For researchers submitting trial data to ClinicalTrials.gov, the Adverse Events module is one of four mandatory results sections. It requires reporting in three primary categories: All-Cause Mortality: A table tracking all deaths that occurred during the study, regardless of cause. Serious Adverse Events (SAEs): A tabular summary of events resulting in death, life-threatening conditions, hospitalization, or significant disability. Other Adverse Events: A table for non-serious events that exceed a specific frequency threshold, such as 5% within any study arm.
Adverse Events Module path is as follows:
Study -> Results Section -> Adverse Events Module -> Event Groups
Study -> Results Section -> Adverse Events Module -> Serious Events
Study -> Results Section -> Adverse Events Module -> Other Events
| Title | Description | Deaths # Affected | Deaths # At Risk | Serious # Affected | Serious # At Risk | Other # Affected | Other # At Risk | View |
|---|---|---|---|---|---|---|---|---|
| Tracheostomy Patients | All consenting participants will receive access to SRAVI (Speech Recognition Application for the Voice Impaired), a communication aid for speech-impaired patients. SRAVI is a software-based mobile application ('app') and can be downloaded onto any device with a standard forward facing camera (e.g., smartphone, tablet). SRAVI has been registered with the Medical and Healthcare products Regulatory Agency (MHRA) and CE marked for intended use. SRAVI is based on Visual Speech Recognition (VSR) technology. Specifically, the LipRead technology can determine speech by analysing the movements of a user's lips as they speak into a camera. SRAVI (Speech Recognition Application for the Voice Impaired): Speech Recognition Application for the Voice Impaired (SRAVI) is a novel communication aid developed by Liopa (a company formed by Queen's University Belfast (QUB) and the Centre for Security Information Technologies (CSIT), QUB). SRAVI is an application-based lip-reading system, and the application ('app') can be downloaded onto any device with a standard forward facing camera (e.g., smartphone, tablet). When the device is held in front of a patient, it will track lip movement and identify phrases being mouthed. | 0 | None | 0 | 31 | 0 | 31 | View |