Muscle Fatigue in People With Cystic Fibrosis: Insight From a Mobile App

Cystic Fibrosis (CF)

Cystic Fibrosis, Fatigue, Fatigability, Mobile app, Validity, Reliability, Muscle power, Strength, Peripheral muscle function

Muscle fitness is an important component of health. For instance, the ability to resist to muscle fatigue development is important for daily functioning. Previous studies have suggested altered muscle function in people with cystic fibrosis. However, it is unclear whether such findings still apply in the modern era of CF. Several studies suggested that recent improvements in therapeutics, including CFTR modulators, may have positive effects on the skeletal muscles, potentially normalizing the ability to resist to muscle fatigue. However, no studies to date compared muscle fatigue between people with cystic fibrosis and healthy controls in a large sample of patients. One difficulty is that muscle fatigue assessment requires high-cost dynamometric instruments, which also leads to a gap between research and clinical practice. Our research group has created a mobile application based on video analysis of the chair rising test that reports values of time, velocity and power as reliable as devices found in a laboratory environment. The application has been shown to be valid and reproducible for measuring muscle fatigue in healthy people. However, a validation is necessary before recommending its use in people with cystic fibrosis.

Objectives: To evaluate the reliability of a mobile app to detect muscle fatigability as decrease in performance after 1minSTS test in people with cystic fibrosis, and to analyze whether muscle fatigability is still increased in people with cystic fibrosis compared to healthy controls. Methods: A discriminant validity and reliability study designed in accordance with the Guidelines for Reporting Reliability and Agreement Studies will be carried out. The study will include at least 34 participants diagnosed with cystic fibrosis and 34 healthy participants matched for age, sex, and physical activity level. A fatigue protocol will be carried out that will consist of chair rising as many times as possible for 60 seconds. A measurement will be carried out before (Pre), immediately after (Post) and one minute after (Post1min) the fatigue protocol through the mobile application (Sit to Stand App). The time, velocity and power values derived from the application will be used as fatigability indicators. The differences between the Pre and Post measurements will be indicative of performance fatigability, while the differences between the Post and Post1min measurements will be indicative of recovery. Heart rate will be recorded during the fatigue protocol and Post1min, as well as muscle and respiratory effort using the Borg CR10 scale. This experimentation will be repeated twice with a difference of 30 minutes in order to analyze the reliability of the measurements. The sample size estimation was calculated using G\*Power 3.1 software. An estimation was performed for each study objective, and the estimation requiring the largest sample size was selected for the study. To analyze whether the level of muscle fatigability is reproducible, a minimum acceptable reliability of ρH0 ≥ 0.5 and an expected reliability of ρH1 ≥ 0.8 were selected. For a two-tailed test with a statistical power ≥ 80% and an alpha error of 0.05, the minimum required sample size was reported as 29 participants. To analyze whether mobile application detects muscle fatigability induced by the fatigue test, an expected moderate effect size (d ≥ 0.7) with a statistical power ≥ 80% and an alpha error of 0.05 was selected, resulting in a minimum desirable sample size of 34 participants per group.

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