Use of either transcranial or <scp>whole‐body</scp> photobiomodulation treatments improves <scp>COVID</scp>‐19 brain fog
Bibliographic record
Abstract
There is increasing recognition of post-COVID-19 sequelae involving chronic fatigue and brain fog, for which photobiomodulation (PBM) therapy has been utilized. This open-label, pilot, human clinical study examined the efficacy of two PBM devices, for example, a helmet (1070 nm) for transcranial (tPBM) and a light bed (660 and 850 nm) for whole body (wbPBM), over a 4-week period, with 12 treatments for two separate groups (n = 7 per group). Subjects were evaluated with a neuropsychological test battery, including the Montreal Cognitive Assessment (MoCA), the digit symbol substitution test (DSST), the trail-making tests A and B, the physical reaction time (PRT), and a quantitative electroencephalography system (WAVi), both pre- and post- the treatment series. Each device for PBM delivery was associated with significant improvements in cognitive tests (p < 0.05 and beyond). Changes in WAVi supported the findings. This study outlines the benefits of utilizing PBM therapy (transcranial or whole-body) to help treat long-COVID brain fog.
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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".