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Predicting Favorable Outcomes in Hospitalized Covid-19 Patients

NCT ID: NCT04570488

Last Updated: 2022-12-27

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

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Recruitment Status

COMPLETED

Total Enrollment

1415 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-05-15

Study Completion Date

2021-12-07

Brief Summary

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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

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To assess if display of low risk of adverse event in EPIC can safely reduce length of stay and plan for discharge.

Conditions

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COVID Corona Virus Infection Adverse Event

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Quality improvement - Display

Display of risk score/ colored flag in Epic patient list column; will be viewable to all frontline workers

EPIC risk score display

Intervention Type OTHER

Display of risk score/ colored flag in Epic patient list column

No Display

No display ("hidden") of risk score/ colored flag in Epic patient list column; not viewable to all frontline workers

No interventions assigned to this group

Interventions

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EPIC risk score display

Display of risk score/ colored flag in Epic patient list column

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

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+.
Minimum Eligible Age

18 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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NYU Langone Health

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Jonathan Austrian, MD

Role: PRINCIPAL_INVESTIGATOR

NYU Langone Health

Locations

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NYU Langone Health

New York, New York, United States

Site Status

Countries

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United States

References

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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.

Reference Type DERIVED
PMID: 35896506 (View on PubMed)

Other Identifiers

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PAU COVID19

Identifier Type: -

Identifier Source: org_study_id