Apical ballooning syndrome or takotsubo cardiomyopathy: a systematic review
Bibliographic record
Abstract
AIMS: To clarify the major features of the apical ballooning syndrome, we performed a systematic review of the existing literature. METHODS AND RESULTS: Review of all relevant case series using the MEDLINE and EMBASE databases resulted in the identification of 14 studies. These studies suggest that the apical ballooning syndrome accounts for approximately 2.0% of ST-segment elevation infarcts, with most cases described in post-menopausal women. The most common clinical presentations are chest pain and dyspnoea, reported in 67.8 and 17.8% of the patients, respectively. Cardiogenic shock (4.2% of the patients) and ventricular fibrillation (1.5%) were not infrequent. ST-segment elevation was reported in 81.6% of the patients, T wave abnormalities in 64.3%, and Q waves in 31.8%. Cardiac biomarkers were usually mildly elevated, as reported in 86.2% of the patients. Typically, patients had left ventricular (LV) dysfunction on admission, with mean ejection fraction ranging from 20 to 49%. However, over a period of days to weeks, all patients experienced dramatic improvement in LV function. The onset of symptoms was often preceded by emotional (26.8%) or physical stress (37.8%). Norepinephrine concentration was elevated in 74.3% of the patients. Prognosis was generally excellent, with full recovery in most patients. In-hospital mortality was 1.1%. Only 3.5% of the patients experienced a recurrence. CONCLUSION: Clinicians should consider this syndrome in the differential diagnosis of patients presenting with chest pain, especially in post-menopausal women with a recent history of emotional or physical stress.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".