Analysis Of Risk Factors For Cognitive Impairment In Cerebral Small Vessel Diseases And Correlation Of Imaging Markers

Objective: Cognitive dysfunction caused by cerebral small vessel diseases(CSVD)is common in clinical practice,and its high occult nature and incidence cause serious burden to the society.We aimed to explore the risk factors for cognitive impairment of CSVD and the relationship between the imaging markers of CSVD and cognitive impairment.So as to provide more diagnostic and evaluation basis for cognitive impairment caused by CSVD in clinic.Methods: We prospectively analyzed 103 consecutive patients with CSVD admitted to the neurological department of Tongji Hospital from May 2018 to September 2019,and the diagnostic criteria of CVSD conformed to the "Chinese consensus on diagnosis and treatment of CSVD in 2015".Clinical baseline data,laboratory data and head magnetic resonance imaging data(including 5 sequences of T1,T2 and T2 FLAIR,DWI and SWI)were recorded respectively.The Mini-Mental State Examination(MMSE)and the Montreal Cognitive Assessment(Mo CA)Beijing edition were used to evaluate the patients’ overall cognitive function.Various cognitive domains impairment of patients were assessed by Auditory Verb Learning test(AVLT)(the edition of huashan hospital affiliated to fudan university),Boston naming test(BNT),Clock drawing test(CDT),Digit Span test(DST)and other special cognitive domain assessment scales.The risk factors of cognitive impairment caused by CSVD and the risk factors of white matter hyperintensities(WMH)and cerebral microbleeds(CMBs)were investigated by univariate analysis and multi-factor analysis.Results:(1)Among the 103 enrolled patients,There were 65 males(63.1%)and 38 females(36.9%),with an average age of 65.90±12.57 years.Multivariate binary Logistic regression found that the total number of CMBs ≥7(OR=1.159,95% CI:1.087-1.236,P<0.001),age(OR=1.070,95% CI:1.004-1.141,P=0.038)were associated with cognitive impairment(MMSE assessed cognitive impairment).The total number of CMBs ≥3(OR=2.566,95% CI:1.350-4.878,P=0.004)was a risk factor for cognitive impairment(MOCA assessed cognitive impairment).(2)Analysis of clinical risk factors for cognitive impairment and damaged cognitive domains Multiple linear regression analysis found When illiteracy was taken as a reference,primary school(β=4.170,P=0.041),middle school(β=4.895,P=0.020),high school(secondary school)(β=5.429,P=0.012),and university(undergraduate)(β=7.021,P=0.002)were positively correlated factors affecting overall cognitive function(MMSE assessment).Likewise,primary school(β=4.987,P=0.043),middle school(β=6.019,P=0.017),high school(secondary school)(β=6.187,P=0.015),and university(undergraduate)(β=7.207,P=0.007)were positively correlated factors affecting overall cognitive function(Mo CA assessment).Multiple linear regression analysis found that the positive correlation factors for BNT scores were high school(secondary school)(β=4.116,P=0.040),and university(undergraduate)(β=5.135,P=0.015).The CDT score of related factors were primary school(β=0.995,P=0.032),middle school(β=1.126,P=0.018),high school(secondary school)(β=1.447,P=0.003),and university(undergraduate)(β=1.667,P=0.001),antiplatelet drug use(β=-0.386,P=0.016),hypertension(β=-0.269,P=0.042).The positive correlation factor for Digit span test(DST)foreward span and backward span score was triglyceride(β=0.307,P=0.038 和 β=0.224,P=0.015).The relevant factors for score of Auditory verbal learning test(AVLT)were university(undergraduate)(β=13.972,P=0.049)and age(β=-0.357,P<0.001).(3)Analysis of imaging characteristics for cognitive impairment and damaged cognitive domains Associated with the imaging features of cognitive impairment of multivariate linear regression analysis discovered that the parietal and occipital WMH(β=-1.596,P<0.001),total CMBs in lobes(β=-0.250,P<0.001)were adverse correlation factors for cognitive dysfunction(MMSE assessed cognitive impairment).Severe basal ganglia WMH(β=-1.692,P=0.041),the parietal and occipital WMH(β=-1.970,P=0.001),total CMBs in lobes(β=-0.222,P=0.002)were negative correlation factors for cognitive dysfunction(Mo CA assessed cognitive impairment).Multiple linear regression analysis of imaging features of impairment in various cognitive domains revealed that the negative correlation factors for BNT scores were the parietooccipital WMH(β=-1.37,P=0.002),total CMBs in lobes(β=-0.206,P<0.001).The adverse correlation factors for CDT scores were the parietooccipital WMH(β=-0.215,P=0.046),total CMBs in lobes and deep location(β=-0.048,P=0.007 and β=-0.046,P=0.024).The adverse correlation factors for DST forward span scores were the presence of WMH in the infratentorial and parietooccipital lobes(β=-0.809,P=0.007 and β=-0.788,P=0.001),total CMBs in lobes(β=-0.063,P=0.031).The negative correlation factors for DST backward span scores were the presence of WMH in the infratentorial parioccipital and temporal lobes(β=-0.468 P=0.028,β=-0.598 P=0.001 and β=-0.421 P=0.050 respectively).The negative correlation factors for the total AVLT scores were the parietooccipital WMH(β=-4.571,P=0.010)and severe basal ganglia WMH(β=-8.075,P=0.002).(4)Clinical features and imaging markers of cognitive impairment and damaged cognitive domains Multiple linear regression analysis of cognitive impairment revealed that primary school(β=4.599,P<0.001),middle school(β=5.150,P=0.001),high school(secondary school)(β=4.854,P<0.001),and university(undergraduate)(β=5.918,P<0.001),total CMBs in lobes(β=-0.229,P<0.001),and the presence of WMH in the infratentorial and parietal occipital lobes(β=-1.391,P=0.006 and β=-1.406,P=0.001)were the correlation factor of MMSE scores.Primary school(β=5.796,P=0.001),middle school(β=6.532,P<0.001),high school(secondary school)(β=6.168,P<0.001),and university(undergraduate)(β=6.401,P<0.001),total CMBs in lobes(β=-0.212,P=0.003),severe WMH in basal ganglia(β=-1.720,P=0.038),and the parietooccipital WMH(β=-1.783,P=0.002)were the correlation factor of Mo CA scores.Multiple linear regression analysis of various cognitive domains found that the correlation factors for BNT scores were primary school(β=3.464,P=0.008),middle school(β=3.857,P=0.003),high school(secondary school)(β=4.216,P=0.002),and university(undergraduate)(β=4.739,P=0.001),total CMBs in lobes(β=-0.189,P<0.001),and the presence of WMH in the infratentorial,parietal occipital and frontal lobes(β=-1.044 P=0.048,β=-1.304 P=0.002 andβ=-0.854,P=0.049 respectively).The correlation factors for CDT scores were primary school(β=1.276,P<0.001),middle school(β=1.363,P<0.001),high school(secondary school)(β=1.517,P<0.001),and university(undergraduate)(β=1.543,P<0.001),hypertension(β=-0.189,P=0.022),total CMBs in cerebral lobes and deep location(β=-0.038,P=0.019 and β=-0.052,P=0.005),and WMH in temporal lobes(β=-0.239,P=0.045).The correlation factors for DST forward span scores were diastolic blood pressure at admission(β=0.022,P=0.021),subatentorial,parietal occipital WMH(β=-0.808,P=0.001 and β=-0.886,P=0.003),total CMBs in lobes(β=-0.059,P=0.040).The correlation factors for DST backward span scores were subatentorial,parietal occipital and temporal lobe WMH(β=-0.447 P=0.036,β=-0.636 P<0.001 and β=-0.430 P=0.042),severe WML in basal ganglia(β=0.540,P=0.027).The correlation factors for the total AVLT scores were primary school(β=11.150,P=0.022),middle school(β=11.160,P=0.025),high school(secondary school)(β=11.612,P=0.023),and university(undergraduate)(β=12.271,P=0.020),supratentorial and parietal occipital WMH(β=-0.792,P=0.005 and β=-4.146,P=0.009),severe WML in basal ganglia(β=-6.181,P=0.009).(5)Risk factors for WMH When MMSE assessed cognitive impairment,the total score of ARWMC ≥10 may have clinical significance,with sensitivity of 84.2% and specificity of 81%.The clinical features and imaging markers affecting severe WMH(ARWMC ≥10)were total CMBs in cerebral lobes(OR=1.583,95% CI:1.229-2.038,P<0.001).When Mo CA assessed cognitive impairment,the total ARWMC score ≥4 may have clinical significance,and its sensitivity is 69.6% and specificity is 91.7%.The clinical feature affecting severe WMH(ARWMC ≥4)was history of antiplatelet medication(OR=3.862,95% CI:1.151-12.956,P=0.029).The clinical features and imaging markers affecting severe WMH were age(OR=1.085,95% CI:1.018-1.157,P=0.012)and total CMBs in the deep(OR=2.072,95% CI:1.326-3.237,P=0.001)and cerebral lobes(OR=1.421,95% CI:1.075-1.877,P=0.014).Multi-factor binary logistic regression of the clinical characteristics affecting WMH in each brain region were as follows: the risk factor that might affect frontal WMH was the history of antiplatelet medication(OR=3.596,95% CI: 0.963-13.431,P=0.057).The possible risk factor for parietal occipital WMH was hypertension(OR =1.964,95% CI:0.889-4.339,P=0.095).The related factors for temporal WMH were history of antiplatelet medication(OR=10.685,95% CI:2.253-50.675,P=0.003),history of diabetes(OR=0.163,95%CI: 0.036-0.739,P=0.019),creatinine(OR=1.033,95%CI: 1.005-1.062,P=0.022)and ALT(OR=1.033,95% CI:1.005-1.062,P=0.022).The adverse factor for subatentorial WMH was gender(male)(OR=3.660,95% CI:1.128-11.874,P=0.031).The risk factor for basal ganglia WMH was history of antiplatelet medication(OR=5.785,95% CI:1.750-19.122,P=0.004).The Clinical features and imaging markers affecting WMH in each brain region were included: the risk factor affecting frontal WMH was total deep CMBs(OR=2.261,95%CI: 1.424-3.590,P=0.001).The risk factor affecting parietooccipital WMH was total CMBs in lobes(OR=1.402,95%CI: 1.192-1.649,P<0.001).The adverse factors affecting temporal WMH were total CMBs in lobes(OR=1.569,95%CI: 1.256-1.959,P<0.001),ALT(OR =0.958,95%CI: 0.924-0.993,P=0.019)and d-dimer(OR=7.095,95%CI: 1.249-40.298,P=0.027).The risk factor for subatentorial WMH was gender(male)(OR=5.540,95%CI: 1.082-28.363,P=0.040).The related factors affecting the basal ganglia WMH were total CMBs in lobes(OR=2.656,95%CI: 1.739-4.058,P<0.001)and age(OR=1.098,95%CI: 1.010-1.195,P=0.029)(6)Risk factors for CMBs Multiple linear regression of the clinical characteristics of the total CMBs and CMBs at each site revealed that the positive correlation factors for the total CMBs and the total lobar CMBs was history of antiplatelet medication(β=6.283,P=0.019 and β=3.566,P=0.003).The correlation factors for the total deep CMBs were the history of antiplatelet medication(β=2.770,P=0.004)and the history of diabetes(β=-2.231,P=0.020).No correlation factors were found in infratentorial CMBs.Multiple linear regression analysis of clinical features and imaging markers of the total CMBs and CMBs in each site showed that the positive correlation factors for the total CMBs and the total Infratentorial CMBs were all the subtentorial WMH(β=6.193,P=0.012 and β=2.273,P=0.004).The positive correlation factors for the total deep CMBs were subatentorial and parietal occipital WML(β=1.555,P=0.036 and β=2.338,P=0.029).The positive correlation factor for the total lobar CMBs was severe WML in basal ganglia(β=3.158,P=0.011).Conclusion: 1.Older age and lower education level are independent risk factors for CSVD cognitive dysfunction.Among them,older age mainly affects memory,and lower education level will affect executive function,memory and naming.2.Hypertension is an independent risk factor for executive function.Executive functions should be evaluated in patients with hypertension,but elevated diastolic blood pressure is an independent protective factor for attention,which may be related to hypoperfusion injury caused by excessive blood pressure.When controlling blood pressure clinically,excessive blood pressure reduction should be avoided.As far as cognitive function is concerned,the ideal blood pressure range also requires a large sample of future research 3.Previous antiplatelet drugs have a correlation with WMH in the temporal lobe and basal ganglia,and the number of CMBs in the lobe and deep brain,but causality requires prospective longitudinal studies with large samples in the future.4.Creatinine is a risk factor for WMH in the temporal lobe,and clinical imaging should be paid attention to in patients with elevated creatinine.d-dimer may be a risk factor for temporal lobe WMH,and a larger sample will be needed in the future.5.WMHs are more likely to occur in the subsurface of male patients,and the progress of WMH in male patients should be paid more attention to in clinical practice.6.Increased CMBs in the brain lobe or WMH in the parietal occipital lobe are independent risk factors for overall cognitive function and each cognitive domain,and clinical imaging performance of these two parts should be emphasized.7.Temporal lobe WMH is a risk factor for visual space and executive function,and behind-the-scenes WMH is a risk factor for language,naming and attention.Clinically,patients with these two lesions should pay attention to the assessment of the cognitive domain.