Anatomic suitability for transapical transcatheter mitral valve implantation using a tether‐based device
Bibliographic record
Abstract
BACKGROUND: Transcatheter mitral valve implantation (TMVI) is a novel therapeutic option for treating symptomatic mitral valve disease. Evaluating patient anatomical suitability is a critical step in the TMVI screening process, but currently requires specialized software and computerized device models. AIMS: This analysis sought to assess the effectiveness of simple and standardized multislice computed tomography (MSCT) anatomic measurements for their ability to discriminate between patients who passed anatomical screening for Tendyne™ TMVI. METHODS: Subjects screened for the Tendyne Expanded Clinical Study from January 2016 through September 2019 were included. Core laboratory screening measurements included mitral annular (MA) dimensions at end-systole and end-diastole, simulated device implantation, and neo-left ventricular outflow tract (LVOT) area. Additionally, nine standard measurements of patient anatomy were assessed for their predictive value of patients passing the anatomic screening process. RESULTS: Out of 496 subjects screened for eligibility, 257 subjects met clinical eligibility criteria with MA dimensions within the manufacturer's suggested range: 153 (59.5%) underwent TMVI while 104 (40.5%) were excluded from the study for other anatomic reasons (76% due to risk of LVOT obstruction). CT-derived left ventricular end-systole diameter (LVESD) had the highest discriminatory power for predicting TMVI anatomical suitability (area under the curve of 0.908, p < 0.0001). The mitral inter-commissural (IC) dimension was best predictive of annular dimensions being within range, with dimensions <30 or >50 mm resulting in a negative predictive value of 94.4%. CONCLUSIONS: MSCT-derived mitral IC dimension and LVESD easily performed measures that are effective predictors of anatomical suitability or screen failure for this tether-based TMVI device.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.020 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".