Supplementary studies

Between May and October 2021, patients from the recovered COVID-19 group were contacted via phone and email and invited to participate in supplementary studies of energy metabolism and patient perspectives. Based on emerging data and observations, these sub-studies were opportunistically conceptualized after the primary study had been initiated. In the supplementary study on energy metabolism, a subset of patients were examined to investigate the role of the most metabolically active organs affecting resting energy expenditure (REE). Notably, organs significantly influence REE, accounting for approximately 75% of this energy metabolism component. Given the systemic effects of COVID-19, understanding potential changes in energy metabolism post-recovery is imperative due to its impact on body composition and nutritional status in general (34–36). By examining the impact of individual organs on REE in those recovered from COVID-19, we aim to gain insights into the lasting metabolic effects of infection, distinct from its acute complications. Knowledge gained could optimize health in the post-recovery phase by guiding targeted interventions. Exclusion criteria for this supplementary study included pregnancy or lactation, having any electronic implant and those who are claustrophobic. Specific protocols were followed for REE assessment as described previously (37). Participant’s REE were assessed using a metabolic cart with ventilated hood system (Vmax^® Series, CareFusion, Yorba Linda, CA, United States) at the Human Nutrition Research Unit (University of Alberta, Edmonton, AB, Canada).

Abnormalities in energy metabolism will be explored compared to commonly used equations. A new approach will be tested to evaluate the resting metabolic rate K(i) values of major organs (liver, heart, lungs, kidneys and brain) and tissues on the basis of a mechanistic model: REE = Σ(K(i) × T(i)), where REE is whole-body REE measured by indirect calorimetry, and T(i) is the mass of individual organs and tissues measured by MRI. With measured REE and T(i), marginal 95% confidence interval for K(i) values will be calculated by stepwise univariate regression analysis (38).

For the supplementary study on patient experiences, we sought to learn about the individual experience of acute and recovered COVID-19 and to determine if patient reported symptoms and experiences correlated to physiologic testing. An audio-taped 45-to-60-min interview was conducted, using an open-ended style. The researcher recorded field notes after each interview, including general observations, any important nonverbal communication, and thoughts or feelings regarding the interview (“memoing”). The data collected was transcribed verbatim and stripped of potential identifiable material by a professional transcription company.

For the analysis, a broad-based data coding system will be created and considered in contrast to other groupings with different properties. These initial codes will then be developed into concepts, themes, and potential sub-themes, into what is termed “pattern recognition.” The final synthesis of the data will be achieved when the researcher has reached a level of interpretation that develops a conceptual definition that will be meaningful and relevant to applied practice.