Improvement in left ventricular function following higher‐risk percutaneous coronary intervention in patients with ischemic cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Surgical revascularization is associated with improved ventricular function and clinical outcomes among patients with ischemic cardiomyopathy. There are less extensive data on changes in ventricular function among patients with ischemic cardiomyopathy undergoing percutaneous coronary intervention (PCI). Accordingly, we sought to assess the extent and predictors of change in left ventricular ejection fraction (ΔLVEF) among patients undergoing hemodynamically-supported PCI. METHODS: We assessed ΔLVEF following hemodynamically-supported PCI (with Impella or intra-aortic balloon counterpulsation) among patients enrolled in the PROTECT II trial and cVAD registry. The ΔLVEF was compared among patients with paired echocardiography at baseline and at least 30 days of follow-up. Independent correlates of ΔLVEF (modeled continuously and with an absolute ΔLVEF≥5%) were assessed using multivariable models. RESULTS: Among the 689 patients with paired echocardiographic data included in the analysis, the mean LVEF improved from 24.8 ± 9.9% to 31.4 ± 13.3% after PCI, for a net increase of 6.5 ± 10.8% (p < .001). A total of 395 (57%) patients had ΔLVEF ≥ 5% following hemodynamically-supported PCI. The number of vessels treated was associated with ΔLVEF (ΔLVEF 5.5% with 1 vessel, 6.6% with 2 vessels, and 8.3% with 3 vessels, p for trend = .046). A lower baseline LVEF, absence of a history of congestive heart failure or aldosterone receptor antagonist use, and a greater number of vessels treated were independent correlates of LVEF improvement. CONCLUSIONS: Among patients with severe left ventricular systolic dysfunction and paired echocardiographic assessments, an improvement in LVEF was observed following hemodynamically-supported PCI.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".