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Record W4367296024 · doi:10.1212/wnl.0000000000202815

Frontal cognitive-behavioural deficits in patients with anti-leucine-rich glioma-inactivated protein 1 antibody encephalitis (S22.004)

2023· article· en· W4367296024 on OpenAlexaffabout
Sydney Lee, Seth Climans, Gregory S. Day, Julien Hébert, S. LaPointe, Ronald Ramos, Claude Steriade, Richard Wennberg, Alexandra Muccilli, David F. Tang‐Wai

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsToronto Western HospitalUniversity Health NetworkJuravinski HospitalLondon Health Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsApathyDisinhibitionEncephalitisCognitionNeuropsychologyPsychologyDementiaFrontotemporal dementiaCognitive declineFrontal lobePediatricsPsychiatryMedicineClinical psychologyInternal medicineDiseaseImmunology

Abstract

fetched live from OpenAlex

Objective: To determine the prevalence of a frontal cognitive-behavioural phenotype in patients with anti-leucine-rich glioma-inactivated protein 1 (LGI1) encephalitis. Background: Cognitive impairment is a common manifestation of anti-LGI1 encephalitis and is typically defined as prominent memory deficits. We frequently encounter frontal cognitive-behavioural deficits when evaluating these patients, but this has yet to be well described in the literature. Design/Methods: We retrospectively identified patients from three tertiary centres in Toronto, Ontario who were diagnosed with anti-LGI1 encephalitis between October 2013 and September 2022. Patient electronic medical records were evaluated for cognitive features and frontal features were categorized based on the diagnostic criteria for behavioural variant frontotemporal dementia (bvFTD). Results: Fifteen patients were identified (median age 65 years [range 18–84]; 8 [53.3%] male). Fourteen (93.3%) patients had cognitive symptoms that localized to the frontal lobe. Two developed these symptoms during treatment with steroids and were therefore excluded from further analysis. The remaining 12 patients presented with behavioural disinhibition (n=11), apathy or inertia (n=5), perseverative, stereotyped or compulsive/ritualistic behaviours (n=4), hyperorality and dietary changes (n=4), a neuropsychological profile with predominant deficits in executive tasks (n=4), and loss of sympathy or empathy (n=1). Seven (46.7%) met diagnostic criteria for possible bvFTD. Of these, 3 had significant functional decline and none had neuroimaging findings consistent with bvFTD. Anterograde memory impairment was common (n=11), and patients also presented with language deficits (n=3) and difficulties with spatial navigation (n=3). Of the 12 patients with frontal symptoms, only 5 had faciobrachial dystonic seizures. Conclusions: Patients with anti-LGI1 encephalitis can exhibit frontal cognitive-behavioural symptoms in addition to memory impairment, and screening for these features on clinical assessment may help to identify the diagnosis. Clinicians should also consider anti-LGI1 encephalitis in the differential diagnosis of bvFTD. Disclosure: Dr. Lee has nothing to disclose. Dr. Climans has nothing to disclose. Dr. Day has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Parabon Nanolabs. The institution of Dr. Day has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Eli Lilly. Dr. Day has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for DynaMed (EBSCO Health). Dr. Day has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Barrow Law. Dr. Day has stock in ANI Pharmaceuticals. The institution of Dr. Day has received research support from National Institutes of Health / NIA. The institution of Dr. Day has received research support from Chan Zuckerberg Initiative. The institution of Dr. Day has received research support from Alzheimer’s Association. The institution of Dr. Day has received research support from National Institutes of Health / NINDS. The institution of Dr. Day has received research support from Horizon Therapeutics. Dr. Day has received personal compensation in the range of $500-$4,999 for serving as a Presenter at Annual Meeting (CME) with American Academy of Neurology. Dr. Day has received personal compensation in the range of $500-$4,999 for serving as a Content Development (CME) with PeerView, Inc. Dr. Day has received personal compensation in the range of $5,000-$9,999 for serving as a Content Development (CME) with Continuing Education, Inc. Dr. Day has a non-compensated relationship as a Clinical Director with AntiNMDA Receptor Encephalitis Foundation that is relevant to AAN interests or activities. Dr. Hebert has nothing to disclose. Dr. Lapointe has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Alexion. Dr. Ramos has nothing to disclose. The institution of Dr. Steriade has received research support from NIH. The institution of Dr. Steriade has received research support from Dorris Duke Fund to Retain Clinician Scientists. Dr. Wennberg has nothing to disclose. Dr. Muccilli has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Biogen. Dr. Muccilli has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Dr. Muccilli has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for EMD Serono. Dr. Tang-Wai has nothing to disclose.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.264
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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