ArticleFrontiers in immunology2022
Risk Prediction Models for Early ICU Admission in Patients With Autoimmune Encephalitis: Integrating Scale-Based Assessments of the Disease Severity.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 8 citations in OpenAlex.
- FDG-PET Associations With Disease Severity and Outcomes in NMDA-Receptor IgG Autoimmune Encephalitis.Annals of clinical and translational neurology · 2026Article
- Autoimmune Encephalitis in Acute Care-Pathology, Diagnosis, and Management.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Early prediction of severe autoimmune encephalitis: development and validation of a model incorporating readily available lactate dehydrogenase.Frontiers in immunology · 2026Article
- Prediction model for severe autoimmune encephalitis: a tool for risk assessment and individualized treatment guidance.Frontiers in neurology · 2025Article
- Clinical spectrum and long-term outcomes of antibody-negative severe autoimmune encephalitis: a retrospective study.Frontiers in immunology · 2025Article
- Predicting ICU Admission in Patients with Autoimmune Glial Fibrillary Acidic Protein Astrocytopathy.ImmunoTargets and therapy · 2025Article
- Characterization and prognosis of autoimmune encephalitis in the neurological intensive care unit: a retrospective study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023Article
- Risk Prediction Models for Invasive Mechanical Ventilation in Patients with Autoimmune Encephalitis: A Retrospective Cohort Study.Journal of immunology research · 2023Article
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Authors and funding
6 authors at 2 institutions in 1 country.
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Abstract
Background: In patients with autoimmune encephalitis (AE), the prediction of progression to a critically ill status is challenging but essential. However, there is currently no standard prediction model that comprehensively integrates the disease severity and other clinical features. The clinical assessment scale in autoimmune encephalitis (CASE) and the modified Rankin Scale (mRS) have both been applied for evaluating the severity of AE. Here, by combining the two scales and other clinical characteristics, we aimed to investigate risk factors and construct prediction models for early critical care needs of AE patients. Methods: Definite and probable AE patients who were admitted to the neurology department of Tongji Hospital between 2013 and 2021 were consecutively enrolled. The CASE and mRS scores were used to evaluate the overall symptom severity at the time of hospital admission. Using logistic regression analysis, we analyzed the association between the total scores of the two scales and critical illness individually and then we evaluated this association in combination with other clinical features to predict early intensive care unit (ICU) admission. Finally, we constructed four prediction models and compared their performances. Results: Of 234 patients enrolled, forty developed critical illness and were early admitted to the ICU (within 14 days of hospitalization). Four prediction models were generated; the models were named CASE, CASE-plus (CASE + prodromal symptoms + elevated fasting blood glucose + elevated cerebrospinal fluid (CSF) white blood cell (WBC) count), mRS and mRS-plus (mRS + prodromal symptoms + abnormal EEG results + elevated fasting blood glucose + elevated CSF WBC count) and had areas under the ROC curve of 0.850, 0.897, 0.695 and 0.833, respectively. All four models had good calibrations. In general, the models containing "CASE" performed better than those including "mRS", and the CASE-plus model demonstrated the best performance. Conclusion: Overall, the symptom severity at hospital admission, as defined by CASE or mRS, could predict early ICU admission, especially when assessed by CASE. Adding other clinical findings, such as prodromal symptoms, an increased fasting blood glucose level and an increased CSF WBC count, could improve the predictive efficacy.
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