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Record W4388563357 · doi:10.1212/nxi.0000000000200178

Clinical Determinants of Longitudinal Disability in LGI-1-IgG Autoimmune Encephalitis

2023· article· en· W4388563357 on OpenAlexaboutno aff
Albert Aboseif, Yadi Li, Moein Amin, Brittany Lapin, Alex Milinovich, Justin Abbatemarco, Jeffrey A. Cohen, Vineet Punia, Alex Rae-Grant, Rachel Galioto, Amy Kunchok

Bibliographic record

VenueNeurology Neuroimmunology & Neuroinflammation · 2023
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsnot available
FundersGenentechEpilepsy SocietyEisaiHorizon TherapeuticsEMD SeronoNational Football League Players AssociationBiogenMylanCleveland ClinicPfizer
KeywordsInterquartile rangeMedicineAutoimmune encephalitisModified Rankin ScaleInternal medicineMontreal Cognitive AssessmentExpanded Disability Status ScaleRetrospective cohort studyEncephalitisPediatricsCognitive impairmentDiseaseImmunologyMultiple sclerosis

Abstract

fetched live from OpenAlex

Background and Objectives Longitudinal outcome studies in leucine-rich glioma inactivated-1 (LGI-1) immunoglobulin G (IgG) autoimmune encephalitis (AE) are needed to inform clinical management and prognostication. This study aims to evaluate longitudinal predictors of disability and disease severity in LGI-1-IgG AE. Methods This retrospective observational study of patients with LGI-1-IgG AE was conducted between 2013-2022. Disability and disease severity were defined by scores on the modified Rankin Scale (mRS) and the clinical assessment scale in AE (CASE), respectively. Demographic variables, clinical/paraclinical data, brain MRI, and Montreal Cognitive Assessment (MOCA) scores were examined as predictors of mRS and CASE scores in logistic and linear regression models, respectively. Results Thirty patients (60% male, median age = 68.5; interquartile range (IQR) = 63.0–75.0) were included, with a median follow-up time of 19.1 months (IQR = 5.3–47.1) The majority developed seizures (29, [97%]) and/or cognitive impairment (30, [100%]) and received acute (27, [90%]) and maintenance (23 [77%]) immunotherapy. The median initial MOCA was 23/30 (IQR = 21.0–25.0). Baseline mRS (median = 2.0, IQR = 2.0–3.0) and CASE (mean = 4.3, SD = 3.7) correlated with one another (r = 0.58, p < 0.001) and with initial MOCA score (mRS r = –0.60, p = 0.012; CASE r = –0.56, p = 0.021) After 12 months from symptom onset, mRS (OR = 0.88, [95% CI = 0.82–0.94], p < 0.001) and CASE (β = −0.03, [SE = 0.01], p < 0.001) improved significantly. Lower initial MOCA score (OR = 0.68, 95% CI = 0.47–0.98, p = 0.041) and temporal lobe(s) T2 hyperintensity (OR = 16.50, 95% CI = 2.29–119.16, p = 0.006) were associated with higher mRS longitudinally. At last follow-up, most patients had persistent memory dysfunction (25, [83%]) while few had ongoing seizure activity (3, [10%]). Discussion Overall, there was a high degree of correlation between mRS and CASE scores in patients with LGI-1-IgG AE, with both scores improving significantly after 12 months. Memory dysfunction and psychiatric disturbance were the most prevalent longitudinal symptoms. Cognitive impairment and temporal lobe T2 hyperintensity at baseline were both associated with greater disability at long-term follow-up, underscoring these as important determinants of disability outcomes in LGI-1-IgG AE.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.042
GPT teacher head0.345
Teacher spread0.303 · 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".

Quick stats

Citations26
Published2023
Admission routes1
Has abstractyes

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