No registrations found.
ID
Source
Brief title
Health condition
COVID19
Sponsors and support
Intervention
Outcome measures
Primary outcome
Lung ultrasound sensitivity to predict COVID-19 diagnosis
Secondary outcome
Lung ultrasound specificity to predict COVID-19 diagnosis
Background summary
We will investigate the value of ultrasound as a first-line examination tool in the process of diagnosing COVID-19. We aim to estimate the test characteristics of artificial intelligence methods on lung ultrasound images for diagnosis of COVID-19 on patients entering the hospital emergency department with COVID-19 symptoms. The outcomes of this study will be relevant for hospitals, but also for any other situations or regions where PCR testing or CT scanning is less available.
Study objective
Artificial intelligence methods on lung ultrasound images is able to predict the presence of lung related signs of COVID-19 with a sensitivity around 90%. Artificial intelligence methods on lung ultrasound images is able to predict the presence of lung related signs of COVID-19 with a specificity around 80%.
Study design
after entering the emergency department
Intervention
Lung ultrasound
Inclusion criteria
- patients who enter the emergency department
- 18 years of age or older
- capacitated (able to make a reasonable judgement of their own interests with regards to the study)
- with (newly developed) symptoms of COVID-19 (fever or chills, cough, shortness of breath or difficulty breathing, new loss of taste or smell, sore throat, congestion or runny nose)
- signed informed consent
Exclusion criteria
- pregnancy
- contra-indications for ultrasound
Design
Recruitment
IPD sharing statement
Followed up by the following (possibly more current) registration
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Other (possibly less up-to-date) registrations in this register
No registrations found.
In other registers
| Register | ID |
|---|---|
| NTR-new | NL9247 |
| Other | Not-WMO METC azM : METC2020-2229 |