The COVID-19 Mobile Health Study (CMHS)

NCT ID: NCT04275947

Last Updated: 2020-02-19

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

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

UNKNOWN

Total Enrollment

450 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-02-14

Study Completion Date

2020-05-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

This study evaluates a brand-new cell phone-based auto-diagnosis system, which is based on the clinical guidelines, clinical experience, and statistic training model. We will achieve secure and 1st hand data from physicians in Wuhan, which including 150 cases in the training cohort and 300 cases in the validation cohort.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

COVID-19

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Training

nCapp, a cell phone-based auto-diagnosis system

Intervention Type OTHER

Combined with 15 questions online, and a predicated formula to auto-diagnosis of the risk of COVID-19

Validation

nCapp, a cell phone-based auto-diagnosis system

Intervention Type OTHER

Combined with 15 questions online, and a predicated formula to auto-diagnosis of the risk of COVID-19

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

nCapp, a cell phone-based auto-diagnosis system

Combined with 15 questions online, and a predicated formula to auto-diagnosis of the risk of COVID-19

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* High risk of COVID-19
* RT-PCR test result of SAR2-CoV-19

Exclusion Criteria

* Not available for RT-PCR test result of SAR2-CoV-19
Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Shanghai Respiratory Research Institution

UNKNOWN

Sponsor Role collaborator

Chinese Alliance Against Lung Cancer

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Bai Chunxue

Chair

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Chunxue Bai

Role: PRINCIPAL_INVESTIGATOR

Shanghai Respiratory Research Institution

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Renmin Hospital of Wuhan University

Wuhan, Hubei, China

Site Status RECRUITING

Countries

Review the countries where the study has at least one active or historical site.

China

Central Contacts

Reach out to these primary contacts for questions about participation or study logistics.

Chunxue Bai

Role: CONTACT

+8618621170011‬

Dawei Yang

Role: CONTACT

+8613564703813

Facility Contacts

Find local site contact details for specific facilities participating in the trial.

Chunxue Bai

Role: primary

References

Explore related publications, articles, or registry entries linked to this study.

Yang D, Zhang X, Powell CA, Ni J, Wang B, Zhang J, Zhang Y, Wang L, Xu Z, Zhang L, Wu G, Song Y, Tian W, Hu JA, Zhang Y, Hu J, Hong Q, Song Y, Zhou J, Bai C. Probability of cancer in high-risk patients predicted by the protein-based lung cancer biomarker panel in China: LCBP study. Cancer. 2018 Jan 15;124(2):262-270. doi: 10.1002/cncr.31020. Epub 2017 Sep 20.

Reference Type BACKGROUND
PMID: 28940455 (View on PubMed)

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

CAALC-008-CMHS

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.

NoRCoRP Assessment Clinic
NCT04710836 COMPLETED