Cardiovascular Disease Risk Factors among Non-Alcoholic Fatty Liver Disease Patients at Makkah, Kingdom of Saudi Arabia
Bibliographic record
Abstract
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is one of the major health problems which is characterized by excessive fat accumulation in the liver. Worldwide, NAFLD has a reported prevalence of 6 to 35 percent in the general population. The prevalence of NAFLD has increased as more patients develop a sedentary lifestyle, metabolic syndrome, and obesity. AIM & OBJECTIVES: To study cardiovascular disease risk factors among NAFLD patients aiming to reduce morbidity and mortality. METHODOLOGY: This was a cross sectional study. Cardiovascular risk factors questionnaire including personal data, BMI, lipid profile and blood pressure was used to obtain the data from 150 patients with ultrasound diagnosed NAFLD and 150 patients with no evidence of NAFLD at Umm Al Qura University medical center, Makkah, Kingdom of Saudi Arabia. RESULTS: 54.7% out of 150 NAFLD patients were males, 91.3% were obese, 50.7% were diabetics, 28% hypertensive, 53.7% had high cholesterol level, 52.7 % had high triglycerides and 64.6% had high LDL level. Results showed significant high prevalence of most of CVD risk factors among NAFD patients in comparison to age matched group of patients without NAFLD. CONCLUSION: NAFLD patients have a high risk of cardiovascular diseases more than non NAFLD.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".