Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT05648227 |
| Other study ID # |
314058 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
July 1, 2022 |
| Est. completion date |
May 1, 2024 |
Study information
| Verified date |
December 2022 |
| Source |
Royal Brompton & Harefield NHS Foundation Trust |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
A retrospective study to evaluate the diagnostic performance of an Artificial Intelligence
enabled software (ArtiQ.Spiro) in UK primary care spirometry datasets.
Description:
This is a retrospective analysis of existing clinical datasets with consecutive spirometry
collected in a primary care setting in the UK. Individual patient data will be included if
the individual meets the study protocol eligibility criteria.
Clinical datasets will be de-identified (name, date of birth, address, postcode, occupation
GP, ethnicity, medications data removed). Individuals will be identified by a study ID
number. The de-identified datasets will contain the minimum information needed for spirometry
and ArtiQ.Spiro - namely age, smoking history, height, weight, primary respiratory symptom -
and the deidentified data exported from the primary care spirometry software.
ArtiQ.Spiro Evaluation (Index Tests for Diagnosis and Quality):
A deidentified dataset will be provided to a machine learning analyst who will apply the
machine learning algorithm of ArtiQ.Spiro. For each individual, the algorithm will produce a
preferred diagnosis (highest probability diagnostic category) (Index Test for Diagnosis) and
an assessment of spirometry quality (Acceptable, Usable, Not Acceptable/Usable) (Index Test
for Quality). No clinical information outside of the spirometry dataset nor reference
standard data will be made available to the analyst.
Reference Standard for Diagnosis:
The clinical dataset, together with available primary care records and secondary care
records, will be used by the senior members of the direct clinical care team (Consultants in
Respiratory Medicine with an interest in integrated respiratory care) to provide a reference
standard for diagnosis. For each individual, two consultants will provide a diagnosis
independently and blinded to the index test (ArtiQ.Spiro) output. If there is agreement, this
diagnosis will be taken as the reference standard for diagnosis for the individual. If there
is no agreement, a third consultant outside the direct clinical care team will be provided
with the same information (but deidentified) to act as final arbitrator.
Reference Standard for Quality:
A deidentified dataset will be provided to a specialist respiratory physiologist. He/she will
grade the quality of each spirometric session according to the official American Thoracic
Society / European Respiratory Society 2019 Technical Statement for Standardization of
Spirometry. For each patient, the quality of the spirometry session will be graded according
to one of three categories: Acceptable, Usable, Not Acceptable/Usable. This will act as the
reference standard for quality. The respiratory physiologists will be blinded to the output
from the Index Test (ArtiQ.Spiro). The respiratory physiologists will also record time taken
to evaluate the dataset.
Data Analysis:
Data analysis will be performed by the research team who will be independent to the direct
clinical care team and the respiratory physiologists who will be providing the reference
standards for diagnosis and quality respectively.
