Temporal Pattern of Cortical Hypoxia in Multiple Sclerosis and Its Significance on Neuropsychological and Clinical Measures of Disability
Bibliographic record
Abstract
Objective Multiple sclerosis (MS) is a degenerative disease of the central nervous system (CNS) characterized by inflammation, demyelination, and axonal damage. It has been hypothesized that hypoxia plays a role in the pathogenesis of MS. This study was undertaken to investigate the reproducibility of non‐invasively measured cortical microvascular hemoglobin oxygenation (StO2) using frequency domain near‐infrared spectroscopy (fdNIRS), investigate its temporal pattern of hypoxia in people with MS (pwMS), and its relationship with neurocognitive function and mood. Methods We investigated the reproducibility of fdNIRS measurements. We measured cortical hypoxia in pwMS, and the relationships between StO2, neurocognitive function, fatigue, and measures of physical disability. Furthermore, we cataloged the temporal pattern of StO2 measured at 1‐week intervals for 4 weeks, and at 8 weeks and ~1 year. Results We show that fdNIRS parameters were highly reproducible in 7 healthy control participants measured over 6 days (p > 0.05). There was low variability between and within subjects. In line with our previous findings, we show that 33% of pwMS (n = 88) have cortical microvascular hypoxia. Over 8 weeks and at ~1 year, StO2 values for normoxic and hypoxic groups did not change significantly. There was no significant association between cognitive function and StO2. This conclusion should be revisited as only a small proportion of the relapsing‐remitting MS group (21%) was cognitively impaired. Interpretation The fdNIRS parameters have high reproducibility and repeatability, and we have demonstrated that hypoxia in MS is a chronic condition, lasting at least a year. The results show a weak relationship between cognitive functioning and oxygenation, indicating future study is required. ANN NEUROL 2023;94:1067–1079
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".