Risk Prediction Algorithms for Prolonged Postoperative Ileus: A Systematic Review.

AimProlonged postoperative ileus (PPOI) is common and is associated with a significant healthcare burden. Previous studies have attempted to predict PPOI clinically using risk prediction algorithms. The aim of this work was to systematically review and compare risk prediction algorithms for PPOI following colorectal surgery.MethodA systematic literature search was conducted using MEDLINE, Embase, Web of Science and CINAHL Plus. Studies that developed and/or validated a risk prediction algorithm for PPOI in adults following colorectal surgery were included. Data were collected on study design, population and operative characteristics, the definition of PPOI used and risk prediction algorithm design and performance. Quality appraisal was assessed using the PROBAST tool.ResultsEleven studies with 87 549 participants were included in our review. Most were retrospective, single-centre analyses (6/11, 55%) and rates of PPOI varied from 10% to 28%. The most commonly used variables were sex (8/11, 73%), age (6/11, 55%) and surgical approach (5/11, 45%). Area under the curve ranged from 0.68-0.78, and only three models were validated. However, there was significant variation in the definition of PPOI used. No study reported sensitivity, specificity or positive/negative predictive values.ConclusionCurrently available risk prediction algorithms for PPOI appear to discriminate moderately well, although there is a lack of validation data. Future studies should aim to use a standardized definition of PPOI, comprehensively report model performance and validate their findings using internal and external methodologies.