Predicting acute postsurgical pain in the postanesthesia care unit: risk tool development and internal validation.

ABSTRACT:

Introduction

Moderate-to-severe acute postsurgical pain (APSP) is experienced by approximately 30% of surgical patients.

Objectives

To improve early APSP management, we developed 2 pragmatic and generalizable point-of-care risk tools to preoperatively predict moderate-to-severe and severe APSP in the postanaesthesia care unit (PACU).

Methods

This was a multicenter prospective cohort study of adult patients undergoing elective surgical procedures between May 2021 and May 2023. Candidate predictors were preidentified. Logistic regression was used to develop the models. Internal validation was conducted with bootstrap resampling. Model performance was assessed by discrimination and calibration. Decision curve analysis was conducted to evaluate clinical utility of the mod

SUBMITTER: Papadomanolakis-Pakis N 

PROVIDER: S-EPMC12410311 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature