• Daniel Segelcke, RosenbergerDaniela CDC, and Esther M Pogatzki-Zahn.
• Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany.
• Curr Opin Anaesthesiol. 2023 Oct 1; 36 (5): 580588580-588.

Purpose Of ReviewPrognostic models for chronic postsurgical pain (CPSP) aim to predict the likelihood for development and severity of CPSP in individual patients undergoing surgical procedures. Such models might provide valuable information for healthcare providers, allowing them to identify patients at higher risk and implement targeted interventions to prevent or manage CPSP effectively. This review discusses the latest developments of prognostic models for CPSP, their challenges, limitations, and future directions.Recent FindingsNumerous studies have been conducted aiming to develop prognostic models for CPSP using various perioperative factors. These include patient-related factors like demographic variables, preexisting pain conditions, psychosocial aspects, procedure-specific characteristics, perioperative analgesic strategies, postoperative complications and, as indicated most recently, biomarkers. Model generation, however, varies and performance and accuracy differ between prognostic models for several reasons and validation of models is rather scarce.SummaryPrecise methodology of prognostic model development needs advancements in the field of CPSP. Development of more accurate, validated and refined models in large-scale cohorts is needed to improve reliability and applicability in clinical practice and validation studies are necessary to further refine and improve the performance of prognostic models for CPSP.Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

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