Blood Plasma Trophic Growth Factors Predict the Outcome in Patients with Acute Ischemic Stroke

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 8th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2020

Год издания: 2020

Идентификатор DOI: 10.1007/978-3-030-45385-5_3

Ключевые слова: Brain, Brain-derived neurotrophic factor, Ischemic stroke, Neurogenesis, Vascular endothelial growth factorBioinformatics, Biomedical engineering, Diagnosis, Forecasting, Acute ischemic stroke, Brain-derived neurotrophic factors, Dynamic assessment, Minimally invasive, Outcome prediction, Plasma concentration, Prognostic significance, Vascular endothelial growth factor, Blood

Аннотация: Stroke is an acute disorder of CNS being the leading factor of mortality and disability of the population. Dynamic assessment of trophic growth factors expression is a promising tool to predict the outcome of ischemic stroke. We investigated the concentration dynamics of the brain-derived neurotrophic factor (BDNF) and vascular endПоказать полностьюothelial growth factor (VEGF) in blood plasma of patients with acute ischemic stroke. 56 patients took part in the study. Venous blood was collected from all patients on the first, 7th and 21st day of their hospital stay. BDNF and VEGF plasma concentrations were measured using ELISA. Our study shows, that not single, but serial dynamic measures of BDNF plasma concentrations in the acute period of ischemic stroke have a prognostic significance. Increasing of the BDNF plasma concentration on day 7 in comparison to the concentration on day 1 was significantly associated with a better clinical outcome of acute ischemic stroke. Extremely high VEGF plasma concentrations (more than 260 pg/mL) on days 1 and 7 from the ischemic stroke onset were significantly associated with a worse clinical outcome on day 21 and a less favorable rehabilitation prognosis. Serial measurement of plasma concentrations of trophic growth factors in patients with ischemic stroke presents a rather simple, reliable and minimally invasive method of dynamic assessment of the clinical course of acute ischemic stroke and early outcome prediction.

Ссылки на полный текст

Издание

Журнал: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Выпуск журнала: vol. 12108 LNBI

Номера страниц: 27-39

ISSN журнала: 03029743

Издатель: Springer

Авторы

  • Roslavtceva V. (I.S. Berzon Krasnoyarsk Interregional Clinical Hospital No 20, 12 Instrumentalnaya Street, Krasnoyarsk, 660123, Russian Federation)
  • Bushmelev E. (Institute of Computational Modelling of SB RAS, Akademgorodok, Krasnoyarsk, 660036, Russian Federation)
  • Astanin P. (Voino-Yasenetsy Krasnoyarsk State Medical University, 1 P. Zheleznyaka Street, Krasnoyarsk, 660022, Russian Federation)
  • Zabrodskaya T. (Voino-Yasenetsy Krasnoyarsk State Medical University, 1 P. Zheleznyaka Street, Krasnoyarsk, 660022, Russian Federation)
  • Salmina A. (Voino-Yasenetsy Krasnoyarsk State Medical University, 1 P. Zheleznyaka Street, Krasnoyarsk, 660022, Russian Federation)
  • Prokopenko S. (Voino-Yasenetsy Krasnoyarsk State Medical University, 1 P. Zheleznyaka Street, Krasnoyarsk, 660022, Russian Federation)
  • Laptenkova V. (I.S. Berzon Krasnoyarsk Interregional Clinical Hospital No 20, 12 Instrumentalnaya Street, Krasnoyarsk, 660123, Russian Federation)
  • Sadovsky M. (Institute of Computational Modelling of SB RAS, Akademgorodok, Krasnoyarsk, 660036, Russian Federation; Siberian Federal University, 79 Svobodny Prosp., Krasnoyarsk, 660041, Russian Federation)
  • Rojas I.Valenzuela O.Rojas F.Herrera L.J.Ortuno F.

Вхождение в базы данных