Open AccessCombination of procalcitonin and C‐reactive protein levels in the early diagnosis of bacterial co‐infections in children with H1N1 influenza
Author(s) -
Li Zhihao,
He Liya,
Li Shuhua,
He Waner,
Zha Caihui,
Ou Wanxing,
Hou Qiaozhen,
Wang Weiying,
Sun Xin,
Liang Huiying
Publication year - 2019
Publication title -
influenza and other respiratory viruses
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.743
H-Index - 57
eISSN - 1750-2659
pISSN - 1750-2640
DOI - 10.1111/irv.12621
Subject(s) - procalcitonin , medicine , c reactive protein , logistic regression , white blood cell , gastroenterology , h1n1 influenza , biomarker , immunology , sepsis , covid-19 , inflammation , disease , biology , biochemistry , infectious disease (medical specialty)
Objective This study evaluated the diagnostic value of measuring the levels of procalcitonin (PCT) and C‐reactive protein (CRP) to differentiate children co‐infected with H1N1 influenza and bacteria from children infected with H1N1 influenza alone. Methods Consecutive patients (children aged < 5 years) with laboratory‐confirmed H1N1 influenza who were hospitalized or received outpatient care from a tertiary‐care hospital in Canton, China, between January 1, 2012, and September 1, 2017, were included in the present study. Laboratory results, including serum PCT and CRP levels, white blood cell (WBC) counts, and bacterial cultures, were analyzed. The predictive value of the combination of biomarkers versus any of the biomarkers alone for diagnosing bacterial co‐infections was evaluated using logistic regression analyses. Results Significantly higher PCT (1.46 vs 0.21 ng/mL, P < 0.001) and CRP (19.20 vs 5.10 mg/dL, P < 0.001) levels were detected in the bacterial co‐infection group than in the H1N1 infection‐alone group. Using PCT or CRP levels alone, the areas under the curves (AUCs) for predicting bacterial co‐infections were 0.801 (95% CI, 0.772‐0.855) and 0.762 (95% CI, 0.722‐0.803), respectively. Using a combination of PCT and CRP, the logistic regression‐based model, Logit( P ) = −1.912 + 0.546 PCT + 0.087 CRP, showed significantly greater accuracy (AUC: 0.893, 95% CI: 0.842‐0.934) than did the other three biomarkers. Conclusions The combination of PCT and CRP levels could provide a useful method of distinguishing bacterial co‐infections from an H1N1 influenza infection alone in children during the early disease phase. After further validation, the flexible model derived here could assist clinicians in decision‐making processes.