Chinese PLA Institute for Disease Control and Prevention, Beijing, China.
School of Public Health, Peking University, Beijing, China.
Sci Rep. 2017 Nov 21;7(1):15933. doi: 10.1038/s41598-017-15765-z.
Although belonging to one of the most common type of nosocomial infection, there was currently no simple prediction model for lower respiratory tract infections (LRTIs). This study aims to develop a risk index based system for predicting nosocomial LRTIs based on data from a large point-prevalence survey. Among the 49328 patients included, the prevalence of nosocomial LRTIs was 1.70% (95% confidence interval [CI], 1.64% to 1.76%). The areas under the receiver operating characteristic (ROC) curve for logistic regression and fisher discriminant analysis were 0.907 (95% CI, 0.897 to 0.917) and 0.902 (95% CI, 0.892 to 0.912), respectively. The constructed risk index based system also displayed excellent discrimination (area under the ROC curve: 0.905 [95% CI, 0.895 to 0.915]) to identify LRTI in internal validation. Six risk levels were generated according to the risk score distribution of study population, ranging from 0 to 5, the corresponding prevalence of nosocomial LRTIs were 0.00%, 0.39%, 3.86%, 12.38%, 28.79% and 44.83%, respectively. The sensitivity and specificity of prediction were 0.87 and 0.79, respectively, when the best cut-off point of risk score was set to 14. Our study suggested that this newly constructed risk index based system might be applied to boost more rational infection control programs in clinical settings.
虽然属于最常见的医院感染类型之一,但目前尚无用于下呼吸道感染(LRTIs)的简单预测模型。本研究旨在基于大规模患病率调查数据,建立基于风险指数的预测医院获得性 LRTIs 的模型。在纳入的 49328 例患者中,医院获得性 LRTIs 的患病率为 1.70%(95%置信区间 [CI],1.64%至 1.76%)。逻辑回归和 Fisher 判别分析的受试者工作特征曲线下面积分别为 0.907(95%CI,0.897 至 0.917)和 0.902(95%CI,0.892 至 0.912)。所构建的基于风险指数的系统在内部验证中也显示出良好的鉴别能力(ROC 曲线下面积:0.905[95%CI,0.895 至 0.915]),可识别 LRTI。根据研究人群的风险评分分布,共分为 6 个风险等级,范围为 0 至 5,相应的医院获得性 LRTIs 患病率分别为 0.00%、0.39%、3.86%、12.38%、28.79%和 44.83%。当最佳风险评分截断值设定为 14 时,预测的灵敏度和特异性分别为 0.87 和 0.79。本研究表明,该新构建的基于风险指数的系统可能有助于在临床实践中制定更合理的感染控制方案。