Dataset Information

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl- d -Aspartate Receptor Antibody Encephalitis.

ABSTRACT:

Purpose

Anti-N-methyl- d -aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis.

Methods

A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors.

Results

Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ 2 (1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2 ) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated ( P = 0.04) with an increased likelihood of poor outcome.

Conclusions

In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated.

SUBMITTER: Blackman G

PROVIDER: S-EPMC9886530 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl- d -Aspartate Receptor Antibody Encephalitis.

Blackman Graham G Kumar Kieron K Hanrahan John G JG Dalrymple Anthony A Mullatti Nandini N Moran Nick N Valentin Antonio A Gibson Lucy L Pollak Thomas A TA David Anthony S AS

Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society 20210702 2

<h4>Purpose</h4>Anti-N-methyl- d -aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis.<h4>Methods</h4>A retrospective, observational study was conducted of patients admitted to a tertiary cl ...[more]

PMID: 34238869

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Project description:BackgroundRecognizing the predictors of poor short-term prognosis after first-line immunotherapy in patients with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is essential for individualized treatment strategy. The objective of this study was to ascertain the factors that forecast short-term prognosis in patients with anti-NMDAR encephalitis, develop a prognostic prediction model, and authenticate its efficacy in an external validation cohort. Further, all patients were followed-up long-term to assess the factors of long-term outcome and relapses.MethodsA prospective enrollment of patients diagnosed with anti-NMDAR encephalitis was conducted across five clinical centers in China from June 2014 to Mar 2022. The enrolled patients were divided into the derivation and validation sets based on enrollment time. The short-term prognostic model was visualized using a nomogram. Further, all patients were followed-up long-term to assess the factors of long-term outcome.ResultsThis study found that poor short-term prognosis was a risk factor for poor long-term outcome (6-month prognosis, OR 29.792, 95%CI 6.507-136.398, p < 0.001; 12-month prognosis, OR 15.756, 95%CI 3.384-73.075, p < 0.001; 24-month prognosis, OR 5.500, 95%CI 1.045-28.955, p = 0.044). Abnormal behavior or cognitive dysfunction (OR 8.57, 95%CI 1.48-49.79, p = 0.017), consciousness impairment (OR19.32, 95%CI 3.03-123.09, p = 0.002), autonomic dysfunction or central hypoventilation (OR 5.66, 95%CI 1.25-25.75, p = 0.025), CSF pleocytosis (OR 4.33, 95%CI 1.48-12.65, p = 0.007), abnormal EEG (OR 5.48, 95% CI 1.09-27.54, p = 0.039) were independent predictors for a poor short-term prognosis after first-line immunotherapy. A nomogram that incorporated those factors showed good discrimination and calibration abilities. The area under the curve (AUC) for the prognostic model were 0.866 (95%CI: 0.798-0.934) with a sensitivity of 0.761 and specificity of 0.869.ConclusionWe established and validated a prognostic model that can provide individual prediction of short-term prognosis after first-line immunotherapy for patients with anti-NMDAR encephalitis. This practical prognostic model may help neurologists to predict the short-term prognosis early and potentially assist in adjusting appropriate treatment timely.

Project description:ObjectiveTo report the autoantigens of a new category of treatment-responsive paraneoplastic encephalitis.MethodsAnalysis of clinical features, neuropathological findings, tumors, and serum/cerebrospinal fluid antibodies using rat tissue, neuronal cultures, and HEK293 cells expressing subunits of the N-methyl-D-aspartate receptor (NMDAR).ResultsTwelve women (14-44 years) developed prominent psychiatric symptoms, amnesia, seizures, frequent dyskinesias, autonomic dysfunction, and decreased level of consciousness often requiring ventilatory support. All had serum/cerebrospinal fluid antibodies that predominantly immunolabeled the neuropil of hippocampus/forebrain, in particular the cell surface of hippocampal neurons, and reacted with NR2B (and to a lesser extent NR2A) subunits of the NMDAR. NR2B binds glutamate and forms heteromers (NR1/NR2B or NR1/NR2A/NR2B) that are preferentially expressed in the adult hippocampus/forebrain. Expression of functional heteromers (not single subunits) was required for antibody binding. Eleven patients had teratoma of the ovary (six mature) and one a mature teratoma in the mediastinum; five of five tumors examined contained nervous tissue that strongly expressed NR2 subunits and reacted with patients' antibodies. Tumor resection and immunotherapy resulted in improvement or full recovery of eight of nine patients (paralleled by decreased antibody titers); two of three patients without tumor resection died of neurological deterioration. Autopsies showed extensive microgliosis, rare T-cell infiltrates, and neuronal degeneration predominantly involving, but not restricted to, the hippocampus.InterpretationAntibodies to NR2B- and NR2A-containing heteromers of the NMDAR associate with a severe but treatment-responsive encephalitis. Our findings provide a diagnostic test and suggest a model of autoimmune NMDAR-related encephalitis with broad implications for other immune-mediated disorders of memory, behavior, and cognition.

Project description:Traditional static functional connectivity analyses have shown distinct functional network alterations in patients with anti-N-methyl-d-aspartate receptor encephalitis. Here, we use a dynamic functional connectivity approach that increases the temporal resolution of connectivity analyses from minutes to seconds. We hereby explore the spatiotemporal variability of large-scale brain network activity in anti-N-methyl-d-aspartate receptor encephalitis and assess the discriminatory power of functional brain states in a supervised classification approach. We included resting-state functional magnetic resonance imaging data from 57 patients and 61 controls to extract four discrete connectivity states and assess state-wise group differences in functional connectivity, dwell time, transition frequency, fraction time and occurrence rate. Additionally, for each state, logistic regression models with embedded feature selection were trained to predict group status in a leave-one-out cross-validation scheme. Compared to controls, patients exhibited diverging dynamic functional connectivity patterns in three out of four states mainly encompassing the default-mode network and frontal areas. This was accompanied by a characteristic shift in the dwell time pattern and higher volatility of state transitions in patients. Moreover, dynamic functional connectivity measures were associated with disease severity and positive and negative schizophrenia-like symptoms. Predictive power was highest in dynamic functional connectivity models and outperformed static analyses, reaching up to 78.6% classification accuracy. By applying time-resolved analyses, we disentangle state-specific functional connectivity impairments and characteristic changes in temporal dynamics not detected in static analyses, offering new perspectives on the functional reorganization underlying anti-N-methyl-d-aspartate receptor encephalitis. Finally, the correlation of dynamic functional connectivity measures with disease symptoms and severity demonstrates a clinical relevance of spatiotemporal connectivity dynamics in anti-N-methyl-d-aspartate receptor encephalitis.

Dataset Information

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl- d -Aspartate Receptor Antibody Encephalitis.

Purpose

Methods

Results

Conclusions

Publications

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl- d -Aspartate Receptor Antibody Encephalitis.

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