Central post-stroke pain: advances in clinical and preclinical research
Bibliographic record
Abstract
Central poststroke pain (CPSP) is a medical complication that arises poststroke and significantly impacts the quality of life and social functioning of affected individuals. Despite ongoing research, the exact pathomechanisms of CPSP remain unclear, and practical treatments are still unavailable. Our review aims to systematically analyse current clinical and preclinical studies on CPSP, which is critical for identifying gaps in knowledge and guiding the development of effective therapies. The review will clarify the clinical characteristics, evaluation scales and contemporary therapeutic approaches for CPSP based on clinical investigations. It will particularly emphasise the CPSP model initiated by stroke, shedding light on its underlying mechanisms and evaluating treatments validated in preclinical studies. Furthermore, the review will not only highlight methodological limitations in animal trials but also offer specific recommendations to researchers to improve the quality of future investigations and guide the development of effective therapies. This review is expected to provide valuable insights into the current knowledge regarding CPSP and can serve as a guide for future research and clinical practice. The review will contribute to the scientific understanding of CPSP and help develop effective clinical interventions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".