Artificial Intelligence to Improve Cardiometabolic Risk Evaluation Using CT Scans (ACRE-CT)

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

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: 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 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.

Personal identifiable data (including the code-break/participant key) collected at the recruitment site will be recorded electronically on a database that is stored on an access-restricted computer and either encrypted and/or located on a secure server and accessed only by authorised staff. Any copies leaving the study site will be completely anonymised/de-identified. Informed consent forms that contain participant names will be stored securely at study sites in locked cupboards and will only be accessible to study staff and authorised personnel.

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;

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.

Obtain blood sample for glucose assessment (time "0" sample). This may be obtained via venepuncture or after cannula insertion. Test a small sample using a near patient glucose testing meter. If the result on the glucose meter is greater than or equal to 11mmol/L, send the blood sample urgently to lab. If it is confirmed by biochemistry to be above 11mmol/L, there is no need to continue test. If the result is less than 11mmol/L on meter, give the patient the glucose solution to drink. Collect a further blood sample at 120 minutes. Send samples all together to laboratory for glucose measurement.

Number of participants identified with pre-diabetes/type 2 diabetes mellitus when fasting blood sample test results are compared against FatHealth algorithm results

The investigators will measure if the fasting blood sample results indicate that the individual has pre-diabetes/type 2 diabetes mellitus and compare if our FatHealth algorithm indicates the same results for the individual

Number of participants identified with pre-diabetes/type 2 diabetes mellitus when oral glucose tolerance test results are compared against FatHealth algorithm results

The investigators will measure if the oral glucose tolerance test results indicate that the individual has pre-diabetes/type 2 diabetes mellitus and compare if our FatHealth algorithm indicates the same results for the individual

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