Post Stroke Pain: Identification, Assessment, and Therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Pain is a common complication after stroke and is associated with the presence of depression, cognitive dysfunction, and impaired quality of life. It remains underdiagnosed and undertreated, despite evidence that effective treatment of pain may improve function and quality of life. SUMMARY: We provide an overview of the means for clinical assessment and risk factors for the development of post-stroke pain, then review the newest available literature regarding the commonest post-stroke pain syndromes, including central post-stroke pain, complex regional pain syndrome, musculoskeletal pain including shoulder subluxation, spasticity-related pain, and post-stroke headache, as well as the available epidemiology and current treatment options. Key Messages: In the best interests of optimizing quality of life and function after stroke, clinicians should be aware of pain as a common complication after stroke, identify those patients at highest risk, directly inquire as to the presence and characteristics of pain, and should be aware of the options for treatment for the various pain syndromes.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it