Intracerebral hemorrhage (ICH) is one of the most devastating forms of stroke. However, studies on ICH at high altitude are insufficient. We aimed to compare the initial manifestations, imaging features and short-term functional outcomes of ICH at different altitudes, and further explore the effect of altitude on the severity and prognosis of ICH. We retrospectively recruited ICH patients from January 2018 to July 2021 from two centers at different altitudes in China. Information regarding to clinical manifestations, neuroimages, and functional outcomes at discharge were collected and analyzed. Association between altitude and initial severity, neuroimages, and short-term prognosis of ICH were also investigated. A total of 724 patients with 400 lowlanders and 324 highlanders were enrolled. Compared with patients from the plain, those at high altitude were characterized by more severe preliminary manifestations ( P < 0.0001), larger hematoma volume ( P < 0.001) and poorer short-term functional outcome ( P < 0.0001). High altitude was independently associated with dependency at discharge (adjusted P = 0.024), in-hospital mortality (adjusted P = 0.049) and gastrointestinal hemorrhage incidence (adjusted P = 0.017). ICH patients from high altitude suffered from more serious initial manifestations and worse short-term functional outcome than lowlanders. Control of blood pressure, oxygen supplementation and inhibition of inflammation may be critical for ICH at high altitude.

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a severe autoimmune neurological disorder characterized by pathogenic antibodies against the NMDAR. A systematic protein profiling approach is warranted to identify biomarkers capable of predicting disease status. An Olink proximity extension assay (PEA) profiled 91 inflammation-related proteins from anti-NMDAR encephalitis patients. Disease severity or prognosis were assessed by CASE score or mRS score at 6-month follow-up. Patients were stratified into distinct molecular clusters using unsupervised clustering. Logistic regression models incorporating selected biomarkers were developed to predict disease severity and prognosis, followed by absolute quantification using ELISA. Patients were classified into four consensus clusters. Clusters 1 and 2 corresponded to the mild group, while Cluster 3 represented the severe group, consistent with CASE score above 6. Cluster 4 showed heterogeneous clinical features. Elevated serum levels of IL-10, IL-6, and SIRT2, as well as increased CSF levels of CXCL10, CXCL11, and MMP10, were positively associated with severe disease. Conversely, several proteins including LTA and CCL11, CCL8, TGFB1, CXCL6 were associated with severe disease or unfavorable 6-month outcomes. A logistic regression model combining serum CXCL6 and CCL11 with CSF MMP10 achieved an area under the curve (AUC) of 0.95 for predicting disease severity. Serum CCL11 alone showed predictive value for 6-month prognosis, with an AUC of 0.79. These findings delineate distinct protein signatures associated with clinical heterogeneity of anti-NMDAR encephalitis. Prediction models incorporating multiple biomarkers may provide an approach for disease severity stratification and prognosis forecast.