• Anaesthesia · Dec 2024

    Review

    Prognostic clinical prediction models for acute post-surgical pain in adults: a systematic review.

    • Nicholas Papadomanolakis-Pakis, Philip V Munch, Nicolai Carlé, Camilla G Uhrbrand, Simon Haroutounian, and Lone Nikolajsen.
    • Department of Anaesthesiology and Intensive Care, Aarhus University Hospital, Aarhus, Denmark.
    • Anaesthesia. 2024 Dec 1; 79 (12): 133513471335-1347.

    BackgroundAcute post-surgical pain is managed inadequately in many patients undergoing surgery. Several prognostic risk prediction models have been developed to identify patients at high risk of developing moderate to severe acute post-surgical pain. The aim of this systematic review was to describe and evaluate the methodological conduct of these prediction models.MethodsWe searched MEDLINE, EMBASE and CINAHL for studies of prognostic risk prediction models for acute post-surgical pain using predetermined criteria. Prediction model performance was evaluated according to discrimination and calibration. Adherence to TRIPOD guidelines was assessed. Risk of bias and applicability was independently assessed by two reviewers using the prediction model risk of bias assessment tool.ResultsWe included 14 studies reporting on 17 prediction models. The most common predictors identified in final prediction models included age; surgery type; sex or gender; anxiety or fear of surgery; pre-operative pain intensity; pre-operative analgesic use; pain catastrophising; and expected surgical incision size. Discrimination, measured by the area under receiver operating characteristic curves or c-statistic, ranged from 0.61 to 0.83. Calibration was only reported for seven models. The median (IQR [range]) overall adherence rate to TRIPOD items was 62 (53-66 [47-72])%. All prediction models were at high risk of bias.ConclusionsEffective prediction models could support the prevention and treatment of acute post-surgical pain; however, existing models are at high risk of bias which may affect their reliability to inform practice. Consideration should be given to the goals, timing of intended use and desired outcomes of a prediction model before development.© 2024 The Author(s). Anaesthesia published by John Wiley & Sons Ltd on behalf of Association of Anaesthetists.

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