Ramgopal Sriram, Ambroggio Lilliam, Lorenz Douglas, Shah Samir S, Ruddy Richard M, Florin Todd A
Division of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Department of Pediatrics, University of Colorado and Sections of Emergency Medicine and Hospital Medicine, Children's Hospital Colorado, Aurora, CO, USA.
ERJ Open Res. 2023 Mar 6;9(2). doi: 10.1183/23120541.00339-2022. eCollection 2023 Mar.
The aim of this study was to evaluate biomarkers to predict radiographic pneumonia among children with suspected lower respiratory tract infections (LRTI).
We performed a single-centre prospective cohort study of children 3 months to 18 years evaluated in the emergency department with signs and symptoms of LRTI. We evaluated the incorporation of four biomarkers (white blood cell count, absolute neutrophil count, C-reactive protein (CRP) and procalcitonin), in isolation and in combination, with a previously developed clinical model (which included focal decreased breath sounds, age and fever duration) for an outcome of radiographic pneumonia using multivariable logistic regression. We evaluated the improvement in performance of each model with the concordance (c-) index.
Of 580 included children, 213 (36.7%) had radiographic pneumonia. In multivariable analysis, all biomarkers were statistically associated with radiographic pneumonia, with CRP having the greatest adjusted odds ratio of 1.79 (95% CI 1.47-2.18). As an isolated predictor, CRP at a cut-off of 3.72 mg·dL demonstrated a sensitivity of 60% and a specificity of 75%. The model incorporating CRP demonstrated improved sensitivity (70.0% 57.7%) and similar specificity (85.3% 88.3%) compared to the clinical model when using a statistically derived cutpoint. In addition, the multivariable CRP model demonstrated the greatest improvement in concordance index (0.780 to 0.812) compared with a model including only clinical variables.
A model consisting of three clinical variables and CRP demonstrated improved performance for the identification of paediatric radiographic pneumonia compared with a model with clinical variables alone.
本研究旨在评估生物标志物，以预测疑似下呼吸道感染（LRTI）儿童的影像学肺炎。
我们对3个月至18岁在急诊科因LRTI症状体征接受评估的儿童进行了一项单中心前瞻性队列研究。我们使用多变量逻辑回归评估了四种生物标志物（白细胞计数、绝对中性粒细胞计数、C反应蛋白（CRP）和降钙素原）单独及联合使用时，与先前开发的临床模型（包括局灶性呼吸音减弱、年龄和发热持续时间）对影像学肺炎结局的预测情况。我们使用一致性（c-）指数评估每个模型性能的改善情况。
纳入的580名儿童中，213名（36.7%）有影像学肺炎。在多变量分析中，所有生物标志物均与影像学肺炎有统计学关联，CRP的调整优势比最大，为1.79（95%CI 1.47-2.18）。作为单独的预测指标，CRP截断值为3.72mg·dL时，敏感性为60%，特异性为75%。与临床模型相比，使用统计学得出的截断点时，纳入CRP的模型敏感性提高（70.0%对57.7%），特异性相似（85.3%对88.3%）。此外，与仅包含临床变量的模型相比，多变量CRP模型的一致性指数改善最大（从0.780至0.812）。
与仅包含临床变量的模型相比，由三个临床变量和CRP组成的模型在识别儿童影像学肺炎方面性能更佳。
