A Predictive Nursing Tool for Patient Positioning Safety in Hybrid Digital Subtraction Angiography Operating Rooms

Area of Science:

• Medical Informatics
• Nursing Science
• Surgical Risk Assessment

Background:

• Hybrid operating rooms (ORs) present unique challenges for patient positioning.
• Position-related complications are a significant concern in these settings.
• Predictive tools are needed to assess and mitigate these risks.

Purpose of the Study:

• To develop and validate a nursing predictive assessment tool for position-related complications.
• To incorporate baseline patient-surgical risk and modifiable nursing processes.
• To aid in preoperative assessment and risk updating after patient positioning.

Main Methods:

• Retrospective cohort study of 1,936 adult inpatients in a hybrid OR.
• Developed a predictive model using logistic regression and nomogram construction.
• Assessed model performance using area under the curve, calibration, and Brier score.

Main Results:

• The final model achieved an area under the curve of 0.79 (corrected 0.77).
• Key protective factors included pressure-point protection and intraoperative position checks.
• The tool demonstrated stable discrimination, calibration, and net benefit upon internal validation.

Conclusions:

• The developed nursing tool effectively predicts position-related complications in hybrid ORs.
• Incorporating nursing process variables enhances predictive accuracy.
• The tool supports preoperative risk assessment and post-positioning updates, pending external validation.