Diastolic function improvement is associated with favourable outcomes in patients with acute non-ischaemic cardiomyopathy: insights from the multicentre IMAC-2 trial
Bibliographic record
Abstract
AIMS: Patients with recent onset non-ischaemic cardiomyopathy have a variable clinical course with respect to recovery of left ventricular ejection fraction (LVEF). The aim of this study was to understand whether temporal changes in diastolic function (DF) are associated with clinical outcomes independent of LVEF recovery. METHODS AND RESULTS: The Intervention in Myocarditis and Acute Cardiomyopathy (IMAC)-2 study was a prospective, multicentre trial investigating myocardial recovery in subjects with symptoms onset of <6 months and LVEF ≤40% of non-ischaemic dilated cardiomyopathy related to idiopathic cardiomyopathy or myocarditis. LVEF and DF were measured at presentation and at 6-month follow-up. Of 147 patients (mean age 46 ± 14 years, 40% female), baseline LVEF was 23 ± 8%. At 6 months, LVEF improved to 41 ± 12%, with 71% increasing by at least 10% ejection fraction units. DF improved in 58%, was unchanged in 28%, and worsened in 14%. Over a mean follow-up of 1.8 ± 1.2 years, there were 18 events: 11 heart failure (HF) hospitalizations, 3 deaths, and 4 heart transplants. LVEF (HR = 0.94, 95% CI 0.91-0.98, P = 0.002) and DF improvements at 6 months (HR = 0.32, 95% CI 0.11-0.92, P = 0.03) were independently associated with lower likelihood for the combined end point of death, transplantation, and HF hospitalization. Diastolic functional improvement at 6-month follow-up was as prognostically important as LVEF recovery for these patients, and provided incremental prognostic value to the risk stratification (X(2) increased from 12.6 to 18, P = 0.02). CONCLUSION: In patients with recent onset non-ischaemic cardiomyopathy, DF recovery was associated with favourable outcomes independent of LVEF improvement, adding incremental prognostic value to these patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".