Unveiling the Longitudinal Journey: 3-Year Follow-up of Women with MINOCA and INOCA in a Specialized Heart Centre
Bibliographic record
Abstract
Background Myocardial infarction with no obstructive coronary arteries (MINOCA), and ischemia with no obstructive coronary arteries (INOCA), are female-predominant conditions; clinical trials are lacking to guide medical management for the common underlying vasomotor etiologies. Data on long-term outcomes of (M)INOCA patients following attendance at a women's heart centre (WHC) are lacking. Methods Women diagnosed with MINOCA (n = 51) or INOCA (n = 112) were prospectively followed for 3 years at the Leslie Diamond WHC (LDWHC) in Vancouver. Baseline characteristics, diagnoses, chest-pain type, major adverse cardiac events, hospital encounters, medications, and Seattle Angina Questionnaire (SAQ) responses were compared between the baseline and 3-year timepoints. The χ 2 test was used to compare categorical variables; the Student t test was used for continuous variables. Results MINOCA patients had significantly more nonexertional chest pain and more diagnoses of vasospasm than did INOCA patients, who had more exertional chest pain and more diagnoses of coronary microvascular dysfunction. Following the baseline timepoint, both groups had significant reductions in cardiovascular emergency room visits, with INOCA patients also experiencing fewer cardiovascular hospitalizations. At 3 years, the most commonly prescribed medications were calcium-channel blockers, long-acting nitrates, and beta-blockers, with MINOCA patients having more acetylsalicylic acid use, and INOCA patients having more short-acting nitrate and ranolazine prescriptions. Both groups observed significant improvements in SAQ scores, with greater improvements observed in INOCA patients. Patients with depression or who were prescribed ranolazine at 3 years had worse SAQ scores at baseline. Conclusions The 3-year outcomes of (M)INOCA patients indicate that the LDWHC's comprehensive care model effectively improves diagnostic clarity, reduces the number of hospital encounters, optimizes medication management, and improves self-reported patient well-being.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".