Effects of Therapeutic Ultrasound and Aussie Current With High-Intensity Interval Training on Abdominal Adiposity in Young Adults With Overweight and Obesity: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: More than half of the world's population will be overweight or obese by 2035, and it is known that physical exercise, such as high-intensity interval training (HIIT), is a tool for controlling obesity by improving body composition and the metabolic profile. Noninvasive techniques such as therapeutic ultrasound (TUS) and the Aussie current have shown potential in controlling adipose tissue, but their effects combined with HIIT remain unknown. TUS may be combined with the Aussie current to potentiate the specific effects of each intervention, such as lipolysis induced by TUS and lymphatic activation promoted by the Aussie current. The integration of HIIT into this protocol is justified by its ability to stimulate β-oxidation and facilitate the metabolic use of fatty acids mobilized by the electrophysical resources. Furthermore, the use of HIIT as opposed to moderate-intensity continuous training contributes to reducing the total duration of the intervention. OBJECTIVE: This study aims to evaluate the effects of TUS+Aussie current combined with HIIT on body composition, serum metabolic profile, and cardiovascular autonomic modulation (CAM) in individuals with overweight and obesity. METHODS: This is a randomized, double-blind (researcher and outcome assessor) clinical study. The participants will be randomized into 3 groups: active TUS+Aussie current with HIIT group, placebo for TUS+Aussie current with HIIT group, and TUS+Aussie current-only group. All participants will undergo nutritional monitoring 30 days before the proposed interventions to adjust macronutrients, optimize energy intake, and improve diet quality. Primary outcomes include changes in subcutaneous adipose tissue thickness, body composition, and serum metabolic profile. Secondary outcomes assess perceived stress, body image, blood biochemistry, sleep quality, and CAM. Data analysis involves linear mixed models estimated using the maximum likelihood method with an appropriate covariance matrix structure. RESULTS: A total of 60 participants will be recruited and randomized between February 2024 and June 2025. The baseline assessments and intervention are scheduled to be completed in August 2025, and data collection will be completed by the end of September 2025. Data acquisition is still ongoing; therefore, data analysis has not yet been carried out. CONCLUSIONS: This is the first study to combine TUS+Aussie current with HIIT, potentially integrating the effects of lipolysis and fat oxidation and possible changes in the serum metabolic profile and CAM. The results could optimize treatment duration, promote changes in lipid profile, and maintain cardiovascular health in people with overweight and obesity. TRIAL REGISTRATION: Brazilian Registry of Clinical Trials RBR-4xh6232, Universal Trial Number: U1111-1287-2345; https://ensaiosclinicos.gov.br/rg/RBR-4xh6232. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71829.
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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 | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.041 | 0.008 |
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".