Patient- Specific Functional Scale among people with acute Stroke in Norway
Bibliographic record
Abstract
Purpose: Acute stroke can lead to reduced independence and activity restrictions in daily life. The aims of this study were: 1) to identify which self-reported activities stroke patients had difficulty to perform using the Patient- Specific Functional Scale (PSFS). 2) To evaluate change in PSFS and 3) to investigate different factors associated with change from baseline to 6 months. Design/method: A prospective cohort design where PSFS was used as an outcome measure at baseline, after 4 weeks and 6 months. All activities were classified with ICF. Cognitive function was assessed with Montreal Cognitive Assessment (MoCA). Material: Sixty-one participants, 67 % men, mean age 73 years, were included while admitted to an acute stroke unit. Results: The participants reported 150 activities in PSFS that were classified under the domain mobility (d4), home life (d6) and society and social life areas (d9). There was a statistically significant change on PSFS score from baseline to 6 months. MoCA at baseline was associated with change in PSFS. Conclusion: The participants managed to fill out PFSF and score their difficulty. There was a wide range of activity problems among the participants which suggest that it is important to include patient specific outcome measures for patients with stroke. The participants showed a meaningful change in self-reported activities, and cognitive function was strongest associated with the change in PSFS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".