AzTrials
AzTrials

Artificial IntelligenceNCT05914571

Artificial Intelligence With Determination of Central Venous Catheter Line Associated Infection Risk

An observational study of Artificial Intelligence and Central Venous Catheter Associated Bloodstream Infection, run by Saglik Bilimleri Universitesi.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record
Search all trials

Trial summary

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… Read more about this study

Who is it for?
Ages 18 years and older
How many people
2,000 participants
Where
No sites listed yet
Study dates
Jul 2023to Dec 2024
Phase
Observational
Are there results?
None posted in the registry

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: All patients admitted to the GICU and meeting the research criteria will be included in the study.

Who may be able to join

  • 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.

Who cannot join

  • 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.

About this study

Official title: 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:

Read more
  • 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.

Read the detailed description

The applications of artificial intelligence-based technologies in nursing are still in their infancy, and it is emphasized that nurses have limited participation in these processes. We think that our study will be supportive in determining the focal points in the clinical practice of nurses in terms of determining the risk level and will contribute to the development of patient goals. It is also important in terms of creating evidence for making the effects of nursing practices visible. In this context, the aim of our study is to develop a risk estimation tool to determine the risk levels of individuals in terms of CVC-related infection in adult intensive care patients by using artificial intelligence technology, to test the accuracy of the risk level estimation and to apply the tool to evaluate the results in the clinic. In addition, our secondary aim is to present the effects of nursing care in preventing the risk of CVC-related infection with the artificial intelligence model in an evidence-based manner.

Keywords
nursing, artificial intelligence, Central Venous Catheter Associated Bloodstream Infection

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. risk of central venous catheter infection

    Measured: january 2018 - december 2022

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted22 Jun 2023
  2. Study startJul 2023 (estimated)
  3. Primary completionDec 2023 (estimated)
  4. Study completionDec 2024 (estimated)

Resources

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
Other
Time perspective
Retrospective
Enrolment
2,000 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT05914571
Sponsor's protocol ID
OTCELEBİ
Status last verified
Jun 2023
First submitted
13 Jun 2023
Last updated
22 Jun 2023
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Questions about this trial

What is this clinical trial studying?

An observational study of Artificial Intelligence and Central Venous Catheter Associated Bloodstream Infection, run by Saglik Bilimleri Universitesi.

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 4 inclusion and 5 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: status not confirmed, as of the sponsor's last update on 22 Jun 2023. Status can change between updates, so confirm with the study contact before making plans.

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?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

risk of central venous catheter infection (time frame: january 2018 - december 2022). 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 NCT05914571.

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 22 Jun 2023; AzTrials last refreshed its copy on 6 Nov 2026.

AzTrials uses cookies for analytics and advertising. You can accept or reject them; the site works either way. Privacy Policy.

Free account

Log in to keep searching

You’ve used your 3 free searches. AzTrials is free: log in or create a free account to keep searching clinical trials and save the ones you want to follow.

Create a free accountLog in