Evaluation of Clinical and Paraclinical Findings for the Differential Diagnosis of Autoimmune and Infectious Encephalitis

Validation of a risk score to differentiate autoimmune and viral encephalitis: a Nationwide Cohort Study in Denmark

BACKGROUND

A score to differentiate autoimmune (AE) and viral encephalitis (VE) early upon admission has recently been developed but needed external validation. The objective of this study was to evaluate the performance of the score in a larger and more diagnostically diverse patient cohort.

METHODS

We conducted a retrospective nationwide and population-based cohort study including all adults with encephalitis of definite viral (2015-2022) or autoimmune aetiology (2009-2022) in Denmark. Variables included in the score-model were extracted from patient records and individual risk scores were assessed. The performance of the score was assessed by receiver-operating characteristics (ROC) curve analyses and calculation of the area under the curve (AUC).

RESULTS

A total of 496 patients with encephalitis [AE n = 90, VE n = 287 and presumed infectious encephalitis (PIE) n = 119] were included in the study. The score was highly accurate in predicting cases of AE reaching an AUC of 0.94 (95% CI 0.92-0.97). Having a score ≥ 3 predicted AE with a PPV of 87% and an NPV of 91%. The risk score was found to perform well across aetiological subgroups and applied to the PIE cohort resulted in an AUC of 0.88 (95% CI 0.84-0.93).

CONCLUSION

The excellent performance of the score as reported in the development study was confirmed in this significantly larger and more diverse cohort of patients with encephalitis in Denmark. These results should prompt further prospective testing with wider inclusion criteria.

case of autoimmune GFAP astrocytopathy with eosinophils in the cerebrospinal fluid

Cerebrospinal fluid (CSF) eosinophilia is associated with a narrow differential, primarily including parasitic and fungal infections, neoplasm, and chemical meningitis. It has rarely been reported in neuroinflammatory conditions including as a finding of CSF cytology in two autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy cases. Here we describe a case of autoimmune GFAP astrocytopathy with classic clinical and radiographic features as well as presence of eosinophils in the CSF. This case highlights a potential association of eosinophils in the CSF with autoimmune GFAP astrocytopathy, which may suggest its inclusion in the differential diagnosis of eosinophilic meningitis, encephalitis, or myelitis.

Clinical predictors of encephalitis in UK adults-A multi-centre prospective observational cohort study

OBJECTIVES

Encephalitis, brain inflammation and swelling, most often caused by an infection or the body's immune defences, can have devastating consequences, especially if diagnosed late. We looked for clinical predictors of different types of encephalitis to help clinicians consider earlier treatment.

METHODS

We conducted a multicentre prospective observational cohort study (ENCEPH-UK) of adults (> 16 years) with suspected encephalitis at 31 UK hospitals. We evaluated clinical features and investigated for infectious and autoimmune causes.

RESULTS

341 patients were enrolled between December 2012 and December 2015 and followed up for 12 months. 233 had encephalitis, of whom 65 (28%) had HSV, 38 (16%) had confirmed or probable autoimmune encephalitis, and 87 (37%) had no cause found. The median time from admission to 1st dose of aciclovir for those with HSV was 14 hours (IQR 5-50); time to 1st dose of immunosuppressant for the autoimmune group was 125 hours (IQR 45-250). Compared to non-HSV encephalitis, patients with HSV more often had fever, lower serum sodium and lacked a rash. Those with probable or confirmed autoimmune encephalitis were more likely to be female, have abnormal movements, normal serum sodium levels and a cerebrospinal fluid white cell count < 20 cells x106/L, but they were less likely to have a febrile illness.

CONCLUSIONS

Initiation of treatment for autoimmune encephalitis is delayed considerably compared with HSV encephalitis. Clinical features can help identify patients with autoimmune disease and could be used to initiate earlier presumptive therapy.

Movement disorders in cell surface antibody mediated autoimmune encephalitis: a meta-analysis

Background

Autoimmune encephalitis (AE) is an increasingly recognized neuroinflammatory disease entity in which early detection and treatment leads to the best clinical outcomes. Movement disorders occur in AE but their characteristics are not well defined.

Objectives

To identify the frequency, classification, and prognostic significance of movement disorders in AE.

Methods

We conducted a systematic review and random-effects meta-analysis of movement disorders in cell surface antibody mediated AE. The frequency of any movement disorder as well as the classification of movement disorders in AE serotypes was determined. We looked at adults 18 years and older and included publications that described at least 10 cases. We used the following four electronic databases: Medline (Ovid), EMBASE (Ovid), APA Psychinfo, and Cochrane library.

Results

A total of 1,192 titles and abstracts were reviewed. Thirty-seven studies were included in the final meta-analysis. At least one kind of movement disorder was present in 40% of the entire AE cohort, 53% with anti-NMDA receptor antibodies, 33% with anti-CASPR2 antibodies, 30% with anti-LGI1 antibodies and 13% with anti-GABA receptor antibodies. Dyskinesia was the commonest movement disorder in anti-NMDA antibody mediated AE and faciobrachial dystonic seizures were most frequent in anti-LGI1 antibody mediated AE. Patients with a movement disorder tended to have a higher mortality. The risk of bias in the included studies was mostly moderate or high.

Conclusion

Movement disorders are common in AE and their identification, in conjunction with other clinical and paraclinical features, may facilitate earlier diagnosis. The prognostic implications of movement disorders in AE warrant further dedicated study.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD42023386920.

Spatial and Ecological Factors Modulate the Incidence of Anti-NMDAR Encephalitis-A Systematic Review

Anti-NMDAR encephalitis has been associated with multiple antigenic triggers (i.e., ovarian teratomas, prodromal viral infections) but whether geographic, climatic, and environmental factors might influence disease risk has not been explored yet. We performed a systematic review and a meta-analysis of all published papers reporting the incidence of anti-NMDAR encephalitis in a definite country or region. We performed several multivariate spatial autocorrelation analyses to analyze the spatial variations in the incidence of anti-NMDA encephalitis depending on its geographical localization and temperature. Finally, we performed seasonal analyses in two original datasets from France and Greece and assessed the impact of temperature using an exposure-lag-response model in the French dataset. The reported incidence of anti-NMDAR encephalitis varied considerably among studies and countries, being higher in Oceania and South America (0.2 and 0.16 per 100,000 persons-year, respectively) compared to Europe and North America (0.06 per 100,000 persons-year) (p < 0.01). Different regression models confirmed a strong negative correlation with latitude (Pearson's R = -0.88, p < 0.00001), with higher incidence in southern hemisphere countries far from the equator. Seasonal analyses showed a peak of cases during warm months. Exposure-lag-response models confirmed a positive correlation between extreme hot temperatures and the incidence of anti-NMDAR encephalitis in France (p = 0.03). Temperature analyses showed a significant association with higher mean temperatures and positive correlation with higher ultraviolet exposure worldwide. This study provides the first evidence that geographic and climatic factors including latitude, mean annual temperature, and ultraviolet exposure, might modify disease risk.

Autoimmune encephalitis misdiagnosis and mimics

The diagnosis of autoimmune encephalitis (AE) requires reasonable exclusion of other conditions. The aim of this study is to characterize mimickers and misdiagnoses of AE, thus we performed an independent PubMed search for mimickers of AEs or patients with alternative neurological disorders misdiagnosed as AE. Fifty-eight studies with 66 patients were included. Neoplastic (n = 17), infectious (n = 15), genetic (n = 13), neurodegenerative (n = 8), and other neurological (n = 8) or systemic autoimmune (n = 5) disorders were misdiagnosed as AE. The lack of fulfillment of diagnostic criteria for AE, atypical neuroimaging findings, non-inflammatory CSF findings, non-specific autoantibody specificities and partial response to immunotherapy were major confounding factors.

Evaluation of multiple consensus criteria for autoimmune encephalitis and temporal analysis of symptoms in a pediatric encephalitis cohort

Objective

To evaluate the sensitivity and specificity of current criteria for the diagnosis of autoimmune encephalitis (AE) and the temporal onset of neuropsychiatric symptoms (NP) in a pediatric encephalitis cohort.

Background

Multiple criteria for AE have been developed, including the Graus and pediatric-focused Cellucci consensus criteria, and the Determining Etiology in Encephalitis (DEE) score for patients with encephalitis. Early identification and treatment of AE is crucial to improve outcomes, but this can be difficult given the frequent overlap of clinical presentation between AE and infectious encephalitis (IE).

Design/methods

A retrospective review was conducted of patients seen at our institution from 2000 to 2021 with a final diagnosis of AE or IE. These were narrowed through multiple exclusions to etiology-confirmed IE or antibody-positive/negative AE. Time of onset or results of all symptoms and diagnostics were recorded. Sensitivity and specificity of each criterion under various clinical scenarios were calculated over the first month after initial NP symptom onset.

Results

A total of 23 antibody-positive AE, 9 antibody-negative AE and 23 IE patients were included in final analysis. Under an idealized scenario with rapid initial diagnostic evaluations, the sensitivity for pediatric AE by day 28 after onset of NP symptoms approached 90% for both Cellucci and Graus criteria. Specificity within these 28 days was low without infectious testing results, increasing the greatest with rapid PCR testing and second with infectious antibody testing-reaching ~90% with both. A DEE score of 3 provided a specificity of 100% in identifying IE, but low sensitivity (29%). Symptoms were noted to cluster within several days of onset in IE, but in AE were spread out. Personality/behavioral change, speech change, affective disorder, and sleep disturbance were noted more often in AE, while fever, elevated C-reactive protein or CSF protein, and abnormal MRI-Brain occurred more often in IE.

Conclusion

In this study, we provide the first evaluation of the Cellucci criteria and the first validation of the DEE score in the differentiation of pediatric AE and IE. Further refinement of AE criteria is needed to improve early detection and treatment of pediatric AE.

Differentiating autoimmune encephalitis from schizophrenia spectrum disorders among patients with first-episode psychosis

BACKGROUND

Although differential diagnosis between autoimmune encephalitis and schizophrenia spectrum disorders is crucial for a good outcome, the psychiatric symptoms that distinguish these two conditions have not been identified even though psychiatric symptoms are often the main manifestation of autoimmune encephalitis. Also, there are many situations in clinical psychiatry in which laboratory testing and imaging studies are not available. Because no comparative study of the psychiatric symptoms between these two conditions has been carried out, we explored diagnostically useful psychiatric symptoms in a retrospective case-control study.

METHODS

We recruited 187 inpatients with first-episode psychosis who were admitted to our psychiatric unit and categorized them into two groups: the autoimmune encephalitis group (n = 10) and the schizophrenia spectrum disorders group (n = 177). Differences in the symptoms and signs between the two groups were investigated.

RESULTS

Schneider's first-rank symptoms (e.g., verbal commenting hallucinations and delusional self-experience) were observed only in the schizophrenia spectrum disorders group, whereas altered perception was found more frequently in the autoimmune encephalitis group. Functional status was worse in the autoimmune encephalitis group, and neurological and neuropsychological signs were revealed almost exclusively in this group. A history of mental illness was more frequently reported in the schizophrenia spectrum disorders group than in the autoimmune encephalitis group.

CONCLUSIONS

The psychiatric symptoms, i.e., Schneider's first-rank symptoms and altered perception, together with neurological and neuropsychological signs, functional status, and past history, may help clinicians accurately differentiate these two conditions among patients with first-episode psychosis.

Determining an infectious or autoimmune etiology in encephalitis

Objectives

Early presentation and workup for acute infectious (IE) and autoimmune encephalitis (AE) are similar. This study aims to identify routine laboratory markers at presentation that are associated with IE or AE.

Methods

This was a multi‐center retrospective study at three tertiary care hospitals in New York City analyzing demographic and clinical data from patients diagnosed with definitive encephalitis based on a confirmed pathogen and/or autoantibody and established criteria for clinical syndromes.

Results

Three hundred and thirty‐three individuals with confirmed acute meningoencephalitis were included. An infectious‐nonbacterial (NB) pathogen was identified in 151/333 (45.40%), bacterial pathogen in 95/333 (28.50%), and autoantibody in 87/333 (26.10%). NB encephalitis was differentiated from AE by the presence of fever (NB 62.25%, AE 24.10%; p < 0.001), higher CSF white blood cell (WBC) (median 78 cells/μL, 8.00 cells/μL; p < 0.001), higher CSF protein (76.50 mg/dL, 40.90 mg/dL; p < 0.001), lower CSF glucose (58.00 mg/dL, 69.00 mg/dL; p < 0.001), lower serum WBC (7.80 cells/μL, 9.72 cells/μL; p < 0.050), higher erythrocyte sedimentation rate (19.50 mm/HR, 13.00 mm/HR; p < 0.05), higher C‐reactive protein (6.40 mg/L, 1.25 mg/L; p = 0.005), and lack of antinuclear antibody titers (>1:40; NB 11.54%, AE 32.73%; p < 0.001). CSF‐to‐serum WBC ratio was significantly higher in NB compared to AE (NB 11.3, AE 0.99; p < 0.001). From these findings, the association of presenting with fever, CSF WBC ≥50 cells/μL, and CSF protein ≥75 mg/dL was explored in ruling‐out AE. When all three criteria are present, an AE was found to be highly unlikely (sensitivity 92%, specificity 75%, negative predictive value 95%, and positive predictive value 64%).

Interpretations

Specific paraclinical data at initial presentation may risk stratify which patients have an IE versus AE.

Construction of an Assisted Model Based on Natural Language Processing for Automatic Early Diagnosis of Autoimmune Encephalitis

Introduction

Early diagnosis and etiological treatment can effectively improve the prognosis of patients with autoimmune encephalitis (AE). However, anti-neuronal antibody tests which provide the definitive diagnosis require time and are not always abnormal. By using natural language processing (NLP) technology, our study proposes an assisted diagnostic method for early clinical diagnosis of AE and compares its sensitivity with that of previously established criteria.

Methods

Our model is based on the text classification model trained by the history of present illness (HPI) in electronic medical records (EMRs) that present a definite pathological diagnosis of AE or infectious encephalitis (IE). The definitive diagnosis of IE was based on the results of traditional etiological examinations. The definitive diagnosis of AE was based on the results of neuronal antibodies, and the diagnostic criteria of definite autoimmune limbic encephalitis proposed by Graus et al. used as the reference standard for antibody-negative AE. First, we automatically recognized and extracted symptoms for all HPI texts in EMRs by training a dataset of 552 cases. Second, four text classification models trained by a dataset of 199 cases were established for differential diagnosis of AE and IE based on a post-structuring text dataset of every HPI, which was completed using symptoms in English language after the process of normalization of synonyms. The optimal model was identified by evaluating and comparing the performance of the four models. Finally, combined with three typical symptoms and the results of standard paraclinical tests such as cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), or electroencephalogram (EEG) proposed from Graus criteria, an assisted early diagnostic model for AE was established on the basis of the text classification model with the best performance.

Results

The comparison results for the four models applied to the independent testing dataset showed the naïve Bayesian classifier with bag of words achieved the best performance, with an area under the receiver operating characteristic curve of 0.85, accuracy of 84.5% (95% confidence interval [CI] 74.0–92.0%), sensitivity of 86.7% (95% CI 69.3–96.2%), and specificity of 82.9% (95% CI 67.9–92.8%), respectively. Compared with the diagnostic criteria proposed previously, the early diagnostic sensitivity for possible AE using the assisted diagnostic model based on the independent testing dataset was improved from 73.3% (95% CI 54.1–87.7%) to 86.7% (95% CI 69.3–96.2%).

Conclusions

The assisted diagnostic model could effectively increase the early diagnostic sensitivity for AE compared to previous diagnostic criteria, assist physicians in establishing the diagnosis of AE automatically after inputting the HPI and the results of standard paraclinical tests according to their narrative habits for describing symptoms, avoiding misdiagnosis and allowing for prompt initiation of specific treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00355-7.

Novel qEEG Biomarker to Distinguish Anti-NMDAR Encephalitis From Other Types of Autoimmune Encephalitis

Objective

To establish the diagnostic biomarker of electroencephalogram (EEG) to distinguish between anti-N-methyl-d-aspartate receptor encephalitis (NMDARE) and other types of autoimmune encephalitis (other AEs).

Methods

We reviewed the clinical records of 90 patients with acute encephalitis who were treated in our institution between January 2014 and October 2020. We enrolled the patients who fulfilled the diagnostic criteria for possible AE (pAE) defined by Graus et al. (pAE criteria) and then classified into definite NMDARE and other AEs. We investigated the main syndrome and analyzed all admission EEGs using EEG power value (PV). Statistical significance was tested using the Mann–Whitney U test or Fisher’s exact test.

Results

Twenty-five patients fulfilled the pAE criteria and were classified into 9 with definite NMDARE (median age: 21 years; 8 women) and 12 with other AEs (median age: 37.5 years; 6 women). Four were eventually excluded. Speech dysfunction (9/9 vs. 4/12, p = 0.005) and movement disorders (6/9 vs. 1/12, p = 0.016) were more frequent in NMDARE than in other AEs. The PV analyses revealed the novel quantitative EEG (qEEG) index, namely, fast slow ratio (FSR) (PV of total beta/PV of total theta + delta). The median FSR (0.139 vs. 0.029, p = 0.004) was higher for NMDARE than other AEs, and the receiver operating characteristic curve area of FSR was 0.86 (95% CI 0.70–1.00). A cutoff value of 0.047 yielded a specificity of 0.75 and a sensitivity of 1.00. Focusing on patients who did not meet the “probable NMDARE criteria” in Graus 2016 (proNMDARE criteria) (n = 10), the pretest probability of NMDAR antibody test was 0.30 (3/10), which increased in patients with an FSR greater than the cutoff (n = 5) to 0.60 (3/5).

Conclusions

The NMDARE group highlighted speech dysfunction and movement disorders, and a novel qEEG index FSR accurately distinguished the NMDARE patients from other AEs. The FSR is a promising diagnostic marker for NMDARE that indicates the positive results of NMDAR antibodies in patients with AE when combined with the proNMDARE criteria.

Limbic encephalitis

Limbic encephalitis (LE) is a clinical syndrome defined by subacutely evolving limbic signs and symptoms with structural and functional evidence of mediotemporal damage in the absence of a better explanation than an autoimmune (or paraneoplastic) cause. There are features common to all forms of LE. In recent years, antibody(ab)-defined subtypes have been established. They are distinct regarding underlying pathophysiologic processes, clinical and magnetic resonance imaging courses, cerebrospinal fluid signatures, treatment responsivity, and likelihood of a chronic course. With immunotherapy, LE with abs against surface antigens has a better outcome than LE with abs to intracellular antigens. Diagnostic and treatment challenges are, on the one hand, to avoid overlooking and undertreatment and, on the other hand, to avoid overdiagnoses and overtreatment. LE can be conceptualized as a model disease for the consequences of new onset mediotemporal damage by different mechanisms in adult life. It may be studied as an example of mediotemporal epileptogenesis.

Deep Learning-Enabled Identification of Autoimmune Encephalitis on 3D Multi-Sequence MRI

BACKGROUND

Autoimmune encephalitis (AE) is a noninfectious emergency with severe clinical attacks. It is difficult for the earlier diagnosis of acute AE due to the lack of antibody detection resources.

PURPOSE

To construct a deep learning (DL) algorithm using multi-sequence magnetic resonance imaging (MRI) for the identification of acute AE.

STUDY TYPE

Retrospective.

POPULATION

One hundred and sixty AE patients (90 women; median age 36), 177 herpes simplex virus encephalitis (HSVE) (89 women; median age 39), and 184 healthy controls (HC) (95 women; median age 39) were included. Fifty-two patients from another site were enrolled for external validation.

FIELD STRENGTH/SEQUENCE

3.0 T; fast spin-echo (T₁ WI, T₂ WI, fluid attenuated inversion recovery imaging) and spin-echo echo-planar diffusion weighted imaging.

ASSESSMENT

Five DL models based on individual or combined four MRI sequences to classify the datasets as AE, HSVE, or HC. Reader experiment was further carried out by radiologists.

STATISTICAL TESTS

The discriminative performance of different models was assessed using the area under the receiver operating characteristic curve (AUC). The optimal threshold cut-off was identified when sensitivity and specificity were maximized (sensitivity + specificity - 1) in the validation set. Classification performance using confusion matrices was reported to evaluate the diagnostic value of the models and the radiologists' assessments before being assessed by the paired t-test (P < 0.05 was considered significant).

RESULTS

In the internal test set, the fusion model achieved the significantly greatest diagnostic performance than single-sequence DL models with AUCs of 0.828, 0.884, and 0.899 for AE, HSVE, and HC, respectively. The model demonstrated a consistently high performance in the external validation set with AUCs of 0.831 (AE), 0.882 (HSVE), and 0.892 (HC). The fusion model also demonstrated significantly higher performance than all radiologists in identifying AE (accuracy between the fuse model vs. average radiologist: 83% vs. 72%).

DATA CONCLUSION

The proposed DL algorithm derived from multi-sequence MRI provided desirable identification and classification of acute AE.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Decrease in the cortex/striatum metabolic ratio on [18F]-FDG PET: a biomarker of autoimmune encephalitis

PURPOSE

The aim of this [¹⁸F]-FDG PET study was to determine the diagnostic value of the cortex/striatum metabolic ratio in a large cohort of patients suffering from autoimmune encephalitis (AE) and to search for correlations with the course of the disease.

METHODS

We retrospectively collected clinical and paraclinical data of patients with AE, including brain ¹⁸F-FDG PET/CT. Whole-brain statistical analysis was performed using SPM8 software after activity parametrization to the striatum in comparison to healthy subjects. The discriminative performance of this metabolic ratio was evaluated in patients with AE using receiver operating characteristic curves against 44 healthy subjects and a control group of 688 patients with MCI. Relationship between cortex/striatum metabolic ratios and clinical/paraclinical data was assessed using univariate and multivariate analysis in patients with AE.

RESULTS

Fifty-six patients with AE were included. In comparison to healthy subjects, voxel-based statistical analysis identified one large cluster (p-cluster < 0.05, FWE corrected) of widespread decreased cortex/striatum ratio in patients with AE. The mean metabolic ratio was significantly lower for AE patients (1.16 ± 0.13) than that for healthy subjects (1.39 ± 0.08; p < 0.001) and than that for MCI patients (1.32 ± 0.11; p < 0.001). A ratio threshold of 1.23 allowed to detect AE patients with a sensitivity of 71% and a specificity of 82% against MCI patients, and 98% against healthy subjects. A lower cortex/striatum metabolic ratio had a trend towards shorter delay before ¹⁸F-FDG PET/CT (p = 0.07) in multivariate analysis.

CONCLUSION

The decrease in the cortex/striatal metabolic ratio has a good early diagnostic performance for the differentiation of AE patients from controls.

Clinical Characteristics and Outcome of Neuronal Surface Antibody-Mediated Autoimmune Encephalitis Patients in a National Cohort

Background: In our previous single-center study of autoimmune encephalitis (AE) related autoantibody test results we found positivity in 60 patients out of 1,034 with suspected AE from 2012 through 2018 as part of a Hungarian nationwide program. In our current multicenter retrospective study, we analyzed the clinical characteristics and outcome of AE patients with positive neuronal cell surface autoantibody test results.

Methods: A standard online questionnaire was used to collect demographic and clinical characteristics, laboratory and imaging data, therapy and prognosis of 30 definitive AE patients in four major clinical centers of the region.

Results: In our study, 19 patients were positive for anti-NMDAR (63%), 6 patients (20%) for anti-LGI1, 3 patients for anti-GABABR (10%) and 3 patients for anti-Caspr2 (10%) autoantibodies. Most common prodromal symptoms were fever or flu-like symptoms (10/30, 33%). Main clinical features included psychiatric symptoms (83%), epileptic seizures (73%) and memory loss (50%). 19 patients (63%) presented with signs of central nervous system (CNS) inflammation, which occurred more frequently in elder individuals (p = 0.024), although no significant differences were observed in sex, tumor association, time to diagnosis, prognosis and immunotherapy compared to AE patients without CNS inflammatory markers. Anti-NMDAR encephalitis patients were in more severe condition at the disease onset (p = 0.028), although no significant correlation between mRS score, age, sex and immunotherapy was found. 27% of patients (n = 8) with associated tumors had worse outcome (p = 0.045) than patients without tumor. In most cases, immunotherapy led to clinical improvement of AE patients (80%) who achieved a good outcome (mRS ≤ 2; median follow-up 33 months).

Conclusion: Our study confirms previous publications describing characteristics of AE patients, however, differences were observed in anti-NMDAR encephalitis that showed no association with ovarian teratoma and occurred more frequently among young males. One-third of AE patients lacked signs of inflammation in both CSF and brain MRI, which emphasizes the importance of clinical symptoms and autoantibody testing in diagnostic workflow for early introduction of immunotherapy, which can lead to favorable outcome in AE patients.

Evaluation of the proposed anti-N-methyl-d-aspartate receptor encephalitis clinical diagnostic criteria in psychiatric patients

OBJECTIVE

The gold standard for diagnosing anti-NMDAR encephalitis is demonstration of the antibody in CSF. Clinical diagnostic criteria have been proposed for when this is not available in a timely manner which is evaluated, in this study, for a psychiatric population.

METHODS

This study retrospectively assessed the proposed criteria in patients presenting to psychiatric services for the first time with known anti-NMDAR antibody status. Antibody-positive cases were derived from the literature (conception to December 2019) and a state-wide (Queensland, Australia) cohort. Antibody-negative cases were derived from a service-wide (Metro South, Queensland, Australia) cohort of psychiatric cases which underwent antibody testing for routine organic screening. Sensitivity and specificity were calculated at 1 week following admission and the point of discharge.

RESULTS

The proposed criteria were applied to 641 cases (500 antibody-positive and 141 antibody-negative), demonstrating a sensitivity which increased from around 19% after 1 week to 49% by the point of discharge. Specificity was 100% at both time points. The mean average time to become positive using the proposed criteria was 19.5 days compared to 34.9 days for return of antibody testing.

CONCLUSIONS

High specificity of the proposed criteria, seen in this study, suggests that cases which are positive can be considered for expedited commencement of treatment. However, if clinical suspicion is high despite criteria being negative, it is essential to test CSF for anti-NMDAR antibody.

Comparisons Between Infectious and Autoimmune Encephalitis: Clinical Signs, Biochemistry, Blood Counts, and Imaging Findings

OBJECTIVE

Infectious encephalitis (IE) and autoimmune encephalitis (AE) are symptomatically similar in clinic, however essentially different in pathogenesis. Therefore, the objective of this study was to identify specific features to distinguish the two types of encephalitis for early effective diagnosis and treatments through a comparative analysis.

METHODS

Fifty-nine IE patients and 36 AE patients were enrolled. The patients with IE were divided into viral encephalitis (VE) and bacterial encephalitis (BE) according to the pathogens in cerebrospinal fluid (CSF). Patients with AE were categorized by with or without neural autoantibodies (NAAb). We further divided patients with NAAb into those with neural cell-surface antibodies (NSAbs) or intracellular antibodies (Abs). Clinical features, laboratory data, and imaging findings were compared between AE, IE, and subgroups.

RESULTS

Memory deficits, involuntary movement, and seizures were relatively more commonly presenting symptoms in AE patients (p < 0.05). The positive rate of Pandy test was higher in IE patients (p = 0.007). Decreased leukocyte, erythrocyte, and platelet counts in blood were found in IE patients (p < 0.05). Lower serum calcium level was found in VE compared to BE (p = 0.027). Meanwhile, higher serum calcium level was found in patients with NSAbs compared with intracellular Abs (p = 0.034). However, higher levels of LDH in CSF were found in patients with intracellular Abs (p = 0.009). In magnetic resonance imaging, hippocampus lesions were more commonly present in patients with AE (p = 0.042). Compared with AE patients, more IE patients displayed the background electroencephalogram rhythm of slow-frequency delta (p = 0.013).

CONCLUSION

Involuntary movement and memory deficits were more specifically present in AE patients. CSF Pandy, blood routine test and hippocampus lesions detections were potential markers for distinguishing AE and IE. Further, CSF LDH, and serum calcium levels were potentially useful to distinguish subgroups of encephalitis.

Neuronal damage and neuroinflammation markers in patients with autoimmune encephalitis and multiple sclerosis

Inflammatory diseases of the central nervous system (CNS) are a diagnostic challenge to clinicians. Autoimmune encephalitis (AE) is an important diagnostic consideration in patients with CNS inflammatory disorders; despite of a wide range of neuropsychiatric symptoms it should be diagnosed as soon as possible and the patient transferred to the neurologist. We studied a group of AE patients (n = 24) as compared to multiple sclerosis (MS, n = 61) and control (n = 19) groups. Detailed clinical pictures of patients are presented. We focused on relevant cerebrospinal fluid (CSF) tests like protein levels, cytosis and oligoclonal bands, neuroinflammation indices (interleukin-6, soluble receptor of IL-6, neopterin, anti-ribosomal proteins antibodies) and markers of neurodegeneration (phosphorylated neurofilament heavy chain, pNfh). Elevated neopterin level was found in AE group as compared to the MS and control groups, while protein and pNfh were increased in both AE and MS groups. In the MS group, the cytosis and soluble receptor of IL-6 were higher as compared to the control group. Anti-ribosomal proteins antibodies were increased in a single patient with AE. High levels of protein were predictive of mortality in AE patients, while IL-6 and pNfh were elevated in severe AE patients. AE patients with paraneoplastic etiology demonstrated oligoclonal bands positivity. Taken together, our results suggest the neopterin as an additional marker of autoimmune brain inflammation. Though higher levels of protein, IL-6 and pNfh were found in patients with severe disease progression and death, prognostic values of these markers should be validated in larger cohorts of patients.