Impact of left ventricular ejection fraction on 10-year mortality in the SYNTAX trial
Bibliographic record
Abstract
BACKGROUNDS: The impact of reduced left ventricular ejection fraction (LVEF) on very long-term prognosis following percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) has been debated. The aim of this study was to investigate the impact of LVEF at baseline on 10-year mortality in the SYNTAX trial. METHODS: Patients (n = 1800) were categorized into three sub-groups: reduced (rEF ≤ 40 %), mildly reduced (mrEF 41-49 %), and preserved LVEF (pEF ≥ 50 %). The SYNTAX score 2020 (SS-2020) was applied in patients with LVEF<50 % and ≥ 50 %. RESULTS: Ten-year mortalities were 44.0 %, 31.8 %, and 22.6 % (P < 0.001) in patients with rEF (n = 168), mrEF (n = 179), and pEF (n = 1453). Although no significant differences were observed, the mortality with PCI was higher than with CABG in patients with rEF (52.9 % vs 39.6 %, P = 0.054) and mrEF (36.0 % vs. 28.6 %, P = 0.273), and comparable in pEF (23.9 % vs. 22.2 %, P = 0.275). Calibration and discrimination of the SS-2020 in patients with LVEF<50 % were poor, whilst they were reasonable in those with LVEF≥50 %. The proportion of patients eligible for PCI who had a predicted equipoise in mortality with CABG was estimated to be 57.5 % in patients with LVEF≥50 %. CABG was safer than PCI in 62.2 % of patients with LVEF<50 %. CONCLUSIONS: Reduced LVEF was associated with an increased risk of 10-year mortality in patients revascularized either surgically or percutaneously. Compared to PCI, CABG was safe revascularization in patients with LVEF≤40 %. In patients with LVEF≥50 % individualized 10-year all-cause mortality predicted by SS-2020 was helpful in decision-making whilst the predictivity in patients with LVEF<50 % was poor.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".