ObjectiveTo compare acute treatment responses and long-term outcome in leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis.MethodsRetrospective case series of 118 patients with LGI1 antibody encephalitis evaluated at Mayo Clinic across all US sites from 1 May 2008 to 31 March 2019. Patient clinical data were identified and analysed through the neuroimmunology laboratory and electronic medical record. LGI1 antibody detection was by cell-based indirect immunofluorescence assay of serum, cerebrospinal fluid or both. Clinical outcomes were faciobrachial dystonic seizure (FBDS) resolution, modified Rankin Scale (mRS) score, Kokmen Short Test of Mental Status (STMS) score (0–38 point scale) and neuropsychometric testing results.ResultsCompared with intravenous immunoglobulin (IVIg) (n=21), patients treated with single-agent acute corticosteroids (intravenous, oral or both) (n=49) were more likely to experience resolution of FBDS (61% vs 7%, p=0.002) and improvements in mRS score (ΔmRS score 2 vs 0, p=0.008) and median Kokmen STMS scores (ΔKokmen STMS score 5 points vs 0 points, p=0.01). In 54 patients with long-term follow-up (≥2 years), the median mRS score was 1 (range 0–6) and the median Kokmen STMS score was 36 (range 24–38) after all combinations of immunotherapy. Neuropsychometric testing in 32 patients with long-term follow-up (≥2 years) demonstrated short-term memory impairments in 37%.ConclusionsCorticosteroids appeared more effective acutely than IVIg in improving LGI1 antibody encephalitis in this retrospective comparison of immunotherapies. While improvement with immunotherapy is typical and long-term outcome is favourable, short-term memory deficits are noted in approximately a third of the patients.

Objective:We aimed to determine whether cross-sectional performance on the Cogstate Brief Battery (CBB) and Auditory Verbal Learning Test (AVLT) could identify (1) cognitively unimpaired (CU) participants with preclinical Alzheimer's disease defined by neuroimaging biomarkers of amyloid and tau, and (2) incident mild cognitive impairment (MCI)/dementia. Method: CU participants age 50+ were eligible if they (1) had amyloid (A) and tau (T) imaging within two years of their baseline CBB or (2) had at least one follow-up visit. AUROC analyses assessed the ability of measures to differentiate groups. We also explored the frequency of crosssectional subtle objective cognitive impairment (sOBJ) defined as performance ≤ −1 SD on CBB Learning/Working Memory Composite (Lrn/WM) or AVLT delayed recall using age-corrected normative data.Results: A+T+ (n=33, mean age 79.5) and A+T-(n=61, mean age 77.8) participants were older than A-T-participants (n=146, mean age 66.3), and comparable on sex and education. Lrn/WM

Introduction This study evaluated the diagnostic accuracy of the Cogstate Brief Battery (CBB) for mild cognitive impairment (MCI) and prodromal Alzheimer's disease (AD) in a population‐based sample. Methods Participants included adults ages 50+ classified as cognitively unimpaired (CU, n = 2866) or MCI (n = 226), and a subset with amyloid (A) and tau (T) positron emission tomography who were AD biomarker negative (A–T–) or had prodromal AD (A+T+). Results Diagnostic accuracy of the Learning/Working Memory Composite (Lrn/WM) for discriminating all CU and MCI was moderate (area under the curve [AUC] = 0.75), but improved when discriminating CU A–T– and MCI A+T+ (AUC = 0.93) and when differentiating MCI participants without AD biomarkers from those with prodromal AD (AUC = 0.86). Conventional cut‐offs yielded lower than expected sensitivity for both MCI (38%) and prodromal AD (73%). Discussion Clinical utility of the CBB for detecting MCI in a population‐based sample is lower than expected. Caution is needed when using currently available CBB normative data for clinical interpretation.

Background: Longitudinal, but not cross-sectional, cognitive testing is one option proposed to define transitional cognitive decline for individuals on the Alzheimer’s disease continuum. Objective: Compare diagnostic accuracy of cross-sectional subtle objective cognitive impairment (sOBJ) and longitudinal objective decline (ΔOBJ) over 30 months for identifying 1) cognitively unimpaired participants with preclinical Alzheimer’s disease defined by elevated brain amyloid and tau (A+T+) and 2) incident mild cognitive impairment (MCI) based on Cogstate One Card Learning (OCL) accuracy performance. Methods: Mayo Clinic Study of Aging cognitively unimpaired participants aged 50 + with amyloid and tau PET scans (n = 311) comprised the biomarker-defined sample. A case-control sample of participants aged 65 + remaining cognitively unimpaired for at least 30 months included 64 who subsequently developed MCI (incident MCI cases) and 184 controls, risk-set matched by age, sex, education, and visit number. sOBJ was assessed by OCL z-scores. ΔOBJ was assessed using within subjects’ standard deviation and annualized change from linear regression or linear mixed effects (LME) models. Concordance measures Area Under the ROC Curve (AUC) or C-statistic and odds ratios (OR) from conditional logistic regression models were derived. sOBJ and ΔOBJ were modeled jointly to compare methods. Results: sOBJ and ΔOBJ-LME methods differentiated A+T+ from A-T- (AUC = 0.64, 0.69) and controls from incident MCI (C-statistic = 0.59, 0.69) better than chance; other ΔOBJ methods did not. ΔOBJ-LME improved prediction of future MCI over baseline sOBJ (p = 0.003) but not over 30-month sOBJ (p = 0.09). Conclusion: Longitudinal decline did not offer substantial benefit over cross-sectional assessment in detecting preclinical Alzheimer’s disease or incident MCI.

Background The numeric clinical staging scheme described by the NIA‐AA workgroup proposes evidence of subtle decline on longitudinal cognitive testing as one option to define transitional cognitive decline for individuals in the Alzheimer’s continuum. Few studies have compared longitudinal and cross‐sectional definitions of subtle objective cognitive impairment (sOBJ). The study aim was to compare the diagnostic accuracy of cross‐sectional sOBJ and longitudinal objective cognitive decline (ΔOBJ) for preclinical Alzheimer’s disease (AD) based on Cogstate One Card Learning (OCL) performance. Method We included Mayo Clinic Study of Aging cognitively unimpaired (CU) participants who were A+T+ by amyloid and tau PET assessment (n=32) and A‐T‐ (n=211); all had at least two follow‐up visits. sOBJ was defined as performance ≤ ‐1SD on OCL accuracy using age‐corrected normative data. ΔOBJ was measured using two different methods: (1) within subjects’ standard deviation (WSD) using a ≤ ‐1 z‐score for change to define decline based on Cogstate’s normative change data, and (2) extracted subject‐specific slopes from a linear mixed effects model (LME) which can be interpreted as approximate annual change; decline was defined as slope < 10%ile among a reference sample of CU participants aged 50‐65 at baseline (N=732). Results sOBJ and ΔOBJ‐WSD both showed low sensitivity in detection of A+T+ (9.4% and 12.5%, respectively). Total AUC values did not differ significantly (p=.31) across sOBJ (AUC = .64, CI = .53‐.75) and ΔOBJ‐WSD (AUC = .53, CI = .42‐.65) methods. Sensitivity of the ΔOBJ‐LME method to predict A+T+ was improved (37.5%) when using a conventional cutoff of <10%ile slope and was further improved (56%) when using an optimal derived cutoff equivalent to <17%ile slope within the reference group. Like the sOBJ method, the ΔOBJ‐LME method differentiated groups better than chance (AUC = .69, CI = .58‐.80). Despite increased sensitivity, total AUC values were not significantly different across sOBJ and ΔOBJ‐LME methods (p=.34). However, total AUC of ΔOBJ‐LME was significantly better than ΔOBJ‐WSD (p=.03). Conclusions ΔOBJ may be more sensitive to preclinical AD than sOBJ and may serve as a helpful method for identifying at risk CU individuals if advanced statistical methods are used for defining change.