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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:
Audit to collate 1000 cases and identify features contributing to an algorithm that can predict outcome of miscarriage management for individualized case management.
The study will be conducted at Queen Charlotte's and Chelsea Hospital at Imperial College Healthcare NHS Trusts (Primary Centre of the study).
This is a multi-centre retrospective, cohort observational study.
The study will be conducted over a minimum of three years to enable sufficient time to go through the retrospective data and collate test data sets.
Retrospective annonymised cases of missed miscarriage and incomplete miscarriage managed at Imperial College Healthcare NHS Trust will be analyse:
For each case the following clinical features will be collated and outcomes:
All data will be collected retrospectively and annonymised.
Following data collection, machine learning models and feature reduction methods will be applied to determine the best performing model to predict success or failure of expectant or medical management of miscarriage respectively.
The next phase will include a prospective audit to collect data and test the predictive power of the MLM clinical decision support tool.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Expectant Management of Miscarriage | Cohort that chose to pursue expectant management of miscarriage, final outcome success or failure by day 14 from management choice |
| |
| Medical Management of Miscarriage | Cohort that chose to pursue medical management of miscarriage, final outcome success or failure by day 14 from management choice |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Expectant Management of First Trimester Miscarriage | Other | Expectant Management: Conservative management if miscarriage with follow-up booked in 2 weeks to determine whether complete miscarriage has occurred. |
| Measure | Description | Time Frame |
|---|---|---|
| Machine learning predictive model development for miscarriage management outcomes. | Machine learning predictive model development based on a retrospective audit of approximately 1000 cases of miscarriage. | Jan 2023- June 2024 |
| Measure | Description | Time Frame |
|---|---|---|
| Prospective audit to test and validate predictive model | To increase the sensitivity and specificity of the decision aid by widening the data collection to multiple sites and testing the machine learning model with prospective data. | July 2024-June 2025 |
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Inclusion Criteria:
Exclusion Criteria:
- Final outcome data unavailable
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Cases of missed miscarriage and incomplete miscarriage in the first trimester.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Imperial College Heatlhcare NHS Trust | Recruiting | London | W12 0HS | United Kingdom |
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| Medical Management of First Trimester Miscarriage | Other | Medical Management: Misoprostol taken to manage first trimester miscarriage, with follow-up booked in 2 weeks to determine whether complete miscarriage has occurred. |
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