Prediction of Pressure Injury Risk in ICU Using Data Mining
NCT07306143 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 500
Last updated 2026-05-01
Summary
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.
Conditions
- Pressure Injury
Interventions
- OTHER
-
No intervention
This is a retrospective observational study. No interventions will be applied. All data will be obtained from existing medical records.
Sponsors & Collaborators
-
Abant Izzet Baysal University
lead OTHER
Principal Investigators
-
Saadet Can Çiçek, Assoc. Prof., PhD · Abant Izzet Baysal University
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2026-01-16
- Primary Completion
- 2026-04-01
- Completion
- 2026-04-29
Countries
- Turkey (Türkiye)
Study Locations
More Related Trials
-
Machine Learning in the ICU: Predicting Mortality in Bloodstream Infections (ICU:Intensive Care Unit)
NCT06167083 ·Status: COMPLETED
-
The Investigation of Predicting Mortality and Morbidity in Patients Admitted to Intensive Care Unit With Thoracic Trauma Using Selected Biomarkers and Parameters
NCT06930222 ·Status: COMPLETED
-
Examination of the Pressure Ulcers in Intensive Care Patients.
NCT05795777 ·Status: COMPLETED
-
Machine Learning Prediction of Parameters of Early Warning Scores in Intensive Care Units
NCT06259812 ·Status: ACTIVE_NOT_RECRUITING
-
ICU Mortality Predictors of Trauma Patients
NCT03894111 ·Status: COMPLETED
-
Prevalence of Potentially Inappropriate Treatments
NCT03520270 ·Status: COMPLETED
-
Cross-Cultural Adaptation on CALCULATE in a Critical Care Unit
NCT06851416 ·Status: COMPLETED
-
Arterial and End-Tidal CO2 Gradient as a Mortality Predictor in Critical Care Patients
NCT05341258 ·Status: COMPLETED ·Phase: NA
-
The Impact of POCUS on Treatment Planning and Prognosis in the ICU
NCT06613464 ·Status: COMPLETED
-
Risk Modelling for Quality Improvement in the Critically Ill: Making Best Use of Routinely Available Data
NCT02454257 ·Status: COMPLETED
-
The De-Morton Mobility Index Turkish Version in Intensive Care Patients
NCT05196997 ·Status: COMPLETED
-
Predictors of Mortality in Traumatic Brain Injury Patients in Intensive Care Unit
NCT06183749 ·Status: NOT_YET_RECRUITING
-
The Role of NEWS on Intensive Care Discharges
NCT03626961 ·Status: COMPLETED
-
Assessment of Organ Failure Risk Predictions in ICU
NCT06814327 ·Status: ACTIVE_NOT_RECRUITING
-
Prevalence of Pressure Ulcers Among Critically Ill Patients and Factors Associated With Their Occurrence in the ICU
NCT03912467 ·Status: COMPLETED
-
Predictive Value of the mNutric Score and Survival Analysis in Critically Ill Patients Hospitalised in the Intensive Care Unit
NCT06912204 ·Status: COMPLETED
-
Machine Learning-based Longitudinal Study of Post-ICU Syndrome Development Trajectory in Critically Ill Patients and Construction of Clinical Early Warning Models: a Research Protocol for Longitudinal Study
NCT06427265 ·Status: RECRUITING
-
Predictors of Mortality in Multiple Trauma Patients
NCT07185529 ·Status: COMPLETED
-
Thromboembolic Complications in COVID-19 Patients in Intensive Care Unit
NCT06037707 ·Status: COMPLETED
-
Effect of Blood Group on the Survival Status of Intensive Care Patients
NCT04460625 ·Status: COMPLETED
-
Disease Severity, Mortality Risk, and Muscle Function in Intensive Care Unit Patients
NCT07124442 ·Status: RECRUITING
-
Prospective Validation of GRADY: A Machine Learning Model for Early Sepsis and Bacteremia Detection in ICU Patients
NCT07126106 ·Status: RECRUITING
-
Assessment of Oxygen Extraction Rate Changes Following Red Blood Cell Transfusion in the Intensive Care Unit
NCT05798130 ·Status: COMPLETED
-
Evaluating the Efficacy of Artificial Intelligence Models in Predicting Intensive Care Unit Admission Needs
NCT06494748 ·Status: COMPLETED
-
Investigation of The Prevalence of Sepsis in Adults in Multicenter Intensive Care Unıts in Turkey
NCT03179189 ·Status: UNKNOWN