Cell Biochem Biophys (2015) 71:673–677 DOI 10.1007/s12013-014-0246-4
ORIGINAL PAPER
Analysis of Risk Factors for Vascular Cognitive Impairment in Patients with Cerebral Infarction Xiao-lei An • Chuan-ling Li
Published online: 17 September 2014 Ó Springer Science+Business Media New York 2014
Abstract This study aimed to identify risk factors for vascular cognitive impairment (VCI) in cerebral infarction patients. Associations between VCI and age, gender, blood pressure, lipid levels, glycosylated hemoglobin, atrial fibrillation, tobacco smoking, alcohol consumption, homocysteine (Hcy), and High-Sensitivity C-Reactive Protein (HS-CRP) were evaluated in patients with cerebral infarction (n = 300) using single factor analysis and multivariate logistic regression analysis. By single factor analysis, the age, glycosylated hemoglobin, atrial fibrillation, blood pressure, Hcy, HS-CRP, tobacco smoking, and alcohol consumption were significantly associated with VCI in these patients. By multivariate logistic regression analysis, the age, glycosylated hemoglobin, blood pressure, Hcy, and HS-CRP were revealed as independent risk factors. The age, glycosylated hemoglobin, blood pressure, Hcy, and HS-CRP can serve as predictive factors for VCI in patients with cerebral infarction. Keywords Cerebral infarction Vascular cognitive impairment Risk factors Multivariate logistic regression analysis Montreal cognitive assessment
Introduction With the aging population and growing number of patients with cerebral infarction, the prevalence of vascular cognitive impairment (VCI) is gradually increasing. Currently, VCI became one of the main diseases with a significant impact on health and quality of life in seniors [1]. X. An (&) C. Li Department of Neurology, The Central Hospital of Xuzhou, No. 199 Jiefang South Road, Xuzhou 221009, China e-mail: [email protected]
VCI is a syndrome of an acquired advanced cognitive dysfunction which is caused by a variety of cerebrovascular diseases, especially by cerebral infarction. It is also a chronic progressive disease. When apparent dementia occurs, the clinical diagnosis is relatively easy to make. However, this condition cannot be reversed meaning that patients loose the chance to be effectively treated, leading to a heavy burden on the family and the society [2, 3]. Therefore, it is crucial to identify pertinent risk factors to be able to prevent this debilitating condition. The purpose of our study was to identify the risk factors for VCI in cerebral infarction patients.
Materials and Methods Patients Three hundred patients with cerebral infarction were included in this study. These patients were treated in our Neurology clinic from 2008 to 2010. The patients needed to satisfy the following inclusion criteria to be included in the study. First, patients needed to meet diagnostic criteria for cerebral infarction [4, 5] confirmed by head CT or MRI. Second, the patients should have had no suspected dementia prior to cerebral infarction. Finally, demographic and clinical data needed to be available. The exclusion criteria were: cognitive abnormalities caused by infectious diseases, intoxication, traumatic brain injury, subdural hematoma, intracranial lesions, metabolic disorders, and nutrition-induced disorders. Study Parameters On the day when the patients were admitted, blood specimens were obtained to document the study outcomes prior
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Cell Biochem Biophys (2015) 71:673–677
to hospitalization. Since systolic blood pressure (SBP) mainly affects cerebral perfusion, we utilized SBP as the indicator of pressure. Patients were divided into those with normal blood pressure and those with hypertension (hypertension group) using the SBP value of B 140 mm Hg as the cut-off, similar to the study by Akiguchi et al. [6]. Averages of two or more measurements of blood pressure, lipid profile, glycosylated hemoglobin, homocysteine (Hcy), and High-Sensitivity C-Reactive Protein (HS-CRP) were used to minimize the sampling error. Patients who had a history of cerebral infarction were assigned the rank of ‘‘1’’. Patients who had no history of cerebral infarction were ranked as ‘‘0’’. The Montreal Cognitive Assessment (MoCA), which is an assessment tool for rapid detection of cognitive impairment, was utilized to identify VCI [7, 8]. The MoCA assesses several cognitive domains: visual spatial and executive functions which are ranked 5 points (including clock-drawing test of 3 points), naming skill ranked 3 points, delayed recall (5 points), attention skill ranked 6 points (including calculation skill ranked 3 points), language skill (3 points), abstraction (2 points), and orientation skill ranked 6 points [9, 10]. The maximal number of points is 30. The score of B26 was classified as abnormal. If a patient had education for less than 12 years, 1 point was added to the final score [11–13]. We evaluate MoCA scores on day 2 and day 60 after cerebral infarction. We classified the MoCA scores of patients on day 60 after cerebral infarction into two categories: cognitive impairment (assigned rank ‘‘1’’) and no cognitive impairment (assigned rank ‘‘0’’).
smoking, and drinking habits significantly correlated with VCI in patients with cerebral infarction (p \ 0.05; Table 1).
Statistical Analysis
Multivariate Logistic Regression Analysis
The study design and data collection were performed by both authors. The scale assessment was completed by the first author. The evaluators were formally trained. Blind evaluation was utilized. Excel 2000 was used to create the data file. The SPSS13.0 statistical package was used to perform the single factor analysis of variables, unpaired t test for qualitative data analysis, and v2 test for quantitative data analysis. Then, significant variables were analyzed using multivariate non-conditional logistic regression analysis in order to find the independent risk factors of VCI during the early stage post-stroke.
The above data were introduced into logistic regression multivariate analysis. All analyses were at the level of a = 0.05. We selected five statistically significant independent factors for VCI in these patients. As shown in Table 2, we found that onset age, glycosylated hemoglobin, systolic blood pressure, Hcy, and HS-CRP were independent risk factors.
Results Single Factor Analysis Onset age, glycosylated hemoglobin, combined atrial fibrillation, systolic blood pressure, Hcy, HS-CRP,
123
Table 1 Single-factor analysis of risk factors for vascular cognitive impairment in patients with cerebral infarction Factor
t/v2
Cognitive impairment No (167)
p
Yes (133)
Age
57.12 ± 8.81
66.14 ± 6.23
3.134
0.003
HbA1c
4.23 ± 0.32
6.45 ± 1.11
4.785
0.000
Systolic pressure
120.16 ± 10.12
140.36 ± 14.56
5.887
0.000
Combined AFb (no/yes)
145/22
109/24
5.237
0.015
Key part (no/yes)
119/48
31/102
5.697
0.012
Smoking (no/yes)
100/67
99/34
8.087
0.007
Drinking (no/yes)
96/71
80/53
6.654
0.043
Table 2 Logistic regression analysis for vascular cognitive impairment in early post-stroke stage Factor
OR
95 % CI
p
Age
2.345
1.897–2.245
0.029
HbA1c
1.489
1.054–1.956
0.021
Systolic pressure
1.134
1.011–1.130
0.027
Key part lesion
3.124
1.167–3.012
0.028
Discussion VCI is characterized by the development of various manifestations of cognitive decline, such as progressive loss of memory, psychomotor inefficiency, disorientation in space and time, and loss of executive functions. These are caused by a variety of vascular diseases, especially by cerebral infarction [14–17]. The literature indicates that VCI risk factors include vascular risk factors which can be interfered and can not be interfered, such as demographic and genetic
Cell Biochem Biophys (2015) 71:673–677
factors. Among the former, the most common factor is hypertension, which impairs cognitive function by affecting the metabolism of the brain and damaging the brain structure. Multiple clinical studies showed that long-term hypertension leads to the formation of atherosclerosis and loss of self-regulation of vascular function, impairs blood perfusion of brain tissue and leads to degeneration of white matter and, subsequently, to cognitive impairment [17, 18]. Birkenhager et al. [19] found that blood pressure levels, especially SBP should be kept within a certain range (below 140/90 mmHg) for prevention of cerebrovascular damage and maintenance of sufficient cerebral perfusion to preserve cognitive function. The results of our study seem to support this statement. After adjusting for age, sex, and other influence factors, a higher SBP level ([140 mm Hg) was significantly associated with VCI (odds ratio [OR], 1.134; 95 % confidence interval [CI], 1.011–1.130) in 133 subjects with VCI and 167 cognitively normal subjects. The blood sugar level is an another defined risk factor for VCI [20, 21]. Diabetes causes vascular basement membrane thickening, leading to ischemic and hypoxic brain damage [22–24]. Diabetes can also lead to a variety of metabolic and neurological biochemistry disorders, which eventually cause brain cognitive impairment. Further, long-term hyperglycemia caused by diabetes leads to increased anaerobic metabolism and acidosis which enhances the damage of hypoxic brain tissue. This may also be a mechanism of cognitive impairment [25, 26]. In this study, we used glycosylated hemoglobin to represent the average level of blood sugar for the most recent month. Our findings indicate that the risk of VCI among cerebral infarction patients was 3.1 times higher in patients with glycosylated hemoglobin of C6.0 % compared with patients whose glycosylated hemoglobin was\6.0 % (odds ratio [OR], 1.489; 95 % CI 1.054–1.956). There is a growing appreciation of the importance of inflammatory mechanisms in the pathogenesis of cerebrovascular disease [27, 28]. HS-CRP is a non-specific marker of inflammation increasingly used in clinical practice [29, 30]. In this study, elevated HS-CRP concentrations were significantly associated with cognitive impairment in the multivariate model. Our findings are consistent with a clinical guidelines issued by the Centers for Disease Control and the American Heart Association which highlight that HS-CRP concentrations of [3 mg/L represent high vascular risk [31]. The mechanisms of the association are not entirely demonstrated, however, are likely to be related to impaired endothelial function, which has been associated with cerebral white matter hyperintensities and vascular dementia [32, 33]. The association between HS-CRP and cognitive impairment in patients with cerebral infarction should be a subject of additional studies.
675
A number of observational studies reported an association between Hcy and VCI [34]. However, the mechanism underlying this association remains controversial [35–39]. The elevated Hcy levels may lead to cognitive impairment through cerebrovascular disease or increased cortical or hippocampal atrophy. Further, the elevated Hcy may also be neurotoxic, harmful to neurovascular tissue, or may aggravate amyloid toxic effects on neuronal cells [40–42]. The results of our study are consistent with a number of studies reporting an association of elevated Hcy with cognitive impairment. Moreover, we found that elevated Hcy is an independent risk factor for VCI. Heart diseases, especially myocardial infarction, congestive heart disease, and atrial fibrillation, are risk factors for VCI [43–45]. Insufficient perfusion of brain tissue caused by diminished cardiac output due to atrial fibrillation may be one of the mechanisms of brain damage and cognitive dysfunction [45]. In our study, we found that atrial fibrillation, low-density lipoprotein, long-term smoking, and alcohol consumption were also associated with the occurrence of VCI in patients with cerebral infarction. However, the multivariate logistic regression analysis did not reveal these as independent risk factors for post-stroke VCI. It is possible that these factors may indirectly cause VCI by inducing vascular spasm, or changing blood pressure or glucose levels [45]. In conclusion, we found that onset age, glycosylated hemoglobin, systolic blood pressure, Hcy, and HS-CRP are independent risk factors for VCI. These independent risk factors may be used as predictors of VCI in cerebral infarction patients. Acknowledgments This study was supported by Xuzhou Science and Technology Foundation 2009.
References 1. Panza, F., Frisardi, V., Capurso, C., D’Introno, A., Colacicco, A. M., Seripa, D., et al. (2009). Possible predictors of vascular cognitive impairment-no dementia. Journal of the American Geriatrics Society, 57, 943–944. 2. Ghio, L., Natta, W., Fravega, R., Gotelli, S., Pannocchia, F., Puppo, S., et al. (2011). Cognitive impairment and psychopharmacological treatment: A drug utilization study in the emergency department. International Journal of Geriatric Psychiatry, 26, 438–439. 3. Schneider, L. S. (2009). Commentary on ‘‘a roadmap for the prevention of dementia II: Leon Thal Symposium 2008.’’ A federally funded corporation for the prevention and treatment of cognitive impairment and brain aging. Alzheimers Dementia, 2009(5), 172–179. 4. Woessner, R., & Treib, J. (2002). Ischemic or hemorrhagic stroke? Rapid diagnosis improves prognosis for the patient. MMW Fortschritte der Medizin Das, 144, 24–28. 5. Norrving, B. (2003). Improvements of standards in clinical diagnosis of stroke are needed. Lakartidningen, 100, 3760–3766.
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676 6. Akiguchi, I., & Yamamoto, Y. (2010). Vascular mechanisms of cognitive impairment: Roles of hypertension and subsequent small vessel disease under sympathetic influences. Hypertension Research, 33, 29–31. 7. Rahman, T. T., & El Gaafary, M. M. (2009). Montreal Cognitive Assessment Arabic version: Reliability and validity prevalence of mild cognitive impairment among elderly attending geriatric clubs in Cairo. Geriatrics and Gerontology International, 9, 54–61. 8. Tsai, C. F., Lee, W. J., Wang, S. J., Shia, B. C., Nasreddine, Z., & Fuh, J. L. (2011). Psychometrics of the Montreal Cognitive Assessment (MoCA) and its subscales: Validation of the Taiwanese version of the MoCA and an item response theory analysis. International Psychogeriatrics, 2011, 1–8. 9. Koski, L., Xie, H., & Finch, L. (2009). Measuring cognition in a geriatric outpatient clinic: Rasch analysis of the Montreal Cognitive Assessment. Journal of Geriatric Psychiatry and Neurology, 22, 151–160. 10. Rossetti, H. C., Lacritz, L. H., Cullum, C. M., & Weiner, M. F. (2011). Normative data for the Montreal Cognitive Assessment (MoCA) in a population-based sample. Neurology., 77, 1272–1275. 11. Gagnon, J. F., Postuma, R. B., Joncas, S., Desjardins, C., & Latreille, V. (2010). The Montreal Cognitive Assessment: A screening tool for mild cognitive impairment in REM sleep behavior disorder. Movement Disorders, 25, 936–940. 12. Bernstein, I. H., Lacritz, L., Barlow, C. E., Weiner, M. F., & DeFina, L. F. (2011). Psychometric evaluation of the Montreal Cognitive Assessment (MoCA) in three diverse samples. Clinical Neuropsychology, 25, 119–126. 13. Lu, J., Li, D., Li, F., Zhou, A., Wang, F., Zuo, X., et al. (2011). Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: A population-based study. Journal of Geriatric Psychiatry and Neurology, 24, 184–190. 14. Khedr, E. M., Hamed, S. A., El-Shereef, H. K., Shawky, O. A., Mohamed, K. A., Awad, E. M., et al. (2009). Cognitive impairment after cerebrovascular stroke: Relationship to vascular risk factors. Neuropsychiatric Disease and Treatment, 5, 103–116. 15. Unverzagt, F. W., McClure, L. A., Wadley, V. G., Jenny, N. S., Go, R. C., Cushman, M., et al. (2011). Vascular risk factors and cognitive impairment in a stroke-free cohort. Neurology, 77, 1729–1736. 16. Bereczki, D., & Szatmari, S. (2009). Treatment of dementia and cognitive impairment: What can we learn from the Cochrane Library. Journal of the Neurological Sciences, 283, 207–210. 17. Levine, D. A., & Langa, K. M. (2011). Vascular cognitive impairment: Disease mechanisms and therapeutic implications. Neurotherapeutics., 8, 361–373. 18. Villeneuve, S., Belleville, S., Massoud, F., Bocti, C., & Gauthier, S. (2009). Impact of vascular risk factors and diseases on cognition in persons with mild cognitive impairment. Dementia and Geriatric Cognitive Disorders, 27, 375–381. 19. Birkenhager, W. H., Forette, F., Seux, M. L., Wang, J. G., & Staessen, J. A. (2001). Blood pressure, cognitive functions, and prevention of dementias in older patients with hypertension. Archives of Internal Medicine, 161, 152–156. 20. Mizrahi, E. H., Waitzman, A., Blumstein, T., Arad, M., & Adunsky, A. (2010). Diabetes mellitus predicts cognitive impairment in patients with ischemic stroke. American Journal of Alzheimer’s Disease and Other Dementias, 25, 362–366. 21. Kim, E., Lee, S. H., Lee, K. S., Cheong, H. K., Namkoong, K., Hong, C. H., et al. (2012). AMPK gamma2 subunit gene PRKAG2 polymorphism associated with cognitive impairment as well as diabetes in old age. Psychoneuroendocrinology., 37, 358–365.
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Cell Biochem Biophys (2015) 71:673–677 22. Pasquier, F. (2010). Diabetes and cognitive impairment: How to evaluate the cognitive status? Diabetes and Metabolism, 36(Suppl 3), S100–S105. 23. Xu, W., Caracciolo, B., Wang, H. X., Winblad, B., Backman, L., Qiu, C., et al. (2010). Accelerated progression from mild cognitive impairment to dementia in people with diabetes. Diabetes, 59, 2928–2935. 24. Strachan, M. W. (2011). R D Lawrence Lecture 2010. The brain as a target organ in Type 2 diabetes: Exploring the links with cognitive impairment and dementia. Diabetic Medicine, 28, 141–147. 25. McNay, E. C., & Recknagel, A. K. (2011). Brain insulin signaling: A key component of cognitive processes and a potential basis for cognitive impairment in type 2 diabetes. Neurobiology of Learning and Memory, 96, 432–442. 26. Abbatecola, A. M., Lattanzio, F., Molinari, A. M., Cioffi, M., Mansi, L., Rambaldi, P., et al. (2010). Rosiglitazone and cognitive stability in older individuals with type 2 diabetes and mild cognitive impairment. Diabetes Care, 33, 1706–1711. 27. Noble, J. M., Manly, J. J., Schupf, N., Tang, M. X., Mayeux, R., & Luchsinger, J. A. (2010). Association of C-reactive protein with cognitive impairment. Archives of Neurology, 67, 87–92. 28. Roberts, R. O., Geda, Y. E., Knopman, D. S., Boeve, B. F., Christianson, T. J., Pankratz, V. S., et al. (2009). Association of C-reactive protein with mild cognitive impairment. Alzheimer’s and Dementia, 5, 398–405. 29. Kravitz, B. A., Corrada, M. M., & Kawas, C. H. (2009). Elevated C-reactive protein levels are associated with prevalent dementia in the oldest-old. Alzheimer’s and Dementia, 5, 318–323. 30. Marioni, R. E., Stewart, M. C., Murray, G. D., Deary, I. J., Fowkes, F. G., Lowe, G. D., et al. (2009). Peripheral levels of fibrinogen, C-reactive protein, and plasma viscosity predict future cognitive decline in individuals without dementia. Psychosomatic Medicine, 71, 901–906. 31. De Luigi, A., Fragiacomo, C., Lucca, U., Quadri, P., Tettamanti, M., & Grazia, S. M. (2001). Inflammatory markers in Alzheimer’s disease and multi-infarct dementia. Mechanisms of Ageing and Development, 122, 1985–1995. 32. Dickerson, F., Stallings, C., Origoni, A., Boronow, J., & Yolken, R. (2007). C-reactive protein is associated with the severity of cognitive impairment but not of psychiatric symptoms in individuals with schizophrenia. Schizophrenia Research, 93, 261–265. 33. Hogue, C. W., Jr, Hershey, T., Dixon, D., Fucetola, R., Nassief, A., Freedland, K. E., et al. (2006). Preexisting cognitive impairment in women before cardiac surgery and its relationship with C-reactive protein concentrations. Anesthesia and Analgesia, 102, 1602–1608. 34. Feng, L., Isaac, V., Sim, S., Ng, T. P., Krishnan, K. R., & Chee, M. W. (2011). Associations between elevated homocysteine, cognitive impairment, and reduced white matter volume in healthy old adults. American Journal of Geriatric Psychiatry, 21(2), 164–172. 35. Reitz, C., Tang, M. X., Miller, J., Green, R., & Luchsinger, J. A. (2009). Plasma homocysteine and risk of mild cognitive impairment. Dementia and Geriatric Cognitive Disorders, 27, 11–17. 36. Smith, A. D., Smith, S. M., de Jager, C. A., Whitbread, P., Johnston, C., Agacinski, G., et al. (2010). Homocysteine-lowering by B vitamins slows the rate of accelerated brain atrophy in mild cognitive impairment: A randomized controlled trial. PLoS One, 5, e12244. 37. Ford, A. H., Flicker, L., Hankey, G. J., Norman, P., van Bockxmeer, F. M., & Almeida, O. P. (2012). Homocysteine, methylenetetrahydrofolate reductase C677T polymorphism and cognitive impairment: The health in men study. Molecular Psychiatry, 17, 559–566.
Cell Biochem Biophys (2015) 71:673–677 38. McCaddon, A. (2006). Homocysteine and cognitive impairment; a case series in a General Practice setting. Nutrition Journal, 5, 6. 39. Dimopoulos, N., Piperi, C., Salonicioti, A., Psarra, V., Gazi, F., Nounopoulos, C., et al. (2006). Association of cognitive impairment with plasma levels of folate, vitamin B12 and homocysteine in the elderly. In Vivo, 20, 895–899. 40. Haan, M. N., Miller, J. W., Aiello, A. E., Whitmer, R. A., Jagust, W. J., Mungas, D. M., et al. (2007). Homocysteine, B vitamins, and the incidence of dementia and cognitive impairment: Results from the Sacramento Area Latino Study on Aging. American Journal of Clinical Nutrition, 85, 511–517. 41. Kim, J., Park, M. H., Kim, E., Han, C., Jo, S. A., & Jo, I. (2007). Plasma homocysteine is associated with the risk of mild cognitive impairment in an elderly Korean population. Journal of Nutrition, 137, 2093–2097. 42. Troen, A. M., Chao, W. H., Crivello, N. A., D’Anci, K. E., Shukitt-Hale, B., Smith, D. E., et al. (2008). Cognitive impairment in folate-deficient rats corresponds to depleted brain
677 phosphatidylcholine and is prevented by dietary methionine without lowering plasma homocysteine. Journal of Nutrition, 138, 2502–2509. 43. Flaker, G. C., Pogue, J., Yusuf, S., Pfeffer, M. A., Goldhaber, S. Z., Granger, C. B., et al. (2010). Cognitive function and anticoagulation control in patients with atrial fibrillation. Circulation Cardiovascular Quality and Outcomes, 3, 277–283. 44. Puccio, D., Novo, G., Baiamonte, V., Nuccio, A., Fazio, G., Corrado, E., et al. (2009). Atrial fibrillation and mild cognitive impairment: What correlation? Minerva Cardioangiologica, 57, 143–150. 45. Wozakowska-Kaplon, B., Opolski, G., Kosior, D., JaskulskaNiedziela, E., Maroszynska-Dmoch, E., & Wlosowicz, M. (2009). Cognitive disorders in elderly patients with permanent atrial fibrillation. Kardiologia Polska, 67, 487–493.
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ORIGINAL PAPER
Analysis of Risk Factors for Vascular Cognitive Impairment in Patients with Cerebral Infarction Xiao-lei An • Chuan-ling Li
Published online: 17 September 2014 Ó Springer Science+Business Media New York 2014
Abstract This study aimed to identify risk factors for vascular cognitive impairment (VCI) in cerebral infarction patients. Associations between VCI and age, gender, blood pressure, lipid levels, glycosylated hemoglobin, atrial fibrillation, tobacco smoking, alcohol consumption, homocysteine (Hcy), and High-Sensitivity C-Reactive Protein (HS-CRP) were evaluated in patients with cerebral infarction (n = 300) using single factor analysis and multivariate logistic regression analysis. By single factor analysis, the age, glycosylated hemoglobin, atrial fibrillation, blood pressure, Hcy, HS-CRP, tobacco smoking, and alcohol consumption were significantly associated with VCI in these patients. By multivariate logistic regression analysis, the age, glycosylated hemoglobin, blood pressure, Hcy, and HS-CRP were revealed as independent risk factors. The age, glycosylated hemoglobin, blood pressure, Hcy, and HS-CRP can serve as predictive factors for VCI in patients with cerebral infarction. Keywords Cerebral infarction Vascular cognitive impairment Risk factors Multivariate logistic regression analysis Montreal cognitive assessment
Introduction With the aging population and growing number of patients with cerebral infarction, the prevalence of vascular cognitive impairment (VCI) is gradually increasing. Currently, VCI became one of the main diseases with a significant impact on health and quality of life in seniors [1]. X. An (&) C. Li Department of Neurology, The Central Hospital of Xuzhou, No. 199 Jiefang South Road, Xuzhou 221009, China e-mail: [email protected]
VCI is a syndrome of an acquired advanced cognitive dysfunction which is caused by a variety of cerebrovascular diseases, especially by cerebral infarction. It is also a chronic progressive disease. When apparent dementia occurs, the clinical diagnosis is relatively easy to make. However, this condition cannot be reversed meaning that patients loose the chance to be effectively treated, leading to a heavy burden on the family and the society [2, 3]. Therefore, it is crucial to identify pertinent risk factors to be able to prevent this debilitating condition. The purpose of our study was to identify the risk factors for VCI in cerebral infarction patients.
Materials and Methods Patients Three hundred patients with cerebral infarction were included in this study. These patients were treated in our Neurology clinic from 2008 to 2010. The patients needed to satisfy the following inclusion criteria to be included in the study. First, patients needed to meet diagnostic criteria for cerebral infarction [4, 5] confirmed by head CT or MRI. Second, the patients should have had no suspected dementia prior to cerebral infarction. Finally, demographic and clinical data needed to be available. The exclusion criteria were: cognitive abnormalities caused by infectious diseases, intoxication, traumatic brain injury, subdural hematoma, intracranial lesions, metabolic disorders, and nutrition-induced disorders. Study Parameters On the day when the patients were admitted, blood specimens were obtained to document the study outcomes prior
123
674
Cell Biochem Biophys (2015) 71:673–677
to hospitalization. Since systolic blood pressure (SBP) mainly affects cerebral perfusion, we utilized SBP as the indicator of pressure. Patients were divided into those with normal blood pressure and those with hypertension (hypertension group) using the SBP value of B 140 mm Hg as the cut-off, similar to the study by Akiguchi et al. [6]. Averages of two or more measurements of blood pressure, lipid profile, glycosylated hemoglobin, homocysteine (Hcy), and High-Sensitivity C-Reactive Protein (HS-CRP) were used to minimize the sampling error. Patients who had a history of cerebral infarction were assigned the rank of ‘‘1’’. Patients who had no history of cerebral infarction were ranked as ‘‘0’’. The Montreal Cognitive Assessment (MoCA), which is an assessment tool for rapid detection of cognitive impairment, was utilized to identify VCI [7, 8]. The MoCA assesses several cognitive domains: visual spatial and executive functions which are ranked 5 points (including clock-drawing test of 3 points), naming skill ranked 3 points, delayed recall (5 points), attention skill ranked 6 points (including calculation skill ranked 3 points), language skill (3 points), abstraction (2 points), and orientation skill ranked 6 points [9, 10]. The maximal number of points is 30. The score of B26 was classified as abnormal. If a patient had education for less than 12 years, 1 point was added to the final score [11–13]. We evaluate MoCA scores on day 2 and day 60 after cerebral infarction. We classified the MoCA scores of patients on day 60 after cerebral infarction into two categories: cognitive impairment (assigned rank ‘‘1’’) and no cognitive impairment (assigned rank ‘‘0’’).
smoking, and drinking habits significantly correlated with VCI in patients with cerebral infarction (p \ 0.05; Table 1).
Statistical Analysis
Multivariate Logistic Regression Analysis
The study design and data collection were performed by both authors. The scale assessment was completed by the first author. The evaluators were formally trained. Blind evaluation was utilized. Excel 2000 was used to create the data file. The SPSS13.0 statistical package was used to perform the single factor analysis of variables, unpaired t test for qualitative data analysis, and v2 test for quantitative data analysis. Then, significant variables were analyzed using multivariate non-conditional logistic regression analysis in order to find the independent risk factors of VCI during the early stage post-stroke.
The above data were introduced into logistic regression multivariate analysis. All analyses were at the level of a = 0.05. We selected five statistically significant independent factors for VCI in these patients. As shown in Table 2, we found that onset age, glycosylated hemoglobin, systolic blood pressure, Hcy, and HS-CRP were independent risk factors.
Results Single Factor Analysis Onset age, glycosylated hemoglobin, combined atrial fibrillation, systolic blood pressure, Hcy, HS-CRP,
123
Table 1 Single-factor analysis of risk factors for vascular cognitive impairment in patients with cerebral infarction Factor
t/v2
Cognitive impairment No (167)
p
Yes (133)
Age
57.12 ± 8.81
66.14 ± 6.23
3.134
0.003
HbA1c
4.23 ± 0.32
6.45 ± 1.11
4.785
0.000
Systolic pressure
120.16 ± 10.12
140.36 ± 14.56
5.887
0.000
Combined AFb (no/yes)
145/22
109/24
5.237
0.015
Key part (no/yes)
119/48
31/102
5.697
0.012
Smoking (no/yes)
100/67
99/34
8.087
0.007
Drinking (no/yes)
96/71
80/53
6.654
0.043
Table 2 Logistic regression analysis for vascular cognitive impairment in early post-stroke stage Factor
OR
95 % CI
p
Age
2.345
1.897–2.245
0.029
HbA1c
1.489
1.054–1.956
0.021
Systolic pressure
1.134
1.011–1.130
0.027
Key part lesion
3.124
1.167–3.012
0.028
Discussion VCI is characterized by the development of various manifestations of cognitive decline, such as progressive loss of memory, psychomotor inefficiency, disorientation in space and time, and loss of executive functions. These are caused by a variety of vascular diseases, especially by cerebral infarction [14–17]. The literature indicates that VCI risk factors include vascular risk factors which can be interfered and can not be interfered, such as demographic and genetic
Cell Biochem Biophys (2015) 71:673–677
factors. Among the former, the most common factor is hypertension, which impairs cognitive function by affecting the metabolism of the brain and damaging the brain structure. Multiple clinical studies showed that long-term hypertension leads to the formation of atherosclerosis and loss of self-regulation of vascular function, impairs blood perfusion of brain tissue and leads to degeneration of white matter and, subsequently, to cognitive impairment [17, 18]. Birkenhager et al. [19] found that blood pressure levels, especially SBP should be kept within a certain range (below 140/90 mmHg) for prevention of cerebrovascular damage and maintenance of sufficient cerebral perfusion to preserve cognitive function. The results of our study seem to support this statement. After adjusting for age, sex, and other influence factors, a higher SBP level ([140 mm Hg) was significantly associated with VCI (odds ratio [OR], 1.134; 95 % confidence interval [CI], 1.011–1.130) in 133 subjects with VCI and 167 cognitively normal subjects. The blood sugar level is an another defined risk factor for VCI [20, 21]. Diabetes causes vascular basement membrane thickening, leading to ischemic and hypoxic brain damage [22–24]. Diabetes can also lead to a variety of metabolic and neurological biochemistry disorders, which eventually cause brain cognitive impairment. Further, long-term hyperglycemia caused by diabetes leads to increased anaerobic metabolism and acidosis which enhances the damage of hypoxic brain tissue. This may also be a mechanism of cognitive impairment [25, 26]. In this study, we used glycosylated hemoglobin to represent the average level of blood sugar for the most recent month. Our findings indicate that the risk of VCI among cerebral infarction patients was 3.1 times higher in patients with glycosylated hemoglobin of C6.0 % compared with patients whose glycosylated hemoglobin was\6.0 % (odds ratio [OR], 1.489; 95 % CI 1.054–1.956). There is a growing appreciation of the importance of inflammatory mechanisms in the pathogenesis of cerebrovascular disease [27, 28]. HS-CRP is a non-specific marker of inflammation increasingly used in clinical practice [29, 30]. In this study, elevated HS-CRP concentrations were significantly associated with cognitive impairment in the multivariate model. Our findings are consistent with a clinical guidelines issued by the Centers for Disease Control and the American Heart Association which highlight that HS-CRP concentrations of [3 mg/L represent high vascular risk [31]. The mechanisms of the association are not entirely demonstrated, however, are likely to be related to impaired endothelial function, which has been associated with cerebral white matter hyperintensities and vascular dementia [32, 33]. The association between HS-CRP and cognitive impairment in patients with cerebral infarction should be a subject of additional studies.
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A number of observational studies reported an association between Hcy and VCI [34]. However, the mechanism underlying this association remains controversial [35–39]. The elevated Hcy levels may lead to cognitive impairment through cerebrovascular disease or increased cortical or hippocampal atrophy. Further, the elevated Hcy may also be neurotoxic, harmful to neurovascular tissue, or may aggravate amyloid toxic effects on neuronal cells [40–42]. The results of our study are consistent with a number of studies reporting an association of elevated Hcy with cognitive impairment. Moreover, we found that elevated Hcy is an independent risk factor for VCI. Heart diseases, especially myocardial infarction, congestive heart disease, and atrial fibrillation, are risk factors for VCI [43–45]. Insufficient perfusion of brain tissue caused by diminished cardiac output due to atrial fibrillation may be one of the mechanisms of brain damage and cognitive dysfunction [45]. In our study, we found that atrial fibrillation, low-density lipoprotein, long-term smoking, and alcohol consumption were also associated with the occurrence of VCI in patients with cerebral infarction. However, the multivariate logistic regression analysis did not reveal these as independent risk factors for post-stroke VCI. It is possible that these factors may indirectly cause VCI by inducing vascular spasm, or changing blood pressure or glucose levels [45]. In conclusion, we found that onset age, glycosylated hemoglobin, systolic blood pressure, Hcy, and HS-CRP are independent risk factors for VCI. These independent risk factors may be used as predictors of VCI in cerebral infarction patients. Acknowledgments This study was supported by Xuzhou Science and Technology Foundation 2009.
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