Abstract 18185: Regression of Severe Left Ventricular Hypertrophy After Transcatheter Valve Replacement for Aortic Stenosis: Impact on Clinical Outcomes in PARTNER Cohort A
Bibliographic record
Abstract
Background: Left ventricular (LV) mass regression after aortic valve replacement (AVR) for aortic stenosis (AS) is a favorable effect of LV unloading, but its relationship to improved clinical outcomes is unclear. We examined the effect on clinical outcomes after transcatheter AVR (TAVR) of: 1) amount of LV mass index (LVMi) regression; and 2) persistent severe LV hypertrophy (LVH). Methods: Of 2115 patients with symptomatic AS at high surgical risk receiving TAVR in the PARTNER randomized trial or continued access registry, 462 (55% women) who had severe LVH (LVMi ≥149 g/m 2 men, ≥122 g/m 2 women, by ASE criteria) at baseline (BL) and LVMi measured 6 mo post-TAVR were included in our analysis. The effect of LVMi regression was evaluated by comparing outcomes in patients with greater vs. lesser decrease (dichotomized by median % change) in LVMi between BL and 6 mo, and in those without vs. with persistent severe LVH 6 mo post-TAVR. Cox PH models evaluated rates of all-cause mortality (6-12 mo), rehospitalizations (through 1 yr), and the composite of these two outcomes. Results: LVMi decreased from 173±32 (BL) to 121±25 g/m 2 (6 mo) (p<0.001) in those with greater LVMi regression, and from 164±30 (BL) to 158±34 g/m 2 (6 mo) (p<0.001) in those with lesser LVMi regression. Patients with greater vs. lesser LVMi regression had similar baseline clinical characteristics, a lower rate of rehospitalization (10.5% vs. 19.9%, p=0.006) and lower rate of the composite endpoint of death or rehospitalization (13.2% vs. 21.4%, p=0.02), but a similar rate of death (4.9% vs. 4.8%, p=0.86). Persistent severe LVH at 6 mo post-TAVR was present in 54% (58% of whom were women). Patients without vs. with persistent severe LVH had similar baseline clinical characteristics, a lower rate of rehospitalization (11.9% vs. 18.1%, p=0.053) and lower rate of the composite endpoint of death or rehospitalization (13.3% vs. 20.7%, p=0.03), but a similar rate of death (3.9% vs. 5.7%, p=0.42). Similar results were obtained when including patients with moderate or severe LVH. Conclusions: In high-risk patients with severe AS and severe LVH undergoing TAVR, greater LV mass regression and resolution of initially severe LVH at 6 months are associated with a lower rate of death or repeat hospitalization.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".