Effect of Lifestyle on Coronary Artery Disease in Patients Presenting at Doctors Hospital, Lahore
Bibliographic record
Abstract
Objectives: To study the effect of lifestyle on coronary artery disease and to identify the strength of association between coronary artery disease and lifestyle factors among patients belonging to upper class of Lahore. Method: Seventy-two cases and 72 controls were recruited using convenient purposive sampling technique. Dietary pattern, activity level and socio-demographic profile were assessed with well-designed interview questionnaire. Results: According to statistical analysis of dietary factors, consumption of red meat, bakery products, restaurant food, fast food, soft drinks showed significant association with disease, whereas role of fruits and vegetables was found protective. Use of desi ghee had no significance in causing CAD in current study. Results of BMI and hip-waist ratio showed insignificance. Activity level was also insignificant while smoking and stress were significant. In socio demographic profile, sex of the respondents showed that 68.1% were male and 31.9% were females having CAD, so it was also statistically significant that heart diseases were more in males. Married individuals also showed significant result. Conclusion: According to results, consumption of red meat, bakery products, restaurant food, fast food, soft drinks showed significant association with disease, whereas role of fruits and vegetables was found protective. Whole wheat, desi ghee had no significance in causing CAD in current study. Results of BMI and hip-waist ratio showed insignificance. Activity level was also insignificant while smoking and stress was found to be associated. In socio demographic profile male sex, married individuals showed significant relation with CAD. Education, family type and income had no relation with heart disease in this study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".