Peripheral artery disease (PAD), coronary artery disease (CAD), and cerebrovascular disease (CeVD) are characterized by atherosclerosis and inflammation as their underlying mechanisms. This paper aims to conduct a literature review on pharmacotherapy for PAD, specifically focusing on how different drug classes target pro-inflammatory pathways. The goal is to enhance the choice of therapeutic plans by considering their impact on the chronic subclinical inflammation that is associated with PAD development and progression. We conducted a comprehensive review of currently published original articles, narratives, systematic reviews, and meta-analyses. The aim was to explore the relationship between PAD and inflammation and evaluate the influence of current pharmacological and nonpharmacological interventions on the underlying chronic subclinical inflammation. Our findings indicate that the existing treatments have added anti-inflammatory properties that can potentially delay or prevent PAD progression and improve outcomes, independent of their effects on traditional risk factors. Although inflammation-targeted therapy in PAD shows promising potential, its benefits have not been definitively proven yet. However, it is crucial not to overlook the pleiotropic properties of the currently available treatments, as they may provide valuable insights for therapeutic strategies. Further studies focusing on the anti-inflammatory and immunomodulatory effects of these treatments could enhance our understanding of the mechanisms contributing to the residual risk in PAD and pave the way for the development of novel therapies.

Background: α‐Klotho is a multifunctional protein implicated in vascular aging. Declining Klotho levels are associated with arterial stiffness, endothelial dysfunction, and vascular calcification. We investigated the associations between circulating klotho, aortoiliac calcification, endothelial progenitor cells, and 10‐year survival. Methods: In this retrospective cohort, blinded clinicians scored calcification on computed tomography (0–10 scale: aorta 6 points, iliac 4 points). Plasma klotho was measured by ELISA; endothelial progenitor cell subsets were quantified via flow cytometry. Mortality data were obtained from the Minnesota Death Registry. Results: This study included 148 participants (mean age 72.4±9.6 years; 41% female). Median calcification score was 3 (interquartile range, 1–5). Patients with low calcification had higher Klotho levels (669 [567–841] versus 556 [457–678] pg/mL; P <0.01), with Klotho inversely correlated with calcification (r=−0.315, P <0.01). Stratified by calcification location and severity, the highest Klotho levels were seen in patients without aortic or iliac calcification ( P =0.015). Over 10 years, low Klotho was independently associated with higher mortality (hazard ratio [HR], 3.056 [95% CI 1.288–7.878]; P =0.014). Klotho inversely correlated with mature osteocalcin‐positive EPCs; B=−0.16 (95% CI, −0.29 to −0.02; P =0.027). Immunohistochemistry and immunofluorescence confirmed endothelial Klotho expression in internal mammary artery. Conclusions: Lower circulating Klotho levels are associated with increased aortoiliac calcification and higher 10‐year mortality, supporting a role for Klotho in vascular aging.

Aims: The gut microbiome (GM) is increasingly recognized for its role in atherosclerosis development. However, its potential as a biomarker for risk-stratification in patients with atherosclerotic cardiovascular (CV) comorbidities remains under-explored. This study aimed to identify distinct GM clusters associated with elevated CV risk. Methods: In this prospective observational cohort, patients with coronary artery disease, hypertension, hyperlipidemia, or diabetes mellitus referring to Mayo Clinic from 2013 to 2018 were enrolled. Bacterial DNA was analyzed in the V3-V5 region of 16S rDNA. Beta-diversity was plotted using Principal Coordinates Analysis. Unsupervised hierarchical clustering of the GM classified participants into two clusters. Cox regression evaluated the association between clusters and Major Adverse Cardiac Events (MACE), defined as a composite of cardiac events, heart failure, and all-cause mortality. Permutational Multivariate Analysis of Variance identified clinical factors contributing to cluster assignment. Linear Discriminant analysis identified GM taxa with differential abundance among clusters and their effect sizes. Results: Among 211 participants (median age 60 [IQR: 50–70] years; 57.3% male), two distinct GM profiles emerged (Cluster H: N = 104; Cluster L: N = 107, P < 0.001). Cluster L participants were younger (P < 0.001), more likely female (P = 0.009), and had healthier CV profiles, including lower BMI (P = 0.007), hypertension (P = 0.010), hyperlipidemia (P = 0.005), and lower coronary artery disease prevalence (P = 0.003). Over a median follow-up of 7.4 years, Cluster L had a significantly lower incidence of MACE compared to Cluster H (HR = 0.48, 95% CI: 0.26–0.91, P = 0.024). Cluster L had higher operational taxonomic units (P < 0.001) and lower Bacillota-to-Bacteroidetes ratio (P < 0.001) compared to Cluster H. The predominant taxa in Cluster L included Bacteroides , Alistipes , and Parabacteroides , whereas Blautia , Agathobacter , and Clostridium sensu stricto-1 were more abundant in Cluster H. Conclusion: Distinct GM profiles are associated with varying CV risk, highlighting the potential of unsupervised GM profiling as a novel tool for risk stratification and individualized therapy.

Background: Inadequate preventive dental care may contribute to inflammatory conditions such as periodontitis, increasing cardiovascular disease risk. Artificial intelligence–enabled electrocardiography (AI‐ECG) algorithms accurately estimate cardiovascular disease risk. We investigated the association between inadequate preventive dental care and the AI‐ECG–estimated risk of atrial fibrillation, aortic stenosis, low ejection fraction, cardiac amyloid, cardiovascular aging, and all‐cause mortality. Methods: We retrospectively analyzed 266 637 Mayo Clinic patients (2018–2024) who completed a Social Determinants of Health Survey and had an ECG performed within 1 year of survey completion. AI‐ECG algorithms generated continuous risk scores (0 or 1) for atrial fibrillation, aortic stenosis, low ejection fraction, and amyloid. Cardiac aging was assessed by delta age, calculated as AI‐ECG–estimated physiological age minus the chronological age. Associations with preventive dental care were analyzed using logistic regression. Cox regression evaluated dental care predictiveness on all‐cause mortality. Results: Among 266 637 individuals (mean age, 59.5±16.4 years; 51.1% women), 49 918 (18.7%) reported inadequate preventive dental care. These individuals had higher delta age and increased AI‐ECG–predicted risks of atrial fibrillation, aortic stenosis, amyloid, and reduced ejection fraction (all P <0.001). In multivariable logistic regression models including all AI‐ECG scores, inadequate preventive dental care was associated with higher probabilities of low ejection fraction (odds ratio [OR], 1.80 [95% CI, 1.69–1.91]), atrial fibrillation (OR, 1.10 [95% CI, 1.04–1.17]), aortic stenosis (OR, 1.90 [95% CI, 1.64–2.20]), amyloid (OR, 1.18 [95% CI, 1.12–1.25]), and higher delta age (OR, 1.03 [95% CI, 1.02–1.03]) (all P <0.001). Inadequate preventive dental care predicted all‐cause mortality after adjusting for demographics, risk factors, and AI‐ECG algorithms (HR, 1.45 [95% CI, 1.38–1.53], P <0.001). Conclusions: Inadequate preventive dental care is associated with subclinical cardiovascular disease. AI‐ECG algorithms may facilitate cardiovascular risk stratification among individuals with limited preventive dental care access.

Background: Coronary flow reserve reflects microvascular function, whereas filling pressure indicates myocardial hemodynamic burden. In angina with nonobstructive coronary arteries, abnormalities in either could contribute to a supply–demand mismatch; however, their combined prognostic significance remains unclear. Methods: Patients with angina with nonobstructive coronary arteries who underwent invasive coronary reactivity tests were studied retrospectively. Coronary microvascular dysfunction (CMD) was coronary flow reserve <2.5. An artificial intelligence–enabled ECG marker of elevated filling pressure (AIEFP) was applied as a scalable prognostic marker of myocardial hemodynamic stress. Associations with major adverse cardiovascular events were evaluated using Cox regression and propensity score overlap weighting. Results: Among 1957 patients with angina with nonobstructive coronary arteries (median age, 51.8 years; 67.2% women), CMD+ was identified in 26.4% and AIEFP+ in 6.6%. Over 8 years, 204 patients (10.4%) experienced major adverse cardiovascular events. In nested models, both CMD (hazard ratio [HR]=1.42 [95% CI=1.13–1.78]; P =0.002) and AIEFP (HR=2.28 [95% CI=1.67–3.11]; P <0.001) remained associated with major adverse cardiovascular events after adjustment. Adding AIEFP to the base model improved model fitness (Δχ ² =23.65, P <0.001; ΔAkaike Information Criterion=−21.7) and modestly improved discrimination (ΔHarrell concordance index=0.02, P =0.02). In a 4‐group model, adjusted risks increased in a graded manner. Overlap‐weighted analysis after covariate balance demonstrated distinct temporal risk trajectories: CMD+/AIEFP+ had the highest 1‐year risk (12.7%), and AIEFP+ had the highest cumulative 8‐year risk (57% in CMD− and 51.8% in CMD+). Conclusions: CMD and AIEFP provide complementary prognostic information, with AIEFP remaining significantly associated with outcomes after multivariable adjustment. A dual‐axis framework integrating myocardial hemodynamic stress (AIEFP) and microvascular function (coronary flow reserve) may enhance risk stratification and enable identification of clinically distinct angina with nonobstructive coronary arteries phenotypes with divergent trajectories.