Priorities for Patient‐Centered Research in Valvular Heart Disease: A Report From the National Heart, Lung, and Blood Institute Working Group
Bibliographic record
Abstract
Over the past decade, the field of valvular heart disease (VHD) has rapidly transformed, largely as a result of the development and improvement of less invasive transcatheter approaches to valve repair or replacement. This transformation has been supported by numerous well-designed randomized trials, but they have centered almost entirely on devices and procedures. Outside this scope of focus, however, myriad aspects of therapy and management for patients with VHD have either no guidelines or recommendations based only on expert opinion and observational studies. Further, research in VHD has often failed to engage patients to inform study design and identify research questions of greatest importance and relevance from a patient perspective. Accordingly, the National Heart, Lung, and Blood Institute convened a Working Group on Patient-Centered Research in Valvular Heart Disease, composed of clinician and research experts and patient advocacy experts to identify gaps and barriers to research in VHD and identify research priorities. While recognizing that important research remains to be done to test the safety and efficacy of devices and procedures to treat VHD, we intentionally focused less attention on these areas of research as they are more commonly pursued and supported by industry. Herein, we present the patient-centered research gaps, barriers, and priorities in VHD and organized our report according to the "patient journey," including access to care, screening and diagnosis, preprocedure therapy and management, decision making when a procedure is contemplated (clinician and patient perspectives), and postprocedure therapy and management. It is hoped that this report will foster collaboration among diverse stakeholders and highlight for funding bodies the pressing patient-centered research gaps, opportunities, and priorities in VHD in order to produce impactful patient-centered research that will inform and improve patient-centered policy and care.
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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 | 0.224 | 0.198 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.011 | 0.028 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".