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Development of artificial intelligence based prediction model of postoperative pancreatic fistula and comparison of various prediction models

Development of artificial intelligence based prediction model of postoperative pancreatic fistula and comparison of various prediction models

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0008156
Enrollment
1333
Registered
2023-02-03
Start date
2021-11-04
Completion date
Unknown
Last updated
2023-02-08

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

Conditions

None listed

Interventions

None listed

Sponsors

Asan Medical Center
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: The patients who underwent pancreaticoduodenectomy for various periampullary disease between 2012 and 2018

Exclusion criteria

Exclusion criteria: The patients who underwent total pancreatectomy, distal pancreatectomy, and enucleation

Design outcomes

Primary

MeasureTime frame
Diagnostic performance of prediction for pancreatic fistula—

Secondary

MeasureTime frame
New clinical factors related with pancreatic fistula—

Countries

Korea, Republic of

Contacts

Public ContactWoohyung Lee

Asan Medical Center

ywhnet@amc.seoul.kr+82-2-3010-3933

Outcome results

None listed

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