Memory Deficits in Cancer Patients With Serum NMDA Receptor Autoantibodies
Bibliographic record
Abstract
OBJECTIVES: Neuronal autoantibodies are linked to cognitive impairment in neurologic diseases and can be associated with tumors. In patients with cancer, IgA/IgM N-Methyl-D-Aspartate receptor (NMDAR) autoantibodies are most common, yet their clinical relevance is unclear. We assessed cognitive function in cancer patients with serum NMDAR autoantibodies and compared the results with matched controls. METHODS: For this cross-sectional case-control study in Germany, we recruited 1,055 patients with cancer and tested for neuronal serum autoantibodies. Cognitive assessment was performed blinded to antibody status and after excluding patients with potential confounders of cognitive dysfunction. The tests included verbal memory (Rey Auditory Verbal Learning Test), visuospatial memory (Rey-Osterrieth Complex Figure), and working memory. RESULTS: = 0.40). Memory function decreased with increasing IgA NMDAR autoantibody levels. Both groups performed similarly on measures of attention, executive function, and verbal fluency. DISCUSSION: Serum NMDAR autoantibodies are associated with isolated memory deficits in patients with cancer and might serve as a potential biomarker for cancer-related cognitive impairment.
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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 | 0.002 |
| 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) | 0.002 | 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".