Expanding the Spectrum of TEER Suitability
Bibliographic record
Abstract
BACKGROUND: Anatomical and clinical criteria to define mitral transcatheter edge-to-edge repair (TEER) "unsuitability" have been proposed on the basis of a Heart Valve Collaboratory consensus opinion from physician experience with early-generation TEER devices but lacked an evidence-based approach. OBJECTIVES: The aim of this study was to explore the spectrum of TEER suitability using echocardiographic and clinical outcomes from the EXPAND G4 real-world postapproval study. METHODS: EXPAND G4 is a global, prospective, multicenter, single-arm study that enrolled 1,164 subjects with mitral regurgitation (MR) treated with the MitraClip G4 System. Three groups were defined using the Heart Valve Collaboratory TEER unsuitability criteria: 1) risk of stenosis (RoS); 2) risk of inadequate MR reduction (RoIR); and 3) subjects with baseline moderate or less MR (MMR). A TEER-suitable (TS) group was defined by the absence of these characteristics. Endpoints included independent core laboratory-assessed echocardiographic characteristics, procedural outcomes, MR reduction, NYHA functional class, Kansas City Cardiomyopathy Questionnaire score, and major adverse events through 30 days. RESULTS: Subjects in the RoS (n = 56), RoIR (n = 54), MMR (n = 326), and TS (n = 303) groups had high 30-day MR reduction rates (≤1+: RoS 97%, MMR 93%, and TS 91%; ≤2+: RoIR 94%). Thirty-day improvements in functional capacity (NYHA functional class I or II at 30 days vs baseline: RoS 94% vs 29%, RoIR 88% vs 30%, MMR 79% vs 26%, and TS 83% vs 33%) and quality of life (change in Kansas City Cardiomyopathy Questionnaire score: RoS +27 ± 26, RoIR +16 ± 26, MMR +19 ± 26, and TS +19 ± 24) were safely achieved in all groups, with low major adverse events (<3%) and all-cause mortality (RoS 1.8%, RoIR 0%, MMR 1.5%, and TS 1.3%). CONCLUSIONS: Patients previously deemed TEER unsuitable can be safely and effectively treated with the mitral TEER fourth-generation device.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".