Prediction of Pressure Injury Risk in ICU Using Data Mining (ICU)
Prediction of Pressure Injury Risk in the Intensive Care Unit: A Comparative Analysis of Data Mining Algorithms in a Single-Center Retrospective Cohort
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
This observational study uses a retrospective cohort design to analyze the clinical, demographic, laboratory, and nursing documentation records of adult intensive care unit (ICU) patients hospitalized between October 10, 2020, and October 10, 2025. The purpose of the study is to identify factors associated with the development of pressure injury and to compare the predictive performance of multiple data mining and machine learning algorithms, including logistic regression, decision trees, random forest, support vector machines, and gradient boosting models.
Data collection will involve reviewing archived ICU records, patient files, and nursing observation forms. No new data will be collected directly from patients, and no medical interventions or prospective follow-up will be performed. All extracted data will be fully anonymized prior to analysis. The study will be conducted in accordance with ethical principles and has been approved by the Bolu Abant Izzet Baysal University Non-Interventional Clinical Research Ethics Committee.
The expected outcome of this study is to identify the most accurate predictive model for pressure injury risk and to support clinical decision-making processes by contributing to early prevention strategies in the ICU.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Saadet Can Çiçek, Assoc. Prof., PhD
- Phone Number: +905062846936
- Email: saadet.cancicek@ibu.edu.tr
Study Locations
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Bolu
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Bolu, Bolu, Turkey (Türkiye), 14100
- Bolu Izzet Baysal State Hospital
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Merkez, Bolu, Turkey (Türkiye), 14100
- Bolu Izzet Baysal State Hospital
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria
- Patients hospitalized in the intensive care unit between October 10, 2020, and * October 10, 2025
- Adult patients aged 18 years and older
- Length of intensive care unit stay of at least 24 hours
- Availability of complete and accessible electronic or paper-based medical records
Exclusion Criteria
- Patients younger than 18 years
- Intensive care unit stay shorter than 24 hours Incomplete, missing, or inconsistent electronic or paper-based medical records
- Presence of a pressure injury diagnosed before or at the time of intensive care unit admission
- Inability to extract pressure injury-related data from medical records
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
ICU Patient Cohort
Adult patients who will be hospitalized in the intensive care unit between October 10, 2020 and October 10, 2025.
No interventions will be applied, and all data will be obtained from existing medical records.
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This is a retrospective observational study.
No interventions will be applied.
All data will be obtained from existing medical records.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Prediction accuracy of pressure injury development
Time Frame: 10 October 2020 to 10 October 2025
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The primary outcome is the predictive accuracy of data mining algorithms in identifying the risk of developing pressure injury among patients hospitalized in the intensive care unit (ICU).
Accuracy metrics such as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, precision, recall, and F1-score will be calculated using retrospective medical record data.
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10 October 2020 to 10 October 2025
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Saadet Can Çiçek, Assoc. Prof., PhD, Abant Izzet Baysal University
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- AIBU-SBF-NSY-2025
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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