Ignite Creation Date:
2025-12-24 @ 9:26 PM
Ignite Modification Date:
2025-12-25 @ 7:11 PM
Study NCT ID:
NCT06148532
Status:
ENROLLING_BY_INVITATION
Last Update Posted:
2025-12-12
First Post:
2023-11-20
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
EnCoRe MoMS: Engaging Communities to Reduce Morbidity From Maternal Sepsis (Aim 2)
Sponsor:
Columbia University
Organization:
Study Overview
Official Title:
EnCoRe MoMS: Engaging Communities to Reduce Morbidity From Maternal Sepsis (Aim 2)
Status:
ENROLLING_BY_INVITATION
Status Verified Date:
2025-12
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Sepsis is the second leading cause of maternal death in the U.S. For racial and ethnic minoritized birthing people, especially those who are Black, living in poverty, and from underserved communities, labor and postpartum are particularly vulnerable risk periods. The goal of this multi-center, multidisciplinary observational study is to optimize risk prediction accounting for the social determinants of health, and establish a novel maternal care continuity model to reduce sepsis- related death and disability and increase maternal health equity.
Detailed Description:
Maternal sepsis is the second leading cause of maternal death, major cause of morbidity, and preventable in most cases. EnCoRe MoMS: Engaging Communities to Reduce Morbidity from Maternal Sepsis will (Aim 2) Develop algorithms to optimize prediction of sepsis around delivery and postpartum.
In the UG3 phase, robust community engagement and research infrastructures were established to: Aim 2a. Create a rich electronic health records (EHR) database from the Perinatal Research Consortium (PRC). Aim 2b. Collate neighborhood-level datasets characterizing social determinants of health (SDOH)
In the UH3 phase, the investigators will Aim 2c. Harmonize patient-level EHR and neighborhood-level SDOH datasets and use machine learning models to analyze the individual and joint contributions of patient and neighborhood factors to optimize sepsis risk prediction within the PRC sample.
In the UG3 phase, robust community engagement and research infrastructures were established to: Aim 2a. Create a rich electronic health records (EHR) database from the Perinatal Research Consortium (PRC). Aim 2b. Collate neighborhood-level datasets characterizing social determinants of health (SDOH)
In the UH3 phase, the investigators will Aim 2c. Harmonize patient-level EHR and neighborhood-level SDOH datasets and use machine learning models to analyze the individual and joint contributions of patient and neighborhood factors to optimize sepsis risk prediction within the PRC sample.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
Secondary ID Infos
| Secondary ID | Type | Domain | Link | View |
|---|---|---|---|---|
| 1UG3HD111247 | NIH | None | https://reporter.nih.gov/quic… | View |