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Record W4402962097 · doi:10.1136/svn-2024-003418

Central post-stroke pain: advances in clinical and preclinical research

2024· review· en· W4402962097 on OpenAlexaff
Xiqian Yuan, Siyuan Hu, Xiaochong Fan, Chao Jiang, Yan Xu, Ruochen Hao, Zili Xu, Yiyang Yu, Yousef Rastegar‐Kashkooli, Leo Huang, Tom J. Wang, Qiao Wang, Songxue Su, Limin Wang, Junyang Wang, Menglu Wang, Yun Tai Kim, Ujjal K. Bhawal, Fushun Wang, Ting Zhao, Junmin Wang, Xuemei Chen, Jian Wang

Bibliographic record

VenueStroke and Vascular Neurology · 2024
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsMedicineClinical trialQuality of life (healthcare)Stroke (engine)Psychological interventionPreclinical researchMEDLINEClinical PracticeIntensive care medicinePhysical therapyMedical physicsPathologyPsychiatry

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.094
GPT teacher head0.463
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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