Effect of optically modified polyethylene terephthalate fiber socks on chronic foot pain
Bibliographic record
Abstract
BACKGROUND: Increasing experimental and clinical evidence suggests that illumination of the skin with relatively low intensity light may lead to therapeutic results such as reduced pain or improved wound healing. The goal of this study was to evaluate prospectively whether socks made from polyethylene terephthalate (PET) incorporating optically active particles (Celliant) ameliorates chronic foot pain resulting from diabetic neuropathy or other disorders. Such optically modified fiber is thought to modify the illumination of the skin in the visible and infrared portions of the spectrum, and consequently reduce pain. METHODS: A double-blind, randomized trial with 55 subjects (38 men, 17 women) enrolled (average age 59.7 +/- 11.9 years), 26 with diabetic neuropathy and 29 with other pain etiologies. Subjects twice completed the Visual Analogue Scale (VAS), Brief Pain Inventory (BPI), McGill Pain Questionnaire (MPQ), and SF-36 a week apart (W(1+2)) before receiving either control or Celliant socks. The same questionnaires were answered again one and two weeks (W(3+4)) later. The questionnaires provided nine scores for analyzing pain reduction: one VAS score, two BPI scores, five MPQ scores, and the bodily pain score on the SF-36. Mean W(1+2) and W(3+4) scores were compared to measure pain reduction. RESULTS: More pain reduction was reported by Celliant subjects for 8 of the 9 pain questions employed, with a significant (p = 0.043) difference between controls and Celliant for McGill question III. In neuropathic subjects, Celliant caused more pain reduction in 6 of the 9 questions, but not significantly. In non-neuropathic subjects 8 of 9 questions showed more pain reduction with the Celliant socks. CONCLUSION: Socks with optically modified PET (Celliant) appear to have a beneficial impact on chronic foot pain. The mechanism could be related to the effects seen with illumination of tissues with visible and infrared light. TRIAL REGISTRATION: ClinicalTrials.gov NCT00458497.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| 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".