Evaluation of Image-Based Modelling on Clinical Decisions in Coarctation of the Aorta

NCT ID: NCT02700737

Last Updated: 2016-10-31

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

206 participants

Study Classification

INTERVENTIONAL

Study Start Date

2016-05-31

Study Completion Date

2016-08-31

Brief Summary

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To answer the research question: "Would image-based modelling result in different clinical decisions as compared to clinical practice guidelines?", we will conduct a randomized controlled experiment in which we will compare the hypothetical decisions made by interventional cardiologists who are presented with imaging parameters currently recommended by clinical practice guidelines vs. hypothetical decisions made by interventional cardiologists receiving an expanded list of parameters, including simulation modelling.

Detailed Description

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In collaboration with our three clinical partners, we will first generate two separate imaging datasets for a maximum of three patients recruited to participate in CARDIOPROOF. The first dataset will include the imaging parameters currently recommended by clinical practice guidelines (referred to as "limited dataset"). The second dataset will include an expanded list of parameters, inclusive of information that is available from traditional imaging parameters (as recommended by the guidelines) and simulation modeling (referred to as "image-based modelling dataset").

We will generate both limited and image-based modelling datasets from fully de-identified patients already enrolled in CARDIOPROOF (NCT02591940) who have consented to publication of data in anonymized form.

Using a computerized random-sample function, we will randomly allocate interventional cardiologists into two separate groups and present them with one set of imaging data. The first group will receive a "limited" dataset including only information that is available from traditional diagnostics (as recommended by the clinical practice guidelines) for a pre-specified number of patients (maximum of 3). The second group will receive the full, detailed dataset inclusive of information that is available from traditional diagnostics (as recommended by the guidelines) and simulation modelling for the same set of patients.

We will then ask the interventional cardiologists in the two groups to make (hypothetical) clinical decisions using the dataset of imaging parameters presented to them. The clinical decisions will be hypothetical because patients will have been treated according to clinical practice guidelines and this experiment will retrospectively involve interventional cardiologists who are not directly involved in the care of the patients participating in CARDIOPROOF.

The analysis will focus on each hypothetical scenario and compare the proportions of cardiologists making different types of intervention decisions in the two randomly allocated groups.

Conditions

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Congenital Heart Disease Aortic Coarctation Cardiovascular Disease

Keywords

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cardiovascular modeling aortic coarctation virtual stenting

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

NONE

Study Groups

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Group A

Interventional cardiologists presented with "limited" dataset including only information that is available from imaging parameters currently recommended by clinical practice guidelines.

Group Type ACTIVE_COMPARATOR

Imaging parameters currently recommended by clinical practice guidelines

Intervention Type OTHER

The second dataset will include an expanded list of parameters, inclusive of information that is available from traditional imaging parameters (as recommended by the guidelines) and simulation modeling (referred to as "image-based modelling dataset").

Group B

Interventional cardiologists presented with the full dataset, including imaging parameters currently recommended by clinical practice guidelines and image-based simulation modelling.

Group Type EXPERIMENTAL

Image-based simulation modelling

Intervention Type OTHER

The first dataset will include the imaging parameters currently recommended by clinical practice guidelines (referred to as "limited dataset").

Imaging parameters currently recommended by clinical practice guidelines

Intervention Type OTHER

The second dataset will include an expanded list of parameters, inclusive of information that is available from traditional imaging parameters (as recommended by the guidelines) and simulation modeling (referred to as "image-based modelling dataset").

Interventions

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Image-based simulation modelling

The first dataset will include the imaging parameters currently recommended by clinical practice guidelines (referred to as "limited dataset").

Intervention Type OTHER

Imaging parameters currently recommended by clinical practice guidelines

The second dataset will include an expanded list of parameters, inclusive of information that is available from traditional imaging parameters (as recommended by the guidelines) and simulation modeling (referred to as "image-based modelling dataset").

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Practicing interventional cardiologists
* Has treated patients with coarctation of the aorta during the past 6 months

Exclusion Criteria

* Participation in CARDIOPROOF trial
Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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German Heart Institute

OTHER

Sponsor Role collaborator

Bambino Gesù Hospital and Research Institute

OTHER

Sponsor Role collaborator

University College, London

OTHER

Sponsor Role collaborator

London School of Economics and Political Science

OTHER

Sponsor Role lead

Responsible Party

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Huseyin Naci

Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Huseyin Naci, PhD

Role: PRINCIPAL_INVESTIGATOR

London School of Economics and Political Science

Locations

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London School of Economics and Political Science

London, , United Kingdom

Site Status

Countries

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United Kingdom

References

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Naci H, Salcher-Konrad M, Mcguire A, Berger F, Kuehne T, Goubergrits L, Muthurangu V, Wilson B, Kelm M. Impact of predictive medicine on therapeutic decision making: a randomized controlled trial in congenital heart disease. NPJ Digit Med. 2019 Mar 19;2:17. doi: 10.1038/s41746-019-0085-1. eCollection 2019.

Reference Type DERIVED
PMID: 31304365 (View on PubMed)

Related Links

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http://www.cardioproof.eu

Overall study website

Other Identifiers

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LSEHSC-01001

Identifier Type: -

Identifier Source: org_study_id