| Journal Ref. |
International Journal of Ostheopatic Medicine |
| Intervention |
Health services delivery and reconfiguration - All patients with long COVID referred to the rehabilitation service will be received by a social assistant to allocate the participants in two groups PT or OMT+PT, present the informed consent form and apply the questionnaires that will be used to assess the groups. The interventions will be conducted according to each patient’s clinical presentation, following their usual care and without creating any changes that could denature the routine clinical practice (Table 1). Participants in both groups are not restricted to access other interventions (e.g., medications or self-guided physical activity). In the follow-up questionnaire they may report other interventions in the last three months if any.
The criteria for discontinuing the treatment in both groups include participants request to withdraw from the research, any condition that prevents the participant from reaching the treatment setting, hospitalization, or death. The number of consultations/appointments for each participant will be recorded, as well as possible absences from scheduled appointments. To reduce attrition rate, on every absence the social worker will contact the participant via phone call to inquire about the reason for the absence and encourages the participant to continue the treatment. In the follow-up questionnaire they may report reasons for dropping out of the trial to be categorized as cost, health improvement, aggravation of symptoms, death, or others (e.g., relatives sickness, no allowance work leave).
|
| Number of sites |
1 |
| Countries involved |
Brazil |
| Sample size |
76 |
| Type of statistical analyses |
The sample was calculated using the formula for a superiority trial [45]. Sample size was calculated based on a minimal clinical important difference between groups on 1 point (standard deviation of 2.0 points) on the FSS scores at 2 months [46]; no calculation was performed based on PSFS as to the best of our knowledge minimally important differences are yet to be determined [41]. A total sample of 64 participants (32 per arm) is required considering a type-I error of 5% and type-II error of 20%. With a possible 15% loss to follow-up, the required total sample size is 76 participants. A statistician will conduct the analysis using encoded and deidentified data in R version 4.1.2. The principle of intention-to-treat will be used for analysis [47]. All enrolled participants will be followed through the study and included in the analysis and compared in the outcome measures on the basis of the treatment group to which they were randomly allocated at baseline, regardless of deviations from randomized allocation (e.g., deviated from the treatment protocol, received a different treatment, non-compliance); false inclusions; or missing outcomes (e.g., they started the treatment allocated, subsequently withdrew from the trial, or were lost to follow-up). Sensitivity analysis will be conducted under a per-protocol analysis to test for possible effects of incomplete adherence and loss to follow-up [48]; prerandomization data (age, sex, baseline functional status, time since acute COVID-19 infection, history of ICU admission) will be included as adjustments. Data will be assessed for evidence of departure from normality and will either be transformed or analyzed using a nonparametric equivalent, if required. Comparative summary statistics (difference in means with 95% confidence intervals) will be reported. Independent mixed linear models will be used to test the interaction and main effects of group (OMT+PT, PT) and time (baseline, 2 months, 3 months) for the study outcomes (FSS, PCFS, PCS), considering age sex, time since acute COVID-19 infection, and history of ICU admission as covariates. Baseline variables will be evaluated as predictors and moderators of treatment including terms and interaction models [49]. Missing data will be assumed to be missing at random. Multiple imputation will be used to account for these missing data [50]. Missing values in outcome variables will be estimated using multiple imputation by chained equations after 50 replicated imputed data sets. Variables included in the multiple imputation process included factors group, time, and the respective outcome variable. |
| Risk of bias |
Overall: -
details
Random sequence generation:
Low Risk
Allocation concealment:
Low Risk
Blinding of participants, personal and outcome assessors:
High Risk
Incomplete outcome data:
-
Selective outcome reporting:
-
Other sources of bias:
-
|
| Participant characteristics |
Age: equal to or above 18 years
Condition: Inclusion criteria comprise age equal to or above 18 years; essential and clinical criteria for long COVID at baseline assessment (confirmed preceding infection with SARS-CoV-2, individuals referred for rehabilitation reporting fatigue as major symptom [35]; and ability to understand Portuguese well enough to be able to fill in the questionnaires
Baseline severity: essential and clinical criteria for long COVID at baseline assessment (confirmed preceding infection with SARS-CoV-2
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| Duration of trial |
August 2021 to July 2023 |
| Primary outcome |
fatigue and functional limitations |
| Effect Measures |
|
Events Intervention
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Total
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Events Control
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Total
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Risk Diff.
|
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0
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