Abstract
Objective
Cerebral small vessel disease (CSVD) is a common condition among the elderly population. In patients with CSVD, imaging markers, motor function, and cognition are closely interrelated. This study aimed to analyze the effect of cognition on the association between CSVD burden and motor function.
Methods
This cross-sectional study included 134 patients with CSVD, recruited from the China Imaging-based Biobank of Cerebral Small Vessel Diseases (CIBB-CSVD) at Beijing Tiantan Hospital between January 2020 and May 2023. We obtained demographic and medical profiles, as well as the Montreal Cognitive Assessment (MoCA) score, Short Physical Performance Battery (SPPB) score, a four-point CSVD burden score determined through magnetic resonance imaging (MRI), and gait parameters evaluated using the Codamotion analysis system from all participants.
Results
The mean age of all CSVD patients was 60 ± 12 years. The median scores for the CSVD burden, MoCA, SPPB and modified Rankin Scale (mRS) were 3 (2, 4), 20 (16, 24), 11 (9, 12) and 0 (0, 1), respectively. Significant correlations were observed between age and the CSVD burden score, MoCA score, SPPB score, speed, and stride length (P < 0.05). Patients with higher CSVD burden scores exhibited significantly lower SPPB scores, reduced speed, shorter stride length, and decreased hip and knee range of motion (ROM), as revealed by both univariable linear regression and multivariable regression analyses adjusted for age (P < 0.05). However, after further adjustment for MoCA score, only the association between CSVD burden score and SPPB score remained statistically significant (P < 0.05). Mediation analysis indicated that the MoCA score significantly mediated the associations between CSVD burden score and both SPPB score and knee ROM. The proportion of the effect mediated by the MoCA score was 33.835% for SPPB score and 40.167% for knee ROM.
Conclusions
The CSVD burden influences both SPPB score and knee ROM in patients with mild to moderate cognitive and motor impairments, either directly or indirectly through cognitive decline. Cognitive function, as measured by the MoCA score, plays a significant mediating role in the association between CSVD burden and both SPPB score and knee ROM.
Keywords: Cerebral small vessel disease, Magnetic resonance imaging, Short physical performance battery, Motor, Cognition
Introduction
Cerebral small vessel disease (CSVD) is a common age-related condition, characterized by neuroimaging abnormalities such as white matter hyperintensities (WMHs), lacunes, cerebral microbleeds (CMBs), perivascular spaces (PVSs), and brain atrophy. Previous studies have shown that motor and cognitive impairments in CSVD are closely associated with these imaging markers [1–3]. These disorders impact the quality of life and life expectancy of individuals with CSVD. A study conducted by the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) revealed that gait, cognition, and imaging markers of CSVD are associated with an 8-year risk of mortality [4]. These findings highlight the importance of simultaneously considering motor, cognitive, and imaging characteristics, and of exploring their interrelationships to better understand clinical outcomes in CSVD.
According to previous studies, cognitive and motor functions share a common neuroanatomical basis and are closely interconnected [5, 6]. Gait is not only an automated motor activity but also requires executive function, attention, as well as judgment of both external and internal cues [5]. The temporal and causal relationships between gait and cognitive dysfunction remain incompletely understood. Holtzer et al. reported that the protective effects of executive function and episodic memory against declines in gait speed during aging are more pronounced in individuals with higher cognitive reserve [7].
In patients with CSVD, both motor and cognitive impairments are associated with changes observed in imaging studies. The CSVD burden score serves as a comprehensive tool for evaluating the overall severity of imaging findings and may effectively represent the extent of CSVD. The MoCA score was a rapid screening instrument for cognitive dysfunction. We hypothesise that the CSVD burden score is associated with motor performance, and that this association may, in part, be mediated by cognitive decline as measured by the MoCA score.
Methods
Participants
This cross-sectional study included 134 patients with CSVD, recruited from the China Imaging-based Biobank of Cerebral Small Vessel Diseases (CIBB-CSVD) at Beijing Tiantan Hospital between January 2020 and May 2023. All participants underwent both cognitive and motor assessments. This study was approved by the ethics committee of Beijing Tiantan Hospital, and informed consent was obtained from all participants.
The inclusion criteria for CIBB-CSVD are as follows: (1) Age ≥ 18 years; (2) Brain MRI must meet one of the following conditions: (i) Fazekas score ≥ 2; (ii) Fazekas score = 1 with more than two vascular risk factors (hypertension, hyperlipidemia, diabetes mellitus, obesity, smoking); (iii) Fazekas score = 1 with a lacune; (iv) New subcortical lacunar infarction with a diameter of less than 20 mm on MRI; (3) Modified Rankin Scale (mRS) score ≤ 2. The evaluation of CSVD imaging markers was based on the definitions provided in the Standards for Reporting Vascular Changes on Neuroimaging (STRIVE) [8].
The exclusion criteria for CIBB-CSVD are as follows: (1) Acute cerebral infarction; (2) Acute intracerebral hemorrhage; (3) Acute subarachnoid hemorrhage; (4) Diagnosed neurodegenerative diseases; (5) Non-vascular white matter lesions; (6) Psychiatric disorders; (7) Contraindications for MRI; (8) Presence of severe organic diseases; (9) Inability to complete follow-up due to geographical or other reasons; (10) Participation in other clinical trials.
Clinical and scale evaluations
We collected demographic data and medical histories, including age, sex, height, weight, Body Mass Index (BMI), education level, smoking status, hypertension, atrial fibrillation, diabetes mellitus, and hyperlipidemia. The scale assessments included the Montreal Cognitive Assessment (MoCA) and the Short Physical Performance Battery (SPPB) scores.
The MoCA score is a 30-point screening tool designed to assess cognitive impairment, with a particular sensitivity to mild cognitive impairment. The items of the MoCA score have been detailed in a previous study. For patients with 12 years of education or less and a total score below 30 points, one point is added to correct the effect of education level [9].
The SPPB score is a 12-point tool used to evaluate lower extremity function, which includes standing balance, walking speed, and the time taken to rise from a chair five times. Each test has five performance scores ranging from 0 to 4 points, which have been detailed in a previous study [10].
Brain MRI
All participants underwent brain MRI examinations at Beijing Tiantan Hospital using 3-T MRI scanners. We collected T1-weighted, T2-weighted, fluid-attenuated inversion recovery, and diffusion-weighted imaging sequences. The evaluation of CSVD imaging markers was conducted in accordance with the definitions provided in the Standards for Reporting Vascular Changes on Neuroimaging (STRIVE) [8]. The CSVD burden score was calculated based on four imaging markers: WMHs, lacunes, CMBs, and PVSs, with a total score ranging from 0 to 4 points [11].
Gait analysis
Three-dimensional gait analysis was performed for all participants using the Cartesian Optoelectronic Dynamic Anthropometer (Codamotion) system (Charnwood Dynamics Ltd., Leicestershire, UK). The following motor parameters were recorded: speed, stride length, stride time, support phase, hip range of motion (ROM), knee ROM and ankle ROM.
Statistical analysis
We used the mean ± standard deviation and median (P25, P75) to describe numerical variables with normal and nonnormal distributions, respectively. Categorical variables were presented as proportions. The Spearman correlation coefficient was used to assess the correlations of CSVD burden score, MoCA score and motor parameters with age. We evaluated the associations between CSVD burden score and motor parameters using both univariate and multivariable linear regression models. We performed causal mediation analysis under a counterfactual framework [12]. The total effect (TE) was divided into the natural direct effect (NDE) and the natural indirect effect (NIE). The mediation effect is measured by the percentage mediated (PM). A P value < 0.05 (two-sided) was considered statistically significant. All statistical analyses were performed using SAS version 9.4 software (SAS Institute Inc.).
Results
Demographic, clinical and examination characteristics of CSVD patients
The mean age of the 134 CSVD patients was 60 ± 12 years, of whom 55 were female. The median scores for the CSVD burden, MoCA, SPPB and mRS were 3 (2, 4), 20 (16, 24), 11 (9, 12), and 0 (0, 1), respectively (Table 1). Table 1 also presents the distribution of medical histories, along with the means or medians of various demographic and motor parameters, including height, weight, BMI, speed, stride length, stride time, support phase, and ROM for the hip, knee, and ankle.
Table 1.
Demographic, clinical and examination data of CSVD patients
| Characteristics | CSVD patients (N = 134) |
|---|---|
| Age, years, median (IQR) | 60 ± 12 |
| Sex, F/M | 55/79 |
| Height, cm, mean ± SD | 166 ± 8 |
| Weight, kg, mean ± SD | 69.8 ± 10.7 |
| BMI, kg/m2, mean ± SD | 25.3 ± 3.2 |
| Education ≥ 12 years, n (%) | 78 (58%) |
| mRS score, median (IQR) | 0 (0, 1) |
| Currently or previously smoking, n (%) | 60 (45%) |
| Hypertension, n (%) | 87 (65%) |
| Atrial fibrillation, n (%) | 3 (2%) |
| Diabetes mellitus, n (%) | 37 (28%) |
| Hyperlipidemia, n (%) | 29 (22%) |
| CSVD burden score, median (IQR) | 3 (2, 4) |
| MoCA score, median (IQR) | 20 (16, 24) |
| SPPB score, median (IQR) | 11 (9, 12) |
| Speed, m/s, mean ± SD | 0.87 ± 0.24 |
| Stride length, m, mean ± SD | 0.97 ± 0.20 |
| Stride time, s, median (IQR) | 1.12 (1.06, 1.23) |
| Support phase, %, mean ± SD | 52.7 ± 3.6 |
| Hip ROM, °, median (IQR) | 87.4 (54.3, 130.5) |
| Knee ROM, °, median (IQR) | 58.6 (51.0, 62.4) |
| Ankle ROM, °, median (IQR) | 30.5 (25.8, 34.1) |
CSVD cerebral small vessel disease; F female; M male; BMI Body Mass Index; mRS modified Rankin Scale; MoCA Montreal Cognitive Assessment; SPPB Short Physical Performance Battery; ROM range of motion; SD standard deviation; IQR interquartile range
Correlations between age and CSVD burden score, MoCA score and motor parameters in CSVD patients
In patients with CSVD, the CSVD burden score, MoCA score, SPPB score, speed and stride length were all significantly correlated with age. The CSVD burden score (r = 0.249, P = 0.004) increased significantly, while the MoCA score (r = − 0.295, P = 0.003), SPPB score (r = − 0.270, P = 0.002), speed (r = − 0.289, P = 0.001), and stride length (r = − 0.303, P < 0.001) all decrease significantly with age (Fig. 1).
Fig. 1.
Correlations between age and CSVD burden score, MoCA score and motor parameters in CSVD patients. CSVD cerebral small vessel disease; MoCA Montreal Cognitive Assessment; SPPB Short Physical Performance Battery; ROM range of motion
Associations of motor parameters and MoCA score with CSVD burden score
Patients with higher CSVD burden scores demonstrated significantly lower SPPB scores, reduced speed, shorter stride length, and decreased hip and knee ROM, as revealed by both univariable linear regression and multivariable regression analyses adjusted for age (P < 0.05). After further adjustment for age and MoCA score, only the SPPB score remained significantly associated with the CSVD burden score (Table 2).
Table 2.
Linear regression for the associations between CSVD burden score and motor parameters in CSVD patients
| Dependent variables | CSVD burden score | |||||
|---|---|---|---|---|---|---|
| Univariable regression | Multivariable regression—model 1 | Multivariable regression—model 2 | ||||
| β (95% CI) | P | β (95% CI) | P | β (95% CI) | P | |
| SPPB score | − 0.502 (− 0.811–−0.194) | 0.002 | − 0.400 (− 0.712–−0.088) | 0.013 | − 0.454 (− 0.827–−0.080) | 0.020 |
| Speed | − 0.052 (− 0.082–−0.021) | 0.001 | − 0.041 (− 0.071–−0.011) | 0.009 | − 0.029 (− 0.068–0.011) | 0.161 |
| Stride length | − 0.048 (− 0.074–−0.022) | < 0.001 | − 0.038 (− 0.064–−0.012) | 0.005 | − 0.029 (− 0.064–0.005) | 0.098 |
| Stride time | 0.182 (− 0.133–0.498) | 0.259 | 0.147 (− 0.178–0.472) | 0.378 | 0.004 (− 0.024–0.031) | 0.793 |
| Support phase | 0.009 (− 0.487–0.505) | 0.972 | 0.046 (− 0.469–0.561) | 0.862 | − 0.081 (− 0.748–0.585) | 0.812 |
| Hip ROM | − 10.245 (− 18.008–−2.482) | 0.011 | − 9.213 (− 17.205–−1.222) | 0.026 | − 4.310 (− 11.792–3.173) | 0.263 |
| Knee ROM | − 1.705 (− 2.701–−0.709) | 0.001 | − 1.360 (− 2.359–−0.360) | 0.009 | − 1.016 (− 2.302–0.270) | 0.126 |
| Ankle ROM | − 3.050 (− 6.483–0.384) | 0.084 | − 3.062 (− 6.611–0.488) | 0.093 | − 3.729 (− 8.950–1.493) | 0.166 |
SPPB Short Physical Performance Battery; ROM range of motion; CI confidence interval
Multivariable regression—model 1 adjusted for age
Multivariable regression—model 2 adjusted for age and MoCA score
Patients with a higher CSVD burden score exhibited significantly lower MoCA score (β, − 1.475; 95% CI, − 1.336–−0.086; P = 0.002).
Mediation analyses
Table 3 presents the total, direct, and indirect associations between CSVD burden score and motor parameters, with the MoCA score acting as a mediator. In the unadjusted analysis, the MoCA score mediated 37.083% of the association between CSVD burden score and SPPB score, and 45.454% of the association with knee ROM.
Table 3.
Associations between CSVD burden score and motor parameters mediated by MoCA score
| Outcome variable | Effect | Unadjusted analysis | Adjusted analysis† | ||
|---|---|---|---|---|---|
| β/estimate (95% CI) | P value | β/estimate (95% CI) | P value | ||
| SPPB score | Total Effect (TE) | − 0.725 (− 1.106, − 0.344) | < 0.001 | − 0.685 (− 1.062, − 0.309) | < 0.001 |
| Natural Direct Effect (NDE) | − 0.456 (− 0.821, − 0.091) | 0.014 | − 0.454 (− 0.818, − 0.089) | 0.015 | |
| Natural Indirect Effect (NIE) | − 0.269 (− 0.475, − 0.063) | 0.010 | − 0.232 (− 0.423, − 0.041) | 0.017 | |
| Percentage Mediated (PM) | 37.083 (8.709, 65.457) | 0.010 | 33.835 (5.670, 61.999) | 0.019 | |
| Speed | Total Effect (TE) | − 0.047 (− 0.086, − 0.009) | 0.016 | − 0.042 (− 0.079, − 0.004) | 0.054 |
| Natural Direct Effect (NDE) | − 0.029 (− 0.068, 0.010) | 0.143 | − 0.029 (− 0.067, 0.010) | 0.146 | |
| Natural Indirect Effect (NIE) | − 0.018 (− 0.035, − 0.001) | 0.041 | − 0.013 (− 0.028, 0.002) | 0.082 | |
| Percentage Mediated (PM) | 38.042 (− 5.247, 81.332) | 0.085 | 31.798 (− 10.889, 74.486) | 0.144 | |
| Stride length | Total Effect (TE) | − 0.048 (− 0.082, − 0.014) | 0.006 | − 0.043 (− 0.076, − 0.010) | 0.011 |
| Natural Direct Effect (NDE) | − 0.030 (− 0.064, 0.004) | 0.085 | − 0.029 (− 0.063, 0.004) | 0.086 | |
| Natural Indirect Effect (NIE) | − 0.018 (− 0.034, − 0.002) | 0.028 | − 0.013 (− 0.027, 0.000) | 0.057 | |
| Percentage Mediated (PM) | 37.245 (− 0.336, 74.826) | 0.052 | 31.341 (− 5.518, 68.199) | 0.096 | |
| Stride time | Total Effect (TE) | 0.010 (− 0.016, 0.035) | 0.459 | 0.008 (− 0.017, 0.033) | 0.535 |
| Natural Direct Effect (NDE) | 0.004 (− 0.022, 0.031) | 0.777 | 0.004 (− 0.023, 0.030) | 0.787 | |
| Natural Indirect Effect (NIE) | 0.006 (− 0.004, 0.015) | 0.245 | 0.004 (− 0.005, 0.013) | 0.337 | |
| Percentage Mediated (PM) | 59.724 (− 123.35, 242.79) | 0.523 | 54.341 (− 146.460, 255.140) | 0.596 | |
| Hip ROM | Total Effect (TE) | − 7.556 (− 14.706, − 0.406) | 0.038 | − 7.301 (− 14.487, − 0.114) | 0.047 |
| Natural Direct Effect (NDE) | − 4.300 (− 11.592, 2.993) | 0.248 | − 4.310 (− 11.603, 2.983) | 0.247 | |
| Natural Indirect Effect (NIE) | − 3.256 (− 6.420, − 0.092) | 0.044 | − 2.991 (− 6.023, 0.041) | 0.053 | |
| Percentage Mediated (PM) | 43.094 (− 9.975, 96.164) | 0.112 | 40.968 (− 11.598, 93.534) | 0.127 | |
| Knee ROM | Total Effect (TE) | − 1.905 (− 3.221, − 0.590) | 0.005 | − 1.698 (− 2.968, − 0.428) | 0.009 |
| Natural Direct Effect (NDE) | − 1.039 (− 2.318, 0.239) | 0.111 | − 1.016 (− 2.270, 0.238) | 0.112 | |
| Natural Indirect Effect (NIE) | − 0.866 (− 1.549, − 0.183) | 0.013 | − 0.682 (− 1.280, − 0.084) | 0.025 | |
| Percentage Mediated (PM) | 45.454 (5.879, 85.028) | 0.024 | 40.167 (0.313, 80.021) | 0.048 | |
| Ankle ROM | Total Effect (TE) | − 4.842 (− 9.681, − 0.002) | 0.050 | − 4.689 (− 9.556, 0.177) | 0.059 |
| Natural Direct Effect (NDE) | − 3.738 (− 8.827, 1.352) | 0.150 | − 3.729 (− 8.818, 1.361) | 0.151 | |
| Natural Indirect Effect (NIE) | − 1.104 (− 2.947, 0.739) | 0.240 | − 0.960 (− 2.695, 0.774) | 0.278 | |
| Percentage Mediated (PM) | 22.801 (− 20.555, 66.157) | 0.303 | 20.482 (− 21.309, 62.274) | 0.337 | |
SPPB Short Physical Performance Battery; ROM range of motion; CI confidence interval
†: Adjusted for age
In the adjusted model, the MoCA score remained a significant mediator of the associations between CSVD burden score and both SPPB score and knee ROM. The proportion of the effect mediated by the MoCA score was 33.835% for SPPB score and 40.167% for knee ROM (Table 3).
Discussion
Population ageing is a growing global concern. As an age-related condition, CSVD has increasingly emerged as a prevalent disorder among older adults. In the present study, the CSVD burden score, MoCA score, SPPB score, speed and stride length were all significantly associated with age. These findings suggest that CSVD may play a pivotal role in the age-related decline of both cognitive and motor functions. Cognitive and motor impairments are two critical symptoms of CSVD, and are believed to result from pathological changes distributed throughout various brain regions [13].
CSVD imaging markers are closely associated with both motor and cognitive impairments. Numerous studies have linked various CSVD imaging markers to motor dysfunction. Previous research has shown that CSVD contributes to gait disturbances by disrupting the structure of white and grey matter, especially through the integrity of periventricular WMH and related cortical thinning [1, 2]. Additional evidence indicates that enlarged PVS are also associated with motor deficits [14]. The presence of CMBs in regions such as the temporal and frontal lobes, basal ganglia, and brainstem has similarly been linked to gait disturbances in individuals with CSVD [15, 16]. Moreover, there is a correlation between brain atrophy and motor impairment [17]. Resembling the relationship between imaging markers and motor dysfunction, researchers have demonstrated a strong relationship between imaging findings and cognitive impairment. WMH has been shown to be associated with cognitive decline, while a higher cognitive reserve appears to mitigate its detrimental effects on cognition [3, 18]. In the present study, we used the CSVD burden score to evaluate the overall severity of CSVD on imaging. Our results indicated that the CSVD burden score was significantly associated with MoCA score and motor parameters. A higher CSVD burden score was associated with lower MoCA score, SPPB score, speed, step length, and hip and knee ROM. These findings are largely consistent with previous studies, reinforcing the link between cumulative CSVD burden and declines in both cognitive and motor performance.
The associations between CSVD burden score and motor parameters, after adjusting for both age and MoCA score, revealed that the SPPB score was significantly associated with CSVD burden score. These results suggest that the SPPB score may serve as a practical and informative indicator of motor impairment related to CSVD burden, which we will discuss in more detail later. Additionally, the MoCA score appears to play a critical role in the relationship between CSVD burden and motor dysfunction. Participants in our study predominantly exhibited mild to moderate impairments in both cognitive and motor functions, with the MoCA, SPPB, and mRS scores recorded as 20 (16, 24), 11 (9, 12), and 0 (0, 1), respectively. Among these patients, we further explored the mediating role of cognitive function, as assessed by the MoCA score, in the relationship between CSVD burden and motor parameters. In unadjusted analysis, the MoCA score significantly mediated the associations between CSVD burden and both SPPB score and knee ROM, with mediated proportions of 37.083% and 45.454%, respectively. After adjusting for age, the mediating effect of the MoCA score remained statistically significant, accounting for 33.835% and 40.167% of the associations with the SPPB score and knee ROM, respectively.
The close associations among imaging markers, motor impairment, and cognitive dysfunction can be attributed to the overlapping neural networks that govern both motor and cognitive functions. Gait control is primarily mediated by frontal subcortical circuits, comprising five distinct pathways. Two of them are related to motor control, while the remaining three are involved in executive functions [6, 19, 20]. MRI studies have confirmed the contributions of WMH and/or focal brain atrophy to both gait and cognitive dysfunction [3, 5, 21]. Motor and cognitive impairments often coexist in older adults. Emerging evidence indicates that cognitive dysfunction may serve as a predictor of future motor impairments [22]. In 2019, the Canadian Consortium on Neurodegeneration in Aging (CCNA) established a consensus recommending the use of shared measures for assessing both mobility and cognition [23]. Previous research conducted by our group has demonstrated that comorbid CSVD may exacerbate both motor and cognitive deficits in patients with Parkinson’s disease. The motor and cognitive impairments in patients with severe CSVD are significantly more pronounced than those in patients with mild CSVD [24]. Moreover, a recent study reported that the combination of gait analysis and eye-tracking technology provides a promising method for detecting cognitive impairment [25]. A more comprehensive understanding of the interrelationships among CSVD burden, motor impairment, and cognitive dysfunction may assist clinicians in formulating preventive strategies aimed at delaying the onset of falls and dementia, ultimately supporting a longer disability-free life expectancy.
As mentioned above, the SPPB score is a rapid, objective, and reliable tool for assessing lower extremity motor dysfunction in patients with CSVD, with strong clinical applicability. In the present study, the SPPB score was significantly associated with the CSVD burden score, and the MoCA score was found to play a significant mediating role in this association. These findings suggest that the SPPB score is particularly well-suited for evaluating motor abnormalities related to imaging and cognitive function in patients with CSVD. Previous studies have also indicated that the SPPB score can predict fall risk in both hospitalized and community-dwelling older primary care patients [26, 27]. Given its ability to comprehensively assess lower extremities motor performance, the SPPB may serve as a valuable tool for evaluating motor impairments in patients with CSVD.
In addition, our results suggest that the knee ROM of CSVD patients decreases significantly with increasing CSVD burden score. The MoCA score plays a significant mediating role in the relationship between CSVD burden score and knee ROM. With respect to muscle control, the knee ROM is predominantly controlled by the quadriceps femoris and hamstrings. We speculate that the CSVD burden reduces knee ROM by affecting the function of these two muscle groups. This hypothesis requires further acquisition of surface electromyography signals from these muscles during walking for validation.
One limitation of this study is that the enrolled CSVD patients predominantly exhibited only mild to moderate cognitive and motor impairments, with few patients presenting severe dysfunction. As a result, the generalisability of the findings and conclusions is restricted. The other limitation is that the study did not perform a comprehensive analysis of imaging features such as WMHs, lacunes, CMBs, and PVSs, nor did it examine cognitive characteristics including attention, executive functions, memory, language, orientation and so on. Future research should explore these various dimensions to deepen understanding.
Conclusions
In patients with CSVD, the CSVD burden, motor performance, and cognitive function are closely interrelated. The CSVD burden score may influence both SPPB score and knee ROM either directly or indirectly through cognitive decline, particularly in patients with mild to moderate cognitive and motor impairments. Cognitive function, as measured by the MoCA score, plays a significant mediating role in the association between CSVD burden and both SPPB score and knee ROM. Furthermore, we speculate that a decreased SPPB score may serve as a potential indicator of motor impairment associated with CSVD burden and cognitive dysfunction.
Acknowledgements
The authors are grateful to Yanan Zhou for technical assistance in gait analysis.
Abbreviations
- CSVD
Cerebral Small Vessel Disease
- mRS
Modified Rankin Scale
- MoCA
Montreal Cognitive Assessment
- SPPB
Short Physical Performance Battery
- ROM
Range Of Motion
- TE
Total Effect
- NDE
Natural Direct Effect
- NIE
Natural Indirect Effect
- PM
Percentage Mediated
Author contributions
S.Y., T.W., Y.P., Y.G., L.G, H.Q., X.L., H.P., W.C. and Y.W. contributed to conceptualization, methodology, review and editing. S.Y. wrote the original draft. H.Y. did the statistical analysis. W.C. and Y.W. supervised and validated the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
The National Natural Science Foundation of China (82425101). Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0504800, 2023ZD0504801, 2023ZD0504802, 2023ZD0504803, 2023ZD0504804). Beijing Municipal Science & Technology Commission (Z231100004823036).
Data availability
The data that support the findings of this study are available from the corresponding authors.
Declarations
Ethics approval and consent to participate
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University (KY2019-140-02, 3 January 2020).
Informed consent
Informed consent was obtained from all subjects involved in the study.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Weiqi Chen, Email: weiqichen@aliyun.com.
Yilong Wang, Email: yilong528@aliyun.com.
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Associated Data
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Data Availability Statement
The data that support the findings of this study are available from the corresponding authors.