Three‐dimensional multidetector computed tomography versus conventional 2‐dimensional transesophageal echocardiography for annular sizing in transcatheter aortic valve replacement: Influence on postprocedural paravalvular aortic regurgitation
Bibliographic record
Abstract
OBJECTIVES: In transcatheter aortic valve replacement (TAVR), the influence of aortic annular assessment with either multidetector computed tomography (MDCT) or conventional transesophageal echocardiography (TEE) on the incidence of postprocedural paravalvular aortic regurgitation (PAR) was evaluated. BACKGROUND: PAR remains a major limitation in TAVR. Appropriate selection of transcatheter heart valve (THV) size is crucial to prevent PAR. METHODS: Outcomes following TAVR with a balloon-expandable THV were compared in two retrospective cohorts identified according to whether THV size selection was based on TEE (study group 1, n = 80) or MDCT (study group 2, n = 58). RESULTS: The two study groups were comparable with regard to baseline clinical, risk score, and echocardiographic characteristics. The incidence of moderate/severe PAR was lower in study group 2 than in group 1, 8.6% versus 28.8% (P < 0.01). The difference between the THV nominal diameter and MDCT annular diameter was predictive of moderate/severe PAR (AUC 0.84; 95% CI: 0.72-0.92). Neither age, gender, body mass index, annular eccentricity index, aortic valve calcification nor the difference between the THV diameter and the TEE annular diameter predicted postprocedural PAR. Increased THV oversizing relative to the MDCT mean annular diameter was associated with reduced severity of PAR. No difference in perprocedural complications between two study groups was observed. CONCLUSION: MDCT-based annular sizing in TAVR significantly reduces postprocedural PAR, and THV oversizing appears pivotal in this aspect. Further delineation of the optimal degree of THV oversizing is needed.
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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 | 0.003 | 0.008 |
| 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".