Machine Learning Miscarriage Management Clinical Decision Support Tool Study
Imperial College London
1,000 participants
Jan 1, 2023
OBSERVATIONAL
Conditions
Summary
Machine learning used to develop an algorithm to determine chance of success with expectant or medical management for an individual patient. Taking into account the following objective measures: * Demographics: Maternal Age, Parity * History: Previous CS, Previous SMM/MVA, Previous Myomectomy * Gestation by LMP * Presenting symptoms: Bleeding score, Pain score * USS Measurements: CRL, GS, RPOC 3 dimensions, Vascularity * Discrepancy between gestation by CRL and LMP Audit to collate 1000 cases and identify features contributing to an algorithm that can predict outcome of miscarriage management for individualized case management.
Eligibility
Inclusion Criteria2
- Missed miscarriage and incomplete miscarriage less than 14weeks gestation
- Follow-up recorded at 2 weeks
Exclusion Criteria1
- \- Final outcome data unavailable
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Interventions
Expectant Management: Conservative management if miscarriage with follow-up booked in 2 weeks to determine whether complete miscarriage has occurred.
Medical Management: Misoprostol taken to manage first trimester miscarriage, with follow-up booked in 2 weeks to determine whether complete miscarriage has occurred.
Locations(1)
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NCT06384144