Impact of Impella protected-percutaneous coronary intervention on left ventricle function recovery of patients with extensive coronary disease and poor left ventricular function
Bibliographic record
Abstract
BACKGROUND: The use of Impella support is increasingly adopted to "protect" patients with severe coronary artery disease (CAD) and left ventricle (LV) dysfunction undergoing percutaneous coronary intervention (PCI). AIMS: To evaluate the impact of Impella-protected (Abiomed, Danvers, Massachusetts, USA) PCIs on myocardial function recovery. METHODS: Patients with significant LV dysfunction undergoing multi-vessel PCIs with pre-intervention Impella implantation were evaluated by echocardiography before PCI and at median follow up of 6 months: global and segmental LV contractile function were assessed by LV ejection fraction (LVEF) and wall motion score index (WMSI), respectively. Extent of revascularization was graded using the British Cardiovascular Intervention Society Jeopardy score (BCIS-JS). Study endpoints were LVEF and WMSI improvement, and its correlation with revascularization. RESULTS: A total of 48 high surgical risk (mean EuroSCORE II 8) patients with median LVEF value of 30%, extensive wall motion abnormalities (median WMSI 2.16), and severe multi-vessel CAD (mean SYNTAX score 35) were included. PCIs brought a significant reduction of ischemic myocardium burden with BCIS-JS decrease from mean value of 12 to 4 (p < 0.001). At follow-up, WMSI reduced from 2.2 to 2.0 (p = 0.004) and LVEF increased from 30% to 35% (p = 0.016). WMSI improvement was proportional to the baseline impairment (R - 0.50, p < 0.001), and confined to revascularized segments (from 2.1 to 1.9, p < 0.001). CONCLUSIONS: In patients with extensive CAD and severe LV dysfunction, multi-vessel Impella-protected PCI was associated to an appreciable contractile recovery, mainly determined by regional wall motion improvement in revascularized segments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".