Influence of baseline left ventricular function on the clinical outcome of surgical ventricular reconstruction in patients with ischaemic cardiomyopathy
Bibliographic record
Abstract
AIMS: The Surgical Treatment for Ischemic Heart Failure (STICH) trial demonstrated no overall benefit when surgical ventricular reconstruction (SVR) was added to coronary artery bypass grafting (CABG) in patients with ischaemic cardiomyopathy. The present analysis was to determine whether, based on baseline left ventricular (LV) function parameters, any subgroups could be identified that benefited from SVR. METHODS AND RESULTS: Among the 1000 patients enrolled, Core Lab measures of baseline LV function with adequate quality were obtained in 710 patients using echocardiography, in 352 using cardiovascular magnetic resonance, and in 344 using radionuclide imaging. The relationship between LV end-systolic volume index (ESVI), end-diastolic volume index, ejection fraction (EF), regional wall motion abnormalities, and outcome were first assessed only by echocardiographic measures, and then by 13 algorithms using a different hierarchy of imaging modalities and their quality. The median ESVI and EF were 78.0 (range: 22.8-283.8) mL/m2 and 28.0%, respectively. Hazard ratios comparing the randomized arms by subgroups of LVESVI and LVEF measured by echocardiography found that patients with smaller ventricles (LVESVI <60 mL/m2) and better LVEF (≥33%) may have benefitted by SVR, while those with larger ventricles (LVESVI >90 mL/m(2)) and lower LVEF (≤25%) did worse with SVR. Algorithms using all three imaging modalities found a weaker relationship between LV global function and the effects of SVR. The extent of regional wall motion abnormality did not influence the effects of SVR. CONCLUSIONS: Subgroup analyses of the STICH trial suggest that patients with less dilated LV and better LVEF may benefit from SVR, while those with larger LV and poorer LVEF may do worse. Clinical Trial Registration #: NCT00023595.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".