Angina pectoris: relation of epidemiological survey to registry data
Bibliographic record
Abstract
BACKGROUND: Self-reported angina symptoms are collected in epidemiological surveys. We aimed at validating the angina symptoms assessed by the Rose Questionnaire against registry data on coronary heart disease. A further aim was to examine the sex paradox in angina implying that women report more symptoms, whereas men have more coronary events. DESIGN: Angina symptoms of 6601 employees of the City of Helsinki were examined using the postal questionnaire survey data combined with coronary heart disease registries. METHODS: The self-reported angina was classified as no symptoms, atypical pain, exertional chest pain, and stable angina symptoms. Reimbursed medications and hospital admissions were available from registries 10 years before the survey. Binomial regression analysis was used. RESULTS: Stable angina symptoms were associated with hospital admissions and reimbursed medications [prevalence ratio (PR), 6.75; 95% confidence interval (CI), 4.56-9.99]. In addition, exertional chest pain (PR, 5.31; 95% CI, 3.45-8.18) was associated with coronary events. All events were more prevalent among men than women (PR, 2.36; 95% CI, 1.72-3.25). CONCLUSION: The Rose Questionnaire remains a valid tool to distinguish healthy people from those with coronary heart disease. However, a notable part of those reporting symptoms have no confirmation of coronary heart disease in the registries. The female excess of symptoms and male excess of events may reflect inequality or delay in access to treatment, problems in identification and diagnosis, or more complex issues related to self-reported angina symptoms.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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".