Impact of anticoagulation therapy on valve haemodynamic deterioration following transcatheter aortic valve replacement
Bibliographic record
Abstract
OBJECTIVE: To evaluate the changes in transvalvular gradients and the incidence of valve haemodynamic deterioration (VHD) following transcatheter aortic valve replacement (TAVR), according to use of anticoagulation therapy. METHODS AND RESULTS: This multicentre study included 2466 patients (46% men; mean age 81±7 years) who underwent TAVR with echocardiography performed at 12-month follow-up. Anticoagulation therapy was used in 707 patients (28.7%) following TAVR (AC group). A total of 663 patients received vitamin K antagonists, and 44 patients received direct oral anticoagulants. A propensity score matching analysis was performed to adjust for intergroup (AC vs non-AC post-TAVR) differences. A total of 622 patients per group were included in the propensity-matched analysis. VHD was defined as a ≥10 mm Hg increase in the mean transprosthetic gradient at follow-up (vs hospital discharge). The mean clinical follow-up was 29±18 months. The mean transvalvular gradient significantly increased at follow-up in the non-AC group within the global cohort (P=0.003), whereas it remained stable over time in the AC group (P=0.323). The incidence of VHD was significantly lower in the AC group (0.6%) compared with the non-AC group (3.7%, P<0.001), and these significant differences remained within the propensity-matched populations (0.6% vs 3.9% in the AC and non-AC groups, respectively, P<0.001). The occurrence of VHD did not associate with an increased risk of all-cause death (P=0.468), cardiovascular death (P=0.539) or stroke (P=0.170) at follow-up. CONCLUSIONS: The lack of anticoagulation therapy post-TAVR was associated with significant increments in transvalvular gradients and a greater risk of VHD. VHD was subclinical in most cases and did not associate with major adverse clinical events. Future randomised trials are needed to determine if systematic anticoagulation therapy post-TAVR would reduce the incidence of VHD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".