SARS-CoV-1 InfectionCORONABEDBOTNCT05787405
Early Diagnosis of Clinical Evolution From SARS-CoV-2
An observational study of SARS-CoV-1 Infection, run by Fondazione Policlinico Universitario Agostino Gemelli IRCCS at 1 site in Italy.
Trial summary
The aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- SARS-CoV-1 Infection
- What is being tested?
- Artificial Intelligence methods
- How many people
- 8,000 participants
- Where
- 1 siteItaly
- Study dates
- 1 Dec 2020to 10 Jan 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: adult patients
Who may be able to join
- adult patients (18 years of age or older)
- admitted to the Gemelli and Columbus Polyclinic
- diagnosis of SARS-CoV-2 infection (suspected cases will also be included).
Who cannot join
- aaaa
Trial locations and contacts
1 site in 1 country.
About this study
Official title: CORONABED.BOT: an Automation Project Using Artificial Intelligence for Early Diagnosis of Clinical Evolution From SARS-CoV-2"
The aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected with SARS-CoV-2.
The objective of CORONABED.BOT is to analyze the care pathways of patients from the same cohort as CORONA.BOT, in order to identify the total length of stay, intensive care occupations and flows between departments, based on variables demographics and first entry clinics Early identification of patients with symptoms compatible with SARS-CoV-2 infection will enable more rapid activation of isolation procedures, contact monitoring/contact history and decisions on the most appropriate clinical pathway in terms of type of treatment and unit. Similarly, the identification of factors correlated with worse outcomes will allow more effective planning for the use of critical resources (such as intensive care and others).
- Conditions
- SARS-CoV-1 Infection
- Being tested
- Artificial Intelligence methods
- Medical subject headings
- Severe Acute Respiratory Syndrome
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence methodsOther
The aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected with SARS-CoV-2.
What is being measured
The primary outcome is the main question the study is designed to answer.
the implementation of prediction models
tThe DataMart built will allow the creation of predictive models both for diagnosis of SARS-coV-2 pneumonia as well as death
Measured: 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Mar 2023
- Study start1 Dec 2020
- Primary completion15 Jun 2023
- Study completion10 Jan 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for SARS-CoV-1 InfectionStudies of the same condition, open and under way.
- More trials run by Fondazione Policlinico Universitario Agostino Gemelli IRCCSThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 8,000 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Rita Murri, Principal investigator, Fondazione Policlinico Universitario Agostino Gemelli IRCCS
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05787405
- Sponsor's protocol ID
- CORONABED.BOT-COVID19- 3447
- Acronym
- CORONABEDBOT
- Status last verified
- Mar 2025
- First submitted
- 16 Mar 2023
- Last updated
- 12 Mar 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 12 Mar 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- CORONABED.BOT: an Automation Project Using Artificial Intelligence for Early Diagnosis of Clinical Evolution From SARS-CoV-2"
- ClinicalTrials.gov ID
- NCT05787405
- Acronym / sponsor ID
- CORONABEDBOT / CORONABED.BOT-COVID19- 3447
- Conditions
- SARS-CoV-1 Infection
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 8,000 participants (actual)
- Lead sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCSUniversity, hospital or other
- Study start
- 1 Dec 2020 (actual)
- Primary completion
- 15 Jun 2023 (actual)
- Study completion
- 10 Jan 2024 (actual)
- First posted
- 28 Mar 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected with SARS-CoV-2.
The objective of CORONABED.BOT is to analyze the care pathways of patients from the same cohort as CORONA.BOT, in order to identify the total length of stay, intensive care occupations and flows between departments, based on variables demographics and first entry clinics Early identification of patients with symptoms compatible with SARS-CoV-2 infection will enable more rapid activation of isolation procedures, contact monitoring/contact history and decisions on the most appropriate clinical pathway in terms of type of treatment and unit. Similarly, the identification of factors correlated with worse outcomes will allow more effective planning for the use of critical resources (such as intensive care and others).
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- adult patients
Key inclusion criteria (3 listed)
- adult patients (18 years of age or older)
- admitted to the Gemelli and Columbus Polyclinic
- diagnosis of SARS-CoV-2 infection (suspected cases will also be included).
Key exclusion criteria (1 listed)
- aaaa
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence methodsThe aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected with SARS-CoV-2. | Other | – |
Primary outcome
the implementation of prediction models
Time frame: 24 months
tThe DataMart built will allow the creation of predictive models both for diagnosis of SARS-coV-2 pneumonia as well as death
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Mar 2025.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Rita Murri principal investigator
Fondazione Policlinico Universitario Agostino Gemelli IRCCS
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of SARS-CoV-1 Infection, run by Fondazione Policlinico Universitario Agostino Gemelli IRCCS at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 12 Mar 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
the implementation of prediction models (time frame: 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Mar 2025.