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Record W4405569256 · doi:10.1186/s10194-024-01932-x

Pain profiling in migraine: a systematic review of Quantitative Sensory Testing (QST), Conditioned Pain Modulation (CPM), and Corneal Confocal Microscopy (CCM)

2024· review· en· W4405569256 on OpenAlexaboutno aff
Floor C. van Welie, Albert Dahan, Monique van Velzen, Gisela M. Terwindt

Bibliographic record

VenueThe Journal of Headache and Pain · 2024
Typereview
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMigraineQuantitative sensory testingMedicineChronic MigraineVisual analogue scaleSensory systemChronic painAudiologyAnesthesiaPhysical therapyPsychologyNeuroscience

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this systematic review is to identify pain profiling parameters that are reliably different between patients with migraine and healthy controls, using Quantitative Sensory Testing (QST) including Temporal Summation (TS), Conditioned Pain Modulation (CPM), and Corneal Confocal Microscopy (CCM). METHODS: A comprehensive literature search was conducted (up to 23 May 2024). The quality of the research was assessed using the Newcastle-Ottawa Scale (NOS) for non-randomized studies. RESULTS: Twenty-eight studies were included after screening. The QST studies indicate that migraine patients exhibit lower pressure pain thresholds (PPT), particularly in the trigeminal region. A previous meta-analysis reported lower heat pain thresholds (HPT). CPM studies suggest a (mild) inhibitory or absent response in migraine patients, not different from controls. High-frequency and chronic migraine patients may exhibit a facilitatory CPM response. With repeated executions of CPM, migraine patients display a diminishing CPM response, a phenomenon not observed in control subjects. CCM investigations in migraine patients revealed conflicting outcomes, likely as a result of small sample sizes and limited characterization of migraine features. CONCLUSION: Pain profiling migraine patients varies due to sensory modality, applied methods, anatomical sites, and migraine features. Understanding pain profiling offers insights into migraine pathophysiology, requiring careful selection of parameters and differentiation among migraine subtypes.

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)0.034
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.105
GPT teacher head0.395
Teacher spread0.291 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
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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