Prediction Models for Intraoperative Acquired Pressure Injury of Adults: A Systematic Review and Critical Appraisal.

Abstract

Significance: Postoperative Pressure Injuries (PIs) present unique risks, requiring dedicated research for accurate assessment. Despite the increasing number of Intraoperative Acquired Pressure Injury (IAPI) prediction models, their risk of bias and clinical applicability remains unclear. Recent Advances: Adhered to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement requirements, IAPI prediction models of adult inpatients (≥18 years) were systematically retrieved from eight databases. Bias risk and applicability were evaluated using the Prediction model Risk Of Bias Assessment Tool (PROBAST), followed by narrative synthesis. Critical Issues: From 837 studies, 25 were included, covering 32 prediction models. Most studies (88%) were single-center and conducted in China, Korea, the United States, or Singapore, spanning various surgical specialties. Among 26,142 participants, IAPI incidence ranged from 4.1% to 41.75%. Common predictors included surgery duration, age, and diabetes. Areas Under the Curve (AUC) values varied from 0.702 to 0.984, but calibration was underreported. All studies had high bias risk, with 22 models exhibiting applicability concerns. Future Directions: The development of IAPI models requires a clear definition of the timing and personnel responsible for assessing PIs, with a preference for prospective data collection and thorough internal and external validation. Adherence to the critical appraisal and data extraction for systematic reviews of prediction modeling studies checklist and PROBAST guidelines can improve reporting quality. Models should be user-friendly, clinically applicable, and rigorously validated. Precisely defining and rigorously selecting predictors is critical to reducing variability. Future research should adopt more stringent designs to develop high-quality models capable of effectively guiding clinical practice. PROSPERO registration number: CRD42024502726.