Smartphone-Assisted High-Intensity Interval Training in Inflammatory Rheumatic Disease Patients: Randomized Controlled Trial
Bibliographic record
Abstract
Background Patients with inflammatory rheumatic diseases (IRDs) experience disease-related barriers to physical training. Compared with the general population, IRD patients are reported to have reduced maximal oxygen uptake (VO2max) and physical activity levels. Supervised high-intensity interval training (HIIT) is documented to counteract the reduced VO2max and poor cardiovascular health associated with IRDs. However, supervised HIIT is resource demanding. Objective This study sought to investigate if self-administered 4×4-min HIIT guided by a smartphone app (Myworkout GO) could yield similar HIIT-induced effects as standard 4×4-min HIIT performed under the guidance and supervision of health care professionals. The effects studied were on VO2max and health-related quality of life (HRQoL). Methods Forty patients (33 female patients, mean age 48 years, SD 12 years; 7 male patients, mean age 52 years, SD 11 years) diagnosed with rheumatoid arthritis, spondyloarthritis, or systemic lupus erythematosus were randomized to a supervised group (SG) or an app group (AG). Both groups were instructed to perform 4×4-min intervals with a rate of perceived exertion of 16 to 17, corresponding to 85% to 95% of the maximal heart rate, twice a week for 10 weeks. Treadmill VO2max and HRQoL measured using RAND-36 were assessed before and after the exercise period. Results VO2max increased (P<.001) in both groups after 10 weeks of HIIT, with improvements of 3.6 (SD 1.3) mL/kg/min in the SG and 3.7 (SD 1.5) mL/kg/min in the AG. This was accompanied by increases in oxygen pulse in both groups (P<.001), with no between-group differences apparent for either measure. Improvements in the HRQoL dimensions of bodily pain, vitality, and social functioning were observed for both groups (P<.001 to P=.04). Again, no between-group differences were detected. Conclusions High-intensity 4×4-min interval training increased VO2max and HRQoL, contributing to patients’ reduced cardiovascular disease risk, improved health and performance, and enhanced quality of life. Similar improvements were observed following HIIT when IRD patients were guided using perceived exertion by health care professionals or the training was self-administered and guided by the app Myworkout GO. Utilization of the app may help reduce the cost of HIIT as a treatment strategy in this patient population. Trial Registration ClinicalTrials.gov NCT04649528; https://clinicaltrials.gov/ct2/show/NCT04649528
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".