Assessment of cognitive function and its predictors in patients with multiple sclerosis: a case–control study.
Saved in:
| Title: | Assessment of cognitive function and its predictors in patients with multiple sclerosis: a case–control study. |
|---|---|
| Authors: | Basci, Dila (AUTHOR), Tulek, Zeliha (AUTHOR) |
| Source: | Neurological Sciences. Mar2023, Vol. 44 Issue 3, p1009-1016. 8p. 5 Charts. |
| Subjects: | Cognitive ability, Multiple sclerosis, Medical personnel, Functional assessment, Cognitive testing, Test anxiety |
| Geographic Terms: | Istanbul (Turkey) |
| Abstract: | Introduction: Cognitive dysfunction can be seen in patients with MS (PwMS) and has been gaining attention in recent years. This study aimed to assess cognitive function and its determinants in PwMS using Addenbrooke Cognitive Assessment Battery (ACE-R). Material and methods: This case–control study was conducted at an outpatient MS clinic in Istanbul. The sample consisted of 60 consecutive patients with definite MS and 60 matched controls. Cognitive function was evaluated by using the ACE-R. Subjective cognitive function, anxiety, depression, and fatigue were evaluated by validated scales. Results: The mean age of the patients was 38.8, and the time since diagnosis was nine years. The majority of the patients had relapsing–remitting MS. Compared to age, sex, and education-matched healthy controls, all ACE-R scores, attention/orientation (p = 0.020), memory (p = 0.003), verbal fluency (p = 0.002), language (p = 0.002), visuospatial (p = 0.001), and general cognitive functioning (p < 0.001), were found to be lower in PwMS. The patients obtained the lowest scores in memory and fluency and the highest in the visuospatial domain. Age, education, mobility, subjective cognitive dysfunction, anxiety, depression, and fatigue were associated with cognitive test scores. However, only education, depression, and fatigue remained significant in the multivariable analysis. Conclusion: This study revealed impaired domains of cognitive functioning and its predictors in PwMS. Understanding cognitive dysfunction and its predictors in PwMS may enable healthcare providers to identify patients who might benefit from interventions to improve cognitive function. Assessment of PwMS at outpatient clinics with a practical cognitive test that does not require special competence can be suggested. [ABSTRACT FROM AUTHOR] |
| Copyright of Neurological Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Introduction: Cognitive dysfunction can be seen in patients with MS (PwMS) and has been gaining attention in recent years. This study aimed to assess cognitive function and its determinants in PwMS using Addenbrooke Cognitive Assessment Battery (ACE-R). Material and methods: This case–control study was conducted at an outpatient MS clinic in Istanbul. The sample consisted of 60 consecutive patients with definite MS and 60 matched controls. Cognitive function was evaluated by using the ACE-R. Subjective cognitive function, anxiety, depression, and fatigue were evaluated by validated scales. Results: The mean age of the patients was 38.8, and the time since diagnosis was nine years. The majority of the patients had relapsing–remitting MS. Compared to age, sex, and education-matched healthy controls, all ACE-R scores, attention/orientation (p = 0.020), memory (p = 0.003), verbal fluency (p = 0.002), language (p = 0.002), visuospatial (p = 0.001), and general cognitive functioning (p < 0.001), were found to be lower in PwMS. The patients obtained the lowest scores in memory and fluency and the highest in the visuospatial domain. Age, education, mobility, subjective cognitive dysfunction, anxiety, depression, and fatigue were associated with cognitive test scores. However, only education, depression, and fatigue remained significant in the multivariable analysis. Conclusion: This study revealed impaired domains of cognitive functioning and its predictors in PwMS. Understanding cognitive dysfunction and its predictors in PwMS may enable healthcare providers to identify patients who might benefit from interventions to improve cognitive function. Assessment of PwMS at outpatient clinics with a practical cognitive test that does not require special competence can be suggested. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 15901874 |
| DOI: | 10.1007/s10072-022-06524-8 |
