parsonnet评分均不优于阜外风险评分。
阜外风险评分的逻辑算法是一种简单、客观、便捷且准确的评分系统，可用于预测后天性心脏瓣膜病手术后ICU的延长住院时间。
