COVID-19 Smart Diagnosis in the Emergency Department: all-in in Practice

Dimitra S Mouliou1,2, Ioannis Pantazopoulos1,2, Konstantinos I Gourgoulianis2

  • 1Department of Emergency Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, Larissa, Greece.

Insights

Accurate diagnosis of Coronavirus Disease 19 (COVID-19) is challenging due to varied symptoms and test results. This review proposes diagnostic algorithms for precise and timely identification of SARS-CoV-2 infections.

Area of Science:

  • Infectious Diseases
  • Diagnostic Medicine
  • Public Health

Background:

  • Coronavirus Disease 19 (COVID-19) diagnosis presents significant challenges in emergency departments and senior care facilities.
  • Ambiguous clinical presentations, diverse radiologic and laboratory findings, and unreliable test results contribute to misdiagnoses, particularly in critical cases.
  • Difficulties in diagnosing COVID-19 impact emergency department safety and physician responsibility.

Purpose of the Study:

  • To provide a comprehensive review of diagnostic information for SARS-CoV-2.
  • To summarize medical history, clinical examination, radiology, and laboratory data pertinent to COVID-19 diagnosis.
  • To propose diagnostic algorithms for precise and rapid COVID-19 identification.

Main Methods:

  • Systematic literature review of studies published until December 2021.
  • Data sourced from PubMed, Science Direct, and EMBASE databases.
  • Synthesis of information on general COVID-19 diagnostic criteria.

Main Results:

  • COVID-19 diagnosis is often ambiguous, requiring careful correlation of multiple data points.
  • Effective diagnosis necessitates integrating medical history, physical examination, and extrapulmonary findings.
  • Laboratory and radiologic data are crucial but must be interpreted alongside clinical context.

Conclusions:

  • Accurate COVID-19 diagnosis requires a multifaceted approach.
  • Physicians must correlate diverse clinical, laboratory, and radiologic information for prompt diagnosis.
  • Proposed algorithms aim to enhance diagnostic precision and efficiency in managing suspected COVID-19 cases.
Abstract