Nutritional Status of Coronary Artery Disease Patients—Preliminary Results
Bibliographic record
Abstract
Introduction: Malnutrition is a condition that negatively impacts the clinical outcomes of numerous diseases. The aim of this study was to assess the nutritional status of coronary artery disease (CAD) patients and to investigate its relationship with the main clinical aspects of CAD. Material and methods: 50 CAD patients undergoing coronary angiography were enrolled in this study. The nutritional status assessment was based on Nutritional Risk Score 2002 (NRS 2002), body mass index (BMI), and bioelectrical impedance analysis (BIA) measurements. Results: The analysis showed a moderate inverse correlation between NRS 2002 and BIA phase angle measured at 50 kHz (R: −0.31; p = 0.03) and Z200/5 parameter (R: 0.34; p = 0.02). The analysis of CAD clinical parameters showed a significant correlation between NRS 2002 and Canadian Cardiovascular Society (CCS) class (R: 0.37; p = 0.01). Left ventricle ejection fraction (LVEF) was correlated with BMI (R: 0.38; p = 0.02), however further BIA revealed hydration changes as LVEF was correlated to intracellular (ICF) and extracellular fluid (ECF) proportion: positively with ICF (R: 0.38; p = 0.02) and negatively with ECF (R: −0.39; p = 0.02). Conclusions: NRS 2002 and BIA are valuable tools for nutritional status assessment in CAD patients. Malnutrition is related to the severity of CAD symptoms, particularly in women. Maintaining proper nutritional status can have a potentially important role in this group of patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".