Clinical trial NCT05058690: Artificial Intelligence to Improve Cardiometabolic Risk Evaluation Using CT Scans
Official title: Artificial Intelligence to Improve Cardiometabolic Risk Evaluation Using CT Scans
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Pre-diabetes
Diabetes Mellitus
Lead sponsor: Caristo Diagnostics Limited
Sponsor class: INDUSTRY
Collaborators: name: University of Oxford
name: University of Leeds
name: Milton Keynes University Hospital NHS Foundation Trust
First posted: 2021-09-28
Enrollment: 180
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Multi-centre, prospective cohort, study
Primary purpose: DIAGNOSTIC

Brief summary: To validate the ability of the FatHealth algorithm to identify individuals with pre-diabetes and with type 2 diabetes mellitus

Detailed description: This multicentre prospective study will evaluate the ability of the FatHealth technology to correctly identify individuals with pre-diabetes and diabetes, validating the technology against the current gold-standard diagnostic method, oral glucose tolerance testing.

Participants will be individuals who have undergone a CT scan of the chest (coronary CT angiogram \[CCTA\] or CT chest) as part of observational cohort studies.

Participants will be invited for an oral glucose tolerance test (OGTT), which is the current gold-standard method for detecting pre-diabetes and diabetes mellitus. All patients must have an evaluable OGTT. The study population will include:

1. Approximately 90 individuals who had a CCTA as part of their clinical care (45 identified as having an abnormal FatHealth algorithm calculation and 45 with a normal FatHealth algorithm calculation) will undergo OGTT which is evaluable; and
2. Approximately 90 individuals who had a chest CT as part of their clinical care (45 identified as having an abnormal FatHealth algorithm calculation and 45 with a normal FatHealth algorithm calculation) will undergo OGTT which is evaluable.

Eligibility criteria: Inclusion Criteria:

* Participant is willing and able to give informed consent for participation in the study. Male or Female, aged 18 to 80 years.
* Body mass index (BMI) ≥ 25kg/m2
* FatHealth status assessed as the following:

  * Elevated FatHealth status (50% of participants)
  * Non-elevated FatHealth status (50% of participants)

Exclusion Criteria:

* Participant is unable or unwilling to give informed consent
* Participant is unable to understand English language
* Confirmed diagnosis of diabetes mellitus treated with oral medication or Insulin

Primary outcomes:
measure: Number of participants identified with pre-diabetes/type 2 diabetes mellitus when fasting blood sample test results are compared against FatHealth algorithm results
timeFrame: Baseline
Secondary outcomes:
measure: Number of participants identified with pre-diabetes/type 2 diabetes mellitus when oral glucose tolerance test results are compared against FatHealth algorithm results
timeFrame: 120 minutes after baseline
Other outcomes:
Locations:
Study officials:
References: