Abstract：
BACKGROUND:The mechanisms for improved cognitive function post-bariatric surgery are not well understood. Markers of kidney and liver function (i.e., cystatin C and alkaline phosphatase (ALP)) are elevated in obese individuals and associated with poor neurocognitive outcomes in other samples. Bariatric surgery can improve cystatin C and ALP levels, but no study has examined whether such changes correspond to post-operative cognitive benefits. METHODS:78 bariatric surgery patients completed a computerized cognitive test battery prior to and 12-months after surgery. All participants underwent an eight-hour fasting blood draw to quantify cystatin C and ALP concentrations. RESULTS:Cognitive function improved after surgery. Cystatin C levels decreased at the 12-month follow-up; however, no changes were found in ALP concentrations. At baseline, higher cystatin C levels predicted worse attention/executive function, but no such effects emerged for ALP. Regression analyses controlling for possible medical and demographic confounds and baseline factors revealed that decreased ALP levels following surgery predicted better attention/executive function and memory abilities. Post-surgery changes in cystatin C did not correspond to cognitive improvements. CONCLUSIONS:Decreased ALP levels predicted better cognition following bariatric surgery, suggesting improved liver function as a possible mechanism of post-operative cognitive benefits. Future studies with neuroimaging and longer follow-up periods are needed to determine whether bariatric surgery can decrease risk for adverse brain changes and dementia in severely obese persons via improved metabolic function.
journal_name
J Neurol Scijournal_title
Journal of the neurological sciencesauthors
Alosco ML,Spitznagel MB,Strain G,Devlin M,Cohen R,Crosby RD,Mitchell JE,Gunstad Jdoi
10.1016/j.jns.2014.07.037subject
Has Abstractpub_date
2014-10-15 00:00:00pages
176-80issue
1-2eissn
0022-510Xissn
1878-5883pii
S0022-510X(14)00483-3journal_volume
345pub_type
杂志文章abstract：OBJECTIVE:To provide an improved method for the identification and analysis of brain tumors in MRI scans using a semi-automated computational approach, that has the potential to provide a more objective, precise and quantitatively rigorous analysis, compared to human visual analysis. BACKGROUND:Self-Organizing Maps (S...
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