Relationship of immune cells with disability and cognitive impairment in patients with neuromyelitis optica spectrum disorder.
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the relationship between common clinical immune indicators, disability degree, and cognitive impairment in patients with neuromyelitis optica spectrum disorder (NMOSD). PATIENTS AND METHODS: We retrospectively analyzed lymphocyte subsets and routine parameters in the peripheral blood of 55 patients with NMOSD. We assessed the degree of disability using the Extended Disability Status Scale (EDSS). The Montreal Cognitive Assessment (MoCA) scores were used to assess cognitive function. In addition, we also determined the cytokine levels in 33 patients with NMOSD. The relationships of these immunological indicators with disability and cognitive impairment were assessed using correlation and multiple linear regression analyses. RESULTS: The results of the multiple linear regression analysis suggested that for patients with NMOSD, the neutrophil-lymphocyte ratio (NLR) (β=0.072, p=0.034) and number of attacks (β=0.131, p=0.03) were positively correlated with EDSS scores, whereas the number of attacks was positively correlated with MoCA scores. In addition, we also collected cytokine levels in 33 of these patients. The results of the study showed a positive correlation between IL-10 and EDSS scores and a negative correlation between IL-6 and MoCA scores. CONCLUSIONS: Our results show that these immune cells and cytokines are, to some extent, associated with the degree of disability and cognitive impairment in patients with NMOSD. Closely monitoring these indicators may allow detecting changes in patients' disease courses and predicting the severity of their disease. In clinical practice, this may facilitate early intervention and appropriate treatment decisions, which may improve the management of patient prognosis.
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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) | 0.000 | 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) | 0.001 | 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".