Effective intraoperative pressure injury risk assessment in patients undergoing surgery: A comparative study

Prolonged surgical periods and specific positioning significantly increase the risk of pressure injuries. While various risk assessment tools are available, comparative studies evaluating their predictive performance specifically within the intraoperative setting remain limited. This study aimed to compare the predictive performance of the Braden Scale, the 3 S Intraoperative Pressure Injury Risk Assessment Scale, and the Scott Triggers Pressure Injury Risk Assessment Tool.

A prospective and descriptive study was conducted with 120 adult patients (aged >18 years) undergoing surgeries with an operative duration of ≥3 h. Patient data were collected using a demographic form, along with the Braden, 3 S Scale, and Scott Triggers scales. The study was reported in accordance with the STROBE checklist.

Patients were assessed for pressure injuries immediately upon admission to the post-anesthesia care unit (PACU). All identified pressure injuries were Stage I, occurring most frequently following urology procedures (30%). Patients who developed a pressure injury exhibited significantly higher 3 S Scale scores compared to those who did not (p = 0.003). Furthermore, the 3 S Scale demonstrated significant discriminatory power (Area Under the Curve [AUC] = 0.658; p = 0.001), whereas the Scott Triggers and Braden scales exhibited discrimination levels close to chance (p > 0.05).

The Scott Triggers and Braden scales exhibited limited predictive ability for intraoperative use. In contrast, the 3 S Scale demonstrated a statistically significant association with pressure injury risk and may represent a potentially useful tool for intraoperative assessment; however, its predictive performance appears to be moderate. Overall, current assessment tools are often inadequate for the dynamic surgical environment. There is a critical need to revise existing scales or develop new, comprehensive tools that integrate dynamic intraoperative variables, including surgical positioning, duration of exposure, and hemodynamic instability, to enhance the accuracy and clinical applicability of risk prediction models.