Novel predictors of major adverse cardiovascular events in patients with Takotsubo cardiomyopathy: a contemporary analysis
Bibliographic record
Abstract
BACKGROUND: Takotsubo cardiomyopathy (TCM) is considered a reversible condition; however, it can predispose patients to significant long-term morbidity and mortality. As there is a paucity of literature regarding the long-term clinical outcomes in patients with TCM, we performed a systematic review and meta-analysis to evaluate the clinical, biochemical and imaging factors that are associated with major adverse cardiovascular events (MACE) in these patients. METHOD: A systematic search of databases following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines was utilised to identify studies that reported MACE and mortality in patients with TCM (PROSPERO CRD42025648547). Variable data were extracted and meta-analysed using random-effect modelling. Direct parameter comparisons were conducted using odds ratios (ORs) and standardised mean differences, while a pooled hazard ratio (HR) was meta-analysed for mortality. A two-tailed P-value of <0.05 was deemed significant. RESULTS: Of 320 studies screened, 19 met our inclusion criteria, comprising a total of 6443 patients. Predictors of MACE included a presentation with dyspnoea (OR, 1.41 (95% confidence interval (CI), 1.037-1.907), P = 0.028), Killip-Kimball classification of heart failure >1 (OR, 2.216 (95% CI, 1.673-2.936), P < 0.001) and secondary TCM (OR, 1.538 (95% CI, 1.051-2.251), P = 0.027). Right ventricular involvement (HR, 1.90 (95% CI, 1.14-3.16), P = 0.01) was identified as a predictor of mortality. Physical stressors and diabetes were predictors of both MACE and mortality (P < 0.05). Killip-Kimball class >1 was significantly stronger than dyspnoea (P 0.033 for interaction), while other novel predictors including secondary TCM, diabetes, physical stressors and right ventricular involvement demonstrated comparable effect sizes. CONCLUSION: This study outlines several novel risk factors for poor long-term outcomes in patients with TCM. Identification of these high-risk subpopulations early may allow for more intensive therapy and follow-up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".