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Avoiding bias in self-controlled case series studies of coronavirus disease 2019.
Fonseca-Rodríguez, Osvaldo; Fors Connolly, Anne-Marie; Katsoularis, Ioannis; Lindmark, Krister; Farrington, Paddy.
  • Fonseca-Rodríguez O; Department of Clinical Microbiology, Umeå University, Umeå, Sweden.
  • Fors Connolly AM; Department of Clinical Microbiology, Umeå University, Umeå, Sweden.
  • Katsoularis I; Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
  • Lindmark K; Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
  • Farrington P; School of Mathematics and Statistics, The Open University, Milton Keynes, UK.
Stat Med ; 40(27): 6197-6208, 2021 11 30.
Article in English | MEDLINE | ID: covidwho-1380411
ABSTRACT
Many studies, including self-controlled case series (SCCS) studies, are being undertaken to quantify the risks of complications following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). One such SCCS study, based on all COVID-19 cases arising in Sweden over an 8-month period, has shown that SARS-CoV-2 infection increases the risks of AMI and ischemic stroke. Some features of SARS-CoV-2 infection and COVID-19, present in this study and likely in others, complicate the analysis and may introduce bias. In the present paper we describe these features, and explore the biases they may generate. Motivated by data-based simulations, we propose methods to reduce or remove these biases.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Stroke / COVID-19 Limits: Humans Country/Region as subject: Europa Language: English Journal: Stat Med Year: 2021 Document Type: Article Affiliation country: Sim.9179

Full text: Available Collection: International databases Database: MEDLINE Main subject: Stroke / COVID-19 Limits: Humans Country/Region as subject: Europa Language: English Journal: Stat Med Year: 2021 Document Type: Article Affiliation country: Sim.9179