Santos Marisa, Braga José Ueleres, Gomes Renato Vieira, Werneck Guilherme L
Department of Epidemiology, Social Medicine Institute, State University of Rio de Janeiro, Rio de Janeiro, Brazil.
Infect Control Hosp Epidemiol. 2007 Apr;28(4):382-8. doi: 10.1086/513119. Epub 2007 Mar 16.
To develop a predictive system for the occurrence of nosocomial pneumonia in patients who had cardiac surgery performed.
Retrospective cohort study.Setting. Two cardiologic tertiary care hospitals in Rio de Janeiro, Brazil.
Between June 2000 and August 2002, there were 1,158 consecutive patients who had complex heart surgery performed. Patients older than 18 years who survived the first 48 postoperative hours were included in the study. The occurrence of pneumonia was diagnosed through active surveillance by an infectious diseases specialist according to the following criteria: the presence of new infiltrate on a radiograph in association with purulent sputum and either fever or leukocytosis until day 10 after cardiac surgery. Predictive models were built on the basis of logistic regression analysis and classification and regression tree (CART) analysis. The original data set was divided randomly into 2 parts, one used to construct the models (ie, "test sample") and the other used for validation (ie, "validation sample").
The area under the receiver-operating characteristic (ROC) curve was 69% for the logistic regression model and 76% for the CART model. Considering a probability greater than 7% to be predictive of pneumonia for both models, sensitivity was higher for the logistic regression models, compared with the CART models (64% vs 56%). However, the CART models had a higher specificity (92% vs 70%) and global accuracy (90% vs 70%) than the logistic regression models. Both models showed good performance, based on the 2-graph ROC, considering that 84.6% and 84.3% of the predictions obtained by regression and CART analyses were regarded as valid.
Although our findings are preliminary, the predictive models we created showed fairly good specificity and fair sensitivity.
开发一种针对接受心脏手术患者发生医院获得性肺炎的预测系统。
回顾性队列研究。地点：巴西里约热内卢的两家心脏科三级护理医院。
在2000年6月至2002年8月期间，有1158例连续接受复杂心脏手术的患者。年龄大于18岁且术后前48小时存活的患者被纳入研究。肺炎的发生由传染病专家通过主动监测根据以下标准诊断：心脏手术后第10天内，胸部X光片出现新的浸润影并伴有脓性痰，以及发热或白细胞增多。基于逻辑回归分析和分类回归树（CART）分析构建预测模型。原始数据集被随机分为两部分，一部分用于构建模型（即“测试样本”），另一部分用于验证（即“验证样本”）。
逻辑回归模型的受试者工作特征（ROC）曲线下面积为69%，CART模型为76%。考虑到两个模型中概率大于7%可预测肺炎，逻辑回归模型的敏感性高于CART模型（64%对56%）。然而，CART模型的特异性（92%对70%）和总体准确性（90%对70%）高于逻辑回归模型。基于双图ROC，两个模型均显示出良好的性能，考虑到回归分析和CART分析获得的预测中分别有84.6%和84.3%被视为有效。
尽管我们的发现是初步的，但我们创建的预测模型显示出相当好的特异性和一定的敏感性。
