Setting up a Warehouse of Physiological Data and Biomedical Signals in Adult Intensive Care

Critical Illness Clinical Trial

— REASTOC  

Official title:

Setting up a Warehouse of Physiological Data and Biomedical Signals in Adult Intensive Care

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT02893462
• Other study ID #: REASTOC
• Status: Recruiting
• Start date: January 1, 2015
• Est. completion date: January 1, 2022

Study information

• Verified date: January 2021
• Source: University Hospital, Brest
• Contact: Erwan L'Her, Professor
• Phone: 02 98 34 71 81
• Email: erwan.lher[@]chu-brest.fr
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The aim of this study is the establishment of a warehouse physiological data and biomedical signal in intensive care adult patients in acute situations from particular records from the Philips Intellivue MP70 monitor.

Description:

Cardiopulmonary failures are major public health concerns, due to the aging population. Each of these situations is burdened with a poor prognosis in the medium term and a source of prolonged hospitalizations, generating significant health costs. Early detection and prediction of organ failure could reduce health costs and risks for the patient, offering a reaction early and appropriate medical technology. The proposed approach aims to optimize the knowledge of a complex physiological domain and multi-system, while promoting the automatic transfer of knowledge. The approach proposed data-mining and development of algorithms for detecting and / or predicting a strong potential for disruption because it proposes to apply innovative automated analysis procedures to a fragile patient population, and then a transfer to the medical device industry.

From communicating tools of recording of the signals, the investigator envisage in a global way:

1. the constitution of a warehouse of physiological data of grown-up patients in acute situation (intensive care unit);

2. the development by data mining of a system of detection of organs failures or adverse events basing itself on the application of innovative algorithms, allowing the decision-making operational, from the fusion of arisen ill-assorted events;

3. the use of intelligent tools of auto-learning and elaboration of complex multimodal models for purposes of prediction of events;

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1500
• Est. completion date: January 1, 2022
• Est. primary completion date: January 1, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Any adult patient admitted in Brest University Hospital's intensive care unit for monitoring of vital failure

Exclusion Criteria:

• Refusal to participate

Related Conditions & MeSH terms

• Critical Illness

Locations

Country	Name	City	State
France	CHRU de Brest	Brest

Sponsors (1)

Lead Sponsor	Collaborator
University Hospital, Brest

Country where clinical trial is conducted

France, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Number of participants with physiological signal abnormality	Whereas this is a data mining process (non-deterministic approach), no description can be provided	from two to twenty-four hours