Establishing a Predictive Model for Acute Postoperative Pain at PACU Awakening Based on Preoperative Hypoalbuminemia and Anemia: Clinical Implications for Perioperative Nursing

Background: The management of acute postoperative pain remains a major challenge in perioperative nursing, as it delays recovery and impacts patient satisfaction. Physiological markers such as preoperative serum albumin and hemoglobin are important indicators of pain risk but are often underutilized in conventional nursing assessments. Methods: This single-center, retrospective cohort study, grounded in the Symptom Management Theory, analyzed data from 790 surgical patients who underwent procedures at the First Affiliated Hospital of Wenzhou Medical University between January and December 2023. Preoperative hypoalbuminemia and anemia were identified through routine laboratory tests. The primary outcome was acute postoperative pain, assessed upon awakening in the Post-Anesthesia Care Unit (PACU). Their associations with this outcome were examined using multivariable logistic regression, adjusting for key confounders including analgesic pump use. Finally, a predictive nomogram was developed to visualize the risk. Results: The incidence of acute postoperative pain at PACU Awakening was 45.1%. Both preoperative hypoalbuminemia (OR 1.68, 95% CI 1.19-2.39, p = 0.003) and anemia (OR 1.50, 95% CI 1.04-2.16, p = 0.030) were independent predictors of acute postoperative pain at PACU Awakening. The nomogram demonstrated good calibration and acceptable discrimination (AUC = 0.690, 95% CI 0.653-0.726). Decision curve analysis showed a positive net clinical benefit across a wide range of threshold probabilities. Conclusion: Preoperative hypoalbuminemia and anemia are significant predictors of acute postoperative pain at PACU Awakening. Integrating these biomarkers into routine perioperative nursing assessments enables early identification of at-risk patients and facilitates evidence-based interventions such as nutritional optimization and anemia correction, fostering proactive and personalized pain management strategies. Decision curve analysis showed a positive net clinical benefit across a wide range of threshold probabilities.