Observational Cohort of COVID-19 Patients in Hubei Province (OCCP-HP)

March 6, 2024 updated by: Dao Wen Wang

Observational Cohort of The Effects of Clinical Indicators, Drug Use and Genotypes on The Clinical Prognosis of COVID-19 Patients in Hubei Province

This study intends to use the relevant case data of COVID-19 in Hubei Province, using big data processing and mining methods to evaluate the effects of clinical indicators, drug use and genes on the clinical prognosis of COVID-19 patients, so as to provide a theoretical basis for the treatment of these diseases and reduce the mortality.

Study Overview

Status

Completed

Intervention / Treatment

Detailed Description

Hubei Province, as the forefront of the fight against epidemic, has the largest number of patients infected with SARS-CoV-2 and the highest quality medical data. However, so far, these data have not been fully analyzed, if these data can not be mined and used, it will be a great loss to the whole human race. By fully mining and analyzing these data, we can sum up a large number of experiences related to COVID-19, summarize various laws of this kind of disease, and provide clinical evidence based on large samples for the research of this disease, eventually contribute China's experience to the global fight against the epidemic.

Based on the above background, this study intends to use the relevant case data of COVID-19 in Hubei Province, using big data processing and mining methods to evaluate the effects of clinical indicators, drug use and genes on the clinical prognosis of COVID-19 patients, so as to provide a theoretical basis for the treatment of these diseases and reduce the mortality.

Study Type

Observational

Enrollment (Actual)

68000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Hubei
      • Wuhan, Hubei, China, 430030
        • Tongji Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

14 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

This study is a hospital-based observational study initiated by Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology. Trained researchers are responsible for screening and joining the group. About 6,8000 COVID-19 patients in Hubei Province were expected to be included in this study. Patients enrolled in the group will undergo baseline survey and follow-up according to the program.

Description

Inclusion Criteria:

  1. Age ≥ 18, regardless of gender;
  2. A history of epidemiology, including travel or residence in high-risk areas or other communities with case reports within 14 days before the onset of the disease, or have a history of contact with novel coronavirus infection (those who are positive for nucleic acid tests); or patients with fever or respiratory symptoms from the community with case reports; or aggregative onset;
  3. Corresponding clinical manifestations, including respiratory symptoms such as fever, with typical imaging features of COVID-19, normal or decreased white blood cell count and decreased lymphocyte count in the early stage of the disease;
  4. Clear etiological evidence, including real-time fluorescent RT-PCR detection of novel coronavirus nucleic acid positive, or viral gene sequencing, is highly homologous to novel coronavirus.

Exclusion Criteria:

Patients who meet any of the following criteria cannot be enrolled in this study:

  1. Patients refused to participate in this study;
  2. According to the researchers, patients are unable to complete this study or comply with the requirements of this study (due to management or other reasons).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
patients with coronavirus disease 2019 (COVID-19)
Patients diagnosed with COVID-19 in Hubei Province
No intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
All-cause mortality
Time Frame: 2 years
Numbers and dates of death in each group
2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 1, 2020

Primary Completion (Actual)

March 1, 2024

Study Completion (Actual)

March 1, 2024

Study Registration Dates

First Submitted

November 10, 2022

First Submitted That Met QC Criteria

November 10, 2022

First Posted (Actual)

November 14, 2022

Study Record Updates

Last Update Posted (Actual)

March 7, 2024

Last Update Submitted That Met QC Criteria

March 6, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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