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CovidDB: The Covid-19 Inpatient Database

CovidDB: The Covid-19 Inpatient Database

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04344171
Enrollment
5000
Registered
2020-04-14
Start date
2020-03-30
Completion date
2023-06-30
Last updated
2020-04-21

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

Conditions

COVID-19

Keywords

Sars-Cov-2, Covid-19, antiviral therapy, ventilation, ECMO

Brief summary

The aim of the project is to better understand the Covid-19 inpatient course of the disease and to quickly identify the positive experiences in the treatment in order to update guidelines for the treatment and use of medication.

Detailed description

The exponentially increasing number of SARS-CoV-2 infected people, despite the influence of the currently existing non-medical measures, is generating a rapidly increasing number of inpatients, some of whom need artificial ventilation. The average focus is on the extent to which the hospitals' capacities will be sufficient to adequately treat all patients. Regardless of this, it can be expected that even if the non-medical measures are successful, the number of inpatients treated will remain high in the course of the pandemic. With regard to the distribution of infection, it can be expected that clinics with a wide range of expertise will have to treat a large number of Covid-19 patients. So far, however, there is little to no experience in treating patients. In addition to epidemiological data, only case descriptions and some Chinese studies mostly from Wuhan based on fewer patients are available. In view of the rapidly spreading pandemic, preprints are increasingly being used. What has been missing so far is a uniform, structured recording of the courses of Covid-19 inpatients handled by many clinics, which goes beyond the epidemiological events in terms of depth of detail. With this documentation of real processes, the basis for a large number of studies and the associated better understanding of the disease process could be created. The current dynamics make it imperative that the clinics, even those who have not received the most up-to-date scientific knowledge, cannot wait for the results of studies, but rather need concrete help in the treatment of patients. Efficient assistance within the framework of a close exchange between the treatment units is only possible with a multicentre, uniform documentation environment. The aim of the project is to better understand the Covid-19 inpatient course of the disease and to quickly identify the positive experiences in the treatment in order to update guidelines for the treatment and use of medication.

Interventions

None listed

Sponsors

ClarData
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

* Covid-19 inpatients

Exclusion criteria

* assumed Covid-19 patient

Design outcomes

Primary

MeasureTime frameDescription
Number of days in hospital vs. clinical classificationthrough study completion, an average of 1 yearCorrelation between number of days in hospital and worst clinical classification will be calculated
Outcome comparison between different antiviral therapiesthrough study completion, an average of 1 yearDifferent antivirals and their combinations will be tested and the outcome (cured/deceased) will be assessed
Outcome comparisons between ventilation typesthrough study completion, an average of 1 yearDifferent ventilation types will be tested and the outcome (cured/deceased) will be assessed
Identification of risk factorsthrough study completion, an average of 1 yearClinical and laboratory risk factors will be recorded and the outcome (cured/deceased) will be assessed

Countries

Germany, Romania

Contacts

Primary ContactJulia Ferencz, MD
j.ferencz@clardata.com+4917687607223
Backup ContactSebastian Dieng
s.dieng@clardata.com+4915140212025

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 15, 2026