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Ultrafast Screening of novel coronavirus pneumonia (COVID-19) by Machine Learning Analysis of Exhaled NO

Application of artificial intelligence to develop new theoretical methods to deal with major outbreak

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000035342
Enrollment
Unknown
Registered
2020-08-09
Start date
2020-03-01
Completion date
Unknown
Last updated
2020-08-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

COVID-19

Interventions

Gold Standard:nucleic acid testing (NAT)
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Sponsors

Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology
Lead Sponsor

Eligibility

Sex/Gender
All
Age
21 Years to 89 Years

Inclusion criteria

Inclusion criteria: This study was approved by the Medical Ethics Committee of Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology 1. All Patients and healthy subjects or family members have signed informed consent and agreed to accept the FeNO detection and personal information including age, gender, height, weight and anamnesis collection; 2. Age 20 or older; 3. Body mass index between 18.5 and 29.9 (according to national criteria).

Exclusion criteria

Exclusion criteria: Patients will be excluded if they meet any of the following criteria. 1. Hard to do FeNO test; 2. Subjects eating three hours before the FeNO test; 3. Subjects who smoked or drank alcohol one hour before the FeNO test; 4. Subjects who exercise vigorously one hour before the FeNO test; 5. Subjects who have undergone other lung function tests one hour before the FeNO test.

Design outcomes

Primary

MeasureTime frame
Fractional exhaled nitric oxide;SEN, SPE, ACC, AUC of ROC;

Countries

China

Contacts

Public ContactWei-Qiao Deng

Shandong University

dengwq@sdu.edu.cn+86 13478585430

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026