Evaluation of Clinical Implementation of Machine Learning Based Decision Support for ICU Discharge

NCT05497505 | Unknown

• 1 other identifier: 2021.0528
• Study Type: observational
• Target: 1,500
• Locations: 1 country
• Sites: 2

Brief Summary

Unexpected intensive care unit (ICU) readmission is associated with longer length of stay and increased mortality. Bedside decision support may prevent readmission and mortality and may allow optimizing ICU capacity. Using a recently developed and prospectively validated machine learning model that predicts ICU readmission and mortality rate after ICU discharge and shows trends in these predictions over time, we will evaluate the implementation of the European conformity (CE)-marked software based on this model (Pacmed Critical, Pacmed, Amsterdam) by investigating whether the software improves diagnostic accuracy compared to routine clinical evaluation by the treatment team and whether availability of the information from this software leads to changes in discharge management (either postponing or advancing discharge) for patients considered eligible for discharge.

Conditions

Critical Illness

Outcome Measures

Primary Outcomes (2)

• area under the receiver operating characteristic curve (AUROC)

  comparison of AUROC between Pacmed Critical model and intensivists estimation in predicting ICU readmission and/or mortality within 7 days following ICU discharge

  7 days after ICU discharge

• calibration curve (goodness-of-fit)

  comparison of calibration curves (binned estimations) of Pacmed Critical model and intensivists estimation in predicting ICU readmission and/or mortality within 7 days following ICU discharge

  7 days after ICU discharge

Secondary Outcomes (9)

• Number of changes in ready-for-discharge decision after reviewing decision support

  through study completion (estimated 1 year)

• Readmission rate within 7 days after ICU discharge

  7 days after ICU discharge

• Mortality rate within 7 days after ICU discharge

  7 days after ICU discharge

• Length of ICU stay

  up to 90 days after ICU admission

• Length of hospital stay

  up to 90 days after hospital admission

Study Arms (2)

Discharged patients with decision support (On-period)

For patients that have been evaluated as eligible for discharge: the current ICU discharge process will be followed based on routine clinical evaluation by the treatment team in combination with ICU discharge protocols. In addition, Pacmed Critical will be used as an additional source of information. Final discharge decision will be made by lead unit intensivist responsible for medical care.

Device: Pacmed Critical

Discharged patients without decision support (Off-period)

For patients that have been evaluated as eligible for discharge: the current ICU discharge process will be followed based on routine clinical evaluation by the treatment team in combination with ICU discharge protocols. Final discharge decision will be made by lead unit intensivist responsible for medical care.

Interventions

Pacmed Critical DEVICE

For patients in the On-period, Pacmed Critical will be available as decision support after initial eligibility screening for ICU discharge by treatment team

Discharged patients with decision support (On-period)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Adult (age \>= 18 years) patients admitted to Intensive Care unit

You may qualify if:

• Admission to intensive care or medium care unit
• Age \>= 18 years
• ICU admission \> 4 hours
• Eligible for discharge at the discretion of the treatment team by not requiring treatment that can only be provided on the ICU (including but not limited to mechanical ventilation, high flow oxygen, vasopressor/inotropes, continuous renal replacement therapy).

You may not qualify if:

• No-return (to ICU/MCU) policy and/or palliative/end-of-life care
• Coronavirus disease (COVID)-19
• Patients directly transferred to other hospitals after discharge

Sponsors & Collaborators

• Patrick J. Thoral: lead
• Leiden University Medical Center: collaborator

Study Sites (2)

Amsterdam UMC, location VUmc

Amsterdam, North Holland, 1081HV, Netherlands

RECRUITING

Leiden University Medical Center (LUMC)

Leiden, South Holland, 2333 ZA, Netherlands

RECRUITING

Related Publications (2)

• Thoral PJ, Fornasa M, de Bruin DP, Tonutti M, Hovenkamp H, Driessen RH, Girbes ARJ, Hoogendoorn M, Elbers PWG. Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support: Uniting Intensivists and Data Scientists. Crit Care Explor. 2021 Sep 10;3(9):e0529. doi: 10.1097/CCE.0000000000000529. eCollection 2021 Sep.

  PMID: 34589713 BACKGROUND

• Thoral PJ, Peppink JM, Driessen RH, Sijbrands EJG, Kompanje EJO, Kaplan L, Bailey H, Kesecioglu J, Cecconi M, Churpek M, Clermont G, van der Schaar M, Ercole A, Girbes ARJ, Elbers PWG; Amsterdam University Medical Centers Database (AmsterdamUMCdb) Collaborators and the SCCM/ESICM Joint Data Science Task Force. Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example. Crit Care Med. 2021 Jun 1;49(6):e563-e577. doi: 10.1097/CCM.0000000000004916.

  PMID: 33625129 BACKGROUND

Related Links

• Sponsor Corporate Website

MeSH Terms

Conditions

Critical Illness

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Patrick J Thoral, MD

  Amsterdam UMC, location VUmc

  STUDY DIRECTOR

Central Study Contacts

Patrick J Thoral, MD

CONTACT

+31 20 444 3924; p.thoral@amsterdamumc.nl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: July 25, 2022
• First Posted: August 11, 2022
• Study Start: March 10, 2022
• Primary Completion: June 1, 2023
• Study Completion: June 1, 2023
• Last Updated: August 11, 2022

Record last verified: 2022-08

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, CSR, ANALYTIC CODE
• Time Frame: Within 3 months after publication acceptance
• Access Criteria: * Scientific Research * Data Processing/Transfer Agreement (NFU format)

Locations

NL (2)