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A Clinical Study on Predicting Infection Load of Urinary Calculi Based on CT Imaging Features

Construction and Clinical Validation of a CT Radiomics-Based Prediction Model for Bacterial Load in Urinary Calculi

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600129597
Enrollment
Unknown
Registered
2026-08-06
Start date
2026-09-01
Completion date
Unknown
Last updated
2026-08-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Urolithiasis, Urinary Tract Infection

Interventions

Model Validation Cohort:NA
Model Construction Cohort:NA

Sponsors

Fuzhou University Affiliated Provincial Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: 1.Aged 18 to 75 years old with signed informed consent; 2.Confirmed as having upper urinary calculi by urinary system CT; 3.Scheduled for minimally invasive stone removal surgery such as PCNL or RIRS, with complete preoperative CT images and postoperative stone specimens available;

Exclusion criteria

Exclusion criteria: 1.Complicated with other diseases such as urinary system malformation, stenosis, tumor, or tuberculosis; 2.Incomplete preoperative CT images or unavailable/contaminated postoperative stone specimens; 3.Pregnant women, patients with severe liver and renal dysfunction, coagulation disorders, or those with missing clinical data;

Design outcomes

Primary

MeasureTime frame
AUC, sensitivity, specificity and accuracy of the prediction model;

Secondary

MeasureTime frame
Incidence of postoperative infection and sepsis;Bacterial load, endotoxin level and biofilm content in urinary calculi;

Countries

China

Contacts

Public ContactZesong Yang

Fuzhou University Affiliated Provincial Hospital

33320298@qq.com+86 591 88618618

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Aug 25, 2026