Abstract 11638: Physician Attitudes Toward Beta Blocker and Antiplatelet Therapy in Spontaneous Coronary Artery Dissection Patients
Bibliographic record
Abstract
Background: Spontaneous Coronary Artery Dissection (SCAD) primarily affects younger women and is a cause of acute coronary syndrome for which medical management guidelines and clinical trial data are lacking. Our study assessed physician attitudes toward beta blocker (BB) and antiplatelet therapy (APT) in SCAD. Methods: We conducted an online survey among 165 physicians who treat SCAD. Data were collected about their demographics, BB and APT prescribing practices in hypothetical SCAD patients each with one key difference from the base case, and willingness to randomize patients to BB or no BB and to dual APT [DAPT] (12 months of aspirin and P2Y12 inhibitor, then only aspirin) or single APT [SAPT] (3 months of aspirin, then no APT). Results were analyzed with descriptive statistics and chi-squared test. Results (Table): Of the respondents, 163 (99%) were cardiologists, and 64 (39%) were women. When considering BB at discharge, 88% of physicians would prescribe BB in the base case of an otherwise healthy 49-year-old woman with SCAD, with higher likelihood of prescribing BB in a patient with hypertension or ejection fraction (EF) < 50%. Most physicians (95%) were willing to randomize the base case to BB or no BB. Respondents expressed uncertainty about the benefit of BB use, particularly in patients with normal blood pressure or with EF > 50%. When considering APT at discharge, 38% of physicians would prescribe DAPT, 46% would prescribe SAPT, and 16% would prescribe no APT in the base case. Most physicians (92%) were willing to randomize the base case to the DAPT or SAPT strategies. Physicians expressed concern about inadequate and excessive APT, indicating a range of opinions. Conclusion: Most physicians would prescribe BB and APT at discharge after SCAD, with the type of APT varying widely. Nearly all were willing to randomize patients to BB or no BB and to DAPT or SAPT. Our results suggest clinical equipoise exists for BB and APT use in SCAD and point to the need for clinical trial data.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.004 | 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".