Archivio Istituzionale della Ricerca - Università degli Studi della Campania "Luigi Vanvitelli"
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Investigations for diagnosis of secondary hypertension in children: yield and costs
No full textBackground: Screening for secondary hypertension is not recommended for all hypertensive patients, but missing these cases is critical. We aimed to (i) assess hypertension causes in a cohort of hypertensive children, (ii) determine the costs and contributions of an extended diagnostic work-up to screen for secondary hypertension, and (iii) compare the performance of a “short diagnostic work-up” with the protocols of the American Academy of Pediatrics (AAP) and European Society of Hypertension (ESH). Methods: We conducted a retrospective, single-center study of 70 hypertensive patients aged 1–18 years. All underwent an extended work-up to exclude secondary hypertension. Diagnostic findings, test counts, and costs were analyzed. A short work-up (serum creatinine, fasting glucose, electrolytes, urinalysis, kidney ultrasound (US), and renal artery Doppler US), as well as the AAP and ESH protocols, was evaluated for performance and costs. Results: Secondary hypertension was identified in 29 patients (41.4%). The extended protocol identified or excluded secondary causes in all patients. Kidney US had the highest diagnostic yield (37.1%). The short work-up and ESH protocol identified all secondary cases, whereas the AAP protocol missed 15 diagnoses. The extended protocol cost € 17,715.60 (€ 253.08 per patient). Direct cost savings were 64.3% with the short work-up, 92.4% with the AAP protocol, and 76.2% with the ESH protocol. Conclusions: Primary is more common than secondary hypertension in children, with kidney parenchymal disease being the leading secondary cause. As recommended by guidelines, a simplified, focused work-up may offer a cost-effective alternative to extensive screening while maintaining diagnostic accuracy
Liver-Kidney Crosstalk in Major Pediatric Diseases: Unraveling the Complexities and Clinical Challenges
No full textThe liver and kidneys are two of the most vital organs, each with distinct but overlapping functions essential for maintaining homeostasis. The complex interplay between these organs, commonly referred to as liver-kidney crosstalk, plays a crucial role in the pathophysiology of several acute and chronic conditions in childhood. Despite its importance, the precise biological mechanisms driving this interaction remain incompletely understood. This crosstalk is particularly significant in various pediatric diseases (e.g., Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), Hepatorenal Syndrome (HRS), genetic and metabolic disorders, etc.) where shared pathophysiological factors—including systemic inflammation, metabolic disturbances, oxidative stress, and vascular dysfunction—simultaneously affect both organs. Clinically, this interaction presents unique challenges in diagnosing, managing, and treating liver-kidney diseases in affected children. Understanding the pathogenic mechanisms underlying liver-kidney crosstalk is essential for improving patient care and outcomes through an integrated, multidisciplinary approach and personalized treatment strategies. This review aims to explore liver-kidney crosstalk in key pediatric diseases, offering a comprehensive overview of current knowledge, clinical challenges, and potential therapeutic interventions in this complex field
Resilience or decline? Insights from long-term sap flow and wood anatomy monitoring in fire-damaged Pinus pinaster Aiton forest
No full textWildfires represent a major disturbance in Mediterranean forests, often triggering long-term functional decline in surviving trees. Understanding the hydraulic and eco-physiological trend of fire-affected stands is essential to assess whether trees are on a recovery path or progressing toward irreversible decline. In this study, we combined four years of continuous sap flow monitoring with wood anatomical analyses and satellite observations in a Mediterranean pine forest severely affected by fire. Continuous measurements in burned and control trees revealed contrasting transpiration strategies and progressive divergent pattern of hydraulic performance under recurrent drought conditions. Burned trees initially increased transpiration as a compensatory response but gradually exhibited signs of functional impairment, including reduced hydraulic efficiency, altered xylem traits, and limited canopy recovery. Further, remote sensing highlighted persistent canopy degradation and the spread of invasive vegetation, exacerbating water competition and accelerating decline. Control trees, by contrast, maintained a conservative water-use strategy and showed a greater capacity to exploit favorable climatic periods. These findings highlight the vulnerability of fire-damaged forest stands to eco-physiological decline, with potential implications for delayed mortality. The integration of long-term sap flow, wood anatomy, and satellite monitoring emerges as a powerful approach for detecting early-warning signals of resilience loss and informing post-fire forest management in drought-prone ecosystems
NEW ADVANCED FASHION PERSPECTIVES A comparison of knowledge and practices in the digital age
No full textThe article presents two research projects which, although operating with different
methodologies, work in a common field and with complementary tools. The aim
is to illustrate how different approaches can interact and give rise to co-production
processes, generating reasoning about the state of the art in the fashion sector
and how it is evolving. The analysis focuses on the new skills required of fashion
designers, the integration of artificial intelligence as a support tool, and the impact
of innovations in the sector. In particular, it highlights how new technologies
and digital devices not only encourage shared production among the various
“players” in the sector, but also act as catalysts. New creative and productive
scenarios are emerging that enrich, speed up, and innovate the design process
of the Fashion System. While on the one hand it illustrates some of the methods
for identifying professional figures, focusing mainly on some of the activities
that take place in the style office, on the other hand it analyses the impact of AI
in the contemporary scenario, with particular attention to its role
in the development of the creative project. Through the description of distinct
approaches and methodologies that emerged from the analysis of a joint case
study developed during the doctoral programme, the aim is to stimulate new
reflections in the scientific community on the role, relationships and tools
of the designer. The objective is to outline the relationship between the fashion
designer, emerging digital technologies and co-design activities. The dialogue
between doctoral students on these recent issues opens up new perspectives
and research ideas, encouraging the sharing of knowledge and practices
that promote an increasingly collaborative approach. A co-creation environment
capable of generating innovation in the fashion sector through
the creation of extensive networks connecting institutions with businesses in Italy.
Mapping has been used as an analytical tool to represent in a structured way
the relationships between the various professionals working in the fashion
industry, highlighting how the introduction of digital tools and emerging
technologies, including artificial intelligence, affects the processes of defining,
developing and managing a collection project. The success of the experiment opens
up new perspectives for fashion design, raising critical questions about the impact
of artificial intelligence in ethical and creative terms, as well as the transformations
it brings about in manufacturing processes and in the dynamics of interaction
between professionals in the sector. In a constantly evolving context, adopting
a broad vision and investing in people and tools is essential for the future
of Made in Italy
Advanced design conference 2025 proceedings. World design intelligence summit
No full textPeer-reviewed conference proceedings containing academic papers, research presentations and design innovations from the Advanced Design Conference 2025, part of the World Design Intelligence Summit. Features contributions from researchers, practitioners and policymakers across 8 thematic tracks bridging design theory, practice and governance
120. Anton Raphael Mengs, Preparatory study for the Parnassus, 159-1760, black chalk on laid paper, Barcelona, Museu Nacional d'Art de Catalunya
No full textLarge language models performance on pediatrics question: a new challenge
No full textBackground: This study investigates the application and efficacy of large language models (LLMs) in pediatric medicine, focusing on their capability to assist in training and decision support for healthcare professionals. Given the unique challenges in pediatric care, such as age-specific conditions and dosing requirements, we aim to evaluate the performance of various LLMs in this specialized field. Methods: We conducted a comparative analysis of several LLMs, including Claude 3-OPUS, ChatGPT 3.5 and 4, Gemini AI, Llama 2 70B, and Mixtral 8x7B. The models were tested on 227 multiple-choice pediatric questions in Italian before and after undergoing specialized training. The training data consisted of pediatric articles from a medical journal, ensuring compliance with HIPAA regulations by using de-identified and anonymous data. Results: The performance of the LLMs varied significantly. ChatGPT 3.5 improved from 65.20% to 83.70% accuracy (P<0.01) after training, while ChatGPT 4 increased from 77.09% to 91.62% (P<0.01). Gemini 1.0 and Mixtral 8x7B recorded accuracies of 70.48% and 71.37% respectively, both showing significant improvements post-training. Llama 2 70B had a lower performance, improving from 47.58% to 52.86%. Claude 3-OPUS demonstrated robust performance with an 82.82% accuracy pre-training, improving to 95.59% post-training. Conclusions: Our analysis confirms the effectiveness of LLMs in pediatric medicine, highlighting their potential in training and decision support. The study emphasizes the need for specific training datasets that reflect the complexities of pediatric conditions to tailor the models accurately. Moreover, there is a significant opportunity to utilize open-source models as a foundation for developing customized systems through training on dedicated datasets. These strategies promise to enhance the accuracy and accessibility of pediatric healthcare, ultimately improving outcomes for young patients