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Development of risk stratification tool for prediction of preterm birth with Artificial intelligence.

A multicentric prospective cohort study to develop Artificial intelligence-assisted risk stratification tool for prediction of preterm birth. - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2023/11/060089
Enrollment
357
Registered
2023-11-21
Start date
Unknown
Completion date
Unknown
Last updated
2023-12-19

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

Conditions

Health Condition 1: O94- Sequelae of complication of pregnancy, childbirth, and the puerperium

Interventions

Intervention1: Nil: Nil Control Intervention1: Nil: Nil

Sponsors

ICMR
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: All women who had preterm birth ( <37 week’s gestation) either spontaneous or induced, by vaginal route or by cesarean section were included.

Exclusion criteria

Exclusion criteria: Women who had delivery 37 weeks’ of gestation

Design outcomes

Primary

MeasureTime frame
Prevalence of preterm birth in the study population.Timepoint: 3 years 6 months—

Secondary

MeasureTime frame
To describe the sociodemographic and clinical characteristics, and comorbidity of the cohort of pregnant women. To estimate the prevalence of preterm birth in the study population. To identify the characteristics of pregnant women with preterm birth. To determine the risk factors and causes of preterm births.Timepoint: 3 years 6 months—

Countries

India

Contacts

Public ContactDr Kavita Khoiwal

All India Institute of Medical Sciences - Rishikesh

kavita.kh27@gmail.com9690396908

Outcome results

None listed

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