Effect of Baseline Left Ventricular Ejection Fraction on 2-Year Outcomes After Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
Background: Impaired left ventricular function is associated with worse prognosis among patients with aortic stenosis treated medically or with surgical aortic valve replacement. It is unclear whether reduced left ventricular ejection fraction (LVEF) is an independent predictor of adverse outcomes after transcatheter aortic valve replacement. Methods and Results: Patients who underwent transcatheter aortic valve replacement in the PARTNER 2 trials (Placement of Aortic Transcatheter Valves) and registries were stratified according to presence of reduced LVEF (<50%) at baseline, and 2-year risk of cardiovascular mortality was compared using Kaplan–Meier methods and multivariable Cox proportional hazards regression. Of 2991 patients, 839 (28%) had reduced LVEF. These patients were younger, more often males, and were more likely to have comorbidities, such as coronary disease, diabetes mellitus, and renal insufficiency. Compared with patients with normal LVEF, patients with low LVEF had higher crude rates of 2-year cardiovascular mortality (19.8% versus 12.0%, P <0.0001) and all-cause mortality (27.4% versus 19.2%, P <0.0001). Mean aortic valve gradient was not associated with clinical outcomes other than heart failure hospitalizations (hazard ratio [HR], 0.99; CI, 0.99–1.00; P =0.03). After multivariable adjustment, patients with reduced versus normal LVEF had significantly higher adjusted risk of cardiovascular death (adjusted HR, 1.42, 95% CI, 1.11–1.81; P =0.005), but not all-cause death (adjusted HR, 1.20; 95% CI, 0.99–1.47; P =0.07). When LVEF was treated as continuous variable, it was associated with increased 2-year risk of both cardiovascular mortality (adjusted HR per 10% decrease in LVEF, 1.16; 95% CI, 1.07–1.27; P =0.0006) and all-cause mortality (adjusted HR, 1.09; 95% CI, 1.01–1.16; P =0.02). Conclusions: In this patient-level pooled analysis of PARTNER 2 patients who underwent transcatheter aortic valve replacement, baseline LVEF was an independent predictor of 2-year cardiovascular mortality. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifiers: NCT01314313, NCT02184442, NCT03222128, and NCT02184441.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".