Artigo Acesso aberto Revisado por pares

Characterizing COVID-19: A chief complaint based approach

2020; Elsevier BV; Volume: 45; Linguagem: Inglês

10.1016/j.ajem.2020.09.019

ISSN

1532-8171

Autores

Rimma Perotte, Gregory Sugalski, Joseph P. Underwood, Michael Ullo,

Tópico(s)

Emergency and Acute Care Studies

Resumo

The COVID-19 pandemic has inundated emergency departments with patients exhibiting a wide array of symptomatology and clinical manifestations. We aim to evaluate the chief complaints of patients presenting to our ED with either suspected or confirmed COVID-19 to better understand the clinical presentation of this pandemic.This study was a retrospective computational analysis that investigated the chief complaints of all confirmed and suspected COVID-19 cases presenting to our adult ED (patients aged 22 and older) using a variety of data mining methods. Our study employed descriptive statistics to analyze the set of complaints that are most common, hierarchical clustering analysis to provide a nuanced way of identifying complaints that co-occur, and hypothesis testing identify complaint differences among age differences.A quantitative analysis of 5015 ED visits of COVID-suspected patients (1483 confirmed COVID-positive patients) identified 209 unique chief complaints. Of the 209 chief complaints, fever and shortness of breath were the most prevalent initial presenting symptoms. In the subset of COVID-19 confirmed positive cases, we discovered seven distinct clusters of presenting complaints. Patients over 65 years of age were more likely to present with weakness and altered mental status.Our research highlights an important aspect of the evaluation and management of COVID-19 patients in the emergency department. Our study identified most common chief complaints, chief complaints differences across age groups, and 7 distinct groups of COVID-19 symptoms. This large-scale effort to classify the most commonly reported symptoms in ED patients provides public health officials and providers with data for identifying COVID-19 cases.

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