Investigating health related quality of life and clinical measures in autoimmune encephalitis: a systematic review
Bibliographic record
Abstract
This systematic review sought to understand the types of quality of life or clinical outcome measures currently being utilised for autoimmune encephalitis (AE) patients to determine whether the current measured outcomes accurately represented the full disease burden of AE. This included how the measures were being used (e.g., time point utilised, as an endpoint or as a categorisation method), and what the recorded measures were. The review included all studies that fulfilled the population criteria, which included probable AE. A search conducted on the 24th of June 2024 on PubMed and Embase returned 302 studies that fulfilled the inclusion criteria. Of the 302, the most commonly used measures were the Modified Rankin Scale (mRS) being utilised in 90.07% of studies, followed by Clinical Assessment Scale in Autoimmune Encephalitis (CASE) at 15.56%, Montreal Cognitive Assessment (MoCA) at 7.95%, and finally Mini Mental State Examination (MMSE) at 4.97%. The most common phenotype in the literature was NMDA AE, with 208 studies (68.87%) investigating this cohort. There was significant heterogeneity in the application of measures, such as definitional differences (e.g., a good outcome defined as an mRS of < 1 for some papers, but < 2 for others), utilising measures at differing time points within the disease course of an individual, and the inconsistent reporting of key information, such as comorbidities that may impact the measures being used. This review found the current clinical measures do not holistically encompass the disease burden of AE, with current clinical measures experiencing deficiencies in capturing the effect of AE on sleep and psychosocial function. It is recommended that future studies utilise symptom onset as a standardised time metric, and either a combination of currently available measures, or the creation or validation of new methods to capture disease burden in AE patients.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".