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
Not provided
Not provided
Not provided
Not provided
Not provided
This study aims to evaluate whether the use of AI as a physician support tool is associated with an increase in the detection rate of chest radiographic findings in adults with respiratory complaints, compared to diagnosis performed exclusively by doctors, without AI support. This is a cluster-randomized clinical trial, following the stepped wedge design, and adhering to the guidelines of the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT). In this study, the Diagnostic Support Solution for Chest X-rays - LungAnalysis (LuAna), developed by the Hospital Israelita Albert Einstein (HIAE) within the PROADI-SUS Banco de Imagens, was used.
The clinical trial will be conducted in multiple centers with a diverse population from the public health system, to ensure that the algorithms are validated across a broad demographic profile. The expected benefits are significant, providing greater security for patients, increasing doctors' confidence in interpreting chest X-rays, promoting efficiency and cost savings for healthcare services, and offering promising prospects for other AI applications in imaging diagnostics.
Imaging diagnostic aid tools that use AI and facilitate the identification of findings on chest x-rays can contribute to doctors' care routines and clinicians' and radiologists' reporting routines, as these tools can allow the organization of care queues according to priorities, in addition to identifying subtle findings on the image, thereby reducing errors in reading the RXT and benefiting patients with greater agility in care and a shorter time until diagnosis. However, for reliability, these tools must undergo rigorous validation processes in large populations before implementation.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| App LuAna | Experimental | feedback of the artificial intelligence after the inclusion image in app LuAna. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| App LuAna | Device | Inclusion of chest x-ray images in the LuAna app to receive feedback on lung findings. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Detection rate | Detection rate of "Radiological Findings", before and after Artificial Intelligence assistance, compared to gold standard (report validated twice by thoracic radiologists blind to the interpretation of the examining physician and AI result). | through study completion, an average of 1 year |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Joselisa Paiva, PhD | Contact | +55 (11) 9981667340 | joselisa.paiva@einstein.br |
| Name | Affiliation | Role |
|---|---|---|
| Joselisa Paiva, PhD | Hospital Israelita Albert Einstein | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| FEAS Curitiba | Recruiting | Curitiba | Paraná | 81130-160 | Brazil |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D055370 | Lung Injury |
| D010996 | Pleural Effusion |
| D011030 | Pneumothorax |
| D006332 | Cardiomegaly |
| D011654 | Pulmonary Edema |
| ID | Term |
|---|---|
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D013898 | Thoracic Injuries |
| D014947 | Wounds and Injuries |
Not provided
Not provided
This is a type of "stepped wedge" cluster randomized clinical trial. In the model standard of this design, interventions are implemented in the clusters randomly and graduate.
Not provided
Not provided
Not provided
Not provided
| D010995 |
| Pleural Diseases |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D006984 | Hypertrophy |
| D020763 | Pathological Conditions, Anatomical |
| D013568 | Pathological Conditions, Signs and Symptoms |