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| Name | Class |
|---|---|
| University of North Carolina, Chapel Hill | OTHER |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Usual Prognostic Approach | No Intervention | Participants will make form a prognosis using their usual approach | |
| ProVent-14 Guided Prognostic Approach | Experimental | Participants will be asked to form a prognosis after being provided the patient's ProVent-14 score and its meaning |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ProVent-14 score | Behavioral | A score to estimate one-year mortality for patients requiring at least 14 days of mechanical ventilation |
|
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of one-year mortality rate predictions | 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 |
| Measure | Description | Time Frame |
|---|---|---|
| Confidence in prediction | 1-10 scale, 10 being most confident | Upon enrollment |
| Comfort communicating prognosis to patient/surrogate | 1-10 scale, 10 being most comfortable |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of factors influencing prediction | Participants will list up to 5 characteristics of the patient's situation that influenced their prediction | One-year after participant enrollment |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jared Greenberg, MD | Contact | 312-942-6744 | jared_greenberg@rush.edu |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Rush University Medical Center | Recruiting | Chicago | Illinois | 60612 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30690645 | Background | 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. | |
| 28528347 |
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to be determined
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| Upon enrollment |
| Recommendation to transition to comfort-focused care | Yes or No | Upon enrollment |
| Accuracy of timing of patient death | 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 |
| Rush Oak Park Hospital | Active, not recruiting | Oak Park | Illinois | 60304 | United States |
| University of North Carolina | Recruiting | Chapel Hill | North Carolina | 27599 | United States |
|
| 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. |
| 26247337 | Background | 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. |
| 30385535 | Background | 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. |