Stijn Verhulst

Introduction: Endothelial dysfunction is an early, reversible marker of cardiovascular disease that can already be detected in childhood. EndoPAT (endothelial peripheral arterial tonometry) provides a noninvasive and operator-independent assessment of endothelial function, but pediatric reference values are not established. By pooling EndoPAT-derived data from existing studies in healthy children, this meta-analysis aims to derive normative values and to evaluate the influence of age, sex, and body mass index (BMI) on endothelial function. Methods: PubMed, Web of Science, and EMBASE were searched up to April 2026 for studies reporting EndoPAT measurements in healthy children aged 5–18 years. Data on study characteristics, participant demographics, and vascular parameters were extracted. Pooled estimates were calculated using random-effects models and meta-regression explored effects of age, sex, and BMI. The study protocol was registered in the PROSPERO database (CRD42025643846). Results: From 8573 records, 54 studies including 3555 healthy children (13.5 ± 2.5 years) were analyzed. The pooled mean reactive hyperemia index (RHI) was 1.73 (95% CI: 1.66–1.81), and meta-regressions showed that RHI increased with age and BMI, with no significant association observed with sex. Conclusion: This meta-analysis demonstrates that adult-derived RHI cutoffs for endothelial dysfunction are not applicable to children. Vascular function during childhood is influenced by age, pubertal stage, and BMI. Therefore, low RHI values in children likely reflect ongoing microvascular maturation rather than true endothelial dysfunction. These findings support the use of pediatric reference values for RHI and highlight the need for standardized pediatric EndoPAT protocols, as well as longitudinal studies to establish normal developmental trajectories and to identify early clinically relevant deviations.

Air pollution poses a major health risk, particularly in children, who spend considerable time in school. We monitored air pollution in school environments and investigated its impact on cardiovascular and neurocognitive outcomes. Seven elementary schools in Antwerp, Belgium, including one open-air school, participated in a longitudinal study. Indoor and outdoor particulate matter (PM) and outdoor NO₂ concentrations were measured. Endothelial function and attentional outcomes were assessed repeatedly (n = 3) in 138 healthy children (mean age of 10.3 ± 0.5 years, 55.8% male). Mixed effect models were used to investigate the association between PM and NO₂ exposure and endothelial and attentional outcomes. This study considered median PM concentrations during the 4 h of the study visits (direct exposure), those during the 24 h (acute exposure) and 1 week preceding the study visits (recent exposure), and monthly NO₂ concentrations. Models were adjusted for sex, age, BMI-z, and visit. Increased direct (4 h) indoor PM exposure was associated with reduced microvascular dilatation, while selective and sustained attention improved with direct and recent PM exposure, respectively. No associations were found with NO₂. Exclusion of the open-air school slightly altered the findings. Larger longitudinal studies with improved exposure assessment are needed to clarify the effects of PM exposure and the influence of (open-air) school environments on children’s learning and development.

Vaccine hesitancy (VH) for childhood immunizations has been widely studied, but no review has synthesized evidence across Europe. This review addresses that gap using both qualitative and quantitative perspectives. A systematic search on February 5th, 2025, was conducted in MEDLINE/PubMed and Web of Science to assess the generalizability of findings regarding parental VH regarding childhood vaccinations (excluding HPV and Influenza) across the WHO European Regions. Forty-nine articles published between January 2015 and December 2024 in English, Dutch or French were included. Using WHO’s 3C model (confidence, convenience, complacency), trust in healthcare professionals (HCPs) emerged as a key factor, while fear of side effects, logistical barriers and low perceived disease risk negatively influenced decisions. Demographic determinants were not generalizable across countries due to methodological and contextual (cultural, socioeconomic and healthcare system) differences, reinforcing the need for tailored approaches. VH remains multidimensional and context-dependent. WHO’s 3C model is a useful tool for understanding VH. Tailored, country-specific strategies are needed, with strong HCP – caregiver relationships and policies addressing practical and socioeconomic barriers to ensure equitable access to childhood vaccination.

Extract In 2024, the European Respiratory Society (ERS) launched a Clinical Research Collaboration (CRC), iDREAM, dedicated to the diagnosis and management of sleep disordered breathing (SDB) in children less than 2 years of age [1, 2]. This CRC aims to address the lack of standardisation in diagnosis and management, in a context where SDB in infants – whether obstructive or central – remains under-recognised despite representing a significant health burden. It seeks to provide clinicians with a better understanding of its epidemiology, natural evolution, and overall impact – cognitive, developmental, metabolic and cardiovascular – in children aged under 2 years of age. This ambitious project will leverage international collaborations, build upon a newly created shared database, and harness digital innovations to foster research, harmonise practices, and ultimately improve outcomes for this vulnerable population. This initiative unites leading experts in paediatric sleep medicine, neonatology, pulmonology, otorhinolaryngology and neurology, together with parents of affected children, and is supported by the paediatric sleep, sleep disordered breathing and chronic respiratory failure group of ERS Assembly 7. Shareable abstract Sleep disordered breathing in children under 2 years remains understudied, and poorly standardised. CRC iDREAM aims to close this gap by building a research network, shared database, and AI-driven tools, while promoting education and knowledge exchange. https://bit.ly/4caQvJW

Background: Cystic fibrosis (CF) is an autosomal recessive inherited chronic disorder that predisposes adults to gastrointestinal malignancies. The latter has not been observed in children, perhaps due to the limited documentation of the copresentation of childhood cancer in CF. The following review will provide a comprehensive overview of the relevant literature on this subject. Methodology: The objective of this study was to identify cases in Belgium over a 25‐year period and to review the literature for similar cases. Our secondary objective was to identify areas of attention during oncological management based on the clinical cases and extant literature. Results: Four cases were diagnosed in Belgium and a further 10 cases were identified in the literature. These fourteen cases exhibited a 1:1 male‐to‐female ratio. Four cases were hematological malignancies, and 10 cases were solid tumors, predominantly neuroblastomas and osteosarcomas. No specific age group predominated at the time of diagnosis of the malignancy. As the literature indicated that organs were at risk in all systems, at increased risk for treatment toxicities, and a need for increased nutritional and antimicrobial support. The threshold for intervention with supportive care should be substantially lower than in non‐CF patients. These patients are predisposed to an increased risk for premature morbidity and mortality. Conclusion: Short and long‐term CF‐specific survivorship care plans should be developed based on both disease entities in anticipation of compounded risks for early cardio‐respiratory disease and an increased awareness of secondary cancer screening. Research into the copresentation of these diseases should be promoted.

Background: Artificial intelligence (AI) has advanced rapidly in adult sleep medicine, but its role in children under 2 years old remains unclear. This scoping review maps the current evidence on AI-enabled diagnostics in neonates, infants and toddlers, identifying challenges, opportunities and research priorities. Methods: A structured scoping review was undertaken up to April 2025, incorporating peer-reviewed studies, normative datasets, regulatory reports and evidence on consumer and commercial technologies. Studies focusing on children under 2 years were prioritised, with older cohorts reviewed where relevant to translation. Findings: No AI tool is validated for independent diagnostic use in this age group. Research prototypes, including automated polysomnography scoring, convolutional neural networks for oximetry and multimodal wearable or radar-based systems, show feasibility but remain experimental. Commercial platforms such as SleepImage, Belun Sleep Health and WatchPAT exclude children under 2 years, while consumer monitors including Owlet, Nanit and Miku are widely used but lack clinical validation. Conclusion: AI in sleep diagnostics for children under 2 years remains an emerging field with high potential but no current clinical readiness. Progress will depend on the development of infant-specific datasets, improved artefact handling, simplified monitoring strategies and human-in-the-loop workflows. Longer-term opportunities include prognostic modelling, circadian analysis and predictive closed-loop systems, but equity and regulatory clarity must guide translation to ensure safe and globally relevant impact.

Computer-aided lung sound analysis (CALSA) paired with digital auscultation provides a cheap, objective, and non-invasive measurement option for healthcare providers. An important task of CALSA algorithms is the detection of the inspiration and expiration breathing phases. In this work, we propose a system that uses a deep learning model to predict the inspiration and expiration phases from a Mel-spectrograms of the lung sound. Multiple convolutional neural networks are investigated alongside vision transformer architectures. Due to the absence of standardized metrics for the evaluation of breathing cycle detection systems, we propose a novel intersection-over-union (IoU) score in order to provide a thorough evaluation. Our final system obtained a duration weighted mean IoU score of 0.82 and an F1 score of 80% for cycle-based detection. Moreover, we demonstrate that the performance of our system is on par with the cycle-labelling performance of respiratory experts and surpasses the performance of other comparable methods. The proposed system was trained, validated, and tested on diverse datasets with a respective 591 minutes, 66 minutes and 146 minutes of respiratory recordings.

The sphingolipidoses Fabry disease, Gaucher disease and Acid sphingomyelinase deficiency (ASMD) are the three most common lysosomal storage diseases for which treatment is currently available. Timely diagnosis with estimation of the disease severity and possibilities of follow-up of patients, whether or not under therapy, is crucial for providing good care and for the prevention of possible lethal complications. With this research we provide an efficient and sensitive detection method; its implementation in clinical practice could optimize the diagnosis and follow-up of patients with Gaucher, Fabry and ASMD. This detection method on dried blood spots (DBS) was validated according to the international Clinical and Laboratory Standards Institute (CLSI) guidelines, looking at reproducibility, linearity, carry-over and lower limit of quantification. Analogously, validation and subsequent comparison of the method validation results using another matrix, the Capitainer blood sampling cards (Capitainers), was fulfilled. The results showed that this detection method is fully applicable clinically when using DBS as well as Capitainers. In addition, even additional improvements of some validation parameters were found when using the Capitainers. Twenty-six patient samples and fifteen healthy samples were analyzed for case finding control. All patient cases were detected without ambiguity. We present a high-resolution mass spectrometry method that provides an accurate analysis for targeted screening, aiming for improved/accelerated diagnosis when added in the diagnostic pathway and monitoring of Fabry, Gaucher and ASMD in DBS as well as in Capitainers, with the main advantages of a small volume of blood samples, guaranteeing stability and easy transportation from the collection site to the laboratory.

Background: Excessive drinking among adolescents in Western Europe is prevalent, posing significant health risks and societal costs. Comprehensive data on adolescent drinking patterns is crucial for developing effective prevention strategies. Data on alcohol intoxication among adolescents provide valuable insights in this context. Methods: To gain insight into the demographic and clinical characteristics of acute alcohol intoxication (AAI) across European countries, we analysed emergency department data on AAI among adolescents (aged 14–17) from 2015 to 2023 in three urban regions: Genoa (Italy), Delft (the Netherlands) and Antwerp (Belgium). Results: Out of 1826 admissions, Belgium had the highest median annual admission rate (51 per 10 000 adolescents), followed by the Netherlands (49 per 10 000) and Italy (37 per 10 000). The median age of patients was 16 years across all countries. Sex was equally distributed among Dutch patients; however, in Italy (not statistically significant, 55.6%) and Belgium (statistically significant, 56.8%), more males were admitted. The median blood alcohol concentration (BAC) was higher in the Netherlands (2.00 g/L) compared with Italy and Belgium (1.84 g/L and 1.97 g/L, respectively). This difference remained statistically significant after adjusting for confounders in a multiple linear regression model on BAC. Finally, the proportion of patients with combined drug use (10.4% of the total population) was similar across the three countries. Conclusions: This is the first international study to consolidate data on AAI in minors from multiple countries, emphasising the need for a unified European database on AAI in adolescents to enhance prevention efforts.