CompletedNCT07306143

Prediction of Pressure Injury Risk in the Intensive Care Unit: A Comparative Analysis of Data Mining Algorithms in a Single-Center Retrospective Cohort

Sponsor: Abant Izzet Baysal University

Trial Details

Condition	Pressure Injury
Intervention	No intervention
Status	Completed
Participants	500
Est. Completion	1 May 2026
Last Updated	1 May 2026

Primary Outcome

Prediction accuracy of pressure injury development

Eligibility Criteria

Inclusion Criteria

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

Trial Sites

Countries

Turkey (Türkiye)

View Registry Entry

Related Analysis

Turkish ICU Study Develops AI-Powered Pressure Injury Risk Prediction Models — Implications for Australian Critical Care

Turkish researchers are developing machine learning algorithms to predict pressure injury risk in ICU patients, potentially revolutionising prevention strategies. The retrospective study of 500 patients could transform how Australian critical care teams identify high-risk patients.

Read full article →

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