NCT06667869: ROMANTIC

multipaRameter mOnitoring systeM for sedAtion iNThe ICu

Recruiting now Last updated 8 June 2025

What this trial tests

trial testing Sedative in Sedation Complication in 80 participants. Currently enrolling.

Timeline

14 February 2025

Primary endpoint
1 July 2026

15 December 2026

Quick facts

Lead sponsor	Pontificia Universidad Catolica de Chile
Status	Recruiting now
Study type	OBSERVATIONAL
Enrollment	80
Start date	14 February 2025
Primary completion	1 July 2026
Estimated completion	15 December 2026
Sites	2 locations across Chile

Drugs / interventions tested

• Sedative — full drug profile →

Conditions studied

• Sedation Complication — all drugs for Sedation Complication →

Sponsor

Pontificia Universidad Catolica de Chile — full company profile →

Who can join

18 and older, any sex, with Sedation Complication. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.