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NCT Number: NCT07328932

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

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.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Shanghai, Shanghai Municipality, 200000, China

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

No intervention (observational study)

Other

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.

Primary outcomes

  1. 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.

Sponsors and collaborators

Lead sponsor

Jian Zhuo

Other

Collaborators

  • Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Registry information

Official study title

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

Acronym: UAS-Model

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Jan 9, 2026
Registry last updated
Jan 9, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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