Development of a Precision Classification Model for Uric Acid Urinary Stones Based on Multimodal Parameters: A Multicenter Observational Study
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 1,650
- 试验地点
- 1
- 主要终点
- Accuracy of multimodal model for identifying uric acid urinary stones.
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
研究组 & 干预措施
Uric Acid Urinary Stones
Patients with urinary tract stones classified as uric acid stones based on postoperative infrared spectroscopy analysis.
干预措施: No intervention (observational study) (Other)
Non-Uric Acid Urinary Stones
Patients with urinary tract stones classified as non-uric acid stones based on postoperative infrared spectroscopy analysis.
干预措施: No intervention (observational study) (Other)
结局指标
主要结局
Accuracy of multimodal model for identifying uric acid urinary stones.
时间窗: 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.
次要结局
未报告次要终点
研究者
Jian Zhuo
Principal Investigator
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine