Influencing factors and risk prediction model for emergence agitation after general anesthesia for primary liver cancer

Abstract

BACKGROUND General anesthesia is commonly used in the surgical management of gastrointestinal tumors; however, it can lead to emergence agitation (EA). EA is a common complication associated with general anesthesia, often characterized by behaviors, such as crying, struggling, and involuntary limb movements in patients. If treatment is delayed, there is a risk of incision cracking and bleeding, which can significantly affect surgical outcomes. Therefore, having a proper understanding of the factors influencing the occurrence of EA and implementing early preventive measures may reduce the incidence of agitation during the recovery phase from general anesthesia, which is beneficial for improving patient prognosis. AIM To analyze influencing factors and develop a risk prediction model for EA occurrence following general anesthesia for primary liver cancer. METHODS Retrospective analysis of clinical data from 200 patients who underwent hepatoma resection under general anesthesia at Wenzhou Central Hospital (January 2020 to December 2023) was conducted. Post-surgery, the Richmond Agitation-Sedation Scale was used to evaluate EA presence, noting EA incidence after general anesthesia. Patients were categorized by EA presence postoperatively, and the influencing factors were analyzed using logistic regression. A nomogram-based risk prediction model was constructed and evaluated for differentiation and fit using receiver operating characteristics and calibration curves. RESULTS EA occurred in 51 (25.5%) patients. Multivariate analysis identified advanced age, American Society of Anesthesiologists (ASA) grade III, indwelling catheter use, and postoperative pain as risk factors for EA (P < 0.05). Conversely, postoperative analgesia was a protective factor against EA (P < 0.05). The area under the curve of the nomogram was 0.972 [95% confidence interval (CI): 0.947-0.997] for the training set and 0.979 (95%CI: 0.951-1.000) for the test set. Hosmer-Lemeshow test showed a good fit (χ 2 = 5.483, P = 0.705), and calibration curves showed agreement between predicted and actual EA incidence. CONCLUSION Age, ASA grade, catheter use, postoperative pain, and analgesia significantly influence EA occurrence. A nomogram constructed using these factors demonstrates strong predictive accuracy.