- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06452797
Prognostic Estimates Among ICU Clinicians
September 10, 2025 updated by: Jared Greenberg, Rush University Medical Center
Prognostic Estimates Among ICU Clinicians Caring for Patients Requiring Prolonged Mechanical Ventilation
One challenge with decision making for mechanically ventilated is that their prognosis is often uncertain.
The ProVent-14 score incorporates clinical variables measured on the 14th day of mechanical ventilation to predict risk of death in one year.
The ProVent-14 is easy to calculate has been externally validated.
However, it is unclear how often clinicians use the ProVent-14 score to predict long-term outcomes for patients requiring 14 days of mechanical ventilation or if it helps clinicians make more accurate predictions.
The purpose of this study is to determine whether ICU clinicians who receive a patient's ProVent-14 score make more accurate predictions for mortality at one year than ICU clinicians who do not.
Study Overview
Status
Recruiting
Conditions
Intervention / Treatment
Study Type
Interventional
Enrollment (Estimated)
238
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Jared Greenberg, MD
- Phone Number: 312-942-6744
- Email: jared_greenberg@rush.edu
Study Locations
-
-
Illinois
-
Chicago, Illinois, United States, 60612
- Recruiting
- Rush University Medical Center
-
Contact:
- Jared A Greenberg, MD
- Phone Number: 312-942-6744
- Email: jared_greenberg@rush.edu
-
Oak Park, Illinois, United States, 60304
- Active, not recruiting
- Rush Oak Park Hospital
-
-
North Carolina
-
Chapel Hill, North Carolina, United States, 27599
- Recruiting
- University of North Carolina
-
Contact:
- David Y Hwang, MD
- Phone Number: 919-966-8178
- Email: david_hwang@med.unc.edu
-
Principal Investigator:
- David Y Hwang
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Description
Inclusion Criteria:
- ICU day-shift attending physician, fellow physician, advanced practice provider, or nurse
- Caring directly for a patient who requires invasive mechanical ventilation, 14-16 days after initial intubation, not actively transitioning to comfort-focused care and not with a neuromuscular disease (i.e. ALS) as a cause of respiratory failure.
Exclusion Criteria:
- None
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
No Intervention: Usual Prognostic Approach
Participants will make form a prognosis using their usual approach
|
|
|
Experimental: ProVent-14 Guided Prognostic Approach
Participants will be asked to form a prognosis after being provided the patient's ProVent-14 score and its meaning
|
A score to estimate one-year mortality for patients requiring at least 14 days of mechanical ventilation
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy of one-year mortality rate predictions
Time Frame: One-year after participant enrollment
|
Associations between participant predictions (0-100% risk of death) and patient outcomes (death or not) will be determined using logistic regression.
Accuracy will be determined by Area Under the Receiver Operating Characteristic (AUROC) analysis.
|
One-year after participant enrollment
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Confidence in prediction
Time Frame: Upon enrollment
|
1-10 scale, 10 being most confident
|
Upon enrollment
|
|
Comfort communicating prognosis to patient/surrogate
Time Frame: Upon enrollment
|
1-10 scale, 10 being most comfortable
|
Upon enrollment
|
|
Recommendation to transition to comfort-focused care
Time Frame: Upon enrollment
|
Yes or No
|
Upon enrollment
|
|
Accuracy of timing of patient death
Time Frame: One-year after participant enrollment
|
Participants who predict the patient has a <50% chance of survival will be asked to predict the month the patient will pass away
|
One-year after participant enrollment
|
Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy of factors influencing prediction
Time Frame: One-year after participant enrollment
|
Participants will list up to 5 characteristics of the patient's situation that influenced their prediction
|
One-year after participant enrollment
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Hough CL, Caldwell ES, Cox CE, Douglas IS, Kahn JM, White DB, Seeley EJ, Bangdiwala SI, Rubenfeld GD, Angus DC, Carson SS; ProVent Investigators and the National Heart Lung and Blood Institute's Acute Respiratory Distress Syndrome Network. Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation. Crit Care Med. 2015 Nov;43(11):2339-45. doi: 10.1097/CCM.0000000000001205.
- Cox CE, White DB, Hough CL, Jones DM, Kahn JM, Olsen MK, Lewis CL, Hanson LC, Carson SS. Effects of a Personalized Web-Based Decision Aid for Surrogate Decision Makers of Patients With Prolonged Mechanical Ventilation: A Randomized Clinical Trial. Ann Intern Med. 2019 Mar 5;170(5):285-297. doi: 10.7326/M18-2335. Epub 2019 Jan 29.
- Detsky ME, Harhay MO, Bayard DF, Delman AM, Buehler AE, Kent SA, Ciuffetelli IV, Cooney E, Gabler NB, Ratcliffe SJ, Mikkelsen ME, Halpern SD. Discriminative Accuracy of Physician and Nurse Predictions for Survival and Functional Outcomes 6 Months After an ICU Admission. JAMA. 2017 Jun 6;317(21):2187-2195. doi: 10.1001/jama.2017.4078.
- Buehler AE, Ciuffetelli IV, Delman AM, Kent SA, Bayard DF, Cooney E, Halpern SD, Detsky ME. Contributors to Intensive Care Unit Clinicians' Predictions of Patient Outcomes: A Qualitative Analysis. Am J Crit Care. 2018 Nov;27(6):445-453. doi: 10.4037/ajcc2018100.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
June 18, 2024
Primary Completion (Estimated)
June 15, 2027
Study Completion (Estimated)
June 15, 2027
Study Registration Dates
First Submitted
June 5, 2024
First Submitted That Met QC Criteria
June 5, 2024
First Posted (Actual)
June 11, 2024
Study Record Updates
Last Update Posted (Estimated)
September 17, 2025
Last Update Submitted That Met QC Criteria
September 10, 2025
Last Verified
September 1, 2025
More Information
Terms related to this study
Other Study ID Numbers
- 24030801
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
UNDECIDED
IPD Plan Description
to be determined
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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