A.1 CSF Findings in Early Active Autoimmune Encephalitis
Bibliographic record
Abstract
Background: Treatment decisions for patients with autoimmune encephalitis (AE) frequently need to be made before results from autoantibody testing are available, as early treatment is associated with better outcomes. Cerebrospinal fluids (CSF) white blood cell (WBC) count and protein concentration measured early on in the disease process is often used, in combination with other clinical factors, to evaluate the likelihood that a patient has AE. Methods: CSF characteristics (WBC count, protein concentration, and oligoclonal banding) measured in a first AE presentation, prior to results of autoantibodies being available, were retrospectively analyzed at two tertiary care centers. Results: Ninety-five patients were included in the study. CSF WBC counts and protein levels were within normal limits for 27% (CI95%: 19–37) of patients with AE. When results of oligoclonal banding were added, 14% (CI95%: 6–16) of patients had “normal” CSF. The median CSF white blood cell count was 8 cells/mm3 (range: 0–544) and the median CSF protein concentration was 0.42 g/L (range: 0.15–3.92). Conclusions: A substantial proportion of patients with early active AE had a CSF WBC count or protein concentration within the normal. Inclusion of CSF oligoclonal banding may help identify a higher proportion of patients with an inflammatory CSF profile early in the disease process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".