Literature DB >> 29770431

Outcome in lacunar stroke: A cohort study.

V Mantero1, C Scaccabarozzi1, E Botto1, G Giussani1, A Aliprandi1, A Lunghi2, E Ciusani3, G Brenna4, A Salmaggi1.   

Abstract

OBJECTIVES: We evaluated a prospective cohort of 150 patients under observation in our centre for lacunar strokes. The purpose of this study was to evaluate the outcome at time of discharge and 6 months after lacunar stroke, as well as the correlation with cardiovascular risk factors and selected biochemical parameters already evaluated on admission. Focus was to identify possible prognostic factors, which might be targeted through appropriate intervention concentrating on reduction in the incidence and impact of early clinical deterioration.
METHODS: 150 patients with a lacunar stroke were included in the present study. A clinical 6-month follow-up was available for 98.7% of the patients. Infarcts were classified by size, shape and location.
RESULTS: The most important predictors of high NIHSS score at time of discharge resulted NIHSS on admission (P < .001), leukocytosis (P = .013), in-hospital infections (P = .016) and size of lacunae (P = .005). Similarly, the most important predictors of poor outcome 6 months later were NIHSS on admission (P = .01), leukocytosis (P = .014), elevated CRP (P = .019), in addition to pre-admission Rankin (P < .001).
CONCLUSION: Although infections are not causatively related to lacunar strokes, their prompt recognition and early treatment, control of inflammatory markers and fever are most important in influencing functional outcome in lacunar stroke.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  C-reactive protein; infections; inflammatory markers; lacunar stroke; outcome

Mesh:

Year:  2018        PMID: 29770431     DOI: 10.1111/ane.12961

Source DB:  PubMed          Journal:  Acta Neurol Scand        ISSN: 0001-6314            Impact factor:   3.209


  1 in total

1.  Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State.

Authors:  Lihong Han; Li Liu; Yankun Hao; Lan Zhang
Journal:  Contrast Media Mol Imaging       Date:  2021-07-26       Impact factor: 3.161

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.