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SEPSIVAC Trial for validation of Ai Software

Clinical Investigation of SepsiTrace AI-SaMD for Early Sepsis Risk Prediction - nil

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/06/113111
Enrollment
5200
Registered
2026-06-29
Start date
Unknown
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

Health Condition 1: A00-B99- Certain infectious and parasitic diseases

Interventions

Intervention1: Nil: Nil

Sponsors

Nivaris Healthcare Pvt Ltd Bengaluru India
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Adult, PICU or NICU admission in eligible care settings Suspected infection, deterioration or acute presentation requiring routine monitoring Adequate routine clinical data available Record permits clinician adjudication Consent / LAR consent where required by IEC

Exclusion criteria

Exclusion criteria: Materially incomplete records Sepsis status cannot be reliably adjudicated Duplicate or technically invalid records Investigator exclusion for scientific, ethical or administrative reasons Patient declines participation where consent is required

Design outcomes

Primary

MeasureTime frame
To evaluate the performance of SepsiTrace for early prediction of sepsis, defined as the ability to identify patients at risk several hours prior to clinician-adjudicated sepsis diagnosis, using routinely collected hospital dataTimepoint: To evaluate the performance of SepsiTrace for early prediction of sepsis, defined as the ability to identify patients at risk several hours prior to clinician-adjudicated sepsis diagnosis, using routinely collected hospital data

Secondary

MeasureTime frame
To quantify the lead time between SepsiTrace risk prediction and clinician-adjudicated sepsis recognition; To assess the operational feasibility of real-world data acquisition in an Indian tertiary-care setting, including data completeness, frequency, and timelinessTimepoint: 1) Lead time between SepsiTrace high-risk output and clinician-adjudicated sepsis recognition; (2) Feasibility of structured data capture (completeness, frequency, timeliness

Countries

India

Contacts

Public ContactAkshay HM

JSS ACADEMY OF HIGHER EDUCATION AND RESEARCH

akshayhm@jssuni.edu.in9980891177

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Aug 10, 2026