The Efficacy and Safety of Transcranial Photobiomodulation for Mild Cognitive Impairment Due to Alzheimer’s Disease: A Randomized, Double-Blind, Sham-Controlled Study
Bibliographic record
Abstract
Background: Transcranial photobiomodulation (tPBM) is a promising noninvasive neuromodulation modality with potential therapeutic benefits for neurodegenerative diseases. Infrared light delivered by a tPBM device penetrates the cortex, stimulating neuronal activity by increasing mitochondrial adenosine triphosphate production and enhancing regional cerebral blood flow. Objective: This study investigated the efficacy and safety of a self-administered, at-home, wearable tPBM device for improving cognitive function in individuals with mild cognitive impairment (MCI) due to Alzheimer’s disease (AD). Methods: Individuals with MCI due to AD, diagnosed according to the National Institute on Aging and Alzheimer’s Association criteria, with a Korean version of Mini-Mental State Examination-2 (K-MMSE2) score of 23–27 and a global Clinical Dementia Rating (CDR) score of 0.5–1.0 were enrolled. Subjects self-administered tPBM six times per week for 12 weeks. Assessments were conducted at weeks 7 and 13 using the Korean version of the Montreal Cognitive Assessment (K-MoCA), K-MMSE2, the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease, and the Geriatric Depression Scale. Results: A total of 26 participants were enrolled. The treatment group showed a statistically significant improvement in K-MoCA scores at week 13 ( p < 0.05) compared with the sham group. Although K-MMSE2 scores improved in the treatment group, the difference was not statistically significant. No serious adverse events were reported. Conclusion: Findings suggest that tPBM is an effective and safe home-use intervention for individuals with MCI, with promising therapeutic and preventative roles in Alzheimer’s dementia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".