Effect of dietary quality on the severity of illness of patients with coronary heart disease
Bibliographic record
Abstract
ObjectiveTo understand the status quo of dietary quality in patients with coronary heart disease and its effect on the severity of illness,so as to provide evidence for guiding patients with coronary heart disease to take rational diet.MethodsA total of 208 patients with coronary heart disease in the Second Affiliated Hospital of Harbin Medical University were surveyed by using Smei⁃Quantitative Food Frequency Questionnaire(SQFFQ) and Mediterranean Diet Questionnaire.ResultsThe qualified rate of diet quality in patients with coronary heart disease was 66.83%.The classification of Canadian Cardiovascular Society(CCS) among patients with coronary heart disease showed that 33 cases at level Ⅰ(15.87%),62 cases at level Ⅱ(29.81%),86 cases at level Ⅲ(41.35%),and 27 cases at level IV(12.98%).Body mass index(BMI),dietary quality,gender and smoking history were the main influencing factors of CCS classification in patients with coronary heart disease(P<0.01).ConclusionThe dietary quality of patients with coronary heart disease needs to be improved.Propaganda and education should be carried out among patients with high BMI,unqualified dietary quality,male and smoking.And balanced diet among patients should be advocated.So as to improve lifestyle and health status of patients with coronary heart disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".