EFFECTS OF MLS-LASER ON NEUROPATHIC PAIN IN DIABETIC SENSОMOTOR NEUROPATHY
Bibliographic record
Abstract
About 20-50 % of patients with diabetes and about 60 % of those with diabetic neuropathy develop neuropathic pain, which is characterized by tingling, burning, sharp, shooting, or stabbing sensations, and even electric shock-like sensations. Painful diabetic neuropathy can significantly affect the quality of life of patients with diabetes, the ability to perform daily activities and negatively affect mood. According to the 2021 consensus of an international panel of experts regarding the treatment of painful distal symmetric polyneuropathy, non-pharmacological forms of treatment should also be considered due to unsatisfactory pharmacotherapy. A number of studies have demonstrated the role of photobiomodulation as a non-pharmacological method of treating painful diabetic neuropathy. The purpose of this placebo-controlled, longitudinal study was to investigate the effect of high-energy MLS-laser therapy on neuropathic pain. Material and methods: A total of 69 cases of patients with type 2 diabetes and painful diabetic neuropathy of the lower extremities were followed, divided into two groups: an experimental - 41 patients received high-energy laser radiation and a control (placebo) group - 28 patients, with a "mock" laser treatment. For objectification of pain, the Bulgarian version of the short form of the McGill pain questionnaire, version SF-MPQ-2, which includes the visual analog scale (VAS), was used. Comparisons between groups were performed with parametric or non parametric tests depending on the distribution of the variables, the number of the compared groups and the study pre test – post test design. Results: The pain index, reported by the McGill questionnaire, in the experimental group, decreased by - 63.2 % at the end of the nine-day treatment and by - 56.1 % at the 90th day after the start of treatment compared to the value before therapy. In the control group, there was a minimal change at the end of treatment (day 21), which did not persist until the end of the observation period (day 90). Conclusions: MLS laser therapy significantly increases the pain threshold and should be considered a safe, non-pharmacological adjunct to standard therapy in patients with painful diabetic peripheral neuropathy.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".