The prognostic importance of the diastolic pulmonary gradient, transpulmonary gradient, and pulmonary vascular resistance in patients undergoing transcatheter aortic valve replacement
Bibliographic record
Abstract
OBJECTIVES: To evaluate the association between markers of precapillary pulmonary hypertension (PH) and survival in transcatheter aortic valve replacement (TAVR). BACKGROUND: The importance of precapillary PH has been sparsely investigated in patients undergoing TAVR. It may prove an important risk factor for poor outcomes. METHODS: We identified patients at our institution undergoing TAVR with a baseline right heart catheterization (RHC) demonstrating PH. We evaluated the association between markers of precapillary PH and survival including the diastolic pulmonary gradient (DPG), transpulmonary gradient (TPG), and pulmonary vascular resistance (PVR). A multivariable analysis was performed using Cox Proportional Hazards Models, adjusting for age, gender, body mass index, and pulmonary artery systolic pressure (PASP) on echocardiography. RESULTS: We identified 133 patients with PH on RHC. Of these 111 had low DPG and 22 had high DPG. All 3 markers of precapillary PH were associated with worse survival post TAVR, with OR of 2.1 (95% CI 1.1-3.9, P = 0.02), 3.4 (95% CI 1.8-6.4, P < 0.001) and 2.5 (95% CI 1.4-4.5, P = 0.003) for high DPG, TPG, and PVR, respectively. On multivariable analysis, both TPG and PVR remained predictors of worse survival, with OR of 3.4 (95% CI 1.7-6.9, P = 0.001) and 2.5 (95% CI 1.4-4.5, P = 0.003). Echocardiographic PASP and DPG were not predictive of survival. CONCLUSIONS: In patients undergoing TAVR, parameters of precapillary PH are associated with lower survival, and provide incremental prognostication over echocardiographic PASP. RHC should continue to play an important role in risk stratification prior to TAVR. © 2017 Wiley Periodicals, Inc.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".