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Evaluation of the Cognitive Performance of Hypertensive Patients with Silent Cerebrovascular Lesions
Published on: April 23, 2021
Predictors for vascular cognitive impairment in stroke patients
Xiangliang Chen1,2, Lihui Duan1, Yunfei Han3
1Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305# East Zhongshan Road, Nanjing, 210002, China.
Vascular cognitive impairment (VCI) affects many stroke survivors. Lower education, female sex, recurrent stroke, and brain atrophy predict VCI in Chinese patients.
Area of Science:
- Neurology
- Neuroscience
- Public Health
Background:
- Vascular cognitive impairment (VCI) affects approximately two-thirds of stroke patients.
- A previous study validated the NINDS-CSN harmonization standard for VCI diagnosis in the Chinese population.
- This study investigated predictors of VCI in Chinese patients following a stroke.
Purpose of the Study:
- To identify key predictors for vascular cognitive impairment (VCI) in Chinese stroke patients.
- To analyze epidemiological, clinical, and neuroimaging factors associated with VCI.
- To provide insights for VCI prevention and management strategies in this demographic.
Main Methods:
- Compared epidemiological, clinical, and neuroimaging data between stroke patients with and without VCI.
- Utilized univariate and logistic regression analyses to determine significant VCI predictors.
- Assessed infarcts, lacunes, white matter hyperintensities, and brain atrophy.
Main Results:
- 56 stroke patients (55.4% diagnosed with VCI) were analyzed.
- VCI was associated with older age, lower education, female sex, recurrent stroke, higher apathy, and worse pre-stroke cognition.
- Independent predictors included lower educational level, female sex, recurrent stroke, and global cortical atrophy.
Conclusions:
- Lower education, female sex, recurrent stroke, and global cortical atrophy are independently associated with VCI in Chinese stroke patients.
- These findings highlight specific risk factors for VCI in this population.
- Understanding these predictors can aid in targeted interventions and improved patient outcomes.
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