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Updated: Aug 16, 2025

Evaluation of the Cognitive Performance of Hypertensive Patients with Silent Cerebrovascular Lesions
Published on: April 23, 2021
Correlations among peripheral blood markers, white matter hyperintensity, and cognitive function in patients with
Binghan Li1, Bingying Du1, Zhengsheng Gu1
1Department of Neurology, Shanghai Changhai Hospital, The Second Military Medical University, Shanghai, China.
Background:
Both inflammation and cerebral white matter injury are closely associated with vascular cognitive impairment (VCI). The aim of this study was to analyze the correlation between peripheral serological markers, white matter injury, and cognitive function in patients with non-disabling ischemic cerebrovascular events (NICE); to identify potential biological markers for the diagnosis and prediction of VCI; and to provide a basis for the early diagnosis and intervention of VCI.
Methods:
We collected clinical data, along with demographic and medical history data, from 151 NICE patients. Fasting venous blood samples were collected. Based on the Montreal Cognitive Assessment (MoCA) after admission, we divided the patients into normal cognitive function (NCF) and VCI groups, and then classified them into mild white matter hyperintensity (mWMH) and severe white matter hyperintensity (sWMH) based on Fazekas scores. The differences in serological marker levels were compared between the cognitive function groups and the white matter hyperintensity groups. Binary logistic regression models and receiver operating characteristic curves were used to analyze the diagnostic predictive value of serological markers for VCI in patients with NICE and in the white matter hyperintensity subgroups.
Results:
Among 151 patients with NICE, 95 were male and 56 were female. Lymphocyte count (OR = 0.405, p = 0.010, 95% CI [0.201, 0.806]), red blood cell count (OR = 0.433, p = 0.010, 95% CI [0.228, 0.821]), and hemoglobin level (OR = 0.979, p = 0.046, 95% CI [0.958, 0.999]) were protective factors for cognitive function in patients with NICE. The sWMH group had a higher age, granulocyte/lymphoid ratio (NLR), and neutrophil percentage but a lower MoCA score, hemoglobin level, and lymphocyte count than the mWMH group. In the mWMH group, lymphocyte count (AUC = 0.713, p = 0.003, 95% CI [0.593, 0.833]) had an acceptable predictive value for the diagnosis of VCI, whereas white blood cell count (AUC = 0.672, p = 0.011, 95% CI [0.545, 0.799]), red blood cell count (AUC = 0.665, p = 0.014, 95% CI [0.545, 0.784]), and hemoglobin level (AUC = 0.634, p = 0.047, 95% CI [0.502, 0.765]) had marginal predictive value for the diagnosis of VCI. In the sWMH group, no significant differences were found in serological markers between the NCF and VCI groups.
Conclusion:
Lymphocyte count, red blood cell count, and hemoglobin level were independent protective factors for cognitive function in patients with NICE; they can be used as potential biological markers to distinguish VCI in patients with NICE and are applicable to subgroups of patients with mWMH.
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