Machine Learning Miscarriage Management Clinical Decision Support Tool Study

Last updated: April 22, 2024
Sponsor: Imperial College London
Overall Status: Active - Recruiting

Phase

N/A

Condition

N/A

Treatment

Medical Management of First Trimester Miscarriage

Expectant Management of First Trimester Miscarriage

Clinical Study ID

NCT06384144
23QC8155
  • Ages 16-55
  • Female
  • Accepts Healthy Volunteers

Study 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 Criteria

Inclusion

Inclusion Criteria:

  • Missed miscarriage and incomplete miscarriage less than 14weeks gestation
  • Follow-up recorded at 2 weeks

Exclusion

Exclusion Criteria:

  • Final outcome data unavailable

Study Design

Total Participants: 1000
Treatment Group(s): 2
Primary Treatment: Medical Management of First Trimester Miscarriage
Phase:
Study Start date:
January 01, 2023
Estimated Completion Date:
June 01, 2026

Study Description

  • Artificial intelligence discovery science: Algorithm Development based on a retrospective Audit of approximately 1000 cases of miscarriage

  • To determine the reliability of the tool with test data sets

  • To increase the sensitivity and specificity of the decision aid by widening the data collection to multiple sites and testing the algorithm with prospective data

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:

  • 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

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.

Connect with a study center

  • Imperial College Heatlhcare NHS Trust

    London, W12 0HS
    United Kingdom

    Active - Recruiting

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