Clinical Characteristics and Cardiovascular Magnetic Resonance Findings in Stress (Takotsubo) Cardiomyopathy
Bibliographic record
Abstract
CONTEXT: Stress cardiomyopathy (SC) is a transient form of acute heart failure triggered by stressful events and associated with a distinctive left ventricular (LV) contraction pattern. Various aspects of its clinical profile have been described in small single-center populations, but larger, multicenter data sets have been lacking so far. Furthermore, it remains difficult to quickly establish diagnosis on admission. OBJECTIVES: To comprehensively define the clinical spectrum and evolution of SC in a large population, including tissue characterization data from cardiovascular magnetic resonance (CMR) imaging; and to establish a set of CMR criteria suitable for diagnostic decision making in patients acutely presenting with suspected SC. DESIGN, SETTING, AND PATIENTS: Prospective study conducted at 7 tertiary care centers in Europe and North America between January 2005 and October 2010 among 256 patients with SC assessed at the time of presentation as well as 1 to 6 months after the acute event. MAIN OUTCOME MEASURES: Complete recovery of LV dysfunction. RESULTS: Eighty-one percent of patients (n = 207) were postmenopausal women, 8% (n = 20) were younger women (aged ≤50 years), and 11% (n = 29) were men. A stressful trigger could be identified in 182 patients (71%). Cardiovascular magnetic resonance imaging data (available for 239 patients [93%]) revealed 4 distinct patterns of regional ventricular ballooning: apical (n = 197 [82%]), biventricular (n = 81 [34%]), midventricular (n = 40 [17%]), and basal (n = 2 [1%]). Left ventricular ejection fraction was reduced (48% [SD, 11%]; 95% confidence interval [CI], 47%-50%) in all patients. Stress cardiomyopathy was accurately identified by CMR using specific criteria: a typical pattern of LV dysfunction, myocardial edema, absence of significant necrosis/fibrosis, and markers for myocardial inflammation. Follow-up CMR imaging showed complete normalization of LV ejection fraction (66% [SD, 7%]; 95% CI, 64%-68%) and inflammatory markers in the absence of significant fibrosis in all patients. CONCLUSIONS: The clinical profile of SC is considerably broader than reported previously. Cardiovascular magnetic resonance imaging at the time of initial clinical presentation may provide relevant functional and tissue information that might aid in the establishment of the diagnosis of SC.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".