Consensus elements for observational research on COVID-19-related long-term outcomes

Area of Science:

• Epidemiology
• Public Health
• Biostatistics

Background:

• Long-term outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are influenced by numerous factors.
• Accurate research on SARS-CoV-2 morbidity and mortality necessitates measuring and controlling for these characteristics.

Purpose of the Study:

• To inform the design, measurement, and analysis of longitudinal studies on long-term outcomes following SARS-CoV-2 infection.
• To identify and operationalize key data elements for observational research on SARS-CoV-2 infection and its consequences.

Main Methods:

• A survey was administered to interprofessional clinicians and scientists to identify factors associated with SARS-CoV-2 infection and outcomes.
• A consensus causal diagram was developed through an iterative process, relating infection to 12-month mortality.
• Minimally sufficient adjustment sets were operationalized using common medical record data elements.

Main Results:

• 31 investigators identified 49 potential risk factors and 72 potential consequences of SARS-CoV-2 infection.
• Risk factors were categorized into demographics, physical health, mental health, personal social, economic factors, and external social/economic factors.
• A consensus directed acyclic graph for mortality was created, including two minimally sufficient adjustment sets.

Conclusions:

• A collectively developed and refined list of data elements for SARS-CoV-2 observational research is presented.
• Accounting for these identified elements can enhance the informativeness of studies on causal pathways for long-term SARS-CoV-2 outcomes.