- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05914571
Artificial Intelligence With Determination of Central Venous Catheter Line Associated Infection Risk
Artificial Intelligence With Determination of Central Venous Catheter Line Associated Infection Risk in Adult Intensive Care Patients
The goal of this methodological, retrospective and prospective study is to; it is a tool to develop a risk estimator tool to detect risk gaps in individuals using artificial intelligence technology that is dangerous for those with CVC in adult intensive care patients, to test risk level estimation frameworks and to evaluate outcomes in the clinic. In our study, it is also our aim to protect, to present the security measures to prevent the risk of CVC with an artificial intelligence model, in an evidence-based way.
The main question[s]it aims to answer are:
- Can the risk of CVC-related infection be determined in adult intensive care patients using artificial intelligence?
- To what degree of accuracy can the risk of CVC-associated infection be determined in adult intensive care patients using artificial intelligence?
- What are the nursing practices that can reduce the risk of CVC-related infections?
Methodology to develop an artificial intelligence-based CVC-associated infection risk level determination algorithm, retrospective using data from Electronic Health Records (EHR) patient data and manual patient files between January 2018 and December 2022 to create the algorithm and test the model accuracy, and the development stages of the model After the completion of the model, up-to-date data were collected for the use of the model and it was planned to be done prospectively.
Study Overview
Status
Detailed Description
Study Type
Enrollment (Estimated)
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Received at least 48 hours of treatment in the GICU,
- Age ≥ 18,
- CVC inserted,
- No existing infection before hospitalization, patient data will be included in the dataset for designing and training the artificial intelligence model.
Exclusion Criteria:
- Age <18,
- Those receiving immunosuppressive therapy,
- Those with multiple organ failure,
- Patients undergoing organ transplantation,
- Patients with a diagnosis of chronic kidney failure, will not be included in the dataset.
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
---|---|
risk of central venous catheter infection
Time Frame: january 2018 - december 2022
|
january 2018 - december 2022
|
Collaborators and Investigators
Sponsor
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- OTCELEBİ
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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