Ghotkar Sanjay V, Grayson Antony D, Fabri Brian M, Dihmis Walid C, Pullan D Mark
Department of Cardiothoracic Surgery, The Cardiothoracic Centre, Liverpool, UK.
J Cardiothorac Surg. 2006 May 31;1:14. doi: 10.1186/1749-8090-1-14.
Patients who have prolonged stay in intensive care unit (ICU) are associated with adverse outcomes. Such patients have cost implications and can lead to shortage of ICU beds. We aimed to develop a preoperative risk prediction tool for prolonged ICU stay following coronary artery surgery (CABG).
5,186 patients who underwent CABG between 1st April 1997 and 31st March 2002 were analysed in a development dataset. Logistic regression was used with forward stepwise technique to identify preoperative risk factors for prolonged ICU stay; defined as patients staying longer than 3 days on ICU. Variables examined included presentation history, co-morbidities, catheter and demographic details. The use of cardiopulmonary bypass (CPB) was also recorded. The prediction tool was tested on validation dataset (1197 CABG patients between 1st April 2003 and 31st March 2004). The area under the receiver operating characteristic (ROC) curve was calculated to assess the performance of the prediction tool.
475 (9.2%) patients had a prolonged ICU stay in the development dataset. Variables identified as risk factors for a prolonged ICU stay included renal dysfunction, unstable angina, poor ejection fraction, peripheral vascular disease, obesity, increasing age, smoking, diabetes, priority, hypercholesterolaemia, hypertension, and use of CPB. In the validation dataset, 8.1% patients had a prolonged ICU stay compared to 8.7% expected. The ROC curve for the development and validation datasets was 0.72 and 0.74 respectively.
A prediction tool has been developed which is reliable and valid. The tool is being piloted at our institution to aid resource management.
在重症监护病房（ICU）停留时间延长的患者与不良预后相关。这类患者会产生成本问题，并可能导致ICU床位短缺。我们旨在开发一种用于预测冠状动脉搭桥手术（CABG）后ICU停留时间延长的术前风险预测工具。
对1997年4月1日至2002年3月31日期间接受CABG的5186例患者进行了开发数据集分析。采用逻辑回归和向前逐步技术来确定ICU停留时间延长的术前风险因素；定义为在ICU停留超过3天的患者。所检查的变量包括病史、合并症、导管及人口统计学细节。还记录了体外循环（CPB）的使用情况。该预测工具在验证数据集（2003年4月1日至2004年3月31日期间的1197例CABG患者）上进行了测试。计算受试者工作特征（ROC）曲线下面积以评估预测工具的性能。
在开发数据集中，475例（9.2%）患者的ICU停留时间延长。被确定为ICU停留时间延长风险因素的变量包括肾功能不全、不稳定型心绞痛、射血分数低、外周血管疾病、肥胖、年龄增加、吸烟、糖尿病、优先级、高胆固醇血症、高血压以及CPB的使用。在验证数据集中，8.1%的患者ICU停留时间延长，而预期为8.7%。开发数据集和验证数据集的ROC曲线分别为0.72和0.74。
已开发出一种可靠且有效的预测工具。该工具正在我们机构进行试点，以辅助资源管理。
