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Application of the Pediatric Early Warning Score in predicting the severity of influenza
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  • Yuanlin Zhou,
  • Li Liu,
  • Jin Shang,
  • Xiaobin Wen,
  • Xiaojia Shen,
  • Yan Liu,
  • Lin Tang,
  • Qian Li,
  • Jingqiu Gan
Yuanlin Zhou
Chengdu Second People's Hospital

Corresponding Author:[email protected]

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Li Liu
Chengdu Second People's Hospital
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Jin Shang
Sichuan Academy of Medical Sciences and Sichuan People's Hospital
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Xiaobin Wen
Chengdu Second People's Hospital
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Xiaojia Shen
Chengdu Second People's Hospital
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Yan Liu
Chengdu Second People's Hospital
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Lin Tang
Chengdu Second People's Hospital
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Qian Li
Chengdu Second People's Hospital
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Jingqiu Gan
Chengdu Second People's Hospital
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Abstract

Objectives: Influenza is a rapidly spreading acute respiratory infectious disease. This disease has a high prevalence and morbidity. Patients with critical influenza require timely admission. Identifying patients with critical influenza and ensuring early admission for such patients is important. The pediatric early warning score (PEWS) is useful for the timely recognition of critical illnesses. However, evidence supporting the efficacy of the PEWS in assessing critical influenza is limited. This study aimed to explore the usefulness of the PEWS as a predictive tool for critical influenza. Methods: One hundred pediatric patients with influenza were included into this study. Their PEWS scores were measured at the emergency department. Unconditional logistic regression was conducted to investigate the association of each parameter between the mildand critical influenza groups. The PEWS and parameters were compared. Receiver operating characteristic (ROC) curves were analyzed. Results: The difference in the PEWS and mean corpuscular hemoglobin (MCH) levels were significantly different between the two groups. Combinations of the PEWS and MCH achieved an R score of 0.501; the square of the R score was 0.2506, and the area under the curve was 0.791 with a cut-off value of 0.4118. The score of the predictive model made up of the PEWS and MCH was: 2.035+0.18*PEWS-0.073*MCH. When the score was higher than 0.4118, the patients tended to have critical influenza. Conclusion: Our predictive model is helpful in the identification of patients with critical influenza; this will help in ensuring timely admission of such cases, and thereby improving their outcomes.