Background Optimizing postoperative pain treatment is essential to minimize morbidity, lower costs, and ensure patient and parent satisfaction. This study aims at identifying pre- and intraoperative parameters predicting opioid needs after laparoscopic appendectomy to enable timely and adequate postoperative pain control.

Materials and Methods A retrospective analysis of patients treated with laparoscopic appendectomy for appendicitis between January 2018 and March 2019 was performed. Multiple logistic regression was applied to identify predictors of opioid demand.

Results Based on our analysis, we developed a prediction tool for opioid requirements after laparoscopic appendectomies in children. The integrated parameters are: presence of turbid fluid, age, white-blood-cell count, symptom duration, and body temperature.

Conclusion We developed an algorithm-based predictor tool that has the potential to better anticipate postoperative pain and, thereby, optimize pain management following laparoscopic appendectomies in children. The proposed predictor tool will need validation through further prospective studies.

背景 优化术后疼痛治疗对于最大程度地降低发病率、降低成本并确保患者和家长的满意度至关重要。本研究旨在确定预测腹腔镜阑尾切除术后阿片类药物需求的术前和术中参数，以便及时和充分地控制术后疼痛。

材料与方法 对 2018 年 1 月至 2019 年 3 月接受腹腔镜阑尾切除术治疗的阑尾炎患者进行回顾性分析。应用多元逻辑回归来确定阿片类药物需求的预测因素。

结果 根据我们的分析，我们开发了一种预测儿童腹腔镜阑尾切除术后阿片类药物需求的工具。综合参数是：是否存在混浊液、年龄、白细胞计数、症状持续时间和体温。

结论 我们开发了一种基于算法的预测工具，它有可能更好地预测术后疼痛，从而优化儿童腹腔镜阑尾切除术后的疼痛管理。拟议的预测工具将需要通过进一步的前瞻性研究进行验证。