Background: It seems that diet is one of the main triggers of migraine; one of the most studied is alcohol, and also, over the years, red wine has been shown to trigger headaches. Therefore, this systematic review and meta-analysis aims to examine the strength of the association between wine consumption and migraine. Methods: In this systematic review and meta-analysis, a search of MEDLINE (via PubMed), Scopus, Cochrane, and Web of Science databases was conducted to assess the association between wine consumption and migraine, covering baseline to December 2023. Pooled Odds Ratio (p-OR) were calculated using the DerSimonian and Laird methods. This study was previously registered in PROSPERO (CRD42024511115). The risk of bias was evaluated using The Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: Five studies were included in this systematic review, and only four of them were in the meta-analysis. Using the DerSimonian and Laird method, the p-OR for the effect of wine consumption on migraine was 0.63 (95% CI 0.36–1.09). The included studies after the risk of bias assessment showed a moderate risk of bias. Conclusions: The findings of this systematic review and meta-analysis indicate that there is no conclusive evidence to support an increased or decreased risk of migraine associated with wine consumption.

Background/Objectives: Patient preoperative cardiorespiratory physical fitness measured by maximal oxygen consumption (VO2max) is highly relevant to postoperative outcomes, with low VO2max associated with a greater symptom burden and a greater prevalence of long-term treatment-related cardiovascular disease risk factors in patients undergoing surgery. A network meta-analysis (NMA) was conducted to determine the effects of different components of prehabilitation, including exercise, nutrition, psychological intervention, and different combinations of the aforementioned interventions, on oxygen consumption in people undergoing major abdominal or cardiothoracic surgery. Methods: A literature search was conducted from inception to December 2025. Randomized controlled trials on the effectiveness of prehabilitation programmes on pre-surgery VO2max were included. The risk of bias was assessed via the Cochrane risk of bias (RoB 2.0) tool, and the quality of evidence was assessed via the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool. Pairwise meta-analyses and NMAs were conducted for direct and indirect evidence. Results: Fourteen studies were included in this NMA. The highest effect (ES) for VO2max scores was for the exercise group versus the control group (ES: 0.44; 95% CI: 0.11, 0.78). When exercise was categorized according to intensity, the highest effect was for high-intensity interval training (HIIT) versus the control (ES: 0.51; 95% CI: 0.04, 0.97). Conclusions: Exercise HIIT should be considered the most effective strategy for improving exercise capacity in patients undergoing major abdominal or cardiothoracic surgery. Given the importance of VO2 as a predictor of morbidity, mortality, and the potential occurrence of adverse events after the procedure in surgical patients, it is essential to include its measurement in future studies to estimate both the risk of procedures and the effect of prehabilitation programmes.

Frailty reduces resilience to surgical stress, increasing vulnerability to adverse outcomes. While recovery efforts traditionally focus on the postoperative phase, the preoperative period offers better opportunities for lifestyle interventions. Prehabilitation aims to increase functional reserve and surgical tolerance, especially in frail older adults. This systematic review and meta-analysis of randomized controlled trials (RCTs) evaluated the effectiveness of multimodal prehabilitation on aerobic capacity—measured by the 6 min walk test (6MWT)—and the length of hospital stay (LOS). A literature search was conducted up to August 2025. Eligible RCTs reported the effects of prehabilitation on functional capacity and LOS. A pairwise meta-analysis was used to calculate pooled mean differences (p-MDs) with 95% confidence intervals (CIs). The risk of bias was assessed via the Cochrane RoB tool, and evidence quality was assessed via the GRADE system. Five studies involving 400 participants were included. The p-MD for the 6MWT showed no significant improvement at any time point: (T1–T2) 9.71 (CI: −38.92; 58.36), (T2–T3) −3.27 (CI: −71.21; 64.65), and (T1–T3) 15.01 (CI: −22.05; 52.07). The LOS was also not significantly reduced (p-MD: −0.464, CI: −0.960; 0.031). Prehabilitation did not significantly improve aerobic capacity or reduce hospital stay. Future research should explore long-term benefits and adherence.

Background: Despite advances in wearable mobile health (mHealth) technologies and their associated apps designed to promote physical activity, and the importance of adapting them to users, little is known about older adults’ perceptions of these technologies. Objective: This review aimed to synthesize and analyze qualitative evidence exploring the perceptions of adults aged 50 years and older regarding areas to improve, barriers to, and facilitators of wearable mHealth technologies (activity trackers and companion apps) to promote physical activity. Methods: A qualitative systematic review and meta-ethnography was conducted. Comprehensive searches were performed across 8 databases (MEDLINE, Scopus, Web of Science, CINAHL, The Cochrane Library Plus, PsycINFO, ProQuest, and ÍnDICEs-CSIC) for articles published in English or Spanish between January 2013 and January 2024. The synthesis followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and ENTREQ (Enhancing Transparency in Reporting the Synthesis of Qualitative Research) guidelines. Results: Ten articles met the inclusion criteria and were synthesized using meta-ethnography. Three main themes emerged: (1) barriers to promoting physical activity caused by wearable mHealth technologies: personal barriers (physical aspects, perceptions about technology, and personal preferences), technological barriers (functionality, content, design, alarms, availability, and accessibility), and environmental barriers (season of the year); (2) personal facilitators (consideration that these apps improve health, perceptions about technology, and personal preferences), technological facilitators (functionality, content, and design), relational facilitators (technological and social support), environmental facilitators (seasonal variations), and health care professionals (support and monitoring by health care services); and (3) personal areas (perceptions about technology and personal preferences), technological areas (functionality, content, and design), and relational areas (technological support). Conclusions: Although older adults acknowledge the potential of wearable mHealth technologies to promote physical activity, their effective engagement is hindered by distinct personal, technological, and environmental barriers. Bridging the digital divide requires designers to prioritize user-centered, age-friendly interfaces that are integrated with continuous support from health care professionals. To promote genuine health equity, future research must rigorously report intersectional demographics to ensure that mHealth interventions mitigate, rather than inadvertently exacerbate, existing disparities.