Risk stratification and prediction value of procalcitonin and clinical severity scores for community-acquired pneumonia in ED

Published:March 22, 2018DOI:



      Community-acquired pneumonia (CAP) is a common presentation to the emergency department (ED) and has high mortality rates. The aim of our study is to investigate the risk stratification and prognostic prediction value of precalcitonin (PCT) and clinical severity scores on patients with CAP in ED.


      226 consecutive adult patients with CAP admitted in ED of a tertiary teaching hospital were enrolled. Demographic information and clinical parameters including PCT levels were analyzed. CURB65, PSI, SOFA and qSOFA scores were calculated and compared between the severe CAP (SCAP) and non-severe CAP (NSCAP) group or the death and survival group. Receiver-operating characteristic (ROC) curves for 28-day mortality were calculated for each predictor using cut-off values. Logistic regression models and area under the curve (AUC) analysis were performed to compare the performance of predictors.


      Fifty-one patients were classified as SCAP and forty-nine patients died within 28days. There was significant difference between either SCAP and NSCAP group or death and survival group in PCT level and CURB65, PSI, SOFA, qSOFA scores (p < 0.001). The AUCs of the PCT and CURB65, PSI, SOFA and qSOFA in predicting SCAP were 0.875, 0.805, 0.810, 0.852 and 0.724, respectively. PCT is superior in predicting SCAP and the models combining PCT and SOFA demonstrated superior performance to those of PCT or the CAP severity score alone. The AUCs of the PCT and CURB65, PSI, SOFA and qSOFA in predicting 28-day mortality were 0.822, 0.829, 0.813, 0.913 and 0.717, respectively. SOFA achieved the highest AUC and the combination of PCT and SOFA had the highest superiority over other combinations in predicting 28-day mortality.


      Serum PCT is a valuable single predictor for SCAP. SOFA is superior in prediction of 28-day mortality. Combination of PCT and SOFA could improve the performance of single predictors. More further studies with larger sample size are warranted to validate our results.


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