Influence of Comprehensive Life Style Intervention in Patients of CHD
Bibliographic record
Abstract
BACKGROUND & OBJECTIVE: Over the past 30 years, the CHD rates have doubled in India whereas CHD rates have declined by 15% in most developed countries due to lifestyle interventions during the same period. So, the present study was conducted to find out the effectiveness of lifestyle intervention in reducing major risk factors in CHD patients in an Indian setting. METHODS: We conducted this randomized controlled trial on 640 eligible subjects who were randomly assigned to two groups. The study group was given an interventional package at baseline and at three months, detailing the aspects of a healthy lifestyle in relation to CHD risk factors whereas no intervention was provided for the control group. The study subjects were followed at three and six months and the risk factors were assessed to find out reduction, if any, in the prevalence of the risk factors amongst them. RESULTS: There was a significant reduction in hypertension, tobacco, and lack of physical activity at three and at six months (p<0.03) when compared to the baseline in the study group. However, there was no significant reduction in obesity at three months (p=0.148) while the reduction in obesity was significant at six months (p=0.0005) in the study group as compared to the control group. The lipid profile reduced significantly at six months but there was no statistically significant reduction in diabetes at six months in the study group as compared to the control group (p=0.419). INTERPRETATION & CONCLUSION: Except for diabetes, the lifestyle intervention was successful in increasing physical activity, improving the hypertension control, and decreasing lipid profile disorders, obesity, and tobacco use in the study group.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".