Neural Regeneration Research | 2021

Association between plasma immunoproteasome and 90-day prognosis after first-ever ischemic stroke

 
 
 
 
 

Abstract


Many blood biomarkers are reportedly helpful for predicting post-stroke cognitive impairment (PSCI), but no biomarkers are widely used in clinical practice. The purpose of this study was to investigate the association between the plasma immunoproteasome and patients’ 90-day prognosis after first-ever acute ischemic stroke. In our prospective, single-center study, 259 patients with first-ever acute ischemic stroke were enrolled from the Department of Neurology, Fujian Provincial Hospital, China, from March to September 2014. Of these, 27 patients (10.4%) had unfavorable outcomes as assessed by the Modified Rankin Scale (scores of 3–6). The National Institutes of Health Stroke Scale score on admission, plasma N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) levels, and immunopro-teasome subunit (low molecular mass peptide [LMP]2, LMP5, and LMP7) levels were significantly higher in the unfavorable outcome group than in the favorable outcome group. To predict unfavorable outcomes, the optimal cutoff points were National Institutes of Health Stroke Scale score > 12, NT-pro-BNP level > 1883.5 pg/mL, and LMP2 level > 841.4 pg/mL. Of the 193 patients that were able to complete the Mini-Mental State Examination at 90 days post-stroke, 66 patients (34.2%) had PSCI. Plasma levels of NT-pro-BNP and LMP2 were higher in patients with PSCI than in those without PSCI. To predict PSCI, the optimal cutoff values were age > 70.5 years and LMP2 level > 630.5 pg/mL. These findings indicate that plasma LMP2 may serve as a new prognostic biomarker of poor outcome and PSCI at 90 days after stroke. This study was approved by the Ethics Committee of Fujian Provincial Hospital, Provincial Clinical Medical College of Fujian Medical University (approval No. K2014-01-003) on January 15, 2014.

Volume 16
Pages 790 - 795
DOI 10.4103/1673-5374.295344
Language English
Journal Neural Regeneration Research

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