Secondary Prevention and Rehabilitation for Spontaneous Coronary Artery Dissection: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Spontaneous coronary artery dissection (SCAD) is a serious, noniatrogenic and nontraumatic cardiac event that predominantly affects women, with a high risk of recurrence. Secondary prevention strategies are not well understood in this population. Therefore, the aim of this systematic review is to determine the current evidence on secondary prevention strategies and their effect on recurrent cardiac events and quality of life (QOL). METHODS: A literature search was conducted on August 21, 2021, of Ovid MEDLINE, Ovid Embase, CINAHL, Cochrane Library (via Wiley), Google Scholar, and ProQuest Dissertations & Theses Global. Literature on adult SCAD survivors who underwent secondary prevention measures with reported outcomes on major adverse cardiovascular events or QOL were included. Articles solely on pregnancy-associated SCAD or fibromuscular dysplasia were excluded. RESULTS: Thirty studies were included in this review. A variety of research methodologies were explored. There were no randomized controlled trials. Overall, the quality of the evidence was moderate. Although evidence on secondary prevention was limited, tailored medical management was shown to have the most effect on decreasing recurrent events. Cardiac rehabilitation (CR) was supported as a safe and effective program for SCAD patients, with no reported associations with recurrent SCAD events or major adverse cardiovascular events. CR along with psychosocial interventions showed promise in improving QOL in SCAD survivors. CONCLUSIONS: Medical management has the most effect in reducing recurrent events. CR, as a secondary prevention program, can provide interventions that might improve QOL. Randomized trial evidence on therapies for patients with SCAD are needed.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".