Suppr超能文献

心脏手术后严重感染的临床预测因素。

Clinical predictors of major infections after cardiac surgery.

作者信息

Fowler Vance G, O'Brien Sean M, Muhlbaier Lawrence H, Corey G Ralph, Ferguson T Bruce, Peterson Eric D

机构信息

Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA.

出版信息

Circulation. 2005 Aug 30;112(9 Suppl):I358-65. doi: 10.1161/CIRCULATIONAHA.104.525790.

Abstract

BACKGROUND

Major infections are infrequent but important complications of cardiac surgery. Predicting their occurrence is essential for future prevention. The objective of the current investigation was to create and validate a bedside scoring system to estimate patient risk for major infection (mediastinitis, thoracotomy or vein harvest site infection, or septicemia) after coronary artery bypass grafting.

METHODS AND RESULTS

Using the Society of Thoracic Surgeons National Cardiac Database, we analyzed 331 429 coronary artery bypass grafting cases from January 1, 2002, to December 31, 2003, to identify risk factors for major infection. Using logistic regression, 2 models were generated and validated using split-sample validation: (1) One limited to preoperative characteristics (preop model) and (2) one model including both preoperative and intraoperative characteristics (combined model). Major infection occurred in 11 636 patients (3.51%) (25.1% mediastinitis, 32.6% saphenous harvest site, 35.0% septicemia, 0.5% thoracotomy, 6.8% multiple sites). Patients with major infection had significantly higher mortality (17.3% versus 3.0%, P<0.0001) and postoperative length of stay >14 days (47.0% versus 5.9%, P<0.0001) than patients without major infection. Both the preop model (c-index 0.697) and combined model (c-index: 0.708) successfully discriminated between high- and low-risk patients. A simplified risk scoring system of 12 variables accurately predicted risk for major infection.

CONCLUSIONS

We identified and validated a model that can identify patients undergoing cardiac surgery who are at high risk for major infection. These high-risk patients may be targeted for perioperative intervention strategies to reduce rates of major infection.

摘要

背景

严重感染是心脏手术中不常见但重要的并发症。预测其发生对于未来的预防至关重要。本研究的目的是创建并验证一种床旁评分系统,以评估冠状动脉旁路移植术后患者发生严重感染(纵隔炎、开胸或静脉取血管部位感染或败血症)的风险。

方法与结果

利用胸外科医师协会国家心脏数据库,我们分析了2002年1月1日至2003年12月31日期间的331429例冠状动脉旁路移植病例,以确定严重感染的危险因素。使用逻辑回归生成了2个模型,并通过拆分样本验证进行了验证:(1)一个仅限于术前特征(术前模型),(2)一个模型包括术前和术中特征(联合模型)。11636例患者(3.51%)发生了严重感染(25.1%为纵隔炎,32.6%为大隐静脉取血管部位感染,35.0%为败血症,0.5%为开胸感染,6.8%为多部位感染)。发生严重感染的患者的死亡率(17.3%对3.0%,P<0.0001)和术后住院时间>14天的比例(47.0%对5.9%,P<0.0001)显著高于未发生严重感染的患者。术前模型(c指数0.697)和联合模型(c指数:0.708)均成功区分了高风险和低风险患者。一个由12个变量组成的简化风险评分系统准确地预测了严重感染的风险。

结论

我们识别并验证了一个模型,该模型可以识别接受心脏手术且发生严重感染风险高的患者。这些高风险患者可能是围手术期干预策略的目标人群,以降低严重感染的发生率。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验