Abstract 11143: Symptom Experience in Women With Ischemia and No Obstructive Coronary Artery Disease: A Mixed Methods Approach
Bibliographic record
Abstract
Introduction: Women with myocardial ischemia but no obstructive coronary artery disease (INOCA) often have coronary microvascular dysfunction, a condition associated with adverse cardiovascular outcomes. INOCA patients have recurrent chest pain and reduced quality of life, but therapeutic strategies to treat INOCA are poorly defined. In this study we used mixed methods to gain an understanding of their symptom patterns and burden clustered with other co-morbid conditions, while considering their overall symptom experience with having chronic angina. Methods: Twenty-four women diagnosed with INOCA based on coronary angiography were enrolled. Qualitative telephone interviews were conducted, recorded, and transcribed verbatim. First and second cycle coding was then used to analyze the qualitative data. Baseline demographics, risk factors, and angina burden by the Seattle Angina Questionnaire (SAQ) were assessed and descriptive statistics were performed. Results: Mean age was 53.2±10.8 years and body mass index was 30.8±6.9 kg/m 2 . Cardiac risk factors were prevalent with 43% hypertension, 57% hyperlipidemia, and 22% diabetes. SAQ scores indicated high angina burden and poor quality of life: 37.7±24.3 (physical limitation), 35.2±31.5 (angina stability), 41.3±23.2 (quality of life). Elemental qualitative coding and analysis identified four major themes: Invisible inscrutable threat, Longing for a normal/safe life, Rejecting labels, and “It has a toll”. A majority (75%) expressed both emotional burden and explicit frustration and dissatisfaction around their diagnosis. Conclusion: Qualitative and quantitative data supported that despite high symptom burden and poor quality of life, patients felt that they were frequently not believed, and that knowledge was limited to manage their condition. Research to close this persistent knowledge gap and to prioritize symptom management to help INOCA patients regain as much normalcy as possible is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".