COVIDNCT04570488
Predicting Favorable Outcomes in Hospitalized Covid-19 Patients
An observational study of COVID and Corona Virus Infection, run by NYU Langone Health at 1 site in United States.
Trial summary
Testing use of predictive analytics to predict which COVID-19+ patients are at low risk for an adverse event (ICU transfer, intubation, mortality, hospice discharge, re-presentation to the ED, oxygen requirements exceeding nasal cannula at 6L/Min) in the next 96 hours Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- COVID, Corona Virus Infection, Adverse Event
- What is being tested?
- EPIC risk score display
- How many people
- 1,415 participants
- Where
- 1 siteUnited States
- Study dates
- 15 May 2020to 7 Dec 2021
- 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 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult hospitalized COVID19+ patients predicted to have no adverse event at 96 events with a threshold at 90% PPV, with at least one low risk during their admission who are discharged alive and have not been in the ICU
Inclusion Criteria: Adult hospitalized COVID19+ patients predicted to have no adverse event at 96 events with a threshold at 90% PPV, with at least one low risk during their admission who are discharged alive and have not been in the ICU
Exclusion Criteria: Age < 18 years not hospitalized for COVID19+.
Trial locations and contacts
1 site in 1 country.
About this study
Testing use of predictive analytics to predict which COVID-19+ patients are at low risk for an adverse event (ICU transfer, intubation, mortality, hospice discharge, re-presentation to the ED, oxygen requirements exceeding nasal cannula at 6L/Min) in the next 96 hours
Read the detailed description
To assess if display of low risk of adverse event in EPIC can safely reduce length of stay and plan for discharge.
- Conditions
- COVID, Corona Virus Infection, Adverse Event
- Being tested
- EPIC risk score display
- Medical subject headings
- Coronavirus Infections
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
EPIC risk score displayOther
Display of risk score/ colored flag in Epic patient list column
| Study group | Role | What they receive |
|---|---|---|
| Quality improvement - Display | Display of risk score/ colored flag in Epic patient list column; will be viewable to all frontline workers Receives: Other: EPIC risk score display | |
| No Display | No display ("hidden") of risk score/ colored flag in Epic patient list column; not viewable to all frontline workers |
What is being measured
The primary outcome is the main question the study is designed to answer.
Reduction in days from first low-risk score to discharge
Reduction in days from first low-risk score to discharge
Measured: 96 Hours
Secondary outcomes (3)
Reduction in length of stay (LOS)
Reduction in LOS for green patients that have not been in the ICU
Measured: 96 hours
Reduction in GTD vs. LOS
Reduction in GTD vs. LOS for all green patients discharged alive vs all patients discharged alive
Measured: 96 hours
No change in 30 day re-ED presentation or hospital admission rate for cohort
No change in 30 day re-ED presentation or hospital admission rate for cohort
Measured: 96 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Sep 2020
- Study start15 May 2020
- Primary completion7 Dec 2021
- Study completion7 Dec 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for COVIDStudies of the same condition, open and under way.
- More trials run by NYU Langone HealthThe 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
- 1,415 participants (actual)
Sponsor and investigators
- Lead sponsor
- NYU Langone Health
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Jonathan Austrian, MD, Principal investigator, NYU Langone Health
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04570488
- Sponsor's protocol ID
- PAU COVID19
- Status last verified
- Dec 2022
- First submitted
- 25 Sep 2020
- Last updated
- 27 Dec 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Major VJ, Jones SA, Razavian N, Bagheri A, Mendoza F, Stadelman J, Horwitz LI, Austrian J, Aphinyanaphongs Y. Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. Appl Clin Inform. 2022 May;13(3):632-640. doi: 10.1055/s-0042-1750416. Epub 2022 Jul 27.
PubMed 35896506
Study at a glance
From the registry record, last updated by the sponsor on 27 Dec 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Predicting Favorable Outcomes in Hospitalized Covid-19 Patients
- ClinicalTrials.gov ID
- NCT04570488
- Acronym / sponsor ID
- PAU COVID19
- Conditions
- COVID, Corona Virus Infection, Adverse Event
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,415 participants (actual)
- Lead sponsor
- NYU Langone HealthUniversity, hospital or other
- Study start
- 15 May 2020 (actual)
- Primary completion
- 7 Dec 2021 (actual)
- Study completion
- 7 Dec 2021 (actual)
- First posted
- 30 Sep 2020 (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.
Testing use of predictive analytics to predict which COVID-19+ patients are at low risk for an adverse event (ICU transfer, intubation, mortality, hospice discharge, re-presentation to the ED, oxygen requirements exceeding nasal cannula at 6L/Min) in the next 96 hours
Detailed description
To assess if display of low risk of adverse event in EPIC can safely reduce length of stay and plan for discharge.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Quality improvement - Display | – | Other: EPIC risk score displayDisplay of risk score/ colored flag in Epic patient list column; will be viewable to all frontline workers |
| No Display | – | –No display ("hidden") of risk score/ colored flag in Epic patient list column; not viewable to all frontline workers |
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult hospitalized COVID19+ patients predicted to have no adverse event at 96 events with a threshold at 90% PPV, with at least one low risk during their admission who are discharged alive and have not been in the ICU
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 |
|---|---|---|
| EPIC risk score displayDisplay of risk score/ colored flag in Epic patient list column | Other | Quality improvement - Display |
Primary outcome
Reduction in days from first low-risk score to discharge
Time frame: 96 Hours
Reduction in days from first low-risk score to discharge
3 secondary outcomes
Reduction in length of stay (LOS)
Time frame: 96 hours
Reduction in GTD vs. LOS
Time frame: 96 hours
No change in 30 day re-ED presentation or hospital admission rate for cohort
Time frame: 96 hours
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 27 Dec 2022.
- Derived from this study: PubMed 35896506Major VJ, Jones SA, Razavian N, Bagheri A, Mendoza F, Stadelman J, Horwitz LI, Austrian J, Aphinyanaphongs Y. Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. Appl Clin Inform. 2022 May;13(3):632-640. doi: 10.1055/s-0042-1750416. Epub 2022 Jul 27.
- Individual participant dataSharing planned: Undecided
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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.
Jonathan Austrian, MD principal investigator
NYU Langone Health
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 COVID and Corona Virus Infection, run by NYU Langone Health at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
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 27 Dec 2022. 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 United States. 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?
Reduction in days from first low-risk score to discharge (time frame: 96 Hours). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04570488, which also lists 1 linked publication.
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 27 Dec 2022.