Cardiac Imaging to Screen Anatomical Suitability for Transapical Transcatheter Mitral Valve Implantation with a Tether-Based Device
Bibliographic record
Abstract
All articles of this category Background: This analysis sought to assess effectiveness of simple but standardized multi-slice computed tomography (MSCT) and transthoracic echocardiographic (TTE) measurements for their ability to discriminate between patients who passed anatomical screening for Tendyne (Abbott Vascular, CA, USA) transcatheter mitral valve implantation (TMVI). Method: Between 01/2016 and 09/2019, a total of 496 patients were screened for TMVI. MSCT- and TTE-screening measurements included left ventricle diameter at end-systole (LVESD) and end-diastole (LVEDD) and mitral intercommissural (IC) diameter. Measurements were performed by independent core laboratory blinded to results of MSCT analysis. Receiver operating characteristic (ROC) curves were constructed for anatomic variables of interest. Area under the curve (AUC) was used to characterize performance of each anatomic measurement in correctly classifying subjects as anatomically suitable. Relationship between MSCT and TTE-derived dimensions was assessed using Pearson's correlation and Bland-Altman analysis. Results: Of 257 subjects meeting clinical eligibility criteria and with mitral anulus dimensions within the manufacturer's suggested range, 153 (59.5%) underwent TMVI, while 104 (40.5%) were excluded for other anatomic reasons, with risk of left ventricle outflow tract obstruction being the most common. MSCT-derived LVESD had the highest discriminatory power for predicting anatomical suitability, with an area under the curve of 0.908 ( p < 0.0001). MSCT and TTE measured LVESD-dimension showed a linear correlation ( r = 0.75), but statistical analysis demonstrated a systematic difference with MSCT measurements being ~5.4 ± 7.3 mm larger on average than TTE. LVESD as measured by TTE demonstrated smaller AUC than LVESD assessed by MSCT for predicting anatomical suitability (AUC = 0.840 for TTE vs. 0.908 for MSCT). IC-diameter was systematically underestimated in TTE compared with MSCT (mean difference –3.8 ± 5.1 mm) with a weak linear correlation ( r = 0.555). Conclusion: In addition to MSCT measured effective predictors LVESD and IC-diameter, LVESD measured by TTE can be used as an easy-to-obtain parameter for initial screening of anatomical suitability for this tether-based TMVI device. Publication History Article published online: 03 February 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".