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Machine Learning

Machine Learning Monitoring for Clinical Deterioration

N/A

Recruiting

Research Sponsored by AgileMD, Inc.

Eligibility Criteria Checklist

Specific guidelines that determine who can or cannot participate in a clinical trial

Must have

Admitted to an eCART-monitored medical-surgical unit (scoring location)

18 years old

Timeline

Screening 3 weeks

Treatment Varies

Follow Up the outcome of covid-19 mortality will be tracked across 12 months

Awards & highlights

Study Summary

This trial tests a tool that predicts when hospitalized patients may need intensive care or die, then offers guidance to help care teams intervene.

Who is the study for?

This trial is for adults over 18 years old who are admitted to specific hospital wards where the eCARTv5 monitoring system is used. It's not open to those under 18 or patients in wards without this technology.Check my eligibility

What is being tested?

The study tests a machine learning tool, eCARTv5, integrated into hospitals' electronic health records. It predicts which patients might soon need intensive care by analyzing their vital signs and lab results.See study design

What are the potential side effects?

Since this trial involves a diagnostic tool rather than medication, there aren't traditional side effects. However, there may be risks related to data privacy or potential stress from increased monitoring.

Eligibility Criteria

Inclusion Criteria

You may be eligible if you check “Yes” for the criteria below

Select...

I am admitted to a unit with eCART monitoring.

Select...

I am 18 years old or older.

Timeline

Screening ~ 3 weeks3 visits

Treatment ~ Varies

Follow Up ~ the outcome of covid-19 mortality will be tracked across 12 months

Screening ~ 3 weeks

Treatment ~ Varies

Follow Up ~the outcome of covid-19 mortality will be tracked across 12 months

This trial's timeline: 3 weeks for screening, Varies for treatment, and the outcome of covid-19 mortality will be tracked across 12 months for reporting.

Treatment Details

Study Objectives

Outcome measures can provide a clearer picture of what you can expect from a treatment.

Primary outcome measures

Hospital mortality for elevated risk patients

Secondary outcome measures

ICU-free days following an eCART elevation

Total hospital length of stay (LOS) for elevated risk patients

Ventilator-free days following an eCART elevation

Other outcome measures

COVID-19 Length of Stay (LOS)

COVID-19 Mortality

Sepsis Length of Stay (LOS)

+1 more

Trial Design

2Treatment groups

Experimental Treatment

Active Control

Group I: Intervention ArmExperimental Treatment1 Intervention

Intervention Arm (experimental): eCARTv5 will monitor all adult medical-surgical (ward) patients at hospitals that implement the tool in their EHR. A pre vs. post analysis will be done to compare the impact of the tool at the intervention hospitals.

Group II: Control ArmActive Control1 Intervention

Control Arm (active comparator): hospital sites that do not implement eCARTv5 will be active comparator.

0 / 2Eligibility criteria met

Find a Location

Who is running the clinical trial?

Department of Health and Human ServicesFED

226 Previous Clinical Trials

898,949 Total Patients Enrolled

AgileMD, Inc.Lead Sponsor

University of Wisconsin, MadisonOTHER

1,189 Previous Clinical Trials

3,139,531 Total Patients Enrolled

Media Library

eCARTv5 clinical deterioration monitoring (Machine Learning) Clinical Trial Eligibility Overview. Trial Name: NCT05893420 — N/A

Cardiac Arrest Research Study Groups: Intervention Arm, Control Arm

Cardiac Arrest Clinical Trial 2023: eCARTv5 clinical deterioration monitoring Highlights & Side Effects. Trial Name: NCT05893420 — N/A

eCARTv5 clinical deterioration monitoring (Machine Learning) 2023 Treatment Timeline for Medical Study. Trial Name: NCT05893420 — N/A

Frequently Asked Questions

These questions and answers are submitted by anonymous patients, and have not been verified by our internal team.

Are there any opportunities to join this experimental research project?

"According to clinicaltrials.gov, the recruitment for this medical trial commenced on December 1st 2022 and was recently modified on June 6th 2023 - thereby demonstrating that it is actively searching for participants."

Answered by AI

How many individuals are participating in this research project?

"Affirmative. According to the clinicaltrials.gov website, this experiment is actively enrolling participants. It was initially posted on December 1st 2022 and recently revised on June 6th 2023; it needs 30000 volunteers from 2 different sites for completion."

Answered by AI

Recent research and studies

clinicaltrials.govStudy

A Rapid Diagnostic of Risk in Hospitalized Patients Using Machine Learning

2022. "A Rapid Diagnostic of Risk in Hospitalized Patients Using Machine Learning". ClinicalTrials.gov. https://clinicaltrials.gov/ct2/show/NCT05893420.

All > Covid 19 > Sepsis