RESUMO
Aging is becoming a severe social phenomenon globally, and the improvements in health care and increased health awareness among the elderly have led to a dramatic increase in the number of surgical procedures. Because of the degenerative changes in the brain structure and function in the elderly, the incidence of perioperative neurocognitive disorders (PND) is much higher in elderly patients than in young people following anesthesia/surgery. PND is attracting more and more attention, though the exact mechanisms remain unknown. A growing body of evidence has shown that the gut microbiota is likely involved. Recent studies have indicated that the gut microbiota may affect postoperative cognitive function via the gut-brain axis. Nonetheless, understanding of the mechanistic associations between the gut microbiota and the brain during PND progression remains very limited. In this review, we begin by providing an overview of the latest progress concerning the gut-brain axis and PND, and then we summarize the influence of perioperative factors on the gut microbiota. Next, we review the literature on the relationship between gut microbiota and PND and discuss how gut microbiota affects cognitive function during the perioperative period. Finally, we explore effective early interventions for PND to provide new ideas for related clinical research.
RESUMO
Voxel-based morphometry (VBM) is a popular non-invasive magnetic resonance imaging technique to investigate brain gray matter (GM) differences between groups. Recently, two VBM studies in migraine have been published in The Journal of Headache and Pain. Reviewing the two and those previous published VBM studies, we found considerable variations of the results. Spatially diverse brain regions with decreased and increased GM alterations and null findings have been reported. It is interesting to know whether there is a reliable brain morphological signature for migraine. Coordinate-based meta-analysis (CBMA) is increasingly used to quantitatively pool individual neuroimaging studies to identify consistent and reliable findings. Several CBMA have been conducted, however, their results were inconsistent. The algorithms for CBMA have evolved and more eligible VBM studies in migraine have been published. We therefore conducted an updated CBMA using the latest algorithms for CBMA, seed-based d mapping with permutation of subject images (SDM-PSI). The present CBMA of 32 VBM studies (41 datasets comprising 1252 patients and 1025 healthy controls) found no evidence of consistent GM alterations in migraine. Sensitivity analysis, subgroup meta-analyses, and meta-regression analyses revealed that the result was robust. This negative result indicates that there is no reliable brain morphological signature for migraine. VBM investigations in migraine remain a heterogeneous field. Many potential confounding factors, such as underpowered sample sizes, variations in demographic and clinical characteristics, and differences in MRI scanners, head coils, scanning parameters, preprocessing procedures, and statistical strategies may cause the inconsistences of the results. Future VBM studies are warranted to enroll well-characterized and homogeneous subtype samples with appropriate sample sizes, comprehensively assess comorbidities and medication status, and use well-validated and standardized imaging protocols and processing and analysis pipelines to produce robust and replicable results in migraine.