ArticleUrolithiasis2020
Formula for predicting the impaction of ureteral stones.
Article in Urolithiasis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 38 citations in OpenAlex.
- Measuring and analyzing objective factors of impacted ureteral stones on Non-Contrast Computed Tomography (NCCT): a retrospective case-control study.Urolithiasis · 2026Article
- Role of ureteral wall thickness and computed tomography imaging in predicting spontaneous passage of ureteral stones.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Article
- Article
- Can ureteric stone impaction be predicted preoperatively using noninvasive parameters? A prospective study.Arab journal of urology · 2026Article
- Pathological and radiological evaluation of ureteral wall thickness measurement in urolithiasis.Urolithiasis · 2025Article
- Risk factors and prediction model for stone mucosa adhesion before retrograde intrarenal surgery.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2025Article
- Development and validation of a non-invasive nomogram for predicting proximal ureteral impacted calculi.World journal of urology · 2025Article
- Can the degree of ureteral stone impaction better predict surgical success and complications? a new classification system.BMC urology · 2025Article
- Advancing decision-making in shock wave lithotripsy for upper ureteral stones: the role of radiological stone impaction markers.Urolithiasis · 2025Article
- Predictive value of NCCT quantitative analysis for proximal and middle impacted ureteral stones.Urolithiasis · 2024Article
- Radiological signs of stone impaction add no value in predicting spontaneous stone passage.Urolithiasis · 2024Article
- Area of hydronephrosis is a useful predictive factor of impacted ureteral stones.Urolithiasis · 2024Article
- Development of a new scoring system predicting medical expulsive therapy success on 4-10 mm distal ureteral stones: medical expulsive therapy stone score (METSS).Urolithiasis · 2023Article
- Prospective observational study on the prognosis of ureteral lesions caused by impacted stones via dual-energy spectral computed tomography.Asian journal of urology · 2023Article
- A nomogram for predicting the risk of residual stone fragments after ureteroscopy.Translational andrology and urology · 2023Article
- Article
- Value of preoperative ureteral wall thickness in prediction of impaction of ureteric stones stratified by size in laser ureteroscopic lithotripsy.BMC urology · 2023Article
- The ratio of CT attenuation values of the ureter above/below ureteral stones is a useful preoperative factor for predicting impacted ureteral stones.Urolithiasis · 2022Article
- The role of inflammatory serum markers and ureteral wall thickness on spontaneous passage of ureteral stone < 10 mm: A prospective cohort study.Annals of medicine and surgery (2012) · 2022Article
- A simple predictive model with internal validation for assessment of stone-left after ureteroscopic lithotripsy in upper ureteral stones.Translational andrology and urology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of the study was to investigate variables that may predict ureteral stone impaction and create a new model to predict more accurately stone impaction based on preoperative NCCT findings. Data of 238 patients who underwent URS were analyzed. Stone size, stone location, Hounsfield unit (HU) value of the stone, ureteral wall thickness (UWT) and grade of hydronephrosis were recorded. HU values of the ureter which are measured proximal and distal to the stone were recorded. Subsequently, we determined the factors that could predict the stone impaction in univariate and multivariate logistic regression analysis. After the AUC analysis for these factors, we created a new model to predict more accurately stone impaction. The formula was named Impacted Stone Formula (ISF). Stone impaction verified endoscopically. Predictors of impacted stones were evaluated using univariate and multivariate logistic regression analyses. Diagnostic value for the prediction of stone impaction was analyzed with receiver operating characteristic (ROC) incline. Overall, there were 196 patients included in the study. Multivariate regression analysis revealed that the HU below/above ratio, UWT, and grade of hydronephrosis were the crucial predictors of stone impaction (OR 20.53, p < 0.001; OR 10.55, p < 0.001; OR 5.95, p = 0.004, respectively). The ROC analysis revealed a cutoff value of 15.15 (AUC 0.958, p < 0.001, sensitivity 91.0%, specificity 97.7%) for the ISF. In conclusion, ISF is the most precise preoperative predictor of impacted stones in patients with ureteral stones. ISF could be used by the urologists before treatment to help preoperative planning and perioperative clinical course.
Indexed as
Identifiers
What OpenQuestion holds
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.