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Neurofilament light is associated with clinical outcome and hemorrhagic transformation in moderate to severe ischemic stroke

BACKGROUND: Ischemic stroke is a leading cause of morbidity and mortality worldwide. One possible predictor is the use of biomarkers especially neurofilament light chain (NFL). OBJECTIVES: To explore whether NFL could predict clinical outcome and hemorrhagic transformation in moderate to severe stro...

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Detalles Bibliográficos
Autores principales: Rattanawong, Wanakorn, Ongphichetmetha, Tatchaporn, Hemachudha, Thiravat, Thanapornsangsuth, Poosanu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827527/
https://www.ncbi.nlm.nih.gov/pubmed/36632518
http://dx.doi.org/10.1177/11795735221147212
Descripción
Sumario:BACKGROUND: Ischemic stroke is a leading cause of morbidity and mortality worldwide. One possible predictor is the use of biomarkers especially neurofilament light chain (NFL). OBJECTIVES: To explore whether NFL could predict clinical outcome and hemorrhagic transformation in moderate to severe stroke. DESIGN: Single center prospective cohort study. METHODS: Fifty-one moderate to severe ischemic stroke patients were recruited. Blood NFL was obtained from patients at admission (First sample) and 24-96 hours later (Second sample). NFL was analyzed with the ultrasensitive single molecule array (Simoa). Later, we calculated incremental rate NFL (IRN) by changes in NFL per day from baseline. We evaluated National Institute of Health stroke scale (NIHSS), modified Rankins score (mRs), and the presence of hemorrhagic transformation (HT). RESULTS: IRN was found to be higher in patients with unfavorable outcome (7.12 vs 24.07, P = .04) as well as Second sample (49.06 vs 71.41, P = .011), while NFL First sample was not significant. IRN had a great correlation with mRS (r = .552, P < .001). Univariate logistic regression model showed OR of IRN and Second sample to be 1.081 (95% CI 1.016-1.149, P = .013) and 1.019 (1.002-1.037, P = .03), respectively. Multiple logistic regression model has shown to be significant. In receiver operating analysis, IRN, Second sample, combined IRN with NIHSS and combined Second sample with NIHSS showed AUC (.744, P = .004; 0.713, P = .01; 0.805, P < .001; 0.803, P < .001, respectively). For HT, First sample and Second sample had significant difference with HT (Z = 2.13, P = .033; Z = 2.487, P = .013, respectively). CONCLUSION: NFL was found to correlate and predict clinical outcome. In addition, it was found to correlate with HT.