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

Sponsor
London School of Economics and Political Science (Other)
Overall Status
Completed
CT.gov ID
NCT02700737
Collaborator
German Heart Institute (Other), Bambino Gesù Hospital and Research Institute (Other), University College, London (Other)
206
1
2
3
68.2

Study Details

Study Description

Brief Summary

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.

Condition or Disease Intervention/Treatment Phase
  • Other: Image-based simulation modelling
  • Other: Imaging parameters currently recommended by clinical practice guidelines
N/A

Detailed Description

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.

Study Design

Study Type:
Interventional
Actual Enrollment :
206 participants
Allocation:
Randomized
Intervention Model:
Parallel Assignment
Masking:
None (Open Label)
Primary Purpose:
Health Services Research
Official Title:
Evaluation of Image-Based Modelling on Clinical Decisions in Coarctation of the Aorta
Study Start Date :
May 1, 2016
Actual Primary Completion Date :
Aug 1, 2016
Actual Study Completion Date :
Aug 1, 2016

Arms and Interventions

Arm Intervention/Treatment
Active Comparator: Group A

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

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").

Experimental: Group B

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

Other: Image-based simulation modelling
The first dataset will include the imaging parameters currently recommended by clinical practice guidelines (referred to as "limited dataset").

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").

Outcome Measures

Primary Outcome Measures

  1. Decision to intervene [Immediate]

    Our primary outcome of interest in this randomized experiment will be 'decision to intervene' by cardiologists evaluating imaging data obtained from patients with aortic coarctation. Interventional cardiologists will be asked the following question: Based on the information presented to you, would you intervene in this patient now? Please provide a yes/no answer.

Eligibility Criteria

Criteria

Ages Eligible for Study:
N/A and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
Yes
Inclusion Criteria:
  • Practicing interventional cardiologists

  • Has treated patients with coarctation of the aorta during the past 6 months

Exclusion Criteria:
  • Participation in CARDIOPROOF trial

Contacts and Locations

Locations

Site City State Country Postal Code
1 London School of Economics and Political Science London United Kingdom

Sponsors and Collaborators

  • London School of Economics and Political Science
  • German Heart Institute
  • Bambino Gesù Hospital and Research Institute
  • University College, London

Investigators

  • Principal Investigator: Huseyin Naci, PhD, London School of Economics and Political Science

Study Documents (Full-Text)

None provided.

More Information

Additional Information:

Publications

None provided.
Responsible Party:
Huseyin Naci, Assistant Professor, London School of Economics and Political Science
ClinicalTrials.gov Identifier:
NCT02700737
Other Study ID Numbers:
  • LSEHSC-01001
First Posted:
Mar 7, 2016
Last Update Posted:
Oct 31, 2016
Last Verified:
Oct 1, 2016
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Keywords provided by Huseyin Naci, Assistant Professor, London School of Economics and Political Science
Additional relevant MeSH terms:

Study Results

No Results Posted as of Oct 31, 2016