Remote digital cognitive assessment reveals cognitive deficits related to hippocampal atrophy in autoimmune limbic encephalitis: a cross-sectional validation study
Bibliographic record
Abstract
Background: Autoimmune limbic encephalitis (ALE) is a neurological disease characterised by inflammation of the limbic regions of the brain, mediated by pathogenic autoantibodies. Because cognitive deficits persist following acute treatment of ALE, the accurate assessment of long-term cognitive outcomes is important for clinical assessments and trials. However, evaluating cognition is costly and an unmet need exists for validated digital methods. Methods: In this cross-sectional validation study, we investigated whether a remote digital platform could identify previously characterised cognitive impairments in patients with chronic ALE and whether digital metrics would correlate with standard neuropsychological assessment and hippocampal volume. Patients with ALE who had a chronic and stable presentation and received a clinical diagnosis of ALE were recruited for this study. The cognitive performance of 21 patients with ALE and 54 age-matched healthy controls - enrolled via the University of Oxford (UK) Cognitive Neurology Lab testing programme - was assessed with a battery of 12 cognitive tasks from the Cognitron online platform. The platform was optimised with National Institute for Health and Care Research (NIHR) support to be deliverable remotely to elderly and patient groups. The primary outcome measure was behavioural performance and corresponding neuroimaging and neuropsychological assessment metrics. Findings: Between February 15, 2021, and April 21, 2022, 21 patients with ALE (mean age 63.01 years, 14 males) and 54 healthy controls (mean age 65.56 years, 23 males) completed the digital cognitive assessment. Patients with ALE performed significantly worse in memory, visuospatial abilities, executive function, and language. No impairments in digit & spatial span, target detection (attention) and emotion discrimination were observed. The global score on the online cognitive tasks correlated significantly with the established Addenbrooke's Cognitive Examination III (ACE) pen-and-paper test. Deficits in visuospatial processing and language were identified in ALE compared to controls using remote digital testing but not using the ACE, highlighting higher sensitivity of computerised testing to residual cognitive impairment. Finally, the hippocampal volumes of patients with ALE and healthy controls correlated with online cognitive scores. Interpretation: These findings demonstrate that subtle cognitive deficits in patients with chronic ALE, who often show full recovery in measures of disability and dependence on daily activities, are detectable using a remote online platform, which also relates to hippocampal atrophy. Such methods may facilitate the characterisation of cognitive profiles in complex neurological diseases. Future longitudinal studies designed to assess the utility of such digital methods for further clinical characterisation are needed. Funding: The Wellcome Trust, Medical Research Council, National Institute for Health Research, Rhodes Scholarship, and the Berrow Foundation Scholarship.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".