Interpreting angina: symptoms along a gender continuum
Bibliographic record
Abstract
BACKGROUND: 'Typical' angina is often used to describe symptoms common among men, while 'atypical' angina is used to describe symptoms common among women, despite a higher prevalence of angina among women. This discrepancy is a source of controversy in cardiac care among women. OBJECTIVES: To redefine angina by (1) qualitatively comparing angina symptoms and experiences in women and men and (2) to propose a more meaningful construct of angina that integrates a more gender-centred approach. METHODS: Patients were recruited between July and December 2010 from a tertiary cardiac care centre and interviewed immediately prior to their first angiogram. Symptoms were explored through in-depth semi-structured interviews, transcribed verbatim and analysed concurrently using a modified grounded theory approach. Angiographically significant disease was assessed at ≥70% stenosis of a major epicardial vessel. RESULTS: Among 31 total patients, 13 men and 14 women had angiograpically significant CAD. Patients describe angina symptoms according to 6 symptomatic subthemes that array along a 'gender continuum'. Gender-specific symptoms are anchored at each end of the continuum. At the centre of the continuum, are a remarkably large number of symptoms commonly expressed by both men and women. CONCLUSIONS: The 'gender continuum' offers new insights into angina experiences of angiography candidates. Notably, there is more overlap of shared experiences between men and women than conventionally thought. The gender continuum can help researchers and clinicians contextualise patient symptom reports, avoiding the conventional 'typical' versus 'atypical' distinction that can misrepresent gendered angina experiences.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".