2.4. Quality Assessment

Quality Assessment was completed by one author, with a second author completing a 10% cross-check for validation. Differences in assessment were resolved by group discussion.

Studies that met the definitions for inclusion were assessed for quality based on their design and reporting. In both cases, we considered whether results offered a direct link between symptoms and potential pathophysiology, if data were collected prospectively or retrospectively, and whether the underlying acute COVID infection was self-reported or confirmed by a validated test. We also considered how LC was defined—whether this was self-reported or in line with the World Health Organisation criteria.

For Review 1 (Table 2), we assessed reviews by the population of patients included (removing those which were entirely hospitalised cohorts) and by the extent to which analysis directly linked pathophysiology to symptoms. We excluded reviews of studies that were purely descriptions of symptom patterns. We identified funding sources and possible conflicts of interest declared by the authors. We also considered the study designs included in each review and whether the authors had performed a quality assessment or risk of bias analysis for the publications they included. We did not exclude on any of these latter considerations. Publications included in this paper were assessed for quality using the NIH National Heart, Lung and Blood Institute’s quality assessment tool for Systematic Reviews and Meta-Analyses [19].

Quality assessment for Review 1.

For Review 2 (Table 3), we additionally classified studies by the number of participants (<25, 25–100, and >100) and assessed how the population sample was defined and whether the study included a control group and considered potential confounding factors in their analysis. Publications that were included were assessed for quality using the NIH National Heart, Lung, and Blood Institute’s standardised evaluation tool, appropriate for the individual study design [19].

Quality assessment for Review 2.

Finally, we used publications from both searches to look at the relationship between symptoms of LC, pathophysiologies underlying these symptoms, and possible treatments or treatment targets. Causal relationships were identified from the extracted data by organ system.

The reporting of this review was guided by the standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement.