Abstract 16471: Illness Perception in Patients Hospitalized for Acute Coronary Syndrome
Bibliographic record
Abstract
Introduction: Studies of Illness perception in patients with acute coronary syndrome (ACS) conducted in Canada and Finland showed that genetic factors, stress and lifestyle behaviors are the most common perceived cause of ACS (unstable angina, myocardial infarction). As illness perception is influenced by the personal experience of the illness and its management, as well as by cultural and social factors, we conducted a study to assess illness perception in patients with acute coronary syndrome in Argentina. Methods: Descriptive, cross-sectional, multicenter study. Adults over 18 years old hospitalized for ACS participated in the study. The day of discharge from the Coronary Care Unit, each subject completed a questionnaire generated and validated in Argentina aimed at assessing illness perception. Clinical data were collected by the treating physician at each participating institution. Results: 109 patients between 33 and 84 years old (mean [SD] age = 61 [12] years, 70% male) were enrolled; 57% was diagnosed with ACS without ST-segment elevation and 37% was diagnosed with acute myocardial infarction (MI) with ST-segment elevation; in 6% the acute MI was indeterminate. Many patients attributed the heart disease to their traditional cardiovascular risk factors: 93% to hypertension, 81% to cholesterol, 71% to diabetes mellitus, 69% to physical inactivity, 67% to obesity, 63% to smoking. Only 30% of patients with a positive family history identified it as a risk factor. Stress, anxiety, and personality were identified as the cause for their heart disease in 71%, 64%, and 42% of patients, respectively. The majority of patients (74%) considered that they should improve the adherence to medications after discharge and 80% that should attend the medical follow-ups. Conclusion: Most patients identified their modifiable risk factors as causal for coronary heart disease. Only 30% of participants with a positive family history recognized it as a risk factor. A high percentage of patients recognized suboptimal behaviors in relation to medication adherence and medical follow-ups.
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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 | 0.002 |
| 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 | 0.001 | 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".