Heart failure (HF) is a systemic syndrome in which venous congestion and impaired perfusion can produce clinically important hepatic dysfunction. The term cardiohepatic syndrome (CHS) describes this bidirectional interaction, but cardiac and hepatic abnormalities are still often evaluated in parallel rather than as a connected hemodynamic process. Ultrasound is uniquely suited to an integrated assessment because it can characterize cardiac structure and function, systemic venous congestion, hepatic hemodynamics, tissue stiffness, and treatment-related change at the bedside. Conventional transthoracic echocardiography remains the foundation of evaluation, while three-dimensional echocardiography and speckle-tracking techniques improve quantification of right ventricular, atrial, and subclinical myocardial dysfunction. Abdominal Doppler ultrasound, venous congestion scoring, and liver elastography add complementary information, although liver stiffness must be interpreted cautiously because congestion, inflammation, cholestasis, and fibrosis can produce overlapping signals. Artificial intelligence may improve acquisition, measurement reproducibility, and multimodal data integration, but external validation and transparent reporting remain essential. This review summarizes contemporary evidence and proposes a practical, sequential pathway that combines echocardiography, venous Doppler findings, liver stiffness, laboratory biomarkers, and dynamic reassessment after decongestion. The central clinical principle is that CHS should be evaluated as a time-varying cardiohepatic phenotype rather than diagnosed from a single cardiac, hepatic, or biochemical measurement.
Abstract Purpose To study left atrial stiffness index (LASI) and left atrial activation time (LA-AT) changes in an older population with silent paroxysmal atrial fibrillation (PAF) compared to age-matched control. Methods Individuals with newly diagnosed PAF and a randomly selected age-matched control group without AF were enrolled from STROKESTOP2-study. All participants had NT-proBNP levels 125–900 ng/L. TTE examinations were analyzed retrospectively offline using dedicated software. Besides conventional echocardiographic measurements, LA-AT was obtained by measuring the time delay between the onset of the P-wave on ECG and tissue Doppler Á peak wave in lateral LA wall. LASI was calculated as the ratio of left ventricular filling (E/é) to peak atrial longitudinal strain (PALS). Results Mean age was 76 ± 0.3 years. The PAF group ( n = 67) presented significant increase of LASI (0.41 (0.29–0.60) vs. 0.32 (0.29–0.43), P = 0.001) and prolonged LA-AT (170 (140–180) ms vs. 140 (120–144) ms, P < 0.001) compared to controls ( n = 94). Subgroup analysis in participants with normal LA volume index (LAVI) ≤ 34 ml/m 2 , LASI and LA-AT remained significantly increased/prolonged in PAF ( N = 27) compared to controls ( N = 72). NT-proBNP-levels did not differ between PAF (228 (181–348) ng/L) and controls (216 (156–317) ng/L) ( P = 0.18). ROC curve analysis identified thresholds LASI > 0.54 and LA-AT > 139 msec for discrimination of silent PAF. Conclusion Indices reflecting LA stiffness and atrial conduction delay were significantly elevated in recently diagnosed PAF patients. LASI and LA-AT thresholds might non-invasively detect early atrial remodeling without structural enlargement in elderly patients with high risk of PAF and mildly increased NT-proBNP levels.
Undetected atrial fibrillation (AF) is an important potential mechanism after cryptogenic stroke. Speckle-tracking echocardiography-derived left atrial (LA) phasic strain and left ventricular global longitudinal strain (LV GLS) have been reported to differ between patients with and without AF subsequently detected after stroke, but the magnitude and consistency of these group-level differences remain uncertain. PubMed, Embase, and Web of Science were searched from inception to May 3, 2026. Eligible reports enrolled adults with cryptogenic ischemic stroke or embolic stroke of undetermined source (ESUS); mixed undetermined-source cerebrovascular cohorts were retained only when the source report explicitly framed the population as cryptogenic stroke/ESUS or undetermined-source cerebrovascular disease. No numerical percentage threshold for cohort composition had been prespecified in the registered protocol. Reports excluded known AF at baseline, measured LV GLS or LA phasic strain by speckle-tracking echocardiography, and reported AF detected during follow-up. Random-effects meta-analyses used raw mean differences (MDs) and complementary Hedges g standardized mean differences (SMDs), with restricted maximum-likelihood estimation, Hartung-Knapp confidence intervals (CIs), and prediction intervals. Prespecified outcome-level deduplication was retained; revision-stage analyses included a monitoring-duration subgroup analysis, a cohort-only reservoir-strain sensitivity analysis, and a conduit-strain sensitivity analysis addressing unresolved values in Bufano et al. Nineteen reports representing 17 cohort clusters were included. Outcome-specific analyses comprised 7 datasets for LV GLS (n = 1,403), 17 for LA reservoir strain (n = 2,755), 10 for the primary LA conduit-strain analysis excluding Bufano et al. (n = 1,958), and 14 for LA contractile strain (n = 2,455). Patients with subsequently detected AF had lower LA reservoir strain (MD, -7.44
Moderate aortic stenosis (AS) has traditionally been considered a transitional and relatively benign stage of valvular disease. Yet, contemporary evidence shows that it is associated with substantial morbidity and mortality even before progression to severe AS. This paper synthesizes current evidence on the limitations of standard echocardiography, highlights the role of advanced imaging and artificial intelligence, and outlines evolving strategies for risk stratification and clinical management. Multimodality imaging provides a more accurate assessment of disease severity beyond conventional echocardiographic parameters: computed tomography aortic valve calcium scoring, cardiac magnetic resonance, and 18 F-sodium fluoride positron emission tomography reveal early myocardial injury and identify rapid progressors. AI further enhances reproducibility and supports the development of emerging prognostic models. A staging approach that integrates ventricular, atrial, and right-sided involvement correlates more closely with clinical outcomes than valve metrics alone, enabling a more comprehensive characterization of disease burden. Although guideline-directed surveillance remains the standard strategy for most patients, selected high-risk individuals, particularly those with adverse remodeling, elevated biomarkers, or recurrent heart failure admissions, may benefit from earlier intervention. While waiting for the results of ongoing randomized trials cardiologist should implement all the imaging multimodality tools available in order to individuate patients in which an earlier treatment of moderate AS will more probably improve long-term outcomes.
Focused cardiac ultrasound (FoCUS) has become the standard of care for bedside assessments of cardiac function. With the integration of artificial intelligence (AI), there is limited evidence comparing it to bedside visual assessments by experienced users. In our prospective study conducted at Tufts Medical Center in Boston, Massachusetts from December 2020 to March 2022, patients ≥ 18 years requiring a TTE were recruited by convenience sampling. They each underwent FoCUS LVEF classification by AI and bedside visual assessment, with TTE as reference. LVEF was calculated by Simpson’s biplane method of disks in AI-FoCUS and TTE, and visual global assessment by the bedside sonographer. Data analysis was completed in October 2025. Our 215 participants had a median age of 63 (IQR 49–73) years with 83 (38.6
