Self-reported health and adverse outcomes among women living with symptoms of angina or unspecific chest pain but no diagnosis of obstructive coronary artery disease—findings from the DenHeart study
Bibliographic record
Abstract
AIMS: The objectives were to describe differences in self-reported health at discharge between women diagnosed with angina or unspecific chest pain and investigate the association between self-reported health and adverse outcomes within 3 years. METHODS AND RESULTS: Data from a national cohort study were used, including data from the DenHeart survey combined with 3 years of register-based follow-up. The population included two groups of women with symptoms of angina but no diagnosis of obstructive coronary artery disease at discharge (women with angina and women with unspecific chest pain). Self-reported health measured with validated instruments was combined with register-based follow-up on adverse outcomes (a composite of unplanned cardiac readmissions, revascularization, or all-cause mortality). Associations between self-reported health and time to first adverse outcomes were investigated with Cox proportional hazard models, reported as hazards ratios with 95% confidence intervals. In total, 1770 women completed the questionnaire (49%). Women with angina (n = 931) reported significantly worse self-reported health on several outcomes compared to women with unspecific chest pain (n = 839). Within the 3 years follow-up, women with angina were more often readmitted (29 vs. 23%, P = 0.011) and more underwent revascularization (10 vs. 1%, P < 0.001), whereas mortality rates were similar (4 vs. 4%, P = 0.750). Self-reported health (physical and mental) was associated with adverse outcomes between both groups (on most instruments). CONCLUSION: Women with angina reported significantly worse self-reported health on most instruments compared to women with unspecific chest pain. Adverse outcomes varied between groups, with women diagnosed with angina experiencing more events. REGISTRATION: ClinicalTrials.gov (NCT01926145).
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".