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How the COVID-19 Pandemic Contributed to Diagnostic Bias
Diagnosis bias in the medical field is a recognized entity that can contribute to misdiagnoses and incorrect management. It remains a constant challenge that must be recognized and addressed. Several factors play a role in the formation of preconceptions which influence the physicians’ decision-maki...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10697045/ http://dx.doi.org/10.7759/cureus.48282 |
Sumario: | Diagnosis bias in the medical field is a recognized entity that can contribute to misdiagnoses and incorrect management. It remains a constant challenge that must be recognized and addressed. Several factors play a role in the formation of preconceptions which influence the physicians’ decision-making process. The aim of this paper is to present a case that was misdiagnosed and mistakenly managed due to diagnosis bias during the coronavirus disease 2019 (COVID-19) pandemic. We also suggest two ways to reduce the risk of diagnosis bias. Multi-inflammatory syndrome of children (MIS-C) was described during the COVID-19 pandemic. The rise in the incidence of MIS-C masked the diagnosis of other diseases that present in a similar fashion. In this paper, we describe the case of a seven-year-old girl, who presented in 2020, with acute onset respiratory distress. Her chest images were suggestive of COVID-19 pneumonitis which prompted the physicians to complete the MIS-C workup by performing an echocardiogram. A large aneurysm of the left main artery was seen which led to a preliminary diagnosis of MIS-C. A repeat echocardiography, 48 hours after the initiation of MIS-C treatment, was suggestive of a large coronary fistula complicated by infective endocarditis and multiple septic pulmonary emboli. It can be inferred that the misdiagnosis occurred as a result of availability and premature-closure biases. Efforts to decrease such biases include group decision-making and using checklists during the assessment of a patient. |
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