Evaluation of psychiatric symptoms in NMDA receptor encephalitis in predicting clinical deterioration and mortality: a systematic review and qualitative synthesis
Bibliographic record
Abstract
BACKGROUND: NMDA receptor encephalitis is a rare limbic encephalitis where autoantibodies target autogenous receptors in the brain, resulting in symptoms including anxiety, restlessness, psychosis, dyskinesias, central hypoventilation and seizures. A significant proportion of affected individuals have associated germ-cell tumours, or with viral infections presumably unmasking some sort of inflammatory process. Treatment often involves immunosuppression, and due to central hypoventilation can result in ICU stay. Here, we sought to examine whether these psychological and behavioural symptoms have prognostic clinical value. METHOD: Given the rare presentation of NMDA encephalitis, we first conducted a systematic review to find case reports, case series and cohort studies that contained individual patient level data which had both a descriptive data of the clinical presenting symptoms, with particular attention to psychiatric symptoms. We then performed both a quantitative and qualitative analysis of the studies that were included in the analysis. Patient level data was then analyzed quantitatively and qualitatively. RESULT: We analyzed over 500 cases published on NMDA receptor encephalitis, that had enough clinical descriptors of their presentation and outcomes. In particular, we observed trends with regards to demographics, clinical symptoms and clinical outcome. Preliminary data points towards an interesting association with psychiatric symptoms (such as paranoia) and clinical outcomes. CONCLUSION: Psychiatric syndromes may yield important prognostic value in NMDA encephalitis.
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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 | 0.015 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.023 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".