Explainable AI for Prospective Pressure Injury Staging

NCT07891689 | Not Yet Recruiting

• 1 other identifier: VYYU-SBF-HAKALTUN-004
• Study Type: observational
• Target: 415
• Locations: 1 country
• Sites: 1

Brief Summary

This prospective observational mixed-methods study aims to develop and evaluate an explainable artificial intelligence model for staging pressure injuries using standardized clinical photographs and expert panel-labeled images from adult patients. The study will also explore nurses' views on the clinical acceptability and usability of the decision-support system through semi-structured interviews.

Conditions

Pressure Injury

Keywords

Pressure injury staging; Explainable artificial intelligence; Machine learning; Clinical decision support; nurses

Outcome Measures

Primary Outcomes (1)

• Accuracy of the Explainable Artificial Intelligence Model in Pressure Injury Staging

  The proportion of pressure injury images correctly staged by the explainable artificial intelligence model compared with the reference staging determined by the expert panel. Accuracy will be calculated as the number of correctly classified images divided by the total number of evaluable images.

  From completion of image collection through completion of data analysis, approximately 8 months

Secondary Outcomes (1)

• Nurses' Views on the Clinical Acceptability and Usability of the Explainable Artificial Intelligence Decision-Support System

  From completion of nurse interviews through completion of qualitative data analysis, approximately 4 months

Study Arms (2)

Adult Patients with Pressure Injuries

Adult patients with pressure injuries whose standardized clinical photographs and clinical data will be collected prospectively. Pressure injuries will be independently staged by an expert panel, and the images will be used to develop and evaluate an explainable artificial intelligence model. No intervention will be administered.

Nurses Participating in Interviews

Approximately 10-15 nurses working in intensive care and surgical units who provide pressure injury care will participate in individual semi-structured interviews. The interviews will explore their views on the clinical acceptability, usability, interpretability, and potential use of the explainable artificial intelligence decision-support system. No intervention will be administered.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population will consist of adults aged 18 years or older with at least one pressure injury who are receiving care in the participating clinical units. Standardized clinical photographs and clinical data will be collected prospectively. In addition, approximately 10-15 nurses working in intensive care or surgical units and involved in pressure injury care will be invited to participate in individual semi-structured interviews. Patients and nurses will participate voluntarily after providing informed consent.

You may qualify if:

• Adults aged 18 years or older.
• Patients with at least one pressure injury.
• Patients whose pressure injury can be photographed according to the study protocol.
• Patients or legally authorized representatives who provide informed consent.
• For the qualitative component:
• Nurses working in intensive care or surgical units.
• Nurses involved in pressure injury care.
• Nurses who provide informed consent and agree to participate in an individual semi-structured interview.

You may not qualify if:

• Patients who do not provide informed consent.
• Patients whose clinical condition does not allow the photography procedure.
• Images that are technically inadequate or do not meet the study quality criteria.
• Nurses who do not provide informed consent.
• Nurses who are unable to complete the interview.

Sponsors & Collaborators

• hatice akaltun: lead
• Yuzuncu Yil University: collaborator

Study Sites (1)

Sbu. Van Education and Research Hospital

Van, 65000, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Pressure Ulcer

Condition Hierarchy (Ancestors)

Skin Ulcer; Skin Diseases; Skin and Connective Tissue Diseases

Central Study Contacts

Hatice Akaltun, lecturer dr

CONTACT

0 (432) 444 50 65; haticeakaltun@yyu.edu.tr

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: lecturer dr

Study Record Dates

• First Submitted: October 18, 2026
• First Posted: October 23, 2026
• Study Start (Estimated): November 1, 2026
• Primary Completion (Estimated): June 1, 2027
• Study Completion (Estimated): October 1, 2027
• Last Updated: October 23, 2026

Record last verified: 2026-10

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)