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Predictive Analytics in Lower Respiratory Tract Infections (VA-LRTIs) (PA in VA-LRTIs)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04727957
Recruitment Status : Not yet recruiting
First Posted : January 27, 2021
Last Update Posted : April 15, 2021
Sponsor:
Information provided by (Responsible Party):
Miia M Jansson, PhD, University of Oulu

Study Description
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Brief Summary:
To determine the accuracy and generalizability of VA-LRTI algorithm to detect and predict three high-incidence and high-impact VAEs from electronic health records data: 1) ventilator-associated event, 2) ventilator-associated pneumonia, and 3) ventilator-associated tracheobronchitis.

Condition or disease Intervention/treatment
Ventilator-Associated Event Other: Diagnostic and prognostic models for VA-LRTIs

Study Design
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Study Type : Observational
Estimated Enrollment : 30000 participants
Observational Model: Case-Control
Time Perspective: Retrospective
Official Title: Predictive Analytics in Ventilator-Associated Events
Estimated Study Start Date : June 1, 2021
Estimated Primary Completion Date : December 31, 2021
Estimated Study Completion Date : December 31, 2021
Groups and Cohorts
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Group/Cohort Intervention/treatment
Dataset for development and testing Other: Diagnostic and prognostic models for VA-LRTIs
Diagnostic and prognostic models for VA-LRTIs
Dataset for external validation Other: Diagnostic and prognostic models for VA-LRTIs
Diagnostic and prognostic models for VA-LRTIs


Outcome Measures
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Primary Outcome Measures :
  1. Number of participants with VA-LRTI as assessed by risk-calculator [ Time Frame: 1.6.-31.12.2021 ]
    Prediction model to be used at the moment of diagnosis and algorithms to be used prior IMV to predict the risk of VA-LRTI.


Secondary Outcome Measures :
  1. Rate of in-hospital mortality [ Time Frame: 1.6.-31.12.2021 ]
    Prediction model to be used at the moment of diagnosis to predict the risk of mortality in VA-LRTIs.


Eligibility Criteria
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Ages Eligible for Study:   16 Years to 100 Years   (Child, Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
Adult mixed medical-surgical ICU patients
Criteria
All invasively ventilated ICU patient (aged 18 or over)
Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04727957


Contacts
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Contact: Miia Jansson, PhD +358 50 470 12 62 miia.jansson@oulu.fi

Locations
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Finland
Univeristy of Oulu
Oulu, Finland
Contact: Miia Jansson, PhD       miia.jansson@oulu.fi   
Sponsors and Collaborators
University of Oulu
More Information
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Responsible Party: Miia M Jansson, PhD, Adjunct Professor, PhD, University of Oulu
ClinicalTrials.gov Identifier: NCT04727957    
Other Study ID Numbers: University of Oulu
First Posted: January 27, 2021    Key Record Dates
Last Update Posted: April 15, 2021
Last Verified: April 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Undecided

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No