Abnormal glymphatic system in patients with autoimmune encephalitis: Relationship with cognitive performance
Bibliographic record
Abstract
OBJECTIVES: We aimed to explore the impact of glymphatic function in patients diagnosed with autoimmune encephalitis (AE). METHODS: In this prospective longitudinal study, patients were recruited from Xijing Hospital between June 2020 and January 2024. Glymphatic function was evaluated using diffusion tensor imaging analysis along the perivascular space (DTI-ALPS). Cognitive impairment was defined as a Montreal Cognitive Assessment (MoCA) score below 26 at the 12-month follow-up. RESULTS: A total of 115 individuals were enrolled, including 85 patients with AE and 30 age- and sex-matched healthy controls (HCs). After correcting for age and sex, patients with AE had a significantly lower baseline ALPS index compared to HCs (1.173, 95 % CI [1.135, 1.210] vs. 1.456, 95 % CI [1.371, 1.541]; P < 0.001). The baseline ALPS index was correlated with cognitive performance, including a positive correlation with the Mini-Mental State Examination (MMSE) score (r = 0.568, P < 0.001) and a positive correlation with the MoCA score (r = 0.645, P < 0.001). In the longitudinal study, the ALPS index gradually increased over the follow-up period (P < 0.001), and a low level of the baseline ALPS index was associated with a higher risk of long-term cognitive impairment (HR [95 % CI] = 1.70 [1.12-2.58], P = 0.013). CONCLUSION: The glymphatic system is impaired in AE patients. A decreased DTI-ALPS index is associated with a decline in cognitive performance. Additionally, a low baseline ALPS index may predict an increased risk of long-term cognitive impairment in AE patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".