assosiation of non alcholic fatty liver disease with coronary artery disease
Bibliographic record
Abstract
OBJECTIVE: To determine the association between non alcoholic fatty liver disease and coronary artery disease. METHODOLOGY: This cross sectional study is conducted from July 2016 to December 2016, in cardiology unit, Lady reading hospital. By using non probability consecutive sampling, patients of all age groups and either gender, presenting to cath: lab for coronary angiography, indicated for angina CCS III, were included in the study. All patients fulfilling inclusion and exclusion criteria were subjected to screening for NAFLD by using ultrasonography. Patients were classified into having no, mild, moderate and sever NAFLD. Correlation between NAFLD and CAD, confirmed on cath: studies, was done using Spearman’s rho test. RESULTS: Total of 370 patients with mean age of 55.36 ± 10.07 years were enrolled in the study, of which 44.6% were females. Known risk factors for CAD like Diabetes mellitus, hypertension, and smoking were present in 63.5%, 64.9% and 23% respectively. 28.4% of patients had no NAFLD, 28.4% had mild, 28.4% had moderate and 14.4% had sever NAFLD. 12.2% had no CAD while mild, moderate and sever disease was present in 36.5%, 31.1% and 2.3% respectively. By using chi square test co relation co efficient between NAFLD and CAD was calculated and came out to be 285.536 ( p value <0.000). NAFLD also increased the odds of having CAD by 2.9 times with a p value for odd ratio <0.000. CONCLUSION: NAFLD is strongly associated as an independent risk factor with CAD and increases the odds of having CAD. KEY WORDS: NAFLD= Non alcoholic fatty liver disease, CAD= Coronary artery disease, CCS= Canadian classification scale, Cath:= Cardiac catheterization
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".