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From the Triage to the Intermediate Area: A Simple and Fast Model for COVID-19 in the Emergency Department

Author

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  • Erika Poggiali

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Enrico Fabrizi

    (DISES & DSS, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy)

  • Davide Bastoni

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Teresa Iannicelli

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Claudia Galluzzo

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Chiara Canini

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Maria Grazia Cillis

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Davide Giulio Ponzi

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Andrea Magnacavallo

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

  • Andrea Vercelli

    (Emergency Department, “Guglielmo da Saliceto” Hospital, 29121 Piacenza, Italy)

Abstract

Introduction: The early identification of patients with SARS-CoV-2 infection is still a real challenge for emergency departments (ED). First, we aimed to develop a score, based on the use of the lung ultrasonography (LUS), in addition to the pre-triage interview, to correctly address patients; second, we aimed to prove the usefulness of a three-path organization (COVID-19, not-COVID-19 and intermediate) compared to a two-path organization (COVID-19, non-COVID-19). Methods: We retrospectively analysed 292 patients admitted to our ED from 10 April to 15 April 2020, with a definite diagnosis of positivity (93 COVID-19 patients) or negativity (179 not-COVID-19 patients) for SARS-COV-2 infection. Using a logistic regression, we found a set of predictors for infection selected from the pre-triage interview items and the LUS findings, which contribute with a different weight to the final score. Then, we compared the organization of two different pathways. Results: The most informative factors for classifying the patient are known nasopharyngeal swab positivity, close contact with a COVID-19 patient, fever associated with respiratory symptoms, respiratory failure, anosmia or dysgeusia, and the ultrasound criteria of diffuse alveolar interstitial syndrome, absence of B-lines and presence of pleural effusion. Their sensitivity, specificity, accuracy, and AUC-ROC are, respectively, 0.83, 0.81, 0.82 and 0.81. The most significant difference between the two pathways is the percentage of not-COVID-19 patients assigned to the COVID-19 area, that is, 10.6% (19/179) in the three-path organization, and 18.9% (34/179) in the two-path organization ( p = 0.037). Conclusions: Our study suggests the possibility to use a score based on the pre-triage interview and the LUS findings to correctly manage the patients admitted to the ED, and the importance of an intermediate area to limit the spread of SARS-CoV-2 in the ED and, as a consequence, in the hospital.

Suggested Citation

  • Erika Poggiali & Enrico Fabrizi & Davide Bastoni & Teresa Iannicelli & Claudia Galluzzo & Chiara Canini & Maria Grazia Cillis & Davide Giulio Ponzi & Andrea Magnacavallo & Andrea Vercelli, 2022. "From the Triage to the Intermediate Area: A Simple and Fast Model for COVID-19 in the Emergency Department," IJERPH, MDPI, vol. 19(13), pages 1-14, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:8070-:d:853147
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    References listed on IDEAS

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    1. Beniamino Murgante & Giuseppe Borruso & Ginevra Balletto & Paolo Castiglia & Marco Dettori, 2020. "Why Italy First? Health, Geographical and Planning Aspects of the COVID-19 Outbreak," Sustainability, MDPI, vol. 12(12), pages 1-44, June.
    2. Tjur, Tue, 2009. "Coefficients of Determination in Logistic Regression Models—A New Proposal: The Coefficient of Discrimination," The American Statistician, American Statistical Association, vol. 63(4), pages 366-372.
    3. Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
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