Clinical characteristics and outcomes in Takotsubo syndrome vs. spontaneous coronary artery dissection: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although a large body of literature describes Takotsubo syndrome (TTS) and spontaneous coronary artery dissection (SCAD) as having overlapping clinical features and benign outcome measures, they differ significantly in their pathophysiological mechanisms, demo-graphic profile, and natural history. Herein, we sought to investigate differences in clinical profile and outcomes between patients of these two conditions. METHODS: Following PRISMA guidelines, we compared TTS and SCAD in adult patients regarding epidemiological, clinical, and prognostic features. A systematic search of PubMed, Embase, and Cochrane Library identified eligible studies, with data extracted and quality assessed using the Newcastle-Ottawa scale. Random effects models were applied for statistical analysis, with heterogeneity evaluated by I2 and sensitivity analysis conducted to ensure robustness. RESULTS: Takotsubo syndrome patients presented more often with dyspnea (46.8% vs. 0.9%; p < 0.001), while SCAD patients displayed typical angina (p < 0.001). In-hospital outcomes were worse for TTS patients, with higher mortality (4.4% vs. 0.8%; RR = 7.41, p = 0.001) and major adverse cardiac events (43.3% vs. 5.2%; RR = 8.35, p < 0.001). At one year, TTS patients had higher all-cause mortality (12.5% vs. 0.8%; p < 0.001) and stroke (2.1% vs. 0.6%; RR = 5.08, p = 0.02). CONCLUSIONS: Poorer outcomes are associated with TTS compared to SCAD. SCAD patients demonstrate better prognoses but remain at risk for recurrent ischemic events.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".