Abstract
Functional magnetic resonance imaging (fMRI) is a useful tool to evaluate brain inefficiencies secondary to cardiovascular diseases (CVDs); nevertheless, limited fMRI studies have been conducted to investigate the effect of CVDs on brain functional changes and cognitive function. This systematic review aims to explore, synthesise, and report fMRI outcomes (resting state and task-based) and cognitive performance in patients with CVDs. Two reviewers independently searched published literature until April 2024 on ScienceDirect, PubMed, Web of Science, and ClinicalTrials.gov adhering to the PRISMA protocol. A total of 26 eligible studies were considered for full-text screening, of which 10 were included in this review. The methodological quality was assessed by mixed methods appraisal tool and was reported as empirically fair. Among 336 subjects with CVDs, aged between 49.90 ± 6.10 to 72.20 ± 5.70 years, the majority had coronary artery diseases (n = 177, 52.68%) and hypertension (n = 200, 59.52%), and approximately half of them were females (n = 169, 50.30%). Based on the qualitative synthesis, subjects with CVDs demonstrated an increased cognitive decline (reduced Mini-Mental State Examination/Montreal Cognitive Assessment mean values) and attenuated task performance (lower mean 2-back task scores and slower reaction time). Results also indicated impaired brain activity at the supplementary motor area associated with poor ejection fraction; reduced default mode network suppression linked to high low-density lipoprotein cholesterol; lower regional homogeneity and amplitude of low-frequency fluctuation values; and reduced functional connectivity. In summary, alterations in brain networks connectivity may have contributed to an impaired cognitive performance in patients with cardiovascular diseases. It can be extrapolated that CVDs tend to alter the brain network connectivity and result in cognitive impairment and poorer task performance. However, for future imaging studies, more stringent and homogenous demographic data are highly recommended.
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