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

NCT ID: NCT02893462

Last Updated: 2024-08-12

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 1500 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2015-01-01
• Study Completion Date: 2027-01-01

Brief 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.

Detailed 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;

Conditions

Critical Illness

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Eligibility Criteria

Inclusion Criteria

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

Exclusion Criteria

• Refusal to participate

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University Hospital, Brest

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Erwan L'Her, Professor

Role: PRINCIPAL_INVESTIGATOR

CHRU de Brest

Locations

CHRU de Brest

Brest, , France

Site Status: RECRUITING

Countries

France

Central Contacts

Erwan L'Her, Professor

Role: CONTACT

erwan.lher@chu-brest.fr

02 98 34 71 81

Facility Contacts

Erwan L'Her, Professor

Role: primary

erwan.lher@chu-brest.fr

02 98 34 71 81

References

Bodenes L, N'Guyen QT, Le Mao R, Ferriere N, Pateau V, Lellouche F, L'Her E. Early heart rate variability evaluation enables to predict ICU patients' outcome. Sci Rep. 2022 Feb 15;12(1):2498. doi: 10.1038/s41598-022-06301-9.

Reference Type: DERIVED

PMID: 35169170 (View on PubMed)

L'Her E, Nazir S, Pateau V, Visvikis D. Accuracy of noncontact surface imaging for tidal volume and respiratory rate measurements in the ICU. J Clin Monit Comput. 2022 Jun;36(3):775-783. doi: 10.1007/s10877-021-00708-x. Epub 2021 Apr 22.

Reference Type: DERIVED

PMID: 33886075 (View on PubMed)

L'Her E, N'Guyen QT, Pateau V, Bodenes L, Lellouche F. Photoplethysmographic determination of the respiratory rate in acutely ill patients: validation of a new algorithm and implementation into a biomedical device. Ann Intensive Care. 2019 Jan 21;9(1):11. doi: 10.1186/s13613-019-0485-z.

Reference Type: DERIVED

PMID: 30666472 (View on PubMed)

Other Identifiers

REASTOC

Identifier Type: -

Identifier Source: org_study_id