ICU患者侵袭性真菌感染风险评分系统的建立和评价

摘要

Objective To analyze the influencing factors of nosocomial invasive fungal infections ( IFIs ) in the intensive care unit and to develop and assess the performance of a scoring system to predict the risk of IFIs. Methods A total of 192 IFIs patients and 192 non - IFIs patients as the control group in the ICU of five hospitals were included for the study between January 2007 and December 2011. Variables associated with IFIs were identified by multivariable logistic regression and used to develop a predictive model. Performance of the scoring system was assessed by receiver - operating characteristics ( ROC ) curve analysis and verified on a test dataset. Results Seven variables were identified as the most important independent risk factors for IFIs and were used to construct a scoring system: age( > 65 year ), solid tumor, chronic renal failure, broad - spectrum antibiotic use, central venous catheter use, multiple - admission in ICU, and Acute Physi-rnology and Chronic Health Evaluation II ( APACHE II ) score. A scoring system was computed by the logistic equation. A cutoff point of 0.454 provided the greatest sensitivity and specificity. The scoring index had good discriminative power, and the area under the receiver operating characteristic curve was 0. 856( 95% CI, 0. 811～0. 901 ). When the scoring system was used in another 128 ICU patients, the total coincidence ratio was 76. 6% between predicted and actual condition. Conclusion Our scoring system can give an early and reliable prognosis of IFIs, which can be used as a guide to perform early intervention and treatment in clinical practice. Future validation of this scoring system is necessary.%目的 了解ICU患者侵袭性真菌感染(IFIs)的危险因素,并建立预测IFIs发生风险的评分系统.方法 选择2007年1月至2011年12月在安徽省5家三级甲等医院(ICU)明确诊断为IFIs的患者,共计192例,并选择192例同期住院的非IFIs患者作为对照组.利用单因素分析进行筛选,然后使用多因素Logistic回归分析发现IFIs的独立危险因素并建立评分系统,采用ROC曲线评价该评分系统.结果 多因素Logistic回归分析结果显示,IFIs独立的危险因素有:年龄(>65岁),慢性肾功能不全,实体肿瘤,使用广谱抗生素,中心静脉导管,多次入住ICU,APACHE II评分.评分系统ROC曲线下面积为0.856(95%CI,0.811～0.901),应用评分系统在测试样本中进行评估,其预测IFIs与实际相符率为76.6%.结论 该评分系统能较准确地预测IFIs的发生,可以为IFIs预警并进行早期干预和治疗提供依据.