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Pediatr. Rep., Volume 18, Issue 4 (August 2026) – 2 articles

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13 pages, 1083 KB  
Article
Heterogeneous Renal Trajectories in Pediatric IgA Nephropathy: A Single-Center Experience Highlighting the Dynamic Nature of Early Disease
by John Dotis, Antonia Kondou, Vasiliki Karava, Maria Tsirevelou, Ioannis Koutras, Olympia Dadoudi, George Liapis, Despoina Tramma, Maria Stamou and Nikoleta Printza
Pediatr. Rep. 2026, 18(4), 84; https://doi.org/10.3390/pediatric18040084 (registering DOI) - 23 Jun 2026
Abstract
Background/Objectives: Pediatric IgA nephropathy (IgAN) is often considered to have a favorable early course. However, its progression is variable, and the prognostic value of histopathological classifications, such as MEST-C, remains incompletely defined in children. This study aimed to characterize clinicopathological features and the [...] Read more.
Background/Objectives: Pediatric IgA nephropathy (IgAN) is often considered to have a favorable early course. However, its progression is variable, and the prognostic value of histopathological classifications, such as MEST-C, remains incompletely defined in children. This study aimed to characterize clinicopathological features and the early disease course in pediatric IgAN and to descriptively examine histopathological findings and clinical outcomes. Methods: This retrospective, single-center study included children with biopsy-confirmed IgAN diagnosed between 2016 and 2025. Clinical, laboratory, and histopathological data were collected, and biopsies were assessed using the Oxford MEST-C classification. Follow-up data, including estimated glomerular filtration rate (eGFR), were analyzed descriptively, with follow-up extending from diagnosis to early 2026. Results: Fourteen patients were included, showing heterogeneous clinical presentations. Mesangial hypercellularity was observed in all cases (100%), with frequent endocapillary hypercellularity (78.6%) and segmental sclerosis (57.1%), consistent with a predominance of active lesions. Over a median follow-up of approximately five years, renal function remained stable in 57.1% of patients, declined in 21.4%, and improved in 14.3%, indicating variability in renal function during follow-up and potential reversibility in a subset of patients. One patient (7.1%) developed severe acute kidney injury requiring temporary dialysis, followed by full recovery. Given the descriptive design and limited sample size, no conclusions regarding associations between histopathological findings and renal outcomes can be drawn. Conclusions: Within this small cohort, pediatric IgAN showed variable renal function courses ranging from stability to decline or partial recovery. These findings should be considered descriptive and hypothesis-generating, supporting longitudinal monitoring in larger pediatric cohorts. Full article
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19 pages, 1465 KB  
Systematic Review
Markerless Motion Capture for Human Movement Estimation Using Artificial Intelligence: A Systematic Review
by Georgina Domènech-Garcia, Xavier Marimon, Andoni Carrasco-Urribarren, Alejandro E. Portela and Caritat Bagur-Calafat
Pediatr. Rep. 2026, 18(4), 83; https://doi.org/10.3390/pediatric18040083 (registering DOI) - 23 Jun 2026
Abstract
Background: Artificial intelligence (AI)-driven markerless motion capture (MMC) technologies are increasingly being integrated into pediatric healthcare to improve the assessment and management of movement disorders. These video-based systems enable non-invasive motion analysis without wearable sensors, facilitating more natural movement assessment in children, [...] Read more.
Background: Artificial intelligence (AI)-driven markerless motion capture (MMC) technologies are increasingly being integrated into pediatric healthcare to improve the assessment and management of movement disorders. These video-based systems enable non-invasive motion analysis without wearable sensors, facilitating more natural movement assessment in children, particularly those with neurological or developmental conditions. Objectives: We evaluated the clinical applicability of AI-based MMC tools in pediatric settings for diagnosis, monitoring of motor development, and rehabilitation. Methods: This systematic review was registered in PROSPERO (CRD42024511787) and conducted by two independent reviewers, with a third reviewer resolving disagreements. The literature published between 2018 and 2025 was systematically searched. Studies involving pediatric populations or clinically relevant pediatric applications of MMC were included. Results: Of 1521 identified studies, 52 were finally selected. The included studies evaluated populations across a wide age range. However, seven of the included articles were specifically focused on underage populations. Infant studies primarily analyzed whole-body movements, emphasizing the relevance of global motor patterns in early development. OpenPose and AlphaPose were the most frequently used frameworks in pediatric research because of their automatic full-body key point detection, whereas DeepLabCut was commonly selected for its customizable labeling capabilities. Theia3D emerged as a promising clinically applicable solution with high accuracy. Most studies evaluated kinematic parameters as objective markers of motor performance and development. However, methodological heterogeneity and limited pediatric-specific validation remain important limitations. Conclusions: AI-driven MMC technologies show considerable potential to support objective, accessible, and child-friendly movement assessment in pediatric clinical practice. Full article
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