Predictors of Symptom Congruence Among Patients With Acute Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The extent of congruence between one's symptom experience and preconceived ideas about the nature of myocardial infarction symptoms (ie, symptom congruence) can influence when acute myocardial infarction (AMI) patients seek medical care. Lengthy delays impede timely receipt of medical interventions and result in greater morbidity and mortality. However, little is known about the factors that contribute to symptom congruence. Hence, the purpose of this study was to examine how AMI patients' symptom experiences and patients' demographic and clinical characteristics contribute to symptom congruence. PARTICIPANTS AND METHODS: Secondary data analyses were performed on interview data that were collected from 135 AMI patients. Hierarchical multiple regression analyses were used to examine how specific symptom attributes and demographic and clinical characteristics contribute to symptom congruence. Chest pain/discomfort and other symptom variables (type and location) were included in step 1 of the analysis, whereas symptom severity and demographic and clinical factors were included in step 2. In a second analysis, quality descriptors of discomfort replaced chest pain/discomfort in step 1. RESULTS: Although chest pain/discomfort, and quality descriptors of heaviness and cutting were significant in step 1 of their respective analyses, all became nonsignificant when the variables in step 2 were added to the analyses. Severe discomfort (β = .29, P < .001), history of AMI (β = .21, P < .01), and male sex (β = .17, P < .05) were significant predictors of symptom congruence in the first analysis. Only severe discomfort (β = .23, P < .01) and history of AMI (β = .17, P < .05) were predictive of symptom congruence in the second analysis. CONCLUSIONS: Although the location and quality of discomfort were important components of symptom congruence, symptom severity outweighed their importance. Nonsevere symptoms were less likely to meet the expectations of AMI symptoms by those experiencing this event. Those without a previous history of AMI also experienced lower levels of symptom congruence. Implications pertaining to these findings are discussed.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".