Clinical characteristics and factors associated with short-term prognosis in adult patients with autoimmune encephalitis of non-neoplastic etiology

Prediction model for severe autoimmune encephalitis: a tool for risk assessment and individualized treatment guidance

Background

Severe autoimmune encephalitis (AE) can cause significant neurological deficits, status epilepticus, status dystonicus, and even death, which can be life-threatening to patients. Accurate risk stratification for severe AE progression is critical for optimizing therapeutic strategies. The comprehensive prediction models for severe AE based on routine clinical data and laboratory indicators remain lacking.

Objective

To develop and validate a prediction model for severe AE to optimize individualized treatment.

Methods

We collected clinical data and laboratory examination results from 207 patients with confirmed AE. The study population was divided into development and validation cohort. A prediction model for severe AE was constructed using a nomogram and was rigorously validated both internally and externally. Severe AE was defined as modified Rankin Scale (mRS) > 2 and Clinical Assessment Scale for Encephalitis (CASE) > 4.

Results

The variables ultimately included in the nomogram for the severe AE predictive model were age, psychiatric and/or behavioral abnormalities, seizures, decreased level of consciousness, cognitive impairment, involuntary movements, autonomic dysfunction, and increased intrathecal IgG synthesis rate. It demonstrated excellent discriminative capacity and calibration through internal-external validation.

Conclusion

The prediction model has highly feasibility in clinical practice, and holds promise as an important tool for risk assessment and guiding individualized treatment in patients with AE.

Interpretable machine learning model for predicting the prognosis of antibody positive autoimmune encephalitis patients

OBJECTIVE

The objective was to utilize nine machine learning (ML) methods to predict the prognosis of antibody positive autoimmune encephalitis (AE) patients.

METHODS

The encephalitis data from the Global Burden of Disease (GBD) study is analyzed to reflect the disease burden of encephalitis. This study included 187 patients with AE. 121 patients as training set and 67 patients as validation set. Decision trees (DT), random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor (KNN), support vector machine (SVM), naive bayes (NB), neural network (NN), light gradient boosting machine (LGBM), and logistic regression (LR) are ML methods used to construct predictive models. The constructed models were validated for discrimination, calibration and clinical applicability using validation set data. Shapley additive explanation (SHAP) analysis was used to explain the model.

RESULTS

The number of encephalitis worldwide deaths, incidence and prevalence is increasing every year from 2010 to 2021. The training set included 121 patients with AE. Univariate analysis and LASSO screening identified six variables. The results of constructing models using 9 ML methods showed RF had the highest accuracy (0.860), followed by XGBoost (0.826), with F1 scores of 0.844 and 0.807, respectively. Validation set data showed good discrimination, calibration and clinical applicability of the model. The SHAP values of infection, CSF monocyte percentage, and prealbumin were 0.906, 0.790, and 0.644, respectively.

LIMITATIONS

As a rare disease, the sample size of this study is relatively small.

CONCLUSION

The model constructed using RF and XGBoost has good performance, good discrimination, calibration, clinical applicability, and interpretability.

Efficacy of immunotherapy and prognosis in anti-LGI1 encephalitis patients: A meta-analysis

OBJECTIVE

To assess the efficacy and safety of immunotherapy for LGI1 antibody encephalitis, and consider the predictors of poor outcomes following immunotherapy.

METHODS

We searched PubMed and Embase for articles reporting the immunotherapy data of anti-LGI1 encephalitis patients. The proportions of patients with poor outcomes (modified Rankin Scale [mRS] score > 2) at 3 months, 12 months, and the last follow-up, as well as the odds ratio [OR] of predictors were pooled.

RESULTS

The review included 162 articles with 1066 patients. The proportion of patients with poor functional outcomes was 21% at 3 months, 14% at 12 months, and 14% at the last follow-up after receiving immunotherapy. The proportion of patients with reported relapse was 16.6%. The mean duration from onset to the first relapse was 15.6 months. Predictors significantly associated with poor outcomes were age (increase of 1 year), the presence of cognitive impairment, and CSF LGI1 antibody positive. We did not find a statistically significant association between the worst mRS score in the acute phase, the presence of faciobrachial dystonic seizures (FBDS), days from symptom onset to immunotherapy, second-line treatment, maintenance immunotherapy, or follow-up time and outcomes.

INTERPRETATION

Although most patients respond to immunotherapy, a minority of patients still have poor outcomes. Advanced age, cognitive impairment, and CSF LGI1 antibody positive are associated with an increased risk of poor outcomes. However, due to the insufficiency of the data, these conclusions need to be interpreted with caution.

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.

Plasma lipid profiles and homocysteine levels in anti-N-methyl-D-aspartate receptor encephalitis

Introduction

We aimed to investigate whether lipid profiles and homocysteine levels in patients with anti-N-methyl-D-aspartate receptor encephalitis are related to clinical presentation and prognosis, which may contribute to further research on the pathogenesis and treatment of this disease.

Methods

This study included a total of 43 patients with anti-N-methyl-D-aspartate receptor encephalitis and 43 sex-age-matched healthy controls. Baseline demography, clinical data, patient outcomes, and ancillary examination results were recorded. Patients were followed up every 2-3 months during the first year. The modified Rankin Scale score was used to evaluate the therapeutic effect and clinical outcome.

Results

Among the 43 patients included in this study, 55.81% were male, the mean age of onset was 27 years old, and the median modified Rankin Scale score on admission was 3.0. Apolipoprotein A-1 was significantly lower in patients with anti-N-methyl-D-aspartate receptor encephalitis compared with healthy controls (p = 0.004). Compared with healthy controls, homocysteine (p = 0.002), apolipoprotein B (p = 0.004), Lpa (p = 0.045), and apolipoprotein B/apolipoprotein A-1 (p = 0.001) were significantly increased in patients with anti-N-methyl-D-aspartate receptor encephalitis. According to the modified Rankin Scale scores, 6 months after discharge, 72.09% of patients had a good prognosis and 27.91% had a poor prognosis. In the good prognosis group, age (p = 0.031), lipoprotein a (p = 0.023), apolipoprotein A-1 (p = 0.027) at baseline, and the modified Rankin Scale score on admission (p = 0.019) were significantly higher than those in the poor prognosis group.

Conclusion

This study suggests the possibility that serum lipid profile and homocysteine play an important role in the pathogenesis of anti-N-methyl-D-aspartate receptor encephalitis, providing support for lipid-lowering treatment of anti-N-methyl-D-aspartate receptor encephalitis patients.

Review and meta-analysis of neuropsychological findings in autoimmune limbic encephalitis with autoantibodies against LGI1, CASPR2, and GAD65 and their response to immunotherapy

OBJECTIVES

It is assumed that autoimmune limbic encephalitis (ALE) demonstrates distinct neuropsychological manifestations with differential responses to immunotherapy according to which associated autoantibody (AAB), if any, is identified. Towards investigating whether this is the case, this study aims to summarize respective findings from the primary literature on ALE with AABs binding to cell surface neural antigens and ALE with AABs against intracellular neural antigens.

METHODS

We chose ALE with AABs against leucine-rich, glioma inactivated protein 1 (LGI1) and contactin-associated protein-like 2 (CASPR2) as the most frequent cell surface membrane antigens, and ALE with AABs to Embryonic Lethal, Abnormal Vision, Like 1 (ELAVL) proteins (anti-Hu) and glutamic acid decarboxylase 65 (GAD65) as the most frequent intracellular neural antigens. The PubMed and Scopus databases were searched on March 1st, 2021 for neuropsychological test and -screening data from patients with ALE of these AAB-types. Findings were reviewed according to AAB-type and immunotherapy status and are presented in a review section and are further statistically evaluated and presented in a meta-analysis section in this publication.

RESULTS

Of the 1304 initial hits, 32 studies on ALE with AABs against LGI1, CASPR2, and GAD65 reporting cognitive screening data could be included in a review. In ALE with AABs against LGI1, CASPR2 and GAD65, memory deficits are the most frequently reported deficits. However, deficits in attention and executive functions including working memory, fluency, and psychological function have also been reported. This review shows that ALE patients with AABs against both LGI1 and CASPR2 show higher percentages of neuropsychological deficits compared to ALE patients with AABs against GAD65 before and after initiation of immunotherapy. However, the methodologies used in these studies were heterogenous, and longitudinal studies were not comparable. Moreover, 21 studies including ALE patients with AABs against LGI1 and GAD65 were also suitable for meta-analysis. No suitable study on ALE with AABs against ELAVL proteins could be identified. Meta-Analyses could be executed for cognitive screening data and only partially, due to the small number of studies. However, in statistical analysis no consistent effect of AAB or immunotherapy on performance in cognitive screening tests could be found.

CONCLUSION

Currently, there is no definite evidence supporting the notion that different AAB-types of ALE exhibit distinct neuropsychological manifestations and respond differently to immunotherapy. Overall, we could not identify evidence for any effect of immunotherapy on cognition in ALE. More systematic, in-depth and longitudinal neuropsychological assessments of patients with different AAB-types of ALE are required in the future to investigate these aspects.

Influential Factors, Treatment and Prognosis of Autoimmune Encephalitis Patients With Poor Response to Short-Term First-Line Treatment

Objective

This study was performed to assess the potential factors for poor short-term first-line treatment response, the appropriate further treatment options, and the prognosis in patients with autoimmune encephalitis (AE).

Methods

This retrospective study consisted of 135 patients with AE. According to their short-term first-line treatment response, patients were divided into the response group and the non-response group. The demographics, clinical characteristics, main accessory examinations, immunotherapy, and outcomes of patients were compared between the two groups. Univariate and multivariate logistic regression models were used to analyze whether non-responders have poor long-term outcomes. Further treatment and prognosis of non-responders were also analyzed.

Results

Of the 128 patients who were treated with first-line immunotherapy, 59 (46.1%) were non-responders. Patients in the non-response group had more symptoms and exhibited a higher proportion of mental behavior disorder, central hypoventilation, and autonomic nervous dysfunction. The modified Rankin scale (mRS) scores and neutrophil-to-lymphocyte ratio (NLR) levels were significantly higher and albumin, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (apoA) levels were significantly lower in the non-response group (p < 0.05, all). Multivariate logistic regression analysis showed that the number of clinical symptoms, mental behavior disorder, central hypoventilation, maximum mRS score, and albumin level was independently associated with non-response to short-term first-line treatment. Non-responders had poor long-term outcomes compared with the responders at all times of followed-up (p < 0.05, all). In multivariable analysis, initial first-line treatment response was independently associated with the long-term prognosis, both at 12-month [odds ratio (OR), 4.74, 95% CI, 1.44–15.59, and p=0.010] and 24-month follow-ups (OR, 8.81, 95% CI, 1.65–47.16; and p = 0.011). Among the non-responders, a higher improvement of mRS scores was observed in those who received second-line treatment than those who had no further treatment or repetition of first-line immunotherapy in the follow-up. However, the rate of a good outcome and median mRS scores were not significantly different among the three groups.

Conclusion

Disease severity, clinical features, anti-N-methyl-D-aspartate receptor subtypes, antibody titers, NLR, albumin, HDL-C, and apoA levels were all associated with non-response to short-term first-line treatment. The short-term first-line treatment response is a valuable predictor of long-term outcomes in patients with AE. Second-line immunotherapy may be a more aggressive treatment option for patients who failed short-term first-line immunotherapy.

Clinical Characteristics and Long-Term Prognosis of Anti-LGI1 Encephalitis: A Single-Center Cohort Study in Beijing, China

Background: This study aimed to analyze the clinical characteristics of anti-leucine-rich glioma-inactivated protein 1 (LGI1) encephalitis patients and investigate prognostic factors by using a large-sample and long-term follow-up cohort.

Methods: The clinical data of 45 patients (29 males; mean age, 57.0 years) from May 2014 to August 2019 were collected. All patients were followed up by face-to-face interviews in the third month after discharge and then by telephone and/or face-to-face interviews every 6 months until November 2020. We evaluated each patient's response to the initial treatments at the first interview and divided them into “responders” and “nonresponders.” Relapses were recorded. At the end of follow-up, each patient was evaluated and reclassified into “complete recovery” or “unhealed” groups. Intergroup differences were assessed.

Results: All patients presented with seizures at the initial consultation. Other common manifestations included cognitive dysfunction (82.2%), psychiatric disturbance (66.7%), sleep disorder (54.5%), and hyponatremia (66.7%). During the follow-up period (32.8 ± 13.5 months), six patients experienced relapse within 6–37 months. We observed that the patients who did not respond to the initial treatments and those who relapsed all had a poor long-term prognosis. The patients in the “unhealed” group were older (p = 0.009), had a lower incidence of generalized tonic–clonic seizures (p = 0.041), and had a higher probability of cerebrospinal fluid (CSF) abnormalities (p = 0.024) than those in the “complete recovery” group.

Conclusion: Anti-LGI1 encephalitis was characterized by seizures, cognitive impairment, psychiatric disturbance, and sleep disorders and was often accompanied by hyponatremia. Patients who responded poorly to the initial treatments and those patients who relapsed had dismal long-term prognoses. Advanced age and CSF abnormalities may be risk factors for poor prognosis, but these still need to be verified.

Lipid profiles and their potential inflammatory effects in anti-N-methyl-D-aspartate receptor encephalitis

BACKGROUND

Growing evidence suggests an association between dyslipidemia and autoimmune diseases. This study aimed to perform a preliminary analysis to investigate the role of lipid profiles in anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis and to preliminarily explore the potential inflammatory effects of lipids on this disease by analyzing the association of lipid profiles with different inflammatory markers.

METHODS

This retrospective study consisted of 40 anti-NMDAR encephalitis patients and 74 healthy controls. Serum lipid profiles and different inflammatory markers were analyzed upon admission and at each follow-up. Lipid profiles were compared among subgroups of patients, which were divided according to clinical characteristics. Correlations between lipid profiles and different inflammatory markers were assessed.

RESULTS

The results showed that lipid profiles were abnormal and were correlated with both disease severity and prognosis in patients with anti-NMDAR encephalitis. Correlations between lipid profiles and different inflammatory markers were observed. After 12 months of treatment, inflammatory markers changed with lipid profiles, and these changes were significantly correlated.

CONCLUSIONS

Lipid profiles are associated with pathogenesis and progression of anti-NMDAR encephalitis, and they are significantly correlated with different inflammatory markers, suggesting that the association of lipids with the disease might be influenced by the inflammatory response.

Glutamate Chemical Exchange Saturation Transfer (GluCEST) Magnetic Resonance Imaging in Pre-clinical and Clinical Applications for Encephalitis

BACKGROUND

Encephalitis is a common central nervous system inflammatory disease that seriously endangers human health owing to the lack of effective diagnostic methods, which leads to a high rate of misdiagnosis and mortality. Glutamate is implicated closely in microglial activation, and activated microglia are key players in encephalitis. Hence, using glutamate chemical exchange saturation transfer (GluCEST) imaging for the early diagnosis of encephalitis holds promise.

METHODS

The sensitivity of GluCEST imaging with different concentrations of glutamate and other major metabolites in the brain was validated in phantoms. Twenty-seven Sprague-Dawley (SD) rats with encephalitis induced by Staphylococcus aureus infection were used for preclinical research of GluCEST imaging in a 7.0-Tesla scanner. For the clinical study, six patients with encephalitis, six patients with lacunar infarction, and six healthy volunteers underwent GluCEST imaging in a 3.0-Tesla scanner.

RESULTS

The number of amine protons on glutamate that had a chemical shift of 3.0 ppm away from bulk water and the signal intensity of GluCEST were concentration-dependent. Under physiological conditions, glutamate is the main contributor to the GluCEST signal. Compared with normal tissue, in both rats and patients with encephalitis, the encephalitis areas demonstrated a hyper-intense GluCEST signal, while the lacunar infarction had a decreased GluCEST signal intensity. After intravenous immunoglobulin therapy, patients with encephalitis lesions showed a decrease in GluCEST signal, and the results were significantly different from the pre-treatment signal (1.34 ± 0.31 vs 5.0 ± 0.27%, respectively; p = 0.000).

CONCLUSION

Glutamate plays a role in encephalitis, and the GluCEST imaging signal has potential as an in vivo imaging biomarker for the early diagnosis of encephalitis. GluCEST will provide new insight into encephalitis and help improve the differential diagnosis of brain disorders.

Magnetic resonanse imaging as a prognostic tool in encephalitis in children

We provide the data on the modern use of MRI of different modalities as a prognostic tool in the encephalitis diagnostics in pediatrics. According to the recent scientific knowledge, this implementation is possible, but its efficacy depends on the modality of MRI: structural, functional or MRI with contrast. Structural MRI efficacy in children with encephalitis is dubious and clearly depends on the etiology and phase of the inflammatory process. In the recent years, the implementation of the functional MRI methods (DTI MRS) and MRI with contrast significantly changed the imaging practice; there are some reports that these modalities of MRI are more effective as a prognostic tool in encephalitis than the structural one. Thus, a future research in this field is needed.