Department of Infectious Diseases, UT Health McGovern Medical School, Houston, Texas, USA.
Johns Hopkins Encephalitis Center, Johns Hopkins University, Baltimore, Maryland, USA.
Clin Infect Dis. 2023 Feb 8;76(3):e1294-e1301. doi: 10.1093/cid/ciac711.
Encephalitis represents a challenging condition to diagnose and treat. To assist physicians in considering autoimmune encephalitis (AE) sooner, we developed and validated a risk score.
The study was conducted as a retrospective cohort of patients with a diagnosis of definite viral encephalitis (VE) and AE from February 2005 to December 2019. Clinically relevant and statistically significant features between cases of AE and VE were explored in a bivariate logistic regression model and results were used to identify variables for inclusion in the risk score. A multivariable logistic model was used to generate risk score values and predict risk for AE. Results were externally validated.
A total of 1310 patients were screened. Of the 279 enrolled, 36 patients met criteria for definite AE and 88 criteria for definite VE. Patients with AE compared with VE were more likely to have a subacute to chronic presentation (odds ratio [OR] = 22.36; 95% confidence interval [CI], 2.05-243.7), Charlson comorbidity index <2 (OR = 6.62; 95% CI, 1.05-41.4), psychiatric and/or memory complaints (OR = 203.0; 95% CI, 7.57-5445), and absence of robust inflammation in the cerebrospinal fluid defined as <50 white blood cells/µL and protein <50 mg/dL (OR = 0.06; 95% CI, .005-0.50). Using these 4 variables, patients were classified into 3 risk categories for AE: low (0-1), intermediate (2-3), and high (4). Results were externally validated and the performance of the score achieved an area under the curve of 0.918 (95% CI, .871-.966).
This risk score allows clinicians to estimate the probability of AE in patients presenting with encephalitis and may assist with earlier diagnosis and treatment.
脑炎的诊断和治疗具有挑战性。为了帮助医生更早地考虑自身免疫性脑炎(AE),我们开发并验证了一个风险评分。
这项研究是对 2005 年 2 月至 2019 年 12 月期间确诊为病毒性脑炎(VE)和 AE 的患者进行的回顾性队列研究。在双变量逻辑回归模型中探讨了 AE 和 VE 病例之间具有临床相关性和统计学意义的特征,并将结果用于确定纳入风险评分的变量。使用多变量逻辑模型生成风险评分值并预测 AE 的风险。结果进行了外部验证。
共筛选了 1310 名患者。在纳入的 279 名患者中,36 名患者符合明确 AE 的标准,88 名患者符合明确 VE 的标准。与 VE 相比,AE 患者更有可能出现亚急性至慢性表现(优势比[OR] = 22.36;95%置信区间[CI],2.05-243.7),Charlson 合并症指数<2(OR = 6.62;95% CI,1.05-41.4),有精神和/或记忆问题(OR = 203.0;95% CI,7.57-5445),且脑脊液中无明显炎症(定义为白细胞<50/μL 和蛋白<50mg/dL)(OR = 0.06;95% CI,0.005-0.50)。使用这 4 个变量,将患者分为 AE 的 3 个风险类别:低(0-1)、中(2-3)和高(4)。结果进行了外部验证,评分的性能获得了 0.918(95%CI,0.871-.966)的曲线下面积。
该风险评分可让临床医生估计患有脑炎的患者发生 AE 的概率,可能有助于更早诊断和治疗。