multipaRameter mOnitoring systeM for sedAtion iNThe ICu

NCT06667869 | Recruiting

• 2 other identifiers: 230926014FONDEF ID24I10057
• Study Type: observational
• Target: 80
• Locations: 1 country
• Sites: 2

Brief Summary

The administration of sedation in Intensive Care Units (ICU) is a vital and complex task, essential for the well-being of critically ill patients. Proper dosing is crucial, as both under-dosing and overdosing have adverse consequences for patients, including risks such as accidental extubation, ventilator disconnections, delirium, prolonged ventilation, ICU stays, and even increased mortality. Monitoring sedation levels is essential to maintain a balance in sedative administration. Clinical scales (RASS/SAS) are currently used as the reference method, but they have limitations. These scales may be inadequate when the patient is unresponsive or when neuromuscular blockers are used. An alternative is electroencephalography (EEG)-based monitors, though they also have limitations in accurately representing the level of hypnosis. The proposal is to develop an advanced multiparameter system called ROMANTIC, which utilizes machine learning algorithms to monitor sedation status continuously. The aim is for this system to surpass current techniques and provide a more accurate determination of sedation levels. ROMANTIC would incorporate a variety of variables, demographic, pharmacological, hemodynamic, respiratory, and EEG data, to predict sedation status in three categories: under-dosing, appropriate dosing, and overdosing. With ROMANTIC, clinical staff (users) are expected to be able to determine sedation levels more quickly and accurately, reducing patients' wake-up times and possibly decreasing the incidence of delirium. In the long term, this could result in fewer ICU bed days, less time on mechanical ventilation, cost savings, and reduced complications. At the end of the project, the goal is to have a prototype model or software that allows non-specialized staff (users) to quickly determine sedation levels in the ICU. This machine learning-based model targets hospitals with ICUs and mechanical ventilation to offer more efficient and cost-effective clinical care. ROMANTIC seeks to innovate in sedation monitoring, providing a more advanced and precise tool for the care of critically ill patients (beneficiaries) in the ICU.

Conditions

Sedation Complication

Keywords

Intensive Care Unit; Machine Learning; Delirium; Mechanical ventilation; Monitoring

Outcome Measures

Primary Outcomes (1)

• Time to extubation

  Time elapsed from the stop of sedative drugs to extubation (assessed up to 72 hours)

  From the start of last window up to extubation (assessed up to 72 hours)

Secondary Outcomes (4)

• Length of Intensive Care Unit stay

  During intensive care unit hospitalization (assessed up to 100 days)

• Length of mechanical ventilation

  During intensive care unit hospitalization (assessed up to 100 days)

• Intensive Care Unit Delirium incidence

  From extubation to discharge from Intensive Care Unit, CAM-ICU assessed twice daily (AM/PM) for the first 5 post extubation days

• Serum concentration of sedative drugs

  At baseline of all data extraction windows (assessed at the first hour of the respective window)

Study Arms (2)

Hospital Clínico Red de Salud UC-Christus

Adult patients admitted to intensive care units at Hospital Clinico Red de Salud UC-Christus who require sedation and mechanical ventilation for more than 24 hours.

Drug: Sedative

Hospital Dr. Sotero del Rio

Adult patients admitted to intensive care units at Hospital Dr. Sotero del Rio who require sedation and mechanical ventilation for more than 24 hours.

Drug: Sedative

Interventions

Sedative DRUG

Patients admitted to intensive care units who require sedation and mechanical ventilation for more than 24 hours.

Also known as: Mechanical ventilation

Hospital Clínico Red de Salud UC-Christus; Hospital Dr. Sotero del Rio

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult patients admitted to intensive care units requiring sedation and mechanical ventilation for more than 24 hours.

You may qualify if:

• Patients admitted to adult critical care units
• Individuals over 18 years old
• Requiring sedation for more than 24 hours
• Patients needing mechanical ventilation for more than 24 hours

You may not qualify if:

• Patients with neurological pathology as the cause of mechanical ventilation (including recovered cardiocirculatory arrest, fulminant liver failure, and neurocritical conditions, except subdural hematomas or subarachnoid hemorrhages).
• Pregnancy
• Presence of psychiatric or intellectual disability prior to hospitalization
• Drug dependency
• History of chronic liver damage with hepatic encephalopathy
• Second period of mechanical ventilation during hospitalization
• Early limitation of therapeutic effort
• Patients under 18 years old

Sponsors & Collaborators

• Pontificia Universidad Catolica de Chile: lead
• Agencia Nacional de Investigacion y Desarrollo, ANID: collaborator

Study Sites (2)

Hospital Dr. Sotero del Rio

Santiago, Metropolitana de Santiago, 7700642, Chile

NOT YET RECRUITING

Hospital Clínico Pontificia Universidad Católica de Chile

Santiago, Santiago Metropolitan, 8330024, Chile

RECRUITING

Related Publications (72)

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  PMID: 37369420 BACKGROUND

• Kang J, Cho YS, Lee M, Yun S, Jeong YJ, Won YH, Hong J, Kim S. Effects of nonpharmacological interventions on sleep improvement and delirium prevention in critically ill patients: A systematic review and meta-analysis. Aust Crit Care. 2023 Jul;36(4):640-649. doi: 10.1016/j.aucc.2022.04.006. Epub 2022 Jun 17.

  PMID: 35718628 BACKGROUND

• Fiest KM, Soo A, Hee Lee C, Niven DJ, Ely EW, Doig CJ, Stelfox HT. Long-Term Outcomes in ICU Patients with Delirium: A Population-based Cohort Study. Am J Respir Crit Care Med. 2021 Aug 15;204(4):412-420. doi: 10.1164/rccm.202002-0320OC.

  PMID: 33823122 BACKGROUND

• Salluh JI, Wang H, Schneider EB, Nagaraja N, Yenokyan G, Damluji A, Serafim RB, Stevens RD. Outcome of delirium in critically ill patients: systematic review and meta-analysis. BMJ. 2015 Jun 3;350:h2538. doi: 10.1136/bmj.h2538.

  PMID: 26041151 BACKGROUND

• Stollings JL, Kotfis K, Chanques G, Pun BT, Pandharipande PP, Ely EW. Delirium in critical illness: clinical manifestations, outcomes, and management. Intensive Care Med. 2021 Oct;47(10):1089-1103. doi: 10.1007/s00134-021-06503-1. Epub 2021 Aug 16.

  PMID: 34401939 BACKGROUND

Biospecimen

Retention: SAMPLES WITHOUT DNA

Blood samples for sedatives quantification

MeSH Terms

Conditions

Delirium

Interventions

Hypnotics and Sedatives; Respiration, Artificial

Condition Hierarchy (Ancestors)

Confusion; Neurobehavioral Manifestations; Neurologic Manifestations; Nervous System Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Neurocognitive Disorders; Mental Disorders

Intervention Hierarchy (Ancestors)

Central Nervous System Depressants; Physiological Effects of Drugs; Pharmacologic Actions; Chemical Actions and Uses; Central Nervous System Agents; Therapeutic Uses; Airway Management; Therapeutics; Resuscitation; Emergency Treatment; Respiratory Therapy

Study Officials

• Juan C. Pedemonte, M.D.

  Pontificia Universidad Catolica de Chile

  STUDY DIRECTOR

Central Study Contacts

Juan C. Pedemonte, M.D.

CONTACT

+56 99 879 8836; jcpedemo@uc.cl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Weeks
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 30, 2024
• First Posted: October 31, 2024
• Study Start: February 14, 2025
• Primary Completion (Estimated): July 1, 2026
• Study Completion (Estimated): December 15, 2026
• Last Updated: June 8, 2025

Record last verified: 2025-02

Locations

CL (2)