ReviewFrontiers in pediatrics2025
New advances in efficacy prediction of extracorporeal shock wave lithotripsy in pediatrics: a narrative review.
Review in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Genetic evidence for potential causal associations between gut microbiota and site-specific urolithiasis risk: a two-sample mendelian randomization study.Urolithiasis · 2026Article
- Optimizing pediatric shock wave lithotripsy: stepwise energy escalation vs. conventional fixed energy.Frontiers in pediatrics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Extracorporeal Shock Wave Lithotripsy (ESWL) has been a cornerstone in treating pediatric urinary stones for nearly four decades, but requires tailored approaches due to anatomical and physiological differences from adults. This review synthesizes current evidence on ESWL efficacy predictors in children, integrating multicenter data and emerging technologies. Key traditional predictors include favorable stone characteristics [density ≤600 Hounsfield units [HU], size ≤15 mm, skin-to-stone distance [SSD] ≤6.6 cm, upper/middle calyx or ureteral location] and patient factors (age ≤3 years, male sex); conversely, urinary tract infections (UTIs), BMI >22, and multiple stones correlate with poorer outcomes. Innovations like dual-energy CT (DECT), AI-based models, shear wave elastography (SWE), and bioelectric impedance analysis (BIA) offer promising non-invasive preoperative assessment. We highlight the need for standardized multifactorial predictive models to optimize pediatric ESWL outcomes. Future directions emphasize AI, big data, and multidisciplinary collaboration to enhance personalized treatment and reduce complications. This analysis provides clinicians with evidence-based tools to refine pediatric ESWL protocols.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.