ReviewCentral European journal of urology2014
Predicting stone composition before treatment - can it really drive clinical decisions?
Review in Central European journal of urology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Prediction models of low-power holmium laser effectiveness in renal stone lithotripsy during retrograde intrarenal surgery.Lasers in medical science · 2022Article
- Correlative investigation between routine clinical parameters of dual-energy computed tomography and the outcomes of extracorporeal shock wave lithotripsy in children with urolithiasis: a retrospective study.Abdominal radiology (New York) · 2021Article
- Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy.BMC urology · 2020Article
- Article
- A stone pushed back to the collecting system - long therapeutic path in centers with limited access to flexible instruments.Central European journal of urology · 2018Article
- Stone heterogeneity index on single-energy noncontrast computed tomography can be a positive predictor of urinary stone composition.PloS one · 2018Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDetermination of stone composition is considered to be crucial for the choice of an optimal treatment algorithm. It is especially important for uric acid stones, which can be dissolved by oral chemolysis and for renal stones smaller than 2 cm, which can be treated with extracorporeal shockwave lithotripsy (ESWL). MATERIAL AND
methodsThis short review identifies the latest papers on radiological assessment of stone composition and presents a comprehensive evaluation of current scientific findings.
resultsStone chemical composition is difficult to predict using standard CT imaging, however, attenuation index measured in Hounsfield units (HU) is related to ESWL outcome. Stone density >1000 HU can be considered predictive for ESWL failure. It seems that stone composition is meaningless in determining the outcome of ureterolithotripsy and percutaneous surgery. Alternative imaging techniques such as Dual-Energy CT or analysis of shape, density and homogeneity of stones on plain X-rays are used as promising methods of predicting stone composition and ESWL outcome.
conclusionsNew imaging techniques facilitate the identification of uric acid stones and ESWL-resistant stones. Therefore, they may help in selecting the best therapeutic option.
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Registered trials
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