Brazilian consensus recommendations on the diagnosis and treatment of autoimmune encephalitis in the adult and pediatric populations
Bibliographic record
Abstract
BACKGROUND: Autoimmune encephalitis (AIE) is a group of inflammatory diseases characterized by the presence of antibodies against neuronal and glial antigens, leading to subacute psychiatric symptoms, memory complaints, and movement disorders. The patients are predominantly young, and delays in treatment are associated with worse prognosis. OBJECTIVE: With the support of the Brazilian Academy of Neurology (Academia Brasileira de Neurologia, ABN) and the Brazilian Society of Child Neurology (Sociedade Brasileira de Neurologia Infantil, SBNI), a consensus on the diagnosis and treatment of AIE in Brazil was developed using the Delphi method. METHODS: A total of 25 panelists, including adult and child neurologists, participated in the study. RESULTS: The panelists agreed that patients fulfilling criteria for possible AIE should be screened for antineuronal antibodies in the serum and cerebrospinal fluid (CSF) using the tissue-based assay (TBA) and cell-based assay (CBA) techniques. Children should also be screened for anti-myelin oligodendrocyte glucoprotein antibodies (anti-MOG). Treatment should be started within the first 4 weeks of symptoms. The first-line option is methylprednisolone plus intravenous immunoglobulin (IVIG) or plasmapheresis, the second-line includes rituximab and/or cyclophosphamide, while third-line treatment options are bortezomib and tocilizumab. Most seizures in AIE are symptomatic, and antiseizure medications may be weaned after the acute stage. In anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis, the panelists have agreed that oral immunosuppressant agents should not be used. Patients should be evaluated at the acute and postacute stages using functional and cognitive scales, such as the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Modified Rankin Scale (mRS), and the Clinical Assessment Scale in Autoimmune Encephalitis (CASE). CONCLUSION: The present study provides tangible evidence for the effective management of AIE patients within the Brazilian healthcare system.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".