Search Results (1,808)

Organoid and organ-on-chip technologies are rapidly evolving platforms for viral research that integrate stem cell biology, tissue engineering, and microfluidics to recapitulate key structural, mechanical, biochemical, and cellular features of human and animal physiology. By incorporating multicellular organoids into perfused microfluidic systems, these models can provide complex, dynamic, and physiologically relevant micro-environments for investigating virus–host interactions that are difficult to capture in conventional two-dimensional cultures and static organoids. Controlled flow, shear stress, extracellular matrix organization, tissue–tissue interfaces, and multicellular signaling enable mechanistic investigation of viral infectivity, dissemination, tissue injury and immune activation. Integration of real-time imaging and biosensors further permits longitudinal monitoring of viral replication, host responses, and tissue integrity, expanding the potential of these platforms for antiviral drug discovery. Recent organoid-on-chip studies using brain, skin, vaginal, respiratory, and intestinal models have demonstrated how tissue architecture, mechanical forces, glycocalyx dynamics, and immune–stromal interactions influence viral tropism and pathogenesis. In this review, we provide a mechanistic and translational overview of organoid and organ-on-chip technologies for studying viral infections, with particular emphasis on models of herpes simplex virus (HSV)-mediated disease. We further examine advances in immune integration, multi-organ systems, biosensing, and computational approaches that are expanding the complexity and predictive potential of these models. Importantly, patient-derived organoids and organ-on-chip platforms can capture interindividual differences in viral susceptibility, host responses, and therapeutic efficacy, providing pharmaceutical research with more precise, patient-relevant data to support drug prioritization and precision antiviral medicine. Finally, we discuss key barriers to broader adoption, including organoid maturation, biological and technical variability, reproducibility, scalability, biosafety, cost, standardization, and regulatory validation. Collectively, these advances position organoid and organ-on-chip technologies as powerful human-relevant models that bridge reductionist in vitro systems and human disease, while continued optimization, standardization, and validation will be essential to realize their full potential for mechanistically informed antiviral discovery, therapeutic development, and precision medicine. Full article

Background/Objectives: Differentiating high-grade glioma recurrence from treatment-related changes remains challenging on conventional MRI. This study evaluated non-contrast arterial spin labeling (ASL) perfusion MRI for this distinction and compared its performance with dynamic susceptibility contrast (DSC) perfusion MRI. Methods: Postoperative follow-up MRI examinations obtained between November 2019 and May 2021 were retrospectively reviewed. The cohort included 63 MRI examinations from 36 adults treated for high-grade glioma. ASL, routine MRI, and DSC images were independently assessed by two neuroradiologists. Final diagnosis was based on histopathology or longitudinal clinical and imaging follow-up. Reader agreement, diagnostic performance, and an exploratory patient-level grouped machine learning analysis using ASL-only, DSC-only, and combined ASL–DSC features were evaluated. Results: ASL- and DSC-derived perfusion parameters were significantly higher in tumor recurrence than in treatment-related changes (all p < 0.001). Both techniques showed high diagnostic performance; DSC achieved the highest accuracy, whereas ASL provided high specificity across readers. Inter-reader agreement ranged from substantial to almost perfect. In grouped cross-validation, ASL-only, DSC-only, and combined models achieved mean AUCs of 0.946, 0.997, and 0.997, respectively. Permutation testing confirmed that combined-model performance exceeded chance expectations (empirical p = 0.002). Conclusions: Non-contrast ASL perfusion showed diagnostic performance comparable to DSC for differentiating high-grade glioma recurrence from treatment effects. ASL may provide a reliable non-invasive alternative for longitudinal surveillance, particularly when gadolinium administration is undesirable or contraindicated. Full article

Time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for noninvasive visualization of arterial anatomy, but extracting hemodynamics like blood velocity typically requires supplementary phase-contrast scans, tagging or multi-TE images. This study proposes a novel, physics-informed computational framework to extract variable fluid velocity directly from standard TOF-MRA signal profiles. We analytically expand the approach-to-steady-state Bloch equations to include convective flow, establishing a mathematical relationship between the spatial decay of longitudinal magnetization and fluid velocity. The velocity derivation was further extended to pointwise estimation over a 1-D centerline, overcoming the limitations of constant-velocity assumptions. To validate and solve this problem, a MATLAB (R2025b) simulation framework was developed to model fluid flow in two variable-geometry flowing tube cases, i.e., continuous narrowing and focal stenosis, under synthetic scanner noise. A global inverse optimization approach utilizing Dual-Tikhonov regularization was applied to stably invert the ill-posed transit time integral, actively penalizing high-frequency numerical ringing while preserving structural curves. The computational simulations successfully recovered ground-truth point-wise velocities, tracking gradual hemodynamic accelerations and sharp stenotic jets. This theoretical framework and the example centerline TOF-MRA signal intensity provide a robust mathematical proof-of-concept that quantitative, localized functional hemodynamic metrics can be extracted from standard structural MRA imaging, establishing a foundation for advanced flow quantification without requiring additional scan time. Full article

Background: Retinal microvascular assessment has emerged as a promising non-invasive approach for evaluating vascular health. Recent advances in retinal imaging technologies have enabled detailed characterization of retinal vascular structure and function, raising interest in their potential role as biomarkers of exercise-related vascular adaptation. This systematic review with narrative synthesis aimed to summarize current evidence regarding the relationship between exercise, physical fitness, and retinal microvascular biomarkers. Methods: A systematic literature search was conducted in PubMed, Scopus, and Web of Science for studies published from January 2021 to June 2026, followed by a supplementary update search to identify eligible publications available through 31 July 2026. Search terms combined retinal microvascular assessment techniques with terms related to exercise, physical activity, physical fitness, and exercise training. Following screening and eligibility assessment, 42 publications were included in the final qualitative synthesis, comprising 20 publications identified through the initial search and 22 additional publications identified through the supplementary update search. Several publications represented complementary analyses of the same or overlapping study cohorts and were therefore not considered independent replications. Results: The included studies comprised observational studies and exercise intervention trials involving healthy individuals and clinical populations. Retinal biomarkers assessed included vessel diameters, arteriovenous ratio (AVR), vessel density, perfusion density, foveal avascular zone (FAZ), retinal oxygen extraction, wall-to-lumen ratio (WLR), and choriocapillaris perfusion parameters. Several studies reported measurable acute and chronic retinal vascular responses to exercise, although the direction, magnitude, and clinical meaning of these changes varied according to population, exercise modality, imaging technique, and biomarker. Observational studies generally reported associations between higher physical activity or cardiorespiratory fitness and a more favorable retinal vascular profile, but causal interpretation remains limited. Conclusions: Retinal microvascular biomarkers appear sensitive to acute physiological stress and may reflect selected adaptations associated with longer-term exercise exposure. However, retinal responses are heterogeneous and biomarker-specific, and their biological and clinical significance remains incompletely established. Methodological heterogeneity, overlapping study cohorts, and the limited number of adequately powered randomized and longitudinal studies constrain causal interpretation and generalizability. Retinal vascular measures should therefore currently be regarded as candidate biomarkers and research tools rather than validated surrogate outcomes or routine clinical measures. Full article

Background/Objectives: Retinal imaging has considerable potential for monitoring Alzheimer’s disease (AD) neurodegeneration, as retinal ganglion cell dendritic atrophy within the inner plexiform layer (IPL) is an early event. We tested whether quantitative optical coherence tomography (OCT) speckle texture analysis combined with supervised machine learning could discriminate AD-related IPL alterations without exogenous contrast agents in a mouse model. Methods: Retinal explants from triple-transgenic AD mice (n = 7, aged 12 months) and C57BL/6 controls (n = 3, aged 15 months) were imaged ex vivo using a custom 1040 nm spectral-domain OCT system. Five grey-level co-occurrence matrix (GLCM) features were extracted from IPL volumes of interest (VOIs) and classified using a linear support vector machine (SVM). Results: AD and control IPL textures formed two completely separable clusters in a two-dimensional feature space defined by contrast and entropy (0°), achieving 100% VOI-level classification accuracy (95% CI: 96.4–100%). However, given the small sample size, VOI-level rather than animal-level validation, lack of histological confirmation, non-interleaved image acquisition, and differences in age/strain between groups, these results represent exploratory dataset separability rather than a validated diagnostic test. Conclusions: These findings demonstrate the feasibility of the ligand-free, texture-based OCT discrimination of IPL alterations, indicating a strong underlying optical signal. Adequately powered, in vivo longitudinal studies with matched controls, interleaved acquisition, animal-level cross-validation, and histological validation are required before any clinical translation. Full article

Backgroundand Objectives: Retinal microcirculation may serve as a surrogate marker of systemic vascular status and can be non-invasively assessed using optical coherence tomography angiography (OCTA). Emerging evidence suggests that retinal and choroidal microvascular alterations may occur following coronavirus disease 2019 (COVID-19) and multisystem inflammatory syndrome in children (MIS-C), potentially reflecting systemic vascular and inflammatory processes. This review summarizes the current evidence regarding retinal and choroidal microvascular changes detected by OCTA in pediatric patients with COVID-19 and MIS-C. Materials and Methods: A structured literature search of the National Center for Biotechnology Information (NCBI) PubMed database was conducted from inception until April 2026. Original English-language studies evaluating retinal and choroidal microcirculation using OCTA in pediatric patients with COVID-19 or MIS-C were identified and reviewed. Results: Available studies suggest variable retinal and choroidal microvascular alterations following COVID-19 and MIS-C, including changes in vessel density, perfusion, and foveal avascular zone parameters. Several investigations reported reduced vessel density, particularly within the deep capillary plexus, whereas others demonstrated increased peripapillary vascular parameters or no significant differences during the observation period. Differences in patient characteristics, disease severity, timing of imaging, OCTA protocols, and study design likely contribute to the heterogeneity of the reported findings. Conclusions: OCTA represents a promising research tool for investigating retinal and choroidal microvascular alterations associated with pediatric COVID-19 and MIS-C. However, the available evidence remains limited by small observational studies, methodological heterogeneity and inconsistent findings. Larger prospective longitudinal studies using standardized imaging protocols are needed to determine the clinical significance and reproducibility of OCTA-derived parameters and to establish whether they may have potential as biomarkers of ocular or systemic vascular involvement. Full article

Background: Sleep-dependent glymphatic clearance has emerged as a potential mechanism linking sleep disruption with Alzheimer’s Disease (AD) pathology. However, the relationship between objectively measured sleep and glymphatic function across the AD continuum remains unclear. Methods: Four databases (PubMed, Embase, Cochrane Library, and PsycINFO) were systematically searched for studies assessing objective sleep metrics and glymphatic-related biomarkers or clearance measures in humans across the AD continuum. Following peer review of the search strategy, supplementary searches of PubMed and Embase using expanded glymphatic and sleep electrophysiology terminology were undertaken to maximize sensitivity. The final database searches identified 416 records. After removal of 72 duplicates, 344 records were screened, 64 reports underwent full-text assessment, and four studies met the inclusion criteria. Results: Four studies involving participants across the AD continuum were included. Objective sleep assessment was performed using polysomnography or electroencephalography, while brain clearance was evaluated using direct or surrogate imaging measures including diffusion tensor image analysis along the perivascular space (DTI-ALPS), perivascular space burden, blood oxygen level-dependent–cerebrospinal fluid (BOLD-CSF) coupling, or direct tracer-based clearance imaging. Across studies, better preserved slow-wave sleep, slow-wave activity, and sleep oscillatory coupling were generally associated with more favorable glymphatic function or glymphatic-related biomarkers. Conversely, disrupted sleep architecture, reduced sleep efficiency, and altered sleep oscillatory coupling were associated with impaired glymphatic clearance or glymphatic dysfunction. Conclusions: Current evidence suggests that objectively measured sleep architecture, particularly slow-wave sleep and sleep oscillatory dynamics, may be associated with biomarkers of brain clearance across the AD continuum. However, the available evidence remains preliminary, is predominantly cross-sectional, and relies largely on indirect measures of brain clearance. Larger longitudinal studies incorporating standardized sleep assessment and validated measures of cerebral clearance are required to clarify temporal relationships, establish causality, and determine whether sleep-targeted interventions influence brain clearance or disease progression. Summary of findings: Preliminary evidence suggests that preserved slow-wave sleep and sleep oscillatory activity are associated with more favorable biomarkers of brain clearance, whereas disrupted sleep architecture is associated with less favorable clearance-related measures. Full article

Background: Optical coherence tomography angiography (OCTA) provides quantitative metrics of the retinal microvasculature, most prominently vessel density (VD), that are increasingly used as biomarkers in ocular, systemic, and cerebrovascular disease. Because OCTA relies on the detection of flow-related motion contrast, image quality has emerged as a pervasive determinant of these metrics, yet its effect has been reported in fragmentary and non-comparable ways across the literature. Methods: We identified OCTA studies indexed in PubMed that examined the relationship between image quality and quantitative OCTA parameters, and we summarised their methods and findings across the macular, foveal avascular zone, and peripapillary regions and across vascular layers. We integrated directly comparable per-unit scan-quality effects using random-effects meta-analysis and separately synthesized direct cross-sectional Pearson correlations between manufacturer-reported image quality and macular vessel-density outcomes from independent healthy cohorts. Results: Higher image quality was associated with higher measured vessel density in every contributing dataset. On the Optovue scan-quality (SQ, 0–10) scale, superficial macular VD increased by 3.46% (95% CI 1.85–5.07) per SQ unit in controlled signal-attenuation experiments and by covariate-adjusted observational estimates ranging from 0.90% to 2.16% per SQ unit; a combined order-of-magnitude estimate across both estimator types was 1.64% (95% CI 1.15–2.12). Peripapillary estimates were heterogeneous and derived from only two independent cohorts; they were therefore summarised descriptively rather than pooled. Across three independent externally authored healthy cohorts reporting direct cross-sectional Pearson correlations, higher image quality was strongly associated with higher macular vessel-density outcomes (random-effects pooled r = 0.64, 95% CI 0.50–0.75; I² = 49%). Conclusions: Image quality is an important, directional confounder of VD-based OCTA metrics whose magnitude can rival the biological or physiological signal of interest. Platform-appropriate standardisation, transparent reporting, and consideration of image quality in acquisition and analysis are therefore important for the valid interpretation of vessel-density measurements, particularly in functional and longitudinal studies. Full article

Objectives: The objective of this study was to longitudinally evaluate mandibular condylar trabecular organization in children with a history of severe early childhood caries (SECC) and caries-free controls using fractal dimension (FD) analysis, and to compare the findings according to sex. Methods: This retrospective follow-up study included 100 children (50 with a history of SECC and 50 caries-free controls) with panoramic radiographs obtained at T0 (5 years) and T1 (8 years). FD analysis of the mandibular condyle was performed using the box-counting method on standardized regions of interest (ROIs; 21 × 21 pixels) following image calibration. Independent and paired t-tests and a linear mixed-effects model were used for statistical analysis at p < 0.05. Results: No significant difference in FD values was observed between the SECC and control groups at T0 (p > 0.05). At T1, the control group exhibited significantly higher FD values than the SECC group (1.151 ± 0.06 vs. 1.076 ± 0.10, p < 0.001). The linear mixed-effects model demonstrated a significant group × time interaction (p < 0.001), indicating different longitudinal trajectories between the groups. Within-group comparisons showed no significant longitudinal change in the SECC group (p > 0.05), whereas FD values increased significantly in the control group (p < 0.001). No significant effects of sex or related interactions were identified (p > 0.05). Conclusions: Children with a history of SECC did not exhibit the age-related longitudinal increase in mandibular condylar FD values observed in caries-free controls. These findings suggest that a history of SECC may be associated with an altered longitudinal pattern of condylar trabecular organization during growth; however, further studies are required to confirm this association. Full article

Objective: Our objective was to describe morphologic features and longitudinal changes observed on high-resolution vessel wall imaging (HR-VWI) in a selected retrospective case series of patients evaluated for suspected inflammatory intracranial vasculopathy. Methods: This retrospective case series included patients who underwent 3T intracranial HR-VWI for suspected inflammatory intracranial vasculopathy. Clinical and imaging data were collected from medical records and imaging archives. Three radiologists reviewed baseline and follow-up examinations for vessel wall enhancement (VWE) pattern and grade, wall thickness, luminal narrowing, arterial distribution, diffusion-restricted lesions, and susceptibility-sensitive findings. Analyses were descriptive and patient-level. Each patient contributed one baseline and one final examination to longitudinal summaries; intermediate scans characterized individual trajectories only. Results: Nineteen patients were included, and 17 underwent serial HR-VWI. Median age was 46 years (IQR, 35.5–60.0 years), and 11 patients were female. Follow-up HR-VWI was available in 17 patients over a median of 391 days (IQR, 237–1819 days; range, 15–4034 days). VWE was present in all patients, with a purely concentric pattern in 15/19 (78.9%). The middle cerebral and internal carotid arteries were involved in 17/19 and 13/19 patients, respectively. Among the 17 patients with paired examinations, VWE grade decreased in 13 patients (76.5%) and remained stable in four patients (23.5%), with the median decreasing from 3.0 to 1.0. Maximum wall thickness decreased in 16 patients and remained stable in one, with the median changing from 2.0 mm to 1.4 mm. Conclusions: In this selected retrospective case series of patients evaluated for suspected inflammatory intracranial vasculopathy, 3T HR-VWI commonly demonstrated concentric VWE and provided descriptive longitudinal information regarding enhancement evolution. These findings should not be interpreted as evidence of diagnostic performance. Full article

Cardiovascular ultrasound is a cornerstone of noninvasive cardiac and vascular assessment, yet conventional interpretation remains operator-dependent, variable, and limited in sensitivity for subclinical disease. Artificial intelligence (AI), particularly machine learning (ML), deep learning (DL), and, most recently, vision–language and foundation models, offers tools to automate, standardize, and extend ultrasound analysis. This narrative review examines the role of AI-enhanced cardiovascular ultrasound in the transition from descriptive imaging toward predictive and personalized medicine. We conducted a structured literature search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar (January 2016–May 2026), combining Medical Subject Headings and free-text terms related to AI and cardiovascular ultrasound. Original studies, meta-analyses, reviews, consensus documents, and seminal works were considered. AI now spans the entire echocardiographic workflow, acquisition guidance, view classification, segmentation (Dice ≈ 0.92–0.94 on public datasets), and automated quantification of ejection fraction and global longitudinal strain, achieving expert-level accuracy and improved reproducibility. Across clinical domains, AI supports ischemia detection on stress echocardiography, heart-failure phenogrouping, Doppler-independent aortic stenosis detection, and carotid plaque characterization for stroke-risk stratification. Emerging vision–language and multitask foundation models (e.g., EchoCLIP, EchoPrime, and PanEcho) point toward general-purpose interpretation, and a growing number of tools (Caption Guidance, Us2.ai, and Ultromics EchoGo) have obtained FDA clearance and/or CE marking. Increasingly, AI-derived imaging biomarkers feed multimodal models that enable individualized risk prediction and therapy selection. AI-enhanced cardiovascular ultrasound is poised to become a central tool of precision cardiology. Realizing its potential will require prospective multicenter validation, cross-vendor standardization, attention to generalizability, interpretability, and reproducibility, and evolving regulatory and ethical frameworks. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a global epidemic strongly associated with an increased risk of heart failure, independent of coronary artery disease or hypertension. This condition, historically termed diabetic cardiomyopathy (DCM) and recently redefined as “diabetic myocardial disorder,” remains frequently underdiagnosed in its subclinical stages. The objective of this non-systematic review is to synthesize current evidence on the pathophysiological mechanisms, diagnostic advancements, and evolving therapeutic strategies for diabetic myocardial involvement. Methods: A comprehensive review of contemporary literature was conducted, focusing on recent consensus statements from the ESC and AHA, large-scale epidemiological data (IDF/WHO), and pivotal clinical trials (EMPA-REG, DAPA-HF, and LEADER). We analyzed the role of multimodal imaging—specifically speckle-tracking echocardiography (STE) and multiparametric cardiac magnetic resonance (CMR)—and circulating biomarkers in early phenotyping. Results: Pathophysiological drivers include lipotoxicity, oxidative stress, and AGE-mediated fibrosis. Advanced imaging techniques, such as global longitudinal strain (GLS) and CMR T1-mapping/ECV quantification, demonstrate superior sensitivity over LVEF in detecting early subendocardial dysfunction and diffuse fibrosis. Furthermore, NT-proBNP serves as a robust prognostic marker for the HFpEF-like trajectory typical of diabetes. Clinically, the therapeutic landscape has shifted with SGLT2 inhibitors and GLP-1 receptor agonists, which provide significant cardioprotection and reduction in heart failure hospitalizations through mechanisms beyond glycemic control. Conclusions: Diabetic myocardial disorder represents a complex continuum within the cardiometabolic spectrum. Early detection through multimodal imaging and biomarkers is essential for risk stratification. Integrating novel glucose-lowering therapies with proven cardiovascular benefits is now mandatory to alter the natural history of the disease and prevent progression to overt heart failure. Full article

Heart failure with preserved ejection fraction (HFpEF) represents an increasingly prevalent clinical syndrome, driven by population ageing and the growing burden of cardiometabolic comorbidities, and is associated with significant morbidity and mortality. Due to its heterogeneous pathophysiology and the frequent absence of overt structural abnormalities, early diagnosis and accurate risk stratification remain challenging. In the current era of emerging disease-modifying therapies, the identification of sensitive imaging markers able to detect early myocardial dysfunction and refine patient characterization has become increasingly important. Speckle-tracking echocardiography has emerged as a valuable tool for the comprehensive evaluation of HFpEF, allowing the assessment of subclinical myocardial impairment beyond conventional parameters. Left ventricular global longitudinal strain (LV-GLS) identifies subtle systolic dysfunction despite preserved left ventricular ejection fraction (LVEF) and provides incremental diagnostic and prognostic information. Accordingly, LV-GLS has been incorporated into contemporary diagnostic algorithms and may represent a promising marker for monitoring disease progression and therapeutic response. Beyond the left ventricle (LV), left atrial (LA) strain has gained increasing relevance as a marker of atrial myopathy and elevated filling pressures. Left atrial reservoir strain (LARS) detects early atrial dysfunction before overt structural remodelling, improves the identification of HFpEF in patients with unexplained dyspnoea, and provides additional prognostic information, including prediction of atrial fibrillation and thromboembolic risk. Moreover, right ventricular free-wall longitudinal strain (RV-FWLS) allows early recognition of right ventricular involvement and has shown important prognostic implications, particularly in relation to pulmonary vascular dysfunction and exercise intolerance. Overall, a multi-chamber strain-based approach may improve HFpEF diagnosis, phenotyping, and risk stratification, supporting a transition toward a more personalized management strategy. Further prospective studies are needed to define the role of strain imaging in guiding therapeutic decisions and monitoring treatment response. Full article

Bronchopulmonary dysplasia (BPD) remains one of the leading chronic respiratory complications of extreme prematurity despite major advances in neonatal intensive care. Current diagnostic definitions are primarily based on respiratory support requirements and provide limited information on the biological heterogeneity and longitudinal evolution of lung injury. Lung ultrasound (LUS) is progressively reshaping the clinical approach to BPD by enabling radiation-free, bedside, and repeatable assessment of peripheral lung abnormalities throughout the neonatal course. This narrative review examines the current role of LUS in BPD, integrating its pathophysiological basis with the available evidence and distinguishing explicitly between its diagnostic, prognostic, monitoring, and treatment-guiding applications, which are supported by markedly different levels of evidence. We discuss how LUS findings reflect the major components of BPD pathophysiology, compare LUS with conventional imaging modalities, and summarize the scanning protocols, semiquantitative scoring systems, examination schedules, and patient populations that have been evaluated to date. We also review the emerging contribution of artificial intelligence to automated image analysis, standardized image acquisition, and personalized risk prediction. Most of the available evidence is prognostic rather than diagnostic: early LUS scores predict BPD subsequently defined at 36 weeks’ postmenstrual age, whereas LUS has not been validated as a diagnostic test for established BPD, and reported cutoffs remain study- and protocol-specific rather than universally applicable. Randomized evidence is confined to LUS-guided surfactant administration, where the demonstrated benefits concern the timing of treatment and the need for invasive ventilation; no trial has yet shown that LUS-guided management reduces the incidence of BPD. Current evidence supports LUS as a complementary imaging modality that extends beyond the assessment of acute neonatal respiratory disease and enables longitudinal bedside monitoring of peripheral lung aeration. Although further multicenter prospective studies are required to harmonize protocols and validate LUS-guided management strategies, the integration of standardized LUS assessment with emerging artificial intelligence technologies has the potential to establish LUS as a key component of precision respiratory care for infants at risk of BPD. Full article

Background: Cardiac arrhythmias in children and adolescents may present with nonspecific symptoms such as precordial pain, palpitations, and syncope. We evaluated the clinical characteristics and rhythm findings of symptomatic pediatric patients and examined cross-sectional associations between reported symptoms and selected rhythm diagnoses, with particular attention to the diagnostic and management yield of ambulatory Holter monitoring. Because symptom timing is not always captured during diagnostic monitoring, associations between reported symptoms and detected rhythm abnormalities must be distinguished from temporal symptom–rhythm correlation and causation. Methods: We conducted an observational study of 119 children and adolescents aged 1–18 years, who were evaluated at a tertiary pediatric hospital for symptoms potentially suggestive of cardiac rhythm abnormalities. Data included demographic characteristics, clinical symptoms, personal and family history, resting electrocardiography, ambulatory Holter monitoring, and exercise testing where clinically indicated. The primary analysis was cross-sectional. Because symptom timing during ambulatory monitoring was not recorded, the study was not designed to establish temporal symptom–rhythm correlation or causality. Descriptive analyses were performed for the final 119-participant cohort. Selected symptom–rhythm associations were evaluated using the contingency table methods with odds ratios (ORs), 95% confidence intervals (CIs), and Fisher’s exact tests where appropriate. Holm’s adjustment was applied to the prespecified family of reconstructed symptom–rhythm comparisons. Results were interpreted according to both statistical evidence and effect-size precision. Results: The cohort comprised 119 participants, including 75 females (63.0%) and 44 males (37.0%). The most frequently reported symptoms were precordial pain (105/119, 88.2%), palpitations (80/119, 67.2%), and syncope or lipothymia (39/119, 32.8%). A family history of sudden cardiac death was reported by 28 participants (23.5%). Forty-two participants (35.3%) had a normal resting ECG, while 77 (64.7%) underwent ambulatory Holter monitoring. Among those undergoing Holter monitoring, 65/77 (84.4%) had rhythm abnormalities detected exclusively by ambulatory monitoring and not identified on the resting ECG. Holter findings resulted in at least one documented management change in 38/77 participants (49.4%). Management categories were not mutually exclusive and included lifestyle or activity adjustment in 21 participants, initiation of antiarrhythmic therapy in 19, medication monitoring in 19, and targeted cardiac imaging, including cardiac magnetic resonance imaging, in 5. In this cross-sectional analysis, reported syncope/lipothymia was strongly associated with the presence of complete atrioventricular block (10/39 [25.6%] versus 1/80 [1.3%]; OR 27.24, 95% CI 3.34–222.29; Fisher’s exact p < 0.001; Holm’s adjusted p approximately 0.0004). The unadjusted association between syncope/lipothymia and the WPW-labelled diagnosis did not remain statistically significant after Holm’s adjustment. No statistically significant associations were identified between syncope/lipothymia and PSVT or VT. Conclusions: In this pediatric cohort, ambulatory Holter monitoring identified rhythm abnormalities not detected on resting ECG in a substantial proportion of monitored participants and resulted in documented changes in clinical management in approximately half of those monitored. Reported syncope/lipothymia was strongly associated with the presence of complete atrioventricular block in the reconstructed cross-sectional analysis. Because symptom timing during monitoring was not recorded, these findings do not establish that the detected rhythm abnormalities caused the reported symptoms or that symptoms predict future rhythm outcomes. Further studies using prospectively defined symptom–rhythm event recording and longitudinal follow-up are needed to evaluate temporal correlation and prognosis. Full article