Critical IllnessREASTOCNCT02893462
Setting up a Warehouse of Physiological Data and Biomedical Signals in Adult Intensive Care
An observational study of Critical Illness, run by University Hospital, Brest at 1 site in France.
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Critical Illness
- How many people
- 1,500 participants
- Where
- 1 siteFrance
- Study dates
- 1 Jan 2015to 1 Jan 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Population of patients admitted in the intensive care unit for monitoring of vital failure
Who may be able to join
- Any adult patient admitted in Brest University Hospital's intensive care unit for monitoring of vital failure
Who cannot join
- Refusal to participate
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site, 1 recruiting
- Recruiting
CHRU de Brest
Brest, 29609
Erwan L'Her, Professor, 02 98 34 71 81, erwan.lher@chu-brest.fr
About this study
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.
Read the 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:
- the constitution of a warehouse of physiological data of grown-up patients in acute situation (intensive care unit);
- 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;
- the use of intelligent tools of auto-learning and elaboration of complex multimodal models for purposes of prediction of events;
- Conditions
- Critical Illness
- Keywords
- data warehousing, data aggregation, data mining
- Medical subject headings
- Critical Illness
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of participants with physiological signal abnormality
Whereas this is a data mining process (non-deterministic approach), no description can be provided
Measured: from two to twenty-four hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Sep 2016 (estimated)
- Study start1 Jan 2015
- Primary completion1 Jan 2025 (estimated)
- Study completion1 Jan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Critical IllnessStudies of the same condition, open and under way.
- More trials run by University Hospital, BrestThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Brest
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Erwan L'Her, Professor, Principal investigator, CHRU de Brest
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02893462
- Sponsor's protocol ID
- REASTOC
- Acronym
- REASTOC
- Status last verified
- Aug 2024
- First submitted
- 30 Aug 2016
- Last updated
- 12 Aug 2024
- Results posted
- No
- Data monitoring committee
- No
- Individual data sharing
- Yes: Ananymized warehouse platform will be shared to other researchers all over the world
Publications
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.
PubMed 35169170L'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.
PubMed 33886075L'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.
PubMed 30666472
Study at a glance
From the registry record, last updated by the sponsor on 12 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Setting up a Warehouse of Physiological Data and Biomedical Signals in Adult Intensive Care
- ClinicalTrials.gov ID
- NCT02893462
- Acronym / sponsor ID
- REASTOC / REASTOC
- Conditions
- Critical Illness
- Keywords
- data warehousing, data aggregation, data mining
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- University Hospital, BrestUniversity, hospital or other
- Study start
- 1 Jan 2015 (actual)
- Primary completion
- 1 Jan 2025 (estimated)
- Study completion
- 1 Jan 2027 (estimated)
- First posted
- 8 Sep 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- the constitution of a warehouse of physiological data of grown-up patients in acute situation (intensive care unit);
- 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;
- the use of intelligent tools of auto-learning and elaboration of complex multimodal models for purposes of prediction of events;
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Population of patients admitted in the intensive care unit for monitoring of vital failure
Key inclusion criteria (1 listed)
- Any adult patient admitted in Brest University Hospital's intensive care unit for monitoring of vital failure
Key exclusion criteria (1 listed)
- Refusal to participate
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Number of participants with physiological signal abnormality
Time frame: from two to twenty-four hours
Whereas this is a data mining process (non-deterministic approach), no description can be provided
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Aug 2024.
- Derived from this study: PubMed 35169170Bodenes 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.
- Derived from this study: PubMed 33886075L'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.
- Derived from this study: PubMed 30666472L'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.
- Individual participant dataSharing planned: Yes. Ananymized warehouse platform will be shared to other researchers all over the world
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Erwan L'Her, Professor principal investigator
CHRU de Brest
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Critical Illness, run by University Hospital, Brest at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Erwan L'Her, Professor (02 98 34 71 81, erwan.lher@chu-brest.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of participants with physiological signal abnormality (time frame: from two to twenty-four hours). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02893462, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Aug 2024.