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Prospective validation of an artificial intelligence diagnostic model for urothelial carcinoma based on urine cytology

Prospective validation of an artificial intelligence diagnostic model for urothelial carcinoma based on urine cytology

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300073192
Enrollment
Unknown
Registered
2023-07-04
Start date
2023-07-07
Completion date
Unknown
Last updated
2023-07-10

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

Conditions

urothelium carcinoma

Interventions

Gold Standard:postoperative histopathological diagnosis and follow-up result
Index test:urine cytology artificial intelligence diagnosis

Sponsors

Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: (1) Age greater than 18 years old; (2) Able to understand the purpose of this clinical trial and sign an informed consent form; (3) Well-prepared and stained slides, clear microscopic observation and scanning, clear and high-quality images; (4) Patients with symptoms of hematuria (intermittent, painless gross hematuria and microscopic hematuria) or bladder irritation (frequency, urgency, dysuria) who have undergone outpatient or inpatient examination; (5) Patients with a history of urothelial carcinoma, recurrence symptoms, and preoperative examination or postoperative outpatient follow-up; (6) Patients undergoing cystectomy or secondary transurethral resection of bladder cancer before surgery; (7) Patients with or without lower urinary tract symptoms undergoing physical examination screening and further examination.

Exclusion criteria

Exclusion criteria: (1) Participants who request to withdraw from this clinical trial midway; (2) Incomplete clinical criteria diagnostic information or inability to obtain a clear diagnostic result; (3) Urine cytology results showing high-grade urothelial cells or suspected high-grade urothelial cells, lacking postoperative pathological results or postoperative negative pathology; (4) Severe fading of slides affecting diagnostic efficacy; (5) Poor imaging quality of scanned images, out of focus and unclear images.

Design outcomes

Primary

MeasureTime frame
Accuracy;sensitivity;Specificity;Positive predictive value;Negative predictive value;

Countries

China

Contacts

Public ContactLin Tianxin

Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University

lintx@mail.sysu.edu.cn+86 137 2400 8338

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 8, 2026