Risk Prediction Models for Early ICU Admission in Patients With Autoimmune Encephalitis: Integrating Scale-Based Assessments of the Disease Severity - Wu, Chunmei; Fang, Yongkang; Zhou, Yingying; Wu, Huiting; Huang, Shanshan; Zhu, Suiqiang (Frontiers in Immunology, 2022)
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 the 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 intensive care unit (ICU) admission. Finally, we constructed four prediction models and compared their performances. Results: Of 301 patients enrolled, ninety developed critical illness and were admitted to the ICU. Four prediction models were generated; the models were named CASE, CASE-plus (CASE + prodromal symptoms + elevated fasting blood glucose + elevated peripheral white blood cell (WBC) count), mRS and mRS-plus (mRS + prodromal symptoms + epilepsy onset + elevated fasting blood glucose + elevated peripheral WBC count) and had areas under the ROC curve of 0.908, 0.935, 0.813 and 0.872, 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 ICU admission, especially when assessed by CASE. Adding other clinical findings, such as prodromal symptoms, an increased fasting blood glucose level and an increased peripheral WBC count, could improve the predictive efficacy.