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Early Detection of Sepsis in Adult ICU Patients Using Machine Learning Techniques at a University Medical College Hospital

Early Detection of Sepsis in Adult ICU Patients Using Machine Learning Techniques at a University Medical College Hospital - NO

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/05/087434
Enrollment
667
Registered
2025-05-22
Start date
Unknown
Completion date
Unknown
Last updated
2026-09-14

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

Conditions

Health Condition 1: 8- Other Procedures

Interventions

Intervention1: NIL: NIL Control Intervention1: NIL: NIL

Sponsors

Institute of Medical Sciences and Sum Hospital, Siksha O Anusandhan Deemed to be University
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: (1) Patients age 18 or greater than 18 years. (2) Infection at the time of admission to the ICU.

Exclusion criteria

Exclusion criteria: (i) Patients are known to be pregnant and lactating women. (iii) Patients with missing data will be excluded from the analysis. (iv) Patients already septic at ICU admission.

Design outcomes

Primary

MeasureTime frame
Development and validation of a machine-learning model for early prediction of sepsis in adult ICU patients, assessed by AUROC, AUPRC, sensitivity, specificity, and accuracy.Timepoint: 6 hours after ICU admission—

Secondary

MeasureTime frame
The risk factors associated with sepsisTimepoint: 15 months—

Countries

India

Contacts

Public ContactProf Dr Sanghamitra Mishra

Institute of Medical Sciences and Sum Hospital , Siksha O Anusandhan Deemed to be University

dean.ims@soa.ac.in7381177222

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Sep 19, 2026