Evidence map›Paper›PMID 41402801›Full record

ArticleBMC urology2025

Applying urinary ultrasound combined with CT to predict the risk of spontaneous ureteral stone passage.

MingBin Xu, YunPeng Wei, JiaWen Zhao, ShuMing He, ChengYang Li

Abstract read
In one paragraph

Article in BMC urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

MingBin XuDepartment of Urology, The Second Affiliated Hospital of Hainan Medical University, Hainan, China.
YunPeng WeiDepartment of Urology, The Second Affiliated Hospital of Hainan Medical University, Hainan, China.
JiaWen ZhaoDepartment of Urology, The First Affiliated Hospital of Guangxi Medical University, Guangxi, China.
ShuMing HeDepartment of Urology, The Second Affiliated Hospital of Hainan Medical University, Hainan, China. heshuming163@sina.com.
ChengYang LiDepartment of Urology, The First Affiliated Hospital of Guangxi Medical University, Guangxi, China. assheep@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to develop a comprehensive predictive model for spontaneous stone passage (SSP) by integrating parameters from urinary ultrasound, non-contrast computed tomography (NCCT), and clinical markers.

methodsThis retrospective cohort study included 303 patients with unilateral solitary ureteral stones (≤10 mm) who underwent both ultrasound and NCCT before conservative management between July 2023 and July 2025. Demographic, clinical, ultrasound, and NCCT parameters were recorded. Patients were followed for one month to assess SSP (NCCT-confirmed expulsion) versus failure. Univariate and multivariable logistic regression analyses were performed, and model performance was evaluated using receiver operating characteristic (ROC) curves, calibration analysis, and decision curve analysis (DCA).

resultsOf the 303 patients, 191 achieved SSP and 112 failed. Independent predictors of SSP included stone location (middle/lower vs. upper ureter), smaller transverse stone diameter, thinner ureteral wall thickness (UWT), higher ureteral jet frequency (UJF), and greater stone-side ureteral jet velocity (all p < 0.05). The integrated model achieved an AUC of 0.829, outperforming NCCT (0.694) and ultrasound (0.774). Calibration and decision curve analyses (DCA) confirmed good agreement and clinical utility.

conclusionsCombining ultrasound and NCCT parameters significantly improved prediction of SSP compared with single-modality approaches. This model enables individualized risk stratification, supporting clinical decision-making to reduce unnecessary interventions and optimize outcomes.

Indexed as

Tomography, X-Ray ComputedUreteral CalculiAdultAgedCohort StudiesFemaleHumansMaleMiddle AgedPredictive Value of TestsRemission, SpontaneousRetrospective StudiesRisk AssessmentUltrasonographyNon-contrast computed tomographyPrediction modelSpontaneous stone passageUreteral stonesUrinary ultrasound

Identifiers

PMID41402801
PMCPMC12709743

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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.