Predicting Episodes of Intracranial Hypertension in Neuro-injured Patients: Development of a Decision Algorithm Using Artificial Intelligence (PREDICT-CE)

Regional University Hospital Center (CHRU)

Status: Enrolling

Conditions: Creation of a Warehouse of Clinical Data and Physiological Signals at the Patient's Bedside

Study type: Observational

Funder types: Other

Identifiers

NCT06555900

29BRC20.0293 - PREDICT-CE

Details and patient eligibility

About

The investigators wish to build up a database of clinical data and physiological signals with a view to developing a predictive algorithm based on continuous analysis of the intracranial pressure waveform and other parameters commonly used in intensive care to predict the occurrence of an episode of intracranial hypertension (HTIC). This algorithm will be designed using supervised learning statistical methods based on innovative statistical analysis methods (artificial intelligence). These methods are classically used to exploit massive data such as sensor data.

Enrollment: 500 estimated patients

Sex: All

Ages: 18 to 99 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• More than 18 years
• admission to intensive care for less than 3 days for a neurological lesion
• Sensor placement for intracranial pressure monitoring

Exclusion criteria

• patient under judicial protection
• refusal to participate
• patients under 18 years of age