A NEW ALLODYNOGRAPHY QUANTIFICATION METHOD FOR SOMATOSENSORY REHABILITATION IN COMPLEX REGIONAL PAIN SYNDROME
Bibliographic record
Abstract
Background and aims: Allodynia is an expression of peripheral and/or central sensitization. Complex Regional Pain Syndrome (CRPS) is a persistent pain condition including sensory, motor, trophic and autonomic abnormalities. According to the somatosensory rehabilitation method, allodynia is quantified by allodynography and rainbow pain scale. Allodynography is a mapping technique where its territory is recorded on paper while the rainbow pain scale is rating the severity of the allodynia. To permit a comparison between patients we integrate the Lund and Browder Chart,used in burns for estimating the body surface area affected. This method assesses the allodynography area as a percentage of the affected limb.Methods:25 patients with CRPS, for at least 6 months were recruited. CRPS was diagnosed according to the Budapest Criteria. Allodynia area of all the patients was assessed using the standard allodynography method and quantified with our method. Interrater reliability was evaluated in 4patients. Furthermore, the allodynia area was tested for correlations with CRPS Severity Score (CSS), pain intensity using the short form McGill pain questionnaire (SFMPQ) and upper and lower limb functional scores.Results: Positive significance correlations (Pearson test) were found between the allodynia area and CSS (r=.546, p=.006), days in disease (r=.402, p=0.46), SFMPQ(r=.627, p=.001), and functional scales (r=.640, p=.006). The method was also found reliable between different clinicians (Cronbach's Alpha=.958).Conclusions:This new allodynography quantification method may serve as a inter- and intra-subject variability index for assessment of disease severity and long-term changes along the treatment process.Source of Financial Support:The research was supported by a research grant from Reuth Research and Development Institute, Tel Aviv, Israel.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".