Clinical factors associated with cognitive impairment in cerebral small vessel disease: a retrospective study

Abstract

Background

Cerebral small vascular disease (CSVD) has an insidious onset and progresses slowly, leading to cognitive impairment. Understanding the clinical characteristics of cognitive impairment is crucial for early identification, prevention, and treatment. This study aimed to analyze risk factors associated with cognitive impairment related to CSVD.

Methods

This retrospective study included 270 patients with CSVD and independent living abilities. Laboratory tests included measurements, such as fasting blood glucose (FBG), glycosylated hemoglobin, and blood creatinine. All patients underwent neuropsychological evaluation, and the main factors influencing cognitive impairment were analyzed using multivariate logistic regression.

Results

Among the patients, 80% (n = 216) had symptomatic cerebral infarction. Factors such as history of symptomatic cerebral infarction, FBG level, blood fibrinogen level, and CSVD total burden score were significantly different between the normal cognition and cognitive impairment groups (p < 0.001, p = 0.049, p = 0.009, p = 0.001, respectively). Logistic regression analysis revealed that age, FBG level, and number of lacunar cerebral infarctions were the main factors influencing cognitive impairment. Age, education level, fibrinogen and d-dimer levels, and CSVD total burden score significantly correlated with the level of cognitive impairment. Impaired daytime function affected the cognitive levels of patients with CSVD (p = 0.043).

Conclusions

This study has highlighted the main risk factors for cognitive impairment in patients with CSVD, such as age, FBG levels, and number of lacunar cerebral infarctions. Additionally, education played a significant role in cognitive outcomes. These findings suggest that managing these risk factors and enhancing cognitive reserve can mitigate the cognitive decline associated with CSVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-026-04911-8.

Background

Cerebral small vessel disease (CSVD) is a prevalent cause of cognitive dysfunction, contributing to 45% of all cases of dementia [1]. Neurological deficits caused by CSVD usually develop insidiously, particularly resulting in cognitive impairment, which significantly affects patients’ quality of life. The clinical diagnosis of mild cognitive impairment (MCI) is challenging, and the condition can gradually progress to dementia, impacting daily life and social activities. Currently, there is no consensus on the pathogenesis of CSVD-related cognitive impairment, and consequently, no precise treatment is available. Previous studies have primarily focused on the association between a single risk factor and cognitive impairment in patients presenting with a single CSVD MRI marker [2]. However, the available evidence remains limited. Therefore, this study aimed to analyze comprehensive risk factors associated with varying degrees of cognitive impairment in patients with common CSVD MRI markers, with the goal of providing new insights for early prevention and clinical management.

Methods

Patients

In this retrospective study, a total of 270 patients with CSVD were followed up at the Department of Neurology of the Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital between December 2022 and December 2024. CSVD diagnosis was based on clinical assessments and confirmed using magnetic resonance imaging (MRI), according to the diagnostic criteria outlined in the “China Small Vascular Disease Expert Consensus 2021” [3].

The exclusion criteria were as follows: (1) brain MRI showing old and new large cerebral infarction (defined as larger than one-third of the middle cerebral artery blood supply area or an Alberta Stroke Program Early CT Score-diffusion weighted imaging (ASPECT-DWI) score < 7 points) [4]; (2) confirmation of dementia caused by other diseases, such as Alzheimer’s disease, Parkinson’s disease, brain tumor, encephalitis, and central nervous system demyelination; and (3) mental or communication disorders affecting the assessment, such as language, vision, and hearing impairments.

All participants volunteered to be included in this study, completed a questionnaire survey involving the cognitive score scale, and provided complete research data. All procedures performed in this study were approved by the Regional Ethical Review Board in Tianjin, China, and were conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from all individual participants included in the study.

Brain MRI

MRI scanning protocol

A Siemens 1.5 T superconducting MRI machine, specifically designed for this study, was used for scanning. The scanning comprised an axial T1-weighted sequence, an axial T2-weighted sequence, axial fluid–attenuated inversion recovery (FLAIR), DWI, and magnetic sensitivity weighted imaging (SWI). Two trained radiologists, blinded to all the clinical data, evaluated the neuroimaging markers of CSVD based on the Standards for Reporting Vascular Changes in Euroimaging criteria [5].

Lacunes were defined as round or ovoid cerebrospinal fluid (CSF) containing cavities with a surrounding rim of hyperintensity in subcortical regions ranging from 3 to 15 mm in diameter. The severity of periventricular white matter hyperintensity (PWMH) and deep WMH (DWMH) was assessed using the Fazekas scale [6]. One point was allocated if (early) confluent DWMH (Fazekas scores 2 and 3) or irregular periventricular hyperintensities extending into the deep white matter (Fazekas score 3) were observed. Cerebral microbleeds (CMBs) were defined as rounded hypointense lesions (2–10 mm in diameter) on SWI sequences. We only considered deep CMBs, as evidence suggests a specific association with (BP-related) arteriolosclerotic CSVD, whereas lobar CMBs are related to amyloid angiopathy [7]. Enlarged perivascular spaces (EPVSs) were defined as round, ovoid, or linear lesions, typically smaller than 3 mm in diameter, which exhibit a CSF-like signal on all sequences and appear hypointense on fluid–attenuated inversion recovery images without a hyperintense rim to distinguish them from old lacunar infarcts [8]. We counted the EPVSs on the slide with the highest number in one hemisphere and graded them based on a previously used three-category ordinal scale (0–10, 10–25, > 25) [9].

Nuclear magnetic load integral of CSVD

Following Klarenbeek’s description, we set the nuclear magnetic load integral of the CSVD to 0–4 points based on the nuclear magnetic resonance performance of each image feature of the CSVD [10]. One point was allocated for each of the following: (1) existence of one or more cavities; (2) presence of one or more MBs; (3) moderately to severely enlarged perivascular space (10–25 or > 25) in the basal ganglia; and (4) early partial fusion of deep brain WMH (Fazekas score of 2 or 3) or irregular periventricular WMH extending to the deep white matter (Fazekas score of 2 or 3).

Sleep assessment

Over the past month, sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI), a questionnaire based on self-reported experiences. The PSQI comprises 19 items, with scores ranging from 0 to 21. A global PSQI score of 5 or more indicates poor sleep quality [11].

Cognition assessment

Patients were classified into normal cognition, MCI, and dementia groups based on their cognitive assessments. The main difference between dementia and MCI lies in the former’s severity of cognitive impairment, which usually interferes with the activities of daily living.

The Montreal Cognitive Assessment Scale (MoCA) was used to assess cognitive function in patients with CSVD [12]. The total MoCA score is 30. Scores of 26–30 indicate normal cognitive function, 18–26 indicates MCI. The MoCA score refers to the evaluator’s years of education. If the education period of the evaluator is ≤ 12 years, one point should be added to the measured score to correct the bias caused by the level of education. Functional abilities were assessed using the activities of daily living scale comprising 20 items [13]. The first 8 items evaluate basic activities of daily living (BADL), while the remaining 12 evaluate instrumental activities of daily living (IADL). In the MCI group, BADL remained intact, while IADL was slightly impaired.

Statistical analysis

Descriptive statistics were used to summarize the data. Values are presented as x ± s for normally distributed measurement data, while the non-normally distributed data are expressed as M (Q1, Q3). Student’s t-test, analysis of variance, and Mann–Whitney U test were used to analyze continuous variables, whether normally or non-normally distributed. Count data were expressed as percentages and analyzed using the chi-square test. Multivariate logistic regression analysis was used to examine the main factors influencing cognitive impairment in CSVD. Spearman’s correlation analyses were conducted to examine the relationship between cognitive levels and clinical factors. The threshold for statistical significance was set at p < 0.05. All statistical analyses were conducted using SPSS V 21.0.

Results

Baseline characteristics

A total of 270 eligible patients with CSVD participated and completed MRI and cognition assessments. Their demographic details are presented in Table 1. Of these, the CSVD cohort exhibited a distinct male predominance (64.07% vs. 35.93%). Additionally, most patients had other chronic diseases, such as hypertension, coronary heart disease, diabetes, and symptomatic stroke. The proportion of these patients exceeded 50%. The distribution of lacunes was highest in the basal ganglia (140, 51.9%), followed by the pons (68, 25.2%), centrum semiovale (55, 20.4%), thalamus (49, 18.1%), and internal capsule (24, 14.1%).

Table 1.

Clinical and biochemical characteristics of the study patients

	All subjects (n = 270)	Cognitive impairment (n = 235)	Cognition normal (n = 35)	T/Z/χ2	p-value
Education (year)	9(9,12)	9(9,12)	12(9,15)	−1.633	0.102
Gender
Men	175(64.81%)	155(65.96%)	20(57.14%)	1.03	0.31
Average age(year)	64.99 ± 7.98	65.51 ± 7.62	61.51 ± 9.48	2.80	0.01*
Smoking history	135(50.0%)	116 (49.36%)	19 (54.29%)	0.30	0.36
Drinking history	85(31.48%)	73(31.06%)	12(34.29%)	0.33	0.85
Past history
Hypertension	225(83.33%)	197(83.83%)	28 (80.00%)	1.11	0.29
Diabetes	131 (48.52%)	115 (48.94%)	16(45.71%)	0.52	0.47
Coronary heart disease	119(44.07%)	108(45.96%)	14(40%)	0.44	0.51
Symptomatic cerebral infarction	212 (78.52%)	191(81.28%)	21(60%)	10.89	< 0.01*
Chronic kidney disease	43(15.83%)	40(17.02%)	3(8.57%)	1.624	0.202
FBG (mmol/L)	6.04(5.20,6.95)	6.08(5.24,7.10)	5.66 (5.01,6.32)	−2.143	0.032*
HbA1c (%)	6.90(6.00,7.63)	6.90(6.05,7.75)	6.10(5.75,7.20)	−1.086	0.278
Blood Fat (mmol/L)
TC	4.94 ± 1.40	4.94 ± 1.46	5.17 ± 0.95	−0.692	0.489
TG	1.72 ± 1.54	1.75 ± 1.60	1.46 ± 0.42	0.788	0.431
LDL	2.95 ± 0.89	2.96 ± 0.93	3.07 ± 0.63	−0.549	0.538
HDL	1.22 ± 0.32	1.21 ± 0.31	1.28 ± 0.29	−0.91	0.364
Renal Function
Cr (μmol/L)	69 (56, 83)	70 (55, 88)	68 (61, 77)	−1.108	0.268
BUN (mmol/L)	6.05(4.91,7.64)	6.00(4.86,7.90)	6.15(5.31,6.90)	−0.393	0.693
UA (μmol/L)	317 (262, 391)	320 (264, 399)	303 (250, 383.5)	−0.617	0.537
Urine protein [N(%)]	65(24.07%)	60(25.53%)	5(14.29%)	2.108	0.146
HCY (μmol/L)	12.91(10.34,17.91)	13.10(10.70,17.82)	10.80(9.66,20.35)	−0.694	0.488
D-Dimer (mg/L)	0.35(0.22,0.59)	0.36(0.23,0.59)	0.27(0.16,0.47)	−1.986	0.047*
FIB (g/L)	3.11(2.59,3.63)	3.13(2.60,3.66)	2.72(2.33,3.47)	−2.163	0.031*
Blood albumin (g/L)	40 ± 5.43	39.92 ± 5.25	40.38 ± 8.00	−0.348	0.728
Fibrinogen/albumin	0.07(0.06,0.09)	0.07(0.06,0.09)	0.06(0.05,0.07)	−2.379	0.017*
Items of Hypertension
4℃ renin (ng/mL)	0.95(0.53,1.41)	1.03(0.60,1.57)	1.18(0.41,1.69)	−0.06	0.952
37℃ renin (ng/mL)	1.98(1.28,2.84)	1.90(1.26,2.88)	2.04(1.58,2.19)	−0.302	0.762
ARR (ratio)	15.37 ± 8.53	16.17 ± 8.37	17.41 ± 9.99	−0.09	0.929
Aldosterone (pg/mL)	139.8 ± 92.65	136.84 ± 74.45	158.93 ± 84.31	−0.016	0.987
PRA (ng/mL/hr)	0.94(0.61,1.36)	0.85(0.54,1.29)	0.92(0.45,1.32)	−0.505	0.613
Thyroid function
fT3 (nmol/L)	2.73 ± 0.49	2.77 ± 0.45	2.71 ± 0.38	−0.299	0.765
fT4 (nmol/L)	0.97 ± 0.13	0.95 ± 0.13	0.97 ± 0.10	0.046	0.964
TSH (mIU/L)	1.96 ± 1.45	1.85 ± 1.26	2.81 ± 1.97	−1.833	0.086
Brain MRI
CMBs	144(53.33%)	136(57.87%)	8(22.86%)	−15.007	< 0.001*
LI (N)	3(2,6)	3(2,6.25)	1(0,2)	−3.736	< 0.001*
PWMH	2(1,3)	2(1,3)	2(1,2)	−2.179	0.029*
DWMH	2(1,2)	2(1,2)	1.5(1,2)	−2.933	0.003*
The total burden score of CSVD	2(1,3)	3(2,3.25)	1(1,2)	−3.475	0.001*

Values are expressed as mean ± standard deviation, number, or median (Q1–Q3)

CHD Coronary heart disease, CKD Chronic kidney disease, FBG fasting blood glucose, HbA1c glycosylated hemoglobin, TC cholesterol, TG triglyceride, LDL low-density lipoprotein, HDL high-density lipoprotein, Cr serum creatinine, BUN serum urea nitrogen, UA serum uric acid, HCY homocysteic acid, FIB fibrinogen, ARR aldosterone-to-renin ratio, PRA plasma renin activity, fT3 free triiodothyronine, fT4 free thyroxin, TSH thyroid stimulating hormone, CMBs cerebral microbleeds, LI lacunes infarction, PWMH periventricular white matter hyperintensities. DWMH deep white matter hyperintensities, CSVD cerebral small vascular disease

^*p < 0.05

Correlation factors of cognitive impairment in patients with CSVD

In the CSVD group, the average age of patients with cognitive impairment (65.51 ± 7.62 years) was higher than that of patients with normal cognitive function (61.51 ± 9.48 years), with a statistically significant difference (T = 2.795, p = 0.006). When compared to patients with normal cognition, those with cognitive impairment had higher fasting blood glucose (FBG) levels (Z = − 2.143, p = 0.032). Additionally, patients with cognitive impairment were more prone to infarction, showing a higher incidence of symptomatic stroke (χ² = 10.893, p = 0.001) and higher levels of blood D-dimer, blood fibrinogen (FIB), and blood fibrinogen/albumin ratio (Z = − 1.986, p = 0.047; Z = − 2.163, p = 0.031; Z = − 2.379, p = 0.017)(Fig. 1). In terms of MRI findings, patients with cognitive impairment in the CSVD group exhibited more severe LIs, a higher frequency of CMBs, and a higher CSVD total burden score (Z = − 3.736, p < 0.001; Z = − 15.007, p < 0.001; Z = − 3.475, p = 0.001) (Fig. 2). Patients with cognitive impairment were more likely to have lacunar infarction located in the basal ganglia and thalamus (χ² = 5.66, p = 0.017; χ² = 4.029, p = 0.045).

Fig. 1.

Patients with cognitive impairment were higher levels of blood D-dimer, blood fibrinogen, and blood fibrinogen/albumin ratio (Z = − 1.985, p = 0.047; Z = − 2.609, p = 0.009; Z = − 2.379, p = 0.017)

Fig. 2.

Patients with cognitive impairment in the CSVD group exhibited higher frequency of lacunes infarction (LI), cerebral microbleeds (CMBs), and white matter hyperintensities (WMH). (Z = 7.756, p = 0.005; Z = − 15.007, p < 0.001; Z = 10.893, p = 0.001)

Multiple logistic regression analysis was employed to examine the association between cognitive impairment and other factors (Table 2). After adjustments for age, years of education, blood FBG level, blood FIB level, and D-dimer level in Model 1, cognitive impairment in CSVD was significantly associated with age and the FBG level (OR: 0.95, 95% CI: 0.91–0.99, p = 0.02; OR: 0.71, 95% CI: 0.52–0.97, p = 0.03). Model 2, in which FGB, FIB, and D-dimer levels were replaced with brain MRI features, including CMBs, number of lacunar cerebral infarctions, PWMH, DWMH, and the total burden scores of CSVD, revealed that the number of lacunar cerebral infarctions was significantly associated with the presence of cognitive impairment (OR: 0.66, 95% CI: 0.50–0.89, p = 0.01). Furthermore, even when the MRI features and serum indexes were simultaneously included as independent variables in Model 3, the blood FBG level and number of lacunar cerebral infarction were significantly associated with the presence of cognitive impairment (OR: 0.69, 95% CI: 0.48–1.00, p = 0.04; OR: 0.68, 95% CI: 0.50–0.91, p = 0.01).

Table 2.

Multiple logistic regression analysis of the association between MRI features and other factors

	Model1			Model 2			Model 3
	OR	95%CI	p-value	OR	95%CI	p-value	OR	95%CI	p-value
Age	0.95	0.91–0.99	0.02*	0.95	0.90–1.00	0.09	0.95	0.90–1.01	0.11
Education (year)	1.13	0.97–1.31	0.11	1.11	0.94–1.31	0.22	1.14	0.96–1.35	0.14
Symptomatic cerebral infarction history				0.64	0.27–1.52	0.31	0.70	0.19–2.71	0.44
FBG (mmol/L)	0.71	0.52–0.97	0.03*				0.69	0.48–1.00	0.04*
D-Dimer (mg/L)	0.93	0.38–2.28	0.97				1.01	0.41–2.52	0.98
FIB (g/L)	0.66	0.41–1.07	0.09				0.91	0.53–1.56	0.73
Brain MRI
CMBs				0.78	0.55–1.10	0.16	0.81	0.57–1.15	0.23
LI (N)				0.66	0.50–0.89	0.01*	0.68	0.50–0.91	0.01*
PWMH				0.78	0.37–1.64	0.50	0.82	0.39–1.76	0.62
DWMH				0.95	0.46–1.97	0.89	0.96	0.46–2.01	0.90
The total burden score of CSVD				0.86	0.42–1.73	0.66	0.78	0.37–1.62	0.50

FBG Fasting blood glucose, FIB Fibrinogen, LI Lacunes infarction, CMBs Cerebral microbleeds, PWMH Periventricular white matter hyperintensities, DWMH Deep white matter hyperintensities, CSVD Cerebral small vascular disease, OR Odds ratio, CI Confidence interval

^*p < 0.05

Comparison of risk factors among various levels of cognition in patients with CSVD

The clinical characteristics of the three groups are shown in Table 3. Patients in the VD group were older. The total proportion of symptomatic cerebral infarctions was higher in the VD and Vascular Cognitive Impairment (VCI) groups (χ² = 9.836, p = 0.007). The cognitively normal group of patients had higher educational levels (Z = 8.723, p = 0.013). Fibrinogen and D-dimer levels were higher in the VD group (Z = 9.837, p = 0.007; Z = 6.772, p = 0.034, respectively). Regarding MRI findings, the VD group had more severe DWMH, a higher proportion of CMBs, more lacunar infarctions, and a higher CSVD total burden score (Z = 15.231, p < 0.001; Z = 19.065, p < 0.001; Z = 8.820, p = 0.012; Z = 12.117, p = 0.002). No significant differences were observed in PWMH levels among the three groups.

Table 3.

Influencing factors of different cognitive levels in patients with CSVD

	Cognition normal (n = 35)	MCI (n = 184)	VD (n = 51)	F/Z/χ2	p-value
Education (year)	12(9,15)	9(9,12)	9(9,12)	8.72	0.01*
Number	35	184	51
Age (year)	61.74 ± 9.82	64.81 ± 7.47	67.59 ± 7.69	5.25	0.01*
Sex (Male, %)	19(54.29%)	119(64.67%)	36(70.59%)	2.43	0.30
Smoking history [N(%)]	21(60%)	95(51.63%)	26(50.98%)	0.89	0.64
Drinking history [N(%)]	13(37.14%)	60(32.61%)	18(35.29%)	0.34	0.84
History [N(%)]
Hypertension	26(74.29%)	154(83.70%)	46(90.20%)	3.85	0.15
Diabetes	15(42.86%)	88(47.83%)	30(58.82%)	2.59	0.25
CHD	14(40%)	78(42.39%)	30(58.82%)	4.79	0.09
CKD	3(8.57%)	29(15.76%)	11(21.67%)	2.63	0.27
Symptomatic CI	21(60%)	145(78.80%)	45(88.25%)	9.84	0.01*
FBG (mmol/L)	5.41(4.89,7.17)	6.47(5.47,7.79)	6.11(5.06,7.02)	3.92	0.14
HbA1c (%)	6.68 ± 1.18	7.08 ± 1.21	6.85 ± 1.05	0.98	0.38
Blood Fat(mmol/L)
TC	5.17 ± 0.95	4.96 ± 1.43	4.89 ± 1.58	0.27	0.76
TG	1.46 ± 0.42	1.44 ± 0.39	2.13 ± 2.70	2.00	0.14
LDL	3.07 ± 0.63	2.98 ± 0.94	2.87 ± 0.90	0.40	0.67
HDL	1.28 ± 0.29	1.20 ± 0.29	1.24 ± 0.38	0.75	0.47
Renal Function
Cr (μmol/L)	65.54 ± 13.53	90.44 ± 79.35	97.05 ± 73.58	1.25	0.29
BUN (mmol/L)	5.57 ± 1.19	7.10 ± 4.44	7.94 ± 5.11	1.96	0.14
UA (μmol/L)	319.05 ± 86.44	330.03 ± 85.47	343.65 ± 109.55	0.58	0.56
Cystatin C (mg/L)	1.34 ± 0.54	2.26 ± 2.98	1.94 ± 1.11	0.20	0.82
Urine protein [N(%)]	5(14.29%)	43(23.37%)	17(33.33%)	4.28	0.12
HCY (μmol/L)	10.80(9.66,20.35)	12.80(10.16,17.60)	14.44(11.14,19.75)	1.63	0.44
D-Dimer (mg/L)	0.20(0.15,0.44)	0.32(0.20,0.46)	0.41(0.28,0.77)	9.84	0.01*
FIB (g/L)	2.86(2.08,3.17)	3.15(2.60,3.66)	3.15(2.60,3.78)	6.77	0.03*
Blood albumin (g/L)	40.38 ± 8.00	40.03 ± 5.42	39.53 ± 4.60	0.19	0.83
Fibrinogen/albumin	0.06(0.05,0.07)	0.07(0.06,0.09)	0.08(0.06,0.10)	5.82	0.05
Thyroid function
fT3 (nmol/L)	2.77 ± 0.45	2.75 ± 0.49	2.70 ± 0.48	0.08	0.93
fT4 (nmol/L)	0.97 ± 0.10	0.97 ± 0.14	0.95 ± 0.13	0.01	0.99
TSH (mIU/L)	2.81 ± 1.97	1.88 ± 1.22	1.76 ± 1.44	0.59	0.25
Brain MRI
CMB [N(%)]	8(22.86%)	108(58.70%)	28(54.92%)	15.23	< 0.01*
LI (N)	1(0,2)	3(1,6)	5(2,8)	19.07	< 0.01*
PWMH	2(1,2)	2(1,3)	2(2,3)	4.79	0.09
DWMH	1.5(1,2)	2(1,2)	2(2,3)	8.82	0.01*
The total burden score	1(1,2)	2(1,3)	2(1,3)	12.12	< 0.01*

MCI Mild cognitive impairment, VD Vascular dementia, CHD Coronary heart disease, CKD Chronic kidney disease, CI Cerebral infarction, FBG Fasting blood glucose, HbA1c Glycosylated hemoglobin, TC Cholesterol, TG Triglyceride, LDL Low-density lipoprotein, HDL High-density lipoprotein, Cr Serum creatinine, BUN Serum urea nitrogen, UA Serum uric acid, HCY Homocysteine acid, FIB Fibrinogen, fT3 Free triiodothyronine, fT4 Free thyroxin, TSH Thyroid stimulating hormone, CMBs Cerebral microbleeds, LI Lacunes infarction, PWMH Periventricular white matter hyperintensities, DWMH Deep white matter hyperintensities, CSVD Cerebral small vascular disease

^*Statistically significant result

Influence of sleep on cognitive impairment in CSVD

The proportion of patients with CSVD and cognitive impairment who reported a history of chronic sleep disorders was approximately 46.7%. Low sleep efficiency was associated with cognitive impairment in patients with CSVD (Z = −2.332, p = 0.020). Impaired daytime function affected the cognitive levels of patients with CSVD (Z = −2.028, p = 0.043) (Table 4).

Table 4.

Sleeping disorders of different cognitive levels in patients with CSVD

Pittsburgh Sleep Quality Assessment	CSVD
	Cognition normal	MCI	VD	Z	p-value
A sleep quality	1 (1,2)	1 (0,2)	1 (1,2)	−0.345	0.730
B sleep latency	1 (0,1.75)	1 (0,2)	1 (0,3)	−0.833	0.405
C sleep duration	1 (0,1)	1 (0,1)	1 (0,1)	−0.225	0.822
D sleep efficiency	1 (0.25,1)	1 (1,1)	1 (1,1)	−0.059	0.953
E Sleep disorders	1 (1,1)	1 (1,1)	1 (1,1)	−0.866	0.387
F hypnogenesis drug	0 (0,0)	0 (0,0)	0 (0,0)	−0.294	0.769
G daytime function	0 (0,1)	0 (0,1)	1 (0,2)	−2.028	0.043*
Total score	5 (4,7.75)	5 (3,8)	6 (4,8)	−0.854	0.393

MCI Mild cognitive impairment, VD Vascular dementia, CSVD Cerebral small vessel disease

^*Statistically significant result

Discussion

In this study, we analyzed the risk factors associated with varying degrees of cognitive impairment in patients with CSVD. Our findings highlight specific risk factors, such as age, the FBG level, and the number of lacunar cerebral infarctions, which significantly correlate with the severity of cognitive impairment in CSVD, offering new insights for early prevention and targeted clinical treatments.

CSVD is a common age-related vascular disease of the brain and is a leading cause of functional loss, disability, and cognitive decline in the elderly [14]. According to our study findings, older age is an independent risk factor for cognitive impairment in CSVD, indicating that older individuals are at a greater risk of cognitive impairment. With increasing age, there is a gradual increase in the severity of arterial wall stiffness in blood vessels. Vascular remodeling, endothelial dysfunction, and stiffness are shared characteristics of hypertension and aging. A cohort study involving 345 patients with hypertension found that 9.1% had MCI, suggesting that hypertension exacerbates white matter sparsity and increases the risk of cognitive impairment [15]. The relationship between large artery stiffening and microvascular disease may be bidirectional, as wave reflection from microvascular sites could increase systolic blood pressure and pulse pressure. Conversely, transmitting increased arterial pulsatility to microvessels could represent a damaging mechanism [16]. Age progression is an uncontrollable factor in the course of life development; however, delaying arteriosclerosis development may be a method for preventing and treating cognitive impairment in CSVD, which has also been a prominent research focus in recent decades.

In this study, high FBG levels were associated with cognitive impairment in patients with CSVD. Type 2 diabetes contributes to CSVD through various mechanisms, including insulin-dependent small-artery dilation, terminal glycosylation, excessive oxidative stress, and epigenetic changes [17]. FBG levels indirectly reflect basal insulin secretion in humans. High FBG levels are associated with insulin resistance, which is significantly associated with cognitive impairment in patients with CSVD. The index of insulin resistance is negatively correlated with MoCA scores [18]. The influence of impaired FBG and insulin resistance on cognitive impairment in CSVD is obvious and will be confirmed by further research in the future.

In a systematic review, the presence of MRI markers of CSVD were found to predict an increased risk of cognitive decline in relatively healthy older adults [19]. VCI is common in patients with lacunar strokes, affecting almost 40% of these individuals [20]. Compared with patients with a single lacunar infarction, those with multiple silent LIs showed poorer performance in semantic fluency and short-delayed verbal memory [21]. This study explored the impact of different CSVD imaging subtypes on cognition. The lacunar infarct count is an independent risk factor for cognitive impairment in CSVD and impacts the severity level of cognitive impairment. For patients with CSVD, risk factors of lacunar infarction, including diabetes mellitus and body mass index (BMI), which are associated with an increased risk of VCI, should be actively controlled [20].

A large longitudinal cohort study (n = 3,569) in South Korea found that WMH predicted the rate of global functional decline and loss of independence in elderly individuals with MCI, an early stage of dementia [22]. In this study, deep white matter lesions were related to cognitive levels in patients with CSVD. Patients with dementia have more severe DWMH. Deep white matter lesions in the brain affect information processing speed and execution abilities in patients with CSVD, establishing connections with gray matter [23]. Furthermore, the location of CMBs is also associated with cognition [24]. Patients with executive dysfunction have more CMBs in the frontal and basal ganglia [25]. CMBs in the basal ganglia may be associated with lower “attention and calculation scores.” By contrast, thalamic CMBs may be independently associated with lower “total function” and “orientation” scores [14]. Appropriate management of risk factors for lacunar infarction, WMH, and CMBs may prevent the occurrence and development of related cognitive disorders.

Sleep is the foundation for recovering strength, energy, learning, and memory. With the accelerated pace of life, an increasing number of people suffer from chronic sleep disorders in China. Poor sleep quality and short sleep duration have notably strong positive associations with an increased risk of hypertension, impaired glucose tolerance, and insulin resistance, which are common risk factors for CSVD [26]. As observed through overnight polysomnography, patients with CSVD showed significantly higher indices in arousal, wake after sleep onset, periodic limb movement during sleep, and periodic limb movement-related arousal, along with lower sleep efficiency, than healthy controls. The occurrence of.

sleep-related breathing disorders (SRBD) was increased in patients with CSVD, particularly in those with acute lacunar stroke located in the brainstem and internal capsule [27]. The incidence of non-breathing-related sleep fragmentation was high in patients with CSVD, and this type of fragmentation was associated with cognitive impairment [28]. In this study, we evaluated subjective sleeping experience and found that lower sleep efficiency and impaired daytime function were associated with cognitive impairment in patients with CSVD.

A high level of education may have a protective effect against cognitive deterioration related to brain vascular damage. In our study, patients with dementia had the fewest years of education, while patients with normal cognition had higher educational attainment. A 6-year follow-up study found that CSVD progresses faster in older, less educated people [29]. Another study found that people with higher education exhibited slower WMH progression, which may be explained by differences in socioeconomic status and lifelong behavioral risk factors associated with early-life educational attainment [30]. Years of full-time education are associated with a lower risk of VCI in patients with lacunar cerebral infarction [2]. Education is an important component and indicator of cognitive reserve (CR). CR suggests that greater intellectual enrichment, including educational attainment, occupational achievement, and social enrichment, engages the brain in compensatory mechanisms [31]. Relevant studies have identified that a higher CR attenuates the negative impact of WMH on cognition [14]. Beyond the educational levels, leisure activities have a protective effect on cognitive function. Scholars have evaluated the impact of nine cognitively stimulating leisure activities (such as learning computers, reading, finishing work, and crossword puzzles) on cognition. After 12 months, patients with WMH who participated in leisure activities exhibited better memory function, processing speed, and executive function more frequently [32]. CR also includes bilingual learning, social activities, family gatherings, and physical exercise. Promoting CR may be a valuable approach for alleviating the negative impact of CSVD on cognitive function.

Our study collected comprehensive clinical data to analyze risk factors associated with different degrees of cognitive impairment related to CSVD. However, it also has some limitations. First, the sample size was small due to the collection of detailed clinical data. Second, some patients were unable to complete all tests. Third, we did not have data on molecular biomarkers for CSVD to further explore potential neuropathological mechanisms underlying the associations of various CSVD markers. In future prospective studies, we plan to continue following patients with CSVD to further confirm these clinical findings and their influence on cognitive function. Future longitudinal studies are warranted to further elucidate the mechanisms underlying these associations and to explore potential therapeutic interventions aimed at reducing the impact of CSVD on cognitive function.

Conclusions

This study demonstrated that the overall cognitive abilities decreased in patients with CSVD. Age, FBG level, and number of lacunar infarctions were independent risk factors for cognitive impairment in CSVD. Additionally, lower sleep efficiency and impaired daytime function were associated with cognitive impairment in CSVD. Managing risk factors of lacunar infarctions (e.g., hypertension, diabetes especially high FBG level, FIB level), improving sleep efficiency, pursuing higher education, and engaging in activities that promote an increase in CR (e.g., computer literacy, reading, and social activities) may be valuable methods for alleviating the progression of cognitive decline in CSVD.

Abbreviations

CSVD

Cerebral small vessel disease

MCI

Mild cognitive impairment

MRI

Magnetic resonance imaging

ASPECT-DWI

Alberta Stroke Program Early CT Score-diffusion weighted imaging

DWI

Diffusion weighted imaging

FLAIR

Fluid–attenuated inversion recovery

SWI

Sensitivity weighted imaging

CSF

Cerebrospinal fluid

PWMH

Periventricular white matter hyperintensity

DWMH

Deep white matter hyperintensity

CMB

Cerebral microbleed

EPVS

Enlarged perivascular space

MoCA

Montreal Cognitive Assessment Scale

BADL

Basic activities of daily living

IADL

Instrumental activities of daily living

FBG

Fasting blood glucose

FIB

Blood fibrinogen

CR

Cognitive reserve

Authors’ contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by XF, SF, and WX. LH, LL, JZ, and RW were responsile for cognitive assessments. XF drafted the first version of the manuscript. All authors read and approved the final manuscript. The co-first author: Xiaocui Wu.

Funding

This study was funded by the Tianjin Science and Technology Program [grant number 18ZXDBSY00080] and the Scientific Research Project of Affiliated Hospital of Tianjin Academy of Traditional Chinese Medicine [grant number 2020015].

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

All procedures performed in this study were approved by the Regional Ethical Review Board in Tianjin, China, and were conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from all individual participants included in the study. Individual patients have significantly reduced cognitive ability, and their legal guardians provided informed consent on their behalf.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.