Development and Verification of a New Coronavirus Multiplex Nucleic Acid Detection System

NCT ID: NCT04311398

Last Updated: 2020-05-14

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-05-13

Study Completion Date

2020-12-01

Brief Summary

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Our project intends to independently develop a fully enclosed rapid detection system for a total of 22 pathogens, including SARS-CoV-2, on the basis of the QIAstat-Dx fully automatic multiple PCR detection platform. The reasonably designed experiments are used to verify the performance of the cartridge detection and prove its clinical application value. The 22 pathogens tested in this project includes 4 coronavirus subtypes, A / B flu, parainfluenza virus, respiratory syncytial virus, etc., which is of great significance for the differential diagnosis of similar patients.

Detailed Description

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COVID-19 has not been well suppressed, and became a pandemic within 3 months globally is mainly because of the virus characteristic in the following aspects:

1. Long incubation period (average 5-7 days, up to 28 days), and the incubation period is contagious
2. Strong transmissibility, virus can be transmitted through aerosol
3. Difficulty distinguishing infected patients from other pathogenic infections
4. High negative rate of nucleic acid detection in upper respiratory tract samples of infected patients, which increases the difficulty of differential diagnosis of infection with other pathogens The existing RT-PCR nucleic acid detection kits for SARS-CoV-2 has two major problems. First, the procedure is not automated leading to higher requirements for personnel operation level and environment sterilize. What's more the kits are SARS-CoV-2 only. Once the test result is negative, it cannot help diagnose the exact pathogen in one time of experiment.

Therefore, this project intends to independently develop a fully enclosed rapid detection system for a total of 22 pathogens, including SARS-CoV-2, on the basis of the QIAstat-Dx fully automatic multiple PCR detection platform. The reasonably designed experiments are used to verify the performance of the cartridge detection and prove its clinical application value. The 22 pathogens tested in this project includes 4 coronavirus subtypes, A / B flu, parainfluenza virus, respiratory syncytial virus, etc., which is of great significance for the differential diagnosis of similar patients.

Conditions

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COVID-19

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Respiratory infection group

Patients went to fever clinic with respiratory infectious symptoms in Huashan Hospital affiliated to Fudan University

New QIAstat-Dx fully automatic multiple PCR detection platform

Intervention Type DIAGNOSTIC_TEST

We use the New QIAstat-Dx fully automatic multiple PCR detection platform to test the enrolled patients

Interventions

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New QIAstat-Dx fully automatic multiple PCR detection platform

We use the New QIAstat-Dx fully automatic multiple PCR detection platform to test the enrolled patients

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Patients went to the fever clinic with respiratory infectious symptoms

Exclusion Criteria

* none
Minimum Eligible Age

16 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Huashan Hospital

OTHER

Sponsor Role lead

Responsible Party

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Wen-hong Zhang

Chief of dpartment of infectious disease

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Huashan Hospital of Fudan University

Shanghai, Shanghai Municipality, China

Site Status

Countries

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China

Central Contacts

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Wenhong Zhang, Doctor

Role: CONTACT

13801844344

Facility Contacts

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Wenhong Zhang, PhD,MD

Role: primary

+86 21 52889999 ext. 8123

Other Identifiers

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KY2020-COVID-19

Identifier Type: -

Identifier Source: org_study_id

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