Paravalvular regurgitation after transcatheter aortic valve replacement in intermediate-risk patients: a pooled PARTNER 2 study
Bibliographic record
Abstract
BACKGROUND: Moderate or worse paravalvular regurgitation (PVR) post transcatheter aortic valve replacement (TAVR) is associated with increased mortality. The mechanisms by which this occurs are not fully understood. AIMS: The aim of this study was to determine the mechanism by which PVR leads to worse outcomes. METHODS: A total of 1,974 intermediate-risk patients who received TAVR in the PARTNER 2 trial and registries were grouped by PVR severity. Clinical and echocardiographic outcomes were compared. RESULTS: Overall 1,176 (60%) patients had none/trace, 680 (34%) had mild, and 118 (6%) had ≥moderate PVR. At two years, ≥moderate PVR patients had increased risks of all-cause (HR 2.33 [1.41-3.85], p-value=0.001) and cardiovascular death (HR 3.30 [1.74-6.28], p-value <0.001), rehospitalisation (HR 2.68 [1.57-4.58], p-value <0.001), and reintervention (HR 14.72 [3.13-69.32], p-value <0.001). Moderate or worse PVR was associated with larger increases in left ventricular (LV) end-diastolic and systolic dimensions and volumes, LV mass indices, and reductions in LV ejection fractions (LVEFs) from 30 days to two years. Mild PVR was not associated with worse outcomes. Adjusting for LV dimensions and LVEF from the one-year echocardiogram, patients with ≥moderate PVR still had an increased risk of all-cause death or rehospitalisation at two years (HR 2.84 [1.25-5.78], p-value=0.009). CONCLUSIONS: Moderate or worse PVR, but not mild PVR, is associated with an increased risk of all-cause and cardiovascular death, rehospitalisation, and reintervention at two years. Moderate or worse PVR is also associated with adverse LV remodelling, which partially mediates how ≥moderate PVR leads to worse outcomes. These results provide dual insights on the deleterious impact of ≥moderate PVR and the contributing mechanisms of poor clinical outcomes.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".