FindTrial
Sign In

Development of a model to predict death at 30 days in patients with complicated abdominal infections

Development and validation of an Artificial Intelligence and machine learning model to predict 30 day mortality in patients with secondary peritonitis - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2024/10/076042
Enrollment
500
Registered
2024-10-29
Start date
Unknown
Completion date
Unknown
Last updated
2024-11-11

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

Conditions

Health Condition 1: K67- Disorders of peritoneum in infectious diseases classified elsewhere

Interventions

Intervention1: Not applicable: Not applicable Control Intervention1: Not applicable: Not applicable

Sponsors

All India Institute of Medical Sciences New Delhi
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Patients with secondary peritonitis including perforation of the hollow viscus, undergoing emergency laparotomy

Exclusion criteria

Exclusion criteria: 1. Patients in whom no significant intra abdominal pathology was found during laparotomy 2. Patients aged > 75 years 3. Patients aged < 18 years

Design outcomes

Primary

MeasureTime frame
Development of the Artificial Intelligence and Machine learning model to predict 30 day mortalityTimepoint: 30 days—

Secondary

MeasureTime frame
Validation and testing of the Artificial Intelligence and Machine learning model to predict 30 day mortalityTimepoint: 30 days—

Countries

India

Contacts

Public ContactBhavana K

AIIMS New Delhi

k.punit@yahoo.com9873106516

Outcome results

None listed

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