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This study is a retrospective record review conducted among adult patients hospitalized in the intensive care unit of a tertiary hospital between October 10, 2020, and October 10, 2025. The aim of the study is to predict the risk of pressure injury development using demographic, clinical, laboratory, and nursing care-related variables by applying multiple data mining algorithms. No intervention, treatment, or patient contact will occur. All data will be extracted from existing electronic and paper-based medical records and will be fully anonymized prior to analysis. The study poses no risk to participants and will be conducted with approval from the institutional review board or ethics committee.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No intervention | Other | This is a retrospective observational study. No interventions will be applied. All data will be obtained from existing medical records. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Prediction accuracy of pressure injury development | 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. | 10 October 2020 to 10 October 2025 |
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Inclusion Criteria
Exclusion Criteria
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Adult patients aged 18 years and older who were hospitalized in the intensive care unit (ICU) of a tertiary public hospital between October 10, 2020, and October 10, 2025 will be included in this retrospective observational study. The study population includes patients with a minimum ICU stay of 24 hours and complete, accessible electronic or paper-based medical records. Patients with missing or inconsistent medical record data or with a pressure injury diagnosed before or at the time of ICU admission will be excluded. All data will be collected retrospectively from existing medical records.
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| Name | Affiliation | Role |
|---|---|---|
| Saadet Can Çiçek, Assoc. Prof., PhD | Abant Izzet Baysal University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Bolu Izzet Baysal State Hospital | Bolu | Bolu | 14100 | Turkey (Türkiye) | ||
| Bolu Izzet Baysal State Hospital |
Individual participant data (IPD) will not be shared because the study uses retrospective clinical records that contain sensitive personal health information. In accordance with institutional policies, ethical committee approval, and national data protection regulations (KVKK), IPD cannot be made publicly available. Only aggregated and de-identified results will be provided in publications.
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| ID | Term |
|---|---|
| D003668 | Pressure Ulcer |
| ID | Term |
|---|---|
| D012883 | Skin Ulcer |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |
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| Merkez |
| Bolu |
| 14100 |
| Turkey (Türkiye) |