Abstract
OBJECTIVES: This study aimed to describe the clinical characteristics of adults with suspected acute community-acquired pneumonia (CAP) on hospitalisation, evaluate their prediction performance for CAP and compare the performance of the model to the initial assessment of the physician. DESIGN: Cross-sectional, multicentre study. SETTING: The data originated from the INfectious DisEases in Emergency Departments study and were collected prospectively from patient interviews and medical records. The study included four Danish medical emergency departments (EDs) and was conducted between 1 March 2021 and 28 February 2022. PARTICIPANTS: A total of 954 patients admitted with suspected infection were included in the study. PRIMARY AND SECONDARY OUTCOME: The primary outcome was CAP diagnosis assessed by an expert panel. RESULTS: According to expert evaluation, CAP had a 28% prevalence. 13 diagnostic predictors were identified using least absolute shrinkage and selection operator regression to build the prediction model: dyspnoea, expectoration, cough, common cold, malaise, chest pain, respiratory rate (>20 breaths/min), oxygen saturation (<96%), abnormal chest auscultation, leucocytes (<3.5×10(9)/L or >8.8×10(9)/L) and neutrophils (>7.5×10(9)/L). C reactive protein (<20 mg/L) and having no previous event of CAP contributed negatively to the final model. The predictors yielded good prediction performance for CAP with an area under the receiver-operator characteristic curve (AUC) of 0.85 (CI 0.77 to 0.92). However, the initial diagnosis made by the ED physician performed better, with an AUC of 0.86 (CI 84% to 89%). CONCLUSION: Typical respiratory symptoms combined with abnormal vital signs and elevated infection biomarkers were predictors for CAP on admission to an ED. The clinical value of the prediction model is questionable in our setting as it does not outperform the clinician's assessment. Further studies that add novel diagnostic tools and use imaging or serological markers are needed to improve a model that would help diagnose CAP in an ED setting more accurately. TRIAL REGISTRATION NUMBER: NCT04681963.