A Scoring System To Predict The Risk Of Nosocomial Invasive Fungal Infections In The Inieiisive Care Unit

Background： Recent years, due to the abuse of broad-spectrum antibiotics,corticosteroids, immunosuppressants and various chemotherapy drugs, more and moreorgan transplantation and patients with acquired immune deficiency syndrome, andother factors, the incidence of nosocomial invasive fungal infections (IFIs) increasedcontinually. ICU patients would be at high risk of IFIs, because the serious conditionand various IFIs risk factors. However, the ICU patients combined with IFIs willaffect the prognosis and reduce the effectiveness. At present, it is hardly for earlydiagnosis and early treatment of invasive fungal infections. Therefore, to explore therisk factors and disease characteristics for IFIs in the ICU patients, and to establish anearly, correct prediction scoring system may be help clinical decision. So this studyuses a variety of known risk factors to establish an IFIs risk scoring system, whichadapt to the status of medical treatment for ICU patients in our country, and to explorethe effectiveness of this system.Objective To analyze its influencing factors of nosocomial invasive fungal infections(IFIs) in the intensive care unit and to develop and assess the performance of ascoring system to predict the risk of IFIs.Methods A total of192IFIs patients and192non-IFIs patients as the control group inthe ICU of five hospitals were included for the study between January,2007andDecember,2011. Variables associated with IFIs were identified by multivariablelogistic regression and used to develop a predictive model. Performance of the scoringsystem was assessed by receiver-operating characteristics (ROC) curve analysis andverified on a test dataset.Results Seven variables were identified as the most important independent riskfactors for IFIs and were used to construct a scoring system: age(>65year), solid tumor, chronic renal failure, broad-spectrum antibiotic use, central venous catheteruse, multiple-admission in ICU，and Acute Physiology and Chronic Health EvaluationII (APACHE II) score. A scoring system was computed by the logistic equation. Acutoff point of0.454provided the greatest sensitivity and specificity. The scoringindex had good discriminative power, the area under the receiver operatingcharacteristic curve was0.856(95%CI,0.811?0.901). When the scoring system wasused in another128ICU patients, the total coincidence ratio was76.6%betweenpredicted 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 clinicalpractice. Future validation of this scoring system is necessary.