• Wen Q Li, Yi Chen, Tie J Liu, Bao Q Xie, Ai S Fu, Li Q Li, Yan L Ge, Pei Min, Yang Lu, Yang Liu, Ye Sun, Lin L Hou, Qin Jing, Hai F Zhang, and Jia B Zhang.
• Clin Lab. 2020 May 1; 66 (5).

BackgroundCAP is the most common cause of death in infectious diseases in developing countries, while also an important cause of death and morbidity in developed countries. In recent years, CURB-65 (or CRB-65) and pneumonia severity index (PSI) scoring systems have been widely used in the prognosis scoring system of CAP. However, each of them has some shortcomings in predicting ICU admission in CAP patients. The aim of this study is to analyze serum inflammatory biomarkers combined age to established a new prediction model in predicting ICU admission in CAP patients.MethodsThis is a retrospective study. The enrolled CAP patients received serum inflammatory biomarker tests, including procalcitonin (PCT), white blood cell count (WBC), hypersensitive C-reactive protein (hs-CRP), and erythrocyte sedimentation rate (ESR). Body temperature and age were also recorded. The main outcome measures were ICU admission. Univariate analysis and binary logistic regression analysis were used to explore the in-dependent risk factors which could be components of a new predicting model for ICU admission in CAP patients. Receiver operating characteristic curves (ROC) were used to evaluate the sensitivity and specificity of the new model, which consisted of the combination of all independent risk factors in predicting the main outcomes.ResultsInitially, 246 CAP patients were admitted to general wards, 61 of whom were subsequently transferred to ICU (61/246). Age, PCT, WBC, and hs-CRP were independent risk factors for subsequent admission to ICU for CAP patients in general wards. The AUC of the ROC curve of new prediction model (the joint model consists of age, PCT, WBC, and hs-CRP) was 0.93 (95% CI 0.85 - 0.96), the sensitivity and specificity were 85.2% and 88.1%, respectively.ConclusionsSerum inflammatory biomarkers combined age have high specificity and sensitivity in predicting ICU admission in adult CAP patients.

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