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Development and Validation of a Machine Learning Model for Predicting Urosepsis Risk After Ureteroscopic Lithotripsy: A Retrospective Multicenter Study

Development and Validation of a Machine Learning Model for Predicting Urosepsis Risk After Ureteroscopic Lithotripsy: A Retrospective Multicenter Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500107022
Enrollment
Unknown
Registered
2025-08-01
Start date
2025-08-01
Completion date
Unknown
Last updated
2025-08-18

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

Conditions

Ureteral stone

Interventions

Observation group:None

Sponsors

Deyang People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Meeting the diagnostic criteria for ureteral stones outlined in the Chinese Guidelines for Diagnosis and Treatment of Urological and Andrological Diseases (2019 Edition); 2.Confirmed surgical indications with no contraindications for ureteroscopic lithotripsy; 3.Patients aged >=18 years; 4.All operating surgeons underwent standardized training and competency assessment;

Exclusion criteria

Exclusion criteria: 1.Patients with comorbid malignancies or immune-compromising conditions; 2.Patients receiving antibiotics for non-urinary infections prior to ureteroscopic lithotripsy; 3.Patients with preoperatively diagnosed sepsis prior to ureteroscopic lithotripsy; 4.Patients undergoing concomitant procedures with ureteroscopic lithotripsy; 5.Patients developing fever or septic shock due to non-urological infections following ureteroscopic lithotripsy;

Design outcomes

Primary

MeasureTime frame
Develop urosepsis;

Countries

China

Contacts

Public ContactJunlian Xiang

Deyang People's Hospital

1256556311@qq.com+86 28 2418 1107

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026