Efficacy of Intravenous Immunoglobulins and Other Immunotherapies in Neurological Disorders and Immunological Mechanisms Involved
Bibliographic record
Abstract
This review aims to explore the role of immunotherapeutic strategies—primarily intravenous immunoglobulin (IVIG), plasma exchange (PLEX), and selected immunomodulatory agents—in the treatment of neurological and psychiatric disorders with suspected or confirmed autoimmune mechanisms. A central focus is placed on understanding the immunopathology of these conditions through the identification and characterization of disease-associated autoantibodies. Disorders such as autoimmune encephalitis, myasthenia gravis, limbic epilepsy, neuropsychiatric systemic lupus erythematosus (NPSLE), and certain forms of schizophrenia have shown clinical responses to immunotherapy, suggesting an underlying autoimmune basis in a subset of patients. The review also highlights the diagnostic relevance of detecting autoantibodies targeting neuronal receptors, such as NMDA and AMPA receptors, or neuromuscular junction components, as biomarkers that guide therapeutic decisions. Furthermore, we synthesize findings from published randomized controlled trials (RCTs) that have validated the efficacy of IVIG and PLEX in specific diseases, such as Guillain–Barré syndrome, and myasthenia gravis. Emerging clinical evidence supports expanding these treatments to other conditions where autoimmunity is implicated. By integrating immunological insights with clinical trial data, this review offers a comprehensive perspective on how immunotherapies may be tailored to target autoimmune contributors to neuropsychiatric disease.
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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".