Mohd Faizal Mohd Zulkifly1, Shazli Ezzat Ghazali2, Normah Che Din2, Ponnusamy Subramaniam2. 1. Health Psychology Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia; Center for Neuroscience Services and Research (P3Neuro), Health Campus, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia. 2. Health Psychology Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia.
Abstract
BACKGROUND: This study aims to estimate the prevalence and explore the predictors for post-stroke cognitive impairment at the community level in Malaysia. METHODS: A total of 50 stroke patients aged 29 to 81-year-old were included in this study. A face to face interview was conducted to gather the demographic and clinical data. Subsequently, assessments including Barthel ADL Index (BI), Addenbrooke's Cognitive Examination-Revised (ACE-R) and Hospital Anxiety and Depression Scale (HADS) were administered to the subjects. RESULTS: The results showed that the prevalence of cognitive impairment was 76% among the studied populations. The subjects' race (Fisher's value= 9.56, P < 0.05) and education level (Fisher's value = 7.29, P < 0.05) were significantly associated with the cognitive status. The depression score was significantly higher in cognitively impaired group [t (48) = -4.42, P < 0.001] while the Barthel Index score was significantly lower in cognitively impaired group (median = 18.00, P < 0.05). The univariate logistic analysis demonstrated that Chinese (OR 7.33, 95% CI = 1.61-33.51), lower education level (OR 9.33, 95% CI = 0.89-97.62), right sided lesion (OR 0.29, 95% CI = 0.06-1.54), left face weaknesses (OR 0.40, 95% CI 0.09-1.83), high cholesterol (OR 0.45, 95% CI = 0.12-1.75), depression (OR 2.16, 95% CI = 0.85-1.35), and Barthel Index (OR 0.79, 95% CI = 0.57-1.10) were significant predictors. Finally, multivariate logistic regression verified that depression was the only significant predictor of post-stroke cognitive impairment (OR 2.03, 95% CI = 1.20-3.45). CONCLUSION: In conclusion, the prevalence of cognitive impairment in this study was higher than other community based studies and depression was a risk factor for cognitive impairment.
BACKGROUND: This study aims to estimate the prevalence and explore the predictors for post-stroke cognitive impairment at the community level in Malaysia. METHODS: A total of 50 strokepatients aged 29 to 81-year-old were included in this study. A face to face interview was conducted to gather the demographic and clinical data. Subsequently, assessments including Barthel ADL Index (BI), Addenbrooke's Cognitive Examination-Revised (ACE-R) and Hospital Anxiety and Depression Scale (HADS) were administered to the subjects. RESULTS: The results showed that the prevalence of cognitive impairment was 76% among the studied populations. The subjects' race (Fisher's value= 9.56, P < 0.05) and education level (Fisher's value = 7.29, P < 0.05) were significantly associated with the cognitive status. The depression score was significantly higher in cognitively impaired group [t (48) = -4.42, P < 0.001] while the Barthel Index score was significantly lower in cognitively impaired group (median = 18.00, P < 0.05). The univariate logistic analysis demonstrated that Chinese (OR 7.33, 95% CI = 1.61-33.51), lower education level (OR 9.33, 95% CI = 0.89-97.62), right sided lesion (OR 0.29, 95% CI = 0.06-1.54), left face weaknesses (OR 0.40, 95% CI 0.09-1.83), high cholesterol (OR 0.45, 95% CI = 0.12-1.75), depression (OR 2.16, 95% CI = 0.85-1.35), and Barthel Index (OR 0.79, 95% CI = 0.57-1.10) were significant predictors. Finally, multivariate logistic regression verified that depression was the only significant predictor of post-stroke cognitive impairment (OR 2.03, 95% CI = 1.20-3.45). CONCLUSION: In conclusion, the prevalence of cognitive impairment in this study was higher than other community based studies and depression was a risk factor for cognitive impairment.
Authors: Wai Kwong Tang; Yang-Kun Chen; Jin-Yan Lu; Adrian Wong; Vincent Mok; Winnie C W Chu; Gabor S Ungvari; Ka Sing Wong Journal: Int J Stroke Date: 2011-12 Impact factor: 5.266
Authors: David S Knopman; Rosebud O Roberts; Yonas E Geda; Bradley F Boeve; V Shane Pankratz; Ruth H Cha; Eric G Tangalos; Robert J Ivnik; Ronald C Petersen Journal: Arch Neurol Date: 2009-05