Man-machine interaction-based phenotyping preprocedurally identifies patients with severe aortic stenosis, who will not recover from cardiac damage following transcatheter aortic valve replacement
Bibliographic record
Abstract
Abstract Background Severe aortic stenosis (AS) can lead to left heart dysfunction, pulmonary hypertension (PH), and eventually right heart failure. Clinical phenotypes therefore appear heterogeneous, depending on disease progression and comorbidities. Purpose This study therefore sought to improve diagnostic and prognostic resolution in patients undergoing transcatheter aortic valve replacement (TAVR) for severe AS by developing a man-machine interaction-based phenotyping approach. Methods Unsupervised agglomerative clustering was applied to preprocedural data from echocardiography and right heart catheterization from 366 consecutively enrolled patients undergoing TAVR for severe AS. Echocardiographic follow-up data, obtained on day 147±75.1 after TAVR, were available from 247 patients (67.5%). Results Cluster analysis revealed four distinct phenotypes, reflecting various extents of disease severity, and hence differing in mortality. Patients from cluster 1 presented with preserved left ventricular ejection fraction (LVEF; 57.2±6.4%) and with normal mean pulmonary artery pressure (mPAP) levels (21.2±6.5 mmHg). In contrast, patients in cluster 2 suffered from postcapillary PH (mPAP: 34.2±7.8 mmHg). Left heart failure (LVEF: 42.4±15.7%), severe PH (mPAP: 46.9±8.5 mmHg), and right heart dysfunction (tricuspid annular plane systolic excursion [TAPSE]: 16.1±4.57 mm) characterized patients in cluster 3. Patients from cluster 4 showed mild postcapillary PH (mPAP: 27.5±9.2 mmHg), yet dilatation of all heart chambers, biventricular dysfunction (LVEF: 47.3±12.2%, TAPSE: 16.8±4.5 mm), and a high prevalence of both mitral and tricuspid regurgitation (12.5% and 14.8%, respectively). Correction of severe AS by TAVR significantly reduced the proportion of patients suffering from concurrent severe mitral regurgitation (from 9.29% to 3.64%, p-value: 0.0015). Moreover, pulmonary artery pressures were ameliorated (estimated systolic pulmonary artery pressure: from 47.2±15.8 mmHg to 43.3±15.1 mmHg, p-value: 0.0079). However, right heart dysfunction as well as the proportion of patients with severe tricuspid regurgitation remained unchanged. Clusters 3 and 4 with persistent right heart dysfunction ultimately displayed 2-year survival rates of 69.2% (95% CI: 56.6–84.7%) and 74.6% (95% CI: 65.9–84.4%), which were significantly lower compared to clusters 1 and 2 with little or no persistent cardiopulmonary impairment (88.3% [95% CI: 83.3–93.5%] and 85.5% [95% CI: 77.1–94.8%]). Conclusion This phenotyping approach preprocedurally identifies patients with severe AS, who will not recover from extra-aortic valve cardiac damage following TAVR and whose survival is therefore significantly reduced. Importantly, not the degree of PH at initial presentation, but the irreversibility of right heart dysfunction determines prognosis. Funding Acknowledgement Type of funding sources: None.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".