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Use of artificial intelligence in the fetal heart beat monitoring in the assessment of neonatal outcome

Efficacy Of Artificial Intelligence Aided Interpretation Of Intrapartum Cardiotocography In The Prediction Of Intrapartum Fetal Compromise And Adverse Neonatal Outcome -A Pilot study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2021/02/031584
Enrollment
5000
Registered
2021-02-26
Start date
Unknown
Completion date
Unknown
Last updated
2021-11-24

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

Conditions

Health Condition 1: O778- Labor and delivery complicated byother evidence of fetal stress

Interventions

None listed

Sponsors

Kasturba medical college Manipal academy of higher education
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: All Consecutive pregnant woman who are admitted for labour in tertiary care hospital, Kasturba hospital Manipal

Exclusion criteria

Exclusion criteria: None

Design outcomes

Primary

MeasureTime frame
signs of Asphyxia fetal distress and hypoxia Pattern of CTG tracingTimepoint: at Birth,pre discharge—

Secondary

MeasureTime frame
Pre-labour risk factors evidence of cerebral redistribution in fetus labour admission test labour progression factors colour of liquorTimepoint: During Labour—

Countries

India

Contacts

Public ContactDr Akhila Vasudeva

Kasturba Medical College

akhila.vasudeva@manipal.edu9591614792

Outcome results

None listed

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