A Comparison of the Sensitivity of Brush Allodynia and Semmes–Weinstein Monofilament Testing in the Detection of Allodynia Within Regions of Secondary Hyperalgesia in Humans
Bibliographic record
Abstract
BACKGROUND: Two of the most common Quantitative Sensory Techniques (QST) employed to detect allodynia include mechanical brush allodynia and Semmes-Weinstein monofilaments. However, their relative sensitivity at detecting allodynia is poorly understood. The purpose of this study was to compare the sensitivity of brush allodynia against Semmes-Weinstein monofilament technique for detecting allodynia within regions of secondary hyperalgesia in humans. METHODS: Twenty subjects (10 males, 10 females; 21.1 ± 0.9 years) were recruited and randomly allocated to allodynia or monofilament groups. Topical capsaicin (Zostrix 0.075%) was applied to a target region defined by C4-C7 dermatomes. Allodynia testing was performed at 0- (baseline) and 10 minutes postcapsaicin. The Semmes-Weinstein group assessed changes in skin sensitivity 8 cm inferior to target region and 2 cm lateral to the spinous process, while brush allodynia was employed to detect the point inferior to the target region where subjects reported changes in skin sensitivity. The distance (cm) from this point to the inferior border of the target region was termed the Allodynia Score. RESULTS: Statistically significant increases in the Allodynia Score were observed at 10 minutes postcapsaicin compared to baseline (P < 0.001). No differences in monofilament scores were observed between 10 minutes postcapsaicin and baseline (P = 0.125). Brush allodynia also demonstrated superior sensitivity, detecting allodynia in 100% of cases compared to 60% in the Semmes-Weinstein group. CONCLUSION: Brush allodynia is more sensitive than Semmes-Weinstein monofilaments for detecting mechanical allodynia in regions of secondary hyperalgesia. Brush allodynia may be preferred over Semmes-Weinstein monofilaments for clinical applications requiring reliable detection of allodynia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".