Longitudinal Disability, Cognitive Impairment, and Mood Symptoms in Patients With Anti-NMDA Receptor Encephalitis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Longitudinal outcomes in anti-NMDA receptor encephalitis (anti-NMDARe) are still not fully understood and may not be adequately captured with the modified Rankin Scale (mRS), often the sole reported outcome. We aim to characterize longitudinal outcomes in anti-NMDARe using multiple outcome measures. METHODS: This single-center, retrospective, observational study examined outcome measures (mRS and Clinical Assessment Scale in Autoimmune Encephalitis [CASE]) in adults with NMDA receptor-IgG in CSF at short- and long-term follow-ups using linear and logistic regression modeling. Patients with evaluations for cognitive impairment (Montreal Cognitive Assessment/Mini-Mental State Examination), depression (Patient Health Questionnaire-9), and anxiety (General Anxiety Disorder-7) >6 months from symptom onset were correlated with final CASE scores. RESULTS: < 0.001), only 9 patients (31%) returned to their premorbid function. Among patients with cognitive and mood evaluations >6 months from onset, moderate-severe cognitive impairment (42%), depression (28%), and anxiety (30%) were frequent. Cognitive and depression measures were associated with final CASE subscores (including memory, language, weakness, and psychiatric). DISCUSSION: Multiple clinical factors influenced short-term outcomes, but only onset weakness influenced long-term mRS, highlighting that mRS is predominantly affected by global motor function. Although mRS and CASE improved over time for most patients, these outcome measures did not capture the full extent of long-term functional impairment in terms of mood, cognition, and the ability to return to premorbid function. This emphasizes the need for increased utilization of more nuanced cognitive and mood outcome measures.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".