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Abstract：
OBJECTIVE: 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.
METHODS: Cross-sectional, multicentre study.
METHODS: 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.
METHODS: A total of 954 patients admitted with suspected infection were included in the study.
METHODS: 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 (<3.5×109/L or >8.8×109/L) and neutrophils (>7.5×109/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%).
CONCLUSIONS: 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.
BACKGROUND: NCT04681963.
METHODS: Cross-sectional, multicentre study.
METHODS: 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.
METHODS: A total of 954 patients admitted with suspected infection were included in the study.
METHODS: 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 (<3.5×109/L or >8.8×109/L) and neutrophils (>7.5×109/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%).
CONCLUSIONS: 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.
BACKGROUND: NCT04681963.
摘要：
目的：本研究旨在描述成人疑似急性社区获得性肺炎（CAP）住院的临床特征，评估他们对CAP的预测性能，并将模型的性能与医生的初始评估进行比较。
方法：横截面，多中心研究。
方法：数据来源于急诊科感染性疾病研究，前瞻性地从患者访谈和医疗记录中收集。该研究包括四个丹麦医疗急诊科（ED），于2021年3月1日至2022年2月28日进行。
方法：本研究共纳入954例疑似感染患者。
方法：主要结果是由专家小组评估的CAP诊断。
结果：根据专家评估，CAP的患病率为28%。使用最小绝对收缩和选择算子回归确定了13个诊断预测因子，以建立预测模型：呼吸困难，咳痰,咳嗽,普通感冒,萎靡不振,胸痛,呼吸频率（>20次呼吸/分钟），氧饱和度(<96%),异常的胸部听诊，白细胞（<3.5×109/L或>8.8×109/L）和中性粒细胞（>7.5×109/L）。C反应蛋白(<20mg/L)和没有CAP的先前事件对最终模型有负贡献。预测因子对CAP具有良好的预测性能，接受者-操作者特征曲线（AUC）下的面积为0.85（CI0.77至0.92）。然而,ED医生的初步诊断表现更好，AUC为0.86（CI84%至89%）。
结论：典型的呼吸道症状结合异常的生命体征和升高的感染生物标志物是ED入院时CAP的预测因子。在我们的设置中，预测模型的临床价值值得怀疑，因为它没有超过临床医生的评估。需要进一步的研究，增加新的诊断工具，并使用成像或血清学标志物，以改善模型，这将有助于诊断CAP在ED设置更准确。
背景：NCT04681963。
方法：横截面，多中心研究。
方法：数据来源于急诊科感染性疾病研究，前瞻性地从患者访谈和医疗记录中收集。该研究包括四个丹麦医疗急诊科（ED），于2021年3月1日至2022年2月28日进行。
方法：本研究共纳入954例疑似感染患者。
方法：主要结果是由专家小组评估的CAP诊断。
结果：根据专家评估，CAP的患病率为28%。使用最小绝对收缩和选择算子回归确定了13个诊断预测因子，以建立预测模型：呼吸困难，咳痰,咳嗽,普通感冒,萎靡不振,胸痛,呼吸频率（>20次呼吸/分钟），氧饱和度(<96%),异常的胸部听诊，白细胞（<3.5×109/L或>8.8×109/L）和中性粒细胞（>7.5×109/L）。C反应蛋白(<20mg/L)和没有CAP的先前事件对最终模型有负贡献。预测因子对CAP具有良好的预测性能，接受者-操作者特征曲线（AUC）下的面积为0.85（CI0.77至0.92）。然而,ED医生的初步诊断表现更好，AUC为0.86（CI84%至89%）。
结论：典型的呼吸道症状结合异常的生命体征和升高的感染生物标志物是ED入院时CAP的预测因子。在我们的设置中，预测模型的临床价值值得怀疑，因为它没有超过临床医生的评估。需要进一步的研究，增加新的诊断工具，并使用成像或血清学标志物，以改善模型，这将有助于诊断CAP在ED设置更准确。
背景：NCT04681963。
