Abstract TP123: Physician perspectives on acute evaluation and determining goals of stroke care for people living with dementia or disability: Results from the SEED mixed-methods study
Bibliographic record
Abstract
Background: Around one in three strokes are experienced by people living with disability or dementia (PLWD), yet there is currently no consensus to guide physicians in evaluating baseline status in this patient population and determining goals of care. We sought to understand how physicians currently approach this complex issue and what challenges they encounter as a critical step towards informing evidence-based best practices for PLWD. Methods: Through separate recruitment strategies, we invited physicians involved in stroke care to participate in semi-structured, in-depth interviews and an online survey, inquiring into perspectives on evaluation and management of PLWD. Interviews were recorded, transcribed, and analyzed applying an interpretive grounded theory approach, using constant comparison throughout the coding process to establish themes and subthemes. Results were triangulated with findings from a descriptive analysis of survey responses. Results: Twenty-eight physicians participated in interviews, while 134 provided survey data, representing 17 countries and 10 medical specialties. Among factors most frequently rated as extremely important in stroke care decision-making (by ≥40% of respondents) were severity of pre-existing dementia/disability and baseline quality of life. Concurrently, interviews highlighted considerable challenges in assessing these factors given time constraints in the acute setting and crudeness of popular screening measures, which fail to capture relevant nuances in patients’ baseline status. Participants further spoke to uncertainties in determining goals of care that align with patients’ best interest. Here, emphasis was placed on the inappropriateness of a mainstream conceptualization of a favorable outcome as maintaining independence, and the need to consider variability in personal and cultural values, support networks, and the broader socioeconomic context. In navigating the complexities of patient-centric care for PLWD who are often unable to voice their wishes, family input and advanced care directives were identified as key facilitators. Conclusions: This mixed-methods study highlights the need for creating evidence-based, tailored strategies for assessing pre-stroke status and defining favourable outcomes for PLWD. Achieving these goals relies on future research co-production with PLWD and their families, ensuring integration of patient priorities and appropriate operationalization of relevant post-stroke outcomes.
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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 | 0.073 | 0.162 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".