Avoiding bias in self-controlled case series studies of coronavirus disease 2019.
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Stroke
/
COVID-19
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
/
Systematic review/Meta Analysis
Limits:
Humans
Country/Region as subject:
Europa
Language:
English
Journal:
Stat Med
Year:
2021
Document Type:
Article
Affiliation country:
Sim.9179
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