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

NCT ID: NCT06555900

Last Updated: 2024-08-15

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-12-17

Study Completion Date

2025-06-30

Brief Summary

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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.

Detailed Description

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Conditions

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

Study Design

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Observational Model Type

OTHER

Study Time Perspective

OTHER

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Maximum Eligible Age

99 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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University Hospital, Brest

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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CHU de Brest

Brest, , France

Site Status RECRUITING

Countries

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France

Central Contacts

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Olivier HUET

Role: CONTACT

0298347288 ext. +33

Facility Contacts

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Olivier Huet

Role: primary

0298347288

Other Identifiers

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29BRC20.0293 - PREDICT-CE

Identifier Type: -

Identifier Source: org_study_id

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