Implementation of shared decision-making for aortic stenosis: Development of a patient decision aid
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background People living with aortic stenosis (AS) experience poor quality of life (QOL), repeat hospitalizations, and a poor prognosis in the absence of valve replacement. There is increasing equipoise in the evidence supporting the use of surgical aortic valve replacement (SAVR) and transcatheter aortic valve implantation (TAVI) in patients likely to derive survival and QOL benefit. A transition to a palliative approach may be a better option in the setting of excessive frailty and comorbid burden. Shared decision-making (SDM) is a bidirectional exchange between patients and health care providers that enables an information exchange about the best available evidence and decisions that consider patients" priorities. The goal is to inform and empower patients to participate in choosing the right decision. Patient decision aids (PDAs) are designed to support the process of SDM and help guide these conversation. To date, Canadians living with AS have not had access to a validated PDA. Study Design We will report on the design of the SharEd DEcision-MaKing for AS (SEEK-AS) study that aims to refine and comprehensively evaluate a set of PDAs and to build capacity for SDM through a unique partnership of patient and clinical knowledge users, multidisciplinary health care providers and researchers, and policy-makers. We will summarize the pilot work completed to obtain a debrief of patient resources used in all Canadian provinces, the draft development of a PDA in concert with a health policy initiative, and the design of an electronic platform to individualize risk in real time during a consultation. We will outline the components of SEEK-AS and the use of a cross-provincial comparative case study design to investigate how to establish an effective and sustainable approach for the implementation of the PDAs using the Knowledge-to-Action conceptual framework. Implications There is a pressing need for the development of evidence-based tools to strengthen the integration of patients" perspectives in the treatment of complex valvular heart disease given the rapid pace of change in technology, indications and practice. The study of the implementation of innovative strategies to achieve this goal is essential to accelerate the pace of change in clinical 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 | 0.063 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".