Abstract T P295: Identifying Unmet Needs 30-days Following Ischemic Stroke: The Post Stroke Checklist
Bibliographic record
Abstract
Background: Stroke care often focuses on acute intervention and treatment, but important long-term sequelae are sometimes overlooked and may not be captured in standard outcome measures. The Post Stroke Checklist (PSC) is a simple tool recently developed by a global panel of stroke experts to identify the unmet needs of stroke survivors. It consists of 11 items addressing a variety of important medical, functional and social issues. The intent is to improve stroke survivor follow-up and ensure that treatable complications are identified and referred for treatment. Methods: The PSC was administered at 30 days post ischemic stroke in 126 recently hospitalized patients in the outpatient clinic of a Comprehensive Stroke Center. Items were originally scored by a nurse and reviewed with a stroke physician. Age range (median) was 31-97 (68) years. All patients were also scored with Barthel Index (BI), NIH Stroke Scale (NIHSS), and modified Rankin Scale (mRS) during the clinic visit. Actionable items were identified by positive responses to any question on the PSC. The number of patients with actionable items was tabulated. Results: The median (range) BI was 100 (10-100), NIHSS was 1 (0-28), and mRS was 1 (0-4). The PSC identified actionable items in 79/124 (64%) patients. In 39/79 (49%) patients, more than one actionable item was identified. The most common items were depression/anxiety 32 (26%), cognitive dysfunction 28 (23%), decreased ability to perform instrumental ADL’s 18 (15%), and any new pain 13 (10%). All other items were scored positively in less than 10% of patients. The PSC was judged acceptable by both stroke professionals and patients, who felt the items on the PSC identified important issues that otherwise, may have been overlooked in a clinic setting. Conclusions: The PSC proved to be a useful tool at 30 days to identify important unmet needs in stroke survivors with mild deficits. The next step in this research is to evaluate patients at 90 days post stroke, when a larger range of deficits is expected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".