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Machine Learning-Based Predictive Modeling for Gastrointestinal Polyp Recurrence in Pediatric Peutz-Jeghers Syndrome

Machine Learning-Based Predictive Modeling for Gastrointestinal Polyp Recurrence in Pediatric Peutz-Jeghers Syndrome

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500103932
Enrollment
Unknown
Registered
2025-06-09
Start date
2025-06-09
Completion date
Unknown
Last updated
2025-06-16

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

Conditions

Peutz-Jeghers Syndrome

Interventions

Polyp recurrence group/non-recurrence group:None

Sponsors

Xi'an Children's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 15 Years

Inclusion criteria

Inclusion criteria: 1. Children diagnosed with PJS according to the diagnostic criteria of the Expert Consensus on the Diagnosis and Treatment of Peutz-Jeghers Syndrome in Small Enteroscopy in China (2022); 2. Age 0-15 years old; 3. Improve gastrointestinal endoscopy

Exclusion criteria

Exclusion criteria: 1. Children with gastrointestinal tumors excluded; 2. Children with too many variables with missing data were excluded

Design outcomes

Primary

MeasureTime frame
Polyp recurrence;—

Countries

China

Contacts

Public ContactShiqiu Xiong

Xi'an Children's Hospital

xsq20180224@163.com+86 157 7312 9322

Outcome results

None listed

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