Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| German Heart Institute | OTHER |
| Bambino Gesù Hospital and Research Institute | OTHER |
| University College, London | OTHER |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
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.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group A | Active Comparator | Interventional cardiologists presented with "limited" dataset including only information that is available from imaging parameters currently recommended by clinical practice guidelines. |
|
| Group B | Experimental | Interventional cardiologists presented with the full dataset, including imaging parameters currently recommended by clinical practice guidelines and image-based simulation modelling. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Image-based simulation modelling | Other | The first dataset will include the imaging parameters currently recommended by clinical practice guidelines (referred to as "limited dataset"). |
| Measure | Description | Time Frame |
|---|---|---|
| Decision to intervene | 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. | Immediate |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Huseyin Naci, PhD | London School of Economics and Political Science | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| London School of Economics and Political Science | London | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31304365 | Derived | 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. |
| Label | URL |
|---|---|
| Overall study website | View source |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Imaging parameters currently recommended by clinical practice guidelines | 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"). |
|
| ID | Term |
|---|---|
| D006330 | Heart Defects, Congenital |
| D001017 | Aortic Coarctation |
| D002318 | Cardiovascular Diseases |
| ID | Term |
|---|---|
| D018376 | Cardiovascular Abnormalities |
| D006331 | Heart Diseases |
| D000013 | Congenital Abnormalities |
| D009358 | Congenital, Hereditary, and Neonatal Diseases and Abnormalities |
Not provided
Not provided