Patel, Anshum

Background: The management of asymptomatic high-grade carotid stenosis remains challenging, particularly in identifying individuals at highest risk for hypoperfusion-related stroke. Impaired cerebrovascular reactivity (CVR) has emerged as a potential predictor of future cerebrovascular events. Objective: To perform a systematic review and meta-analysis to quantify the association between impaired CVR and the risk of ipsilateral ischemic stroke or TIA in patients with asymptomatic high-grade carotid stenosis/occlusion. Methods: A systematic literature search of PubMed, Embase and Scopus was conducted from inception till July 2025. Eligible studies included asymptomatic patients with ≥70% carotid stenosis or occlusion who underwent CVR assessment and reported ipsilateral ischemic stroke or TIA outcomes. Pooled relative risks (RR) with 95% confidence intervals (CIs) were calculated using a random-effects model. Forest plots were generated, and heterogeneity was assessed using the chi-square test and the I 2 statistic. Results: Six prospective observational studies including a total of 361 patients with asymptomatic high-grade carotid stenosis/occlusion (mean age 70.4 years; 73.6% male; 71.2% with hypertension; 28.6% with diabetes; 29.6% current or former smokers) were included in the analysis. Of these, 120 patients had impaired CVR and 241 had preserved CVR. Transcranial Doppler (TCD) was the most frequently used modality to assess CVR, with acetazolamide or CO 2 as the vasodilatory stimulus. Following CVR assessment, patients were monitored for a weighted mean follow-up of 26.2 months (range: 21.5 to 42.5 months). The incidence of ipsilateral ischemic stroke or TIA was 14.2% in patients with impaired CVR versus 2.1% in those with preserved CVR (RR 3.98; 95% CI 1.62–9.76; P = 0.003; Figure 1). When limited to ipsilateral ischemic stroke alone, the incidence was 21.4% in the impaired CVR group compared to 4.3% in the preserved CVR group (RR 3.35; 95% CI 1.54–7.25; P = 0.002; Figure 2). Conclusions: Impaired CVR is associated with a 3- to 4-fold increased risk of ipsilateral ischemic stroke or TIA in patients with high-grade carotid stenosis/occlusion. CVR assessment may help stratify risk and guide individualized management in this population.

Background: Hypertension is a major contributor to global cardiovascular morbidity and mortality. Despite a wide range of pharmacologic treatments, many patients continue to have uncontrolled blood pressure. Recent research highlights the gut microbiota as a modifiable factor in blood pressure regulation through mechanisms involving systemic inflammation, microbial metabolites such as short-chain fatty acids, and angiotensin-converting enzyme modulation. Probiotic and prebiotic supplementation has gained interest as an adjunct strategy, yet existing reviews are limited in scope and often lack robust subgroup analysis. Objective: To systematically evaluate the effect of probiotic and prebiotic supplementation on blood pressure in adults with hypertension or elevated blood pressure, with an emphasis on gut microbiota modulation. Methods: We conducted a systematic search of PubMed, Scopus, Cochrane CENTRAL, and ScienceDirect for articles published from May 1, 2015, to April 30, 2025. ClinicalTrials.gov and PROSPERO were also searched. Eligible studies were randomized controlled trials in English involving adults 19-44 years with hypertension or pre-hypertension, comparing probiotic or prebiotic interventions with placebo, no treatment, or standard care. The primary outcome were changes in systolic and diastolic blood pressure; secondary outcomes included gut microbiota composition, inflammatory markers, endothelial function, and adverse effects. Two independent reviewers screened studies and assessed quality using the Cochrane Risk of Bias Tool 2.0. Results: Of 601 records screened, 23 trials met inclusion criteria. Most studies showed modest reductions in systolic and diastolic blood pressure with probiotic or prebiotic use. Mechanistic insights included improved gut barrier integrity, reduced inflammation, and increased beneficial metabolites. Subgroup analyses suggested efficacy varied by strain type, dosage, duration, and delivery method. Secondary outcomes showed improvements in lipid profiles, insulin resistance, and abundance of Bifidobacterium. Conclusion: Modulation of gut microbiota shows potential as an adjunct approach in managing hypertension.. While short-term benefits are observed, variability across studies limits generalizability. Larger trials with standardized methods are needed to confirm long-term clinical relevance. Keywords: Hypertension, Blood Pressure, Gut Microbiota, Probiotics, Prebiotics, Randomized Controlled Trials, Systematic Review

Abstract Introduction Large language models (LLMs), such as ChatGPT-4, have demonstrated promising potential as diagnostic tools across various medical disciplines. In sleep medicine, artificial intelligence tools are already used to analyze physiological sleep data and are being studied for their potential in phenotyping, endotyping, and predicting treatment responses. However, the effectiveness of LLMs in accurately diagnosing sleep disorders based on clinical history has not yet been studied. This study evaluates ChatGPT-4’s diagnostic performance using clinical vignettes. Methods Nineteen clinical cases were selected from the Case Book of Sleep Medicine, Third Edition (AASM, 2019). Each case included patient history, examination findings, and test results. The vignettes were input into ChatGPT-4 using the following standardized prompt: “Based on the provided case details, generate the top 5 differential diagnoses and identify the most likely final diagnosis: (copy and paste clinical vignette).” The model was tasked with generating both differential diagnoses and a final diagnosis for each case. The AI’s results were compared to reference diagnoses from the case book. Differential diagnoses were measured as the number of matches, and accuracy was reported as a percentage. Final diagnoses were scored as 0 (no match), 1 (partial match), or 2 (full match). Results The mean number of AI-generated differential diagnoses matching the AASM case differential diagnoses was 2.79 ± 0.71 (95% CI: 2.45–3.13). The mean accuracy percentage for differential diagnoses was 63.27% ± 15.61% (95% CI: 55.75%–70.79%), with scores ranging from 33.33% to 100%. For final diagnoses, ChatGPT-4 scored a total of 30 out of a possible 38, with a mean score was 1.58 ± 0.61 (95% CI: 1.29–1.87) out of 2, with 74% of cases achieving a full match. Performance was higher in cases with fewer differential diagnoses, whereas accuracy decreased in more complex cases. Conclusion ChatGPT-4 showed moderate to high accuracy in generating both differential and final diagnoses for sleep disorders. These findings suggest that AI could become a valuable clinical decision-support tool in sleep medicine. However, its inconsistent performance in complex cases highlights the need for further refinement and clinical testing. Support (if any)

Abstract Introduction Regular exercise improves sleep quality by reducing sleep onset latency, extending total sleep duration, and enhancing sleep efficiency, which may alleviate daytime sleepiness. However, the specific impact of exercise on daytime sleepiness remains unclear, with conflicting findings in the literature. We analyzed existing interventional studies which used Epworth Sleepiness Scale (ESS) to measure changes in degree of daytime sleepiness before and after an exercise regimen, allowing us to explore the relationship between exercise and daytime sleepiness. Methods Following PRISMA guidelines, a systematic search was conducted in electronic database of PubMed and Google Scholar from 1991 to the present. Thorough screening and inclusion criteria were applied to identify relevant studies which included ESS assessment before and after an exercise intervention. Also assessed sleep quality by Pittsburgh Sleep Quality Index (PSQI). Results Seven studies met all the inclusion criteria and were included in this study. Exercise exhibited a significantly beneficial impact on sleepiness measured by ESS in four out of seven studies we included in review while two studies showed a marginal reduction in ESS without statistical significance, and one study indicated no change. Additionally, exercise showed an improvement in sleep quality in four out of five studies that included PSQI. Variability in results was noted, influenced by factors such as exercise type, intensity, duration, and timing, as well as individual adherence. Additionally, exercise interventions improved sleep quality, as suggested by reduced scores in PSQI which may indirectly improve daytime sleepiness. Conclusion This analysis of existing interventional studies on exercise and daytime sleepiness suggests exercise can be beneficial for reducing daytime sleepiness and improving sleep quality. While the exact mechanism remains elusive, several factors contribute to the impact of both acute and chronic exercise on daytime sleepiness such as improved sleep quality, regulation of circadian rhythm, neurotransmitters release, stress reduction, increased energy levels, and weight reduction ultimately alleviating daytime sleepiness. Future research will be essential for addressing gaps on how exercise regimen and the underlying mechanisms may prove efficacious on improving daytime sleepiness. Support (if any) Mayo Clinic Florica Research Accelerator for Clinicians Engaged in Research Program