PREDICTION MODEL OF SURGICAL SITE INFECTION IN ABDOMINAL SURGERY: TRADITIONAL STATISTICAL MODELS VERSUS MACHINE LEARNING

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

TCTR

Registry ID

TCTR20221018001

Enrollment

12596

Registered

2022-10-18

Start date

2019-12-01

Completion date

Unknown

Last updated

2026-08-03

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

Conditions

Surgical site infection abdominal surgery surgical site infections prediction model machine learning

Interventions

Patients underwent abdominal surgery

Diagnostic

Abdominal surgery

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: received a primary abdominal procedure including gastrointestinal, colorectal surgery, or a hernia repair.

Exclusion criteria

Exclusion criteria: None

Design outcomes

Primary

Measure	Time frame
surgical site infection 30 days after surgery infection at surgical wound	—

Secondary

Measure	Time frame
N/A N/A N/A	—

Countries

Thailand

Contacts

Public ContactAmarit Tansawet

Faculty of Medicine Ramathibodi Hospital

amarit@nmu.ac.th0813418964

Outcome results

None listed

Source: TCTR (via WHO ICTRP) · Data processed: Aug 9, 2026