Multicenter Study to Develop a Model to Identify Uric Acid Urinary Tract Stones Using CT and Lab Tests (UAS-Model)

January 8, 2026 updated by: Jian Zhuo

Development of a Precision Classification Model for Uric Acid Urinary Stones Based on Multimodal Parameters: A Multicenter Observational Study

Urinary tract stones are a common condition affecting the kidney, ureter, bladder, and urethra. Uric acid stones represent an important subtype of urinary stones and require different prevention and treatment strategies compared with other stone types. However, accurate identification of uric acid stones before treatment remains challenging in routine clinical practice. This multicenter observational study aims to develop and validate a precision classification model to distinguish uric acid urinary tract stones from non-uric acid stones using multimodal parameters. These parameters include patients' clinical characteristics, laboratory test results, and computed tomography (CT) imaging features. Patients undergoing surgical treatment for urinary tract stones at participating centers will be enrolled. Stone composition determined by infrared spectroscopy after surgery will be used as the reference standard. By integrating clinical, laboratory, and imaging data, this study seeks to establish a practical and reliable model to improve the classification of uric acid stones and support individualized clinical management.

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Detailed Description

This is a multicenter observational study designed to develop and validate a precision classification model for uric acid urinary tract stones based on multimodal parameters. The study will be conducted at multiple hospitals in China and will include adult patients undergoing surgical treatment for urinary tract stones involving the kidney, ureter, bladder, or urethra. Clinical data, laboratory parameters (including serum and urine biochemical indices), and CT imaging features will be collected before treatment according to standardized protocols. Stone composition determined by postoperative infrared spectroscopy will serve as the reference standard, with uric acid stones defined based on established compositional criteria. The study population will be divided into training and validation cohorts. Multivariable statistical modeling will be used to identify independent predictors of uric acid stones and to construct a prediction model. Model performance will be evaluated using discrimination, calibration, and clinical utility analyses. The results of this study are expected to provide a clinically applicable tool for more accurate classification of uric acid urinary tract stones, which may facilitate individualized prevention strategies and treatment decision-making in patients with urinary stone disease.

Study Type

Observational

Enrollment (Estimated)

1650

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Shanghai Municipality
      • Shanghai, Shanghai Municipality, China, 200000
        • Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

The study population consists of adult patients with urinary tract stones who undergo surgical treatment at participating centers. Eligible participants include patients with kidney, ureteral, bladder, or urethral stones, with available clinical information, laboratory test results, computed tomography imaging, and postoperative stone composition analysis.

Description

Inclusion Criteria:

  • Patients with a confirmed diagnosis of urinary tract stones, including kidney stones, ureteral stones, bladder stones, or urethral stones.
  • Patients who undergo surgical treatment for urinary tract stones at participating centers during the study period, including ureteroscopy or flexible ureteroscopy lithotripsy, percutaneous nephrolithotomy, pyelolithotomy or ureterolithotomy, or transurethral cystolithotripsy.
  • Patients whose stone composition is determined by postoperative infrared spectroscopy analysis.

Exclusion Criteria:

  • Patients with multiple stones or stones located at multiple sites, such as multiple renal stones or concomitant kidney and ureteral stones, to avoid discrepancies between computed tomography measurements of the target stone and stone composition analysis.
  • Pregnant or breastfeeding women.
  • Patients younger than 18 years of age.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Uric Acid Urinary Stones
Patients with urinary tract stones classified as uric acid stones based on postoperative infrared spectroscopy analysis.
Other: No intervention (observational study)
This is an observational cross-sectional study. Participants are not assigned to any intervention as part of the study. All clinical management, imaging examinations, and laboratory tests are performed as part of routine clinical care.
Non-Uric Acid Urinary Stones
Patients with urinary tract stones classified as non-uric acid stones based on postoperative infrared spectroscopy analysis.
Other: No intervention (observational study)
This is an observational cross-sectional study. Participants are not assigned to any intervention as part of the study. All clinical management, imaging examinations, and laboratory tests are performed as part of routine clinical care.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy of multimodal model for identifying uric acid urinary stones.
Time Frame: Perioperatively
The primary outcome is the diagnostic performance of a multimodal classification model for identifying uric acid urinary tract stones. The model integrates clinical characteristics, laboratory parameters, and computed tomography imaging features. Stone composition determined by postoperative infrared spectroscopy is used as the reference standard. Model performance will be evaluated using discrimination metrics such as the area under the receiver operating characteristic curve.
Perioperatively

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Jian Zhuo

Collaborators

Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Investigators

  • Principal Investigator: Jian Zhuo, PhD, Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 20, 2025

Primary Completion (Estimated)

August 20, 2027

Study Completion (Estimated)

October 20, 2027

Study Registration Dates

First Submitted

December 12, 2025

First Submitted That Met QC Criteria

January 8, 2026

First Posted (Actual)

January 9, 2026

Study Record Updates

Last Update Posted (Actual)

January 9, 2026

Last Update Submitted That Met QC Criteria

January 8, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • IIT2025-087 (Other Grant/Funding Number: Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Individual participant data will not be shared because the study involves multicenter clinical data containing sensitive personal and imaging information. Data sharing is restricted by institutional policies, ethical approvals, and data protection regulations.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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