Background: The intestinal microbiome has been recently linked to several metabolic and chronic disorders, one of which is coronary artery disease (CAD). Our study aimed to analyze the intestinal microbiome of CAD patients and assess the eligibility of dysbiosis as a diagnostic marker of CAD. Methods: PubMed, Scopus, Embase, and Web of Science were searched using terms, such as ‘CAD’ and ‘microbiome’. Only observational controlled studies were included. R version 4.2.2 was used for the analysis. Results: A significant association was found between the CAD group and increased Simpson and Shannon Indices compared with the control group (MD=0.04, 95% CI=0.03–0.05, and MD=0.11, 95% CI=0.01–0.22, respectively). Our analysis yielded a statistically significant association between the CAD group and increased Prevotella genus (MD=13.27, 95% CI=4.12–22.42, P-value=0.004), Catenibacterium genus (MD=0.09, 95% CI=0.09–0.10), Pseudomonas genus (MD=0.54, 95% CI=0.29–0.78, P-value), and Subdoligranulum (MD=−0.06, 95% CI=−0.06 to −0.06) compared with the control group. Another significant association was detected between the CAD group and decreased Bacteroides vulgatus and Bacteroides dorei (MD=−10.31, 95% CI=−14.78 to −5.84, P-value <0.00001). Conclusion: Dysbiosis is an acceptable diagnostic marker of CAD. Decreased B. dorei and B. vulgatus among CAD patients suggests a protective role of these bacteria. Future clinical trials are necessary to investigate the potential benefit of supplementation of these bacteria in treating or preventing CAD.

Type 1 diabetes mellitus (T1DM) can lead to a severe and life-threatening complication called diabetic ketoacidosis (DKA). It is the leading cause of death in children with T1DM [1,2]. It is implic...

Background: In Wolff–Parkinson–White (WPW) syndrome, accurate localization of accessory pathways before catheter ablation can improve procedural planning and efficiency. Several 12‐lead electrocardiographic (ECG) algorithms have been proposed, but their diagnostic performance has not been consistently established. We performed a systematic review and meta‐analysis to assess the accuracy of ECG‐based algorithms for accessory pathway localization in manifest WPW. Methods: Following PRISMA‐DTA recommendations, PubMed, EMBASE, Cochrane CENTRAL, Web of Science, and Scopus were searched from January 1990 to January 2026. Studies enrolling adult or pediatric patients with manifest pre‐excitation who underwent electrophysiological study (EPS) and catheter ablation were included. Successful localization during EPS/ablation served as the reference standard. Random‐effects models were used to calculate pooled diagnostic accuracy, sensitivity, specificity, and diagnostic odds ratios (DOR). Summary receiver operating characteristic and leave‐one‐out sensitivity analyses were also performed. Results: Seventeen studies involving 3159 patients met inclusion criteria. The pooled diagnostic accuracy of ECG algorithms was 0.91 (95% CI 0.85–0.94), although heterogeneity was substantial (I ² = 91.4%). Pooled sensitivity was 0.87 (95% CI 0.73–0.94), and pooled specificity was 0.98 (95% CI 0.95–0.99; I ² = 0%). The pooled DOR was 297.17 (95% CI 46.33–1906.19; p <0.0001). Sensitivity analyses showed stable results after sequential exclusion of individual studies. Conclusion: Twelve‐lead ECG algorithms provide high diagnostic performance for accessory pathway localization in manifest WPW and may be useful adjuncts for pre‐ablation planning, although invasive electrophysiological mapping remains essential.