Lifestyle Intervention Enabled by Mobile Technology on Weight Loss in Patients With Nonalcoholic Fatty Liver Disease: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The prevalence of nonalcoholic fatty liver disease (NAFLD) reaches up to 30% in the Asian adult population, with a higher prevalence in obese patients. Weight reduction is typically recommended for patients at high risk or diagnosed with NAFLD, but is a challenge to achieve. OBJECTIVE: We aimed to evaluate the effect of a lifestyle intervention with a mobile app on weight loss in NAFLD patients. METHODS: who were recruited from a fatty liver outpatient clinic. The patients were randomly allocated to either a control group (n=53) receiving standard care, consisting of dietary and lifestyle advice by a trained nurse, or an intervention group (n=55) utilizing the Nutritionist Buddy (nBuddy) mobile app in addition to receiving dietary and lifestyle advice by a dietitian. Body weight, alanine aminotransferase (ALT), aspartate aminotransferase (AST), waist circumference, and blood pressure were measured at baseline, and then at 3 and 6 months. Intention-to-treat and per-protocol analyses were used for statistical comparisons. RESULTS: The intervention group had a 5-fold higher likelihood (relative risk 5.2, P=.003, 95% CI 1.8-15.4) of achieving ≥5% weight loss compared to the control group at 6 months. The intervention group also showed greater reductions in weight (mean 3.2, SD 4.1 kg vs mean 0.5, SD 2.9 kg; P<.001), waist circumference (mean 2.9, SD 5.0 cm vs mean -0.7, SD 4.4 cm; P<.001), systolic blood pressure (mean 12.4, SD 14.8 mmHg vs mean 2.4, SD 12.4 mmHg; P=.003), diastolic blood pressure (mean 6.8, SD 8.9 mmHg vs mean -0.9, SD 10.0 mmHg; P=.001), ALT (mean 33.5, SD 40.4 IU/L vs mean 11.5, SD 35.2 IU/L; P=.004), and AST (mean 17.4, SD 27.5 U/L vs mean 7.4, SD 17.6 IU/L, P=.03) at 6 months. CONCLUSIONS: Lifestyle intervention enabled by a mobile app can be effective in improving anthropometric indices and liver enzymes in patients with NAFLD. This treatment modality has the potential to be extended to a larger population scale. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12617001001381; https://tinyurl.com/w9xnfmp.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".