Post-coronavirus Disease-2019 Fatigue

Background: COVID-19 is consistently spreading throughout the world, and the number of recovered patients is steadily increasing. Accordingly, a significant number of individuals will develop persisting post-COVID symptoms, while many of them will report on lasting fatigue. The main objective of the current study is to assess risk factors for the development of post-COVID-19 fatigue symptoms. As a secondary aim, the current study is intended to identify pathophysiology and explanatory mechanisms for the post-COVID-19 fatigue.

Study design and population: a nested case-control study will be conducted at Rabin Medical Center (RMC), Beilinson Hospital. RMC runs a post-COVID-19 clinic for adult (age ≥18 years) recovered individuals (diagnosed using a polymerase chain reaction test from a nasopharyngeal sample), who are invited for a comprehensive medical evaluation. During a visit, all individuals undergo pulmonary function testing and an evaluation by an infectious diseases physician, a pulmonologist, and a social worker. The cohort of recovered COVID-19 individuals evaluated at RMC will serve as the population from which the current study participants will be consecutively sampled. The cases would be defined as such if report on lasting fatigue symptoms which appeared following COVID-19, while at least two months have elapsed since COVID-19 diagnosis and the lasting fatigue symptoms are present for at least six weeks. The controls would be defined as those that did not report on fatigue symptoms at any time point since one month following their diagnosis with COVID-19.

Evaluation protocol of cases and controls: All participating individuals (cases and controls) will be assessed following the study protocol. The assessment will be conducted as follows:

First assessment meeting (approximately one hour long) in which the participant will undergo physical examination and blood tests, fill the study questionnaires [demographic, clinical and post-COVID fatigue questionnaire; sleep assessment questionnaires (Epworth sleepiness score [ESS], Pittsburg sleep quality index [PSQI], Insomnia severity index (ISI)]) and depression severity questionnaire (the patient health questionnaire-9 [PHQ-9]), and conduct cognitive fatigue task.

Second assessment meeting: (approximately one hour long) in which the participants will undergo a cardiopulmonary stress test (CPET).

Data collection: The main dependent variable will be the presence of continuing fatigue symptoms. The independent variables included demographic and clinical characteristics. The demographic variables will include: age at diagnosis, sex, marital status and number of children, occupational status (employed, unemployed, or retired), education (number of years at school and higher education), and occupation. The clinical variables will include: smoking status, alcohol and cannabis consumption, basic physical function (independent, limited in certain activities, dependent in activities of daily living, or bedridden), background illnesses, and pharmacotherapy. The acute COVID-19 history will be also collected: disease severity according to the WHO criteria, symptoms (sore throat, nasal congestion, headache anosmia/disguesia, cough, shortness of breath, chest pain, gastrointestinal symptoms, and myalgia), need for hospitalization, hospital complications (veno-thromboembolism, super-imposed bacterial infections), for individuals who were not hospitalized - the site of isolation (home, hotel or another isolation facility) will be collected, time from onset to symptoms resolution, pharmacotherapy directed at COVID-19, and information of other household or family members who were also diagnosed.

Statistical methods: Demographic and clinical variables of the patients with fatigue symptoms (cases) and control group (free from fatigue symptoms) will be compared using bivariate and multivariable conditional logistic regression models. Independent variables will be selected to be included in the multivariable model based on the bivariate analysis. Odds ratios and 95% confidence intervals will be obtained from the conditional logistic regression models. P<0.05 will be considered statistically significant.

Sample size calculation: Disease severity may serve as a potential risk factor for the development of lasting fatigue symptoms. A preliminary analysis revealed that in our cohort of recovered COVID-19 patients, 20% were hospitalized due to their disease's severity. We will therefore assume that the proportions of individuals required hospitalization during the acute phase were 30% and 10% of the cases and controls, respectively. It is also likely that approximately two thirds of our sample would report on persisting fatigue. Under these assumptions, a sample size of 153 individuals (102 in the cases group and 51 in the control group) will yield a statistical power of 80% at a significance level of 5% for detecting a difference of 0.2 between two proportions.