Leblanc Damien, Guichoux Arthur, Sail Marjorie, Boré François, Seegers Valérie, Espitalier Fabien
Department of Anaesthesia and Intensive Care, Angers University Hospital, Angers, France.
Department of Anaesthesia, Bretagne-Atlantique Hospital, Vannes, France.
Acta Anaesthesiol Scand. 2023 Apr;67(4):448-454. doi: 10.1111/aas.14191. Epub 2023 Jan 6.
Modelling acute post-operative pain trajectories may improve the prediction of persistent pain after breast cancer surgery (PPBCS). This study aimed to investigate the predictive accuracy of early post-operative pain (EPOP) trajectories in the development of PPBCS.
MATERIALS & METHODS: This observational study was conducted in a French Comprehensive Cancer Centre and included patients who underwent breast cancer surgery from December 2017 to November 2018. Perioperative and follow-up data were obtained from medical records, and anaesthesia and perioperative charts. EPOP was defined as pain intensity during the first 24 h after surgery, and modelled by a pain trajectory. K-means clustering method was used to identify patient subgroups with similar EPOP trajectories. The prevalence of moderate-to-severe PPBCS (numeric rating scale ≥4) was evaluated until 24 months after surgery.
A total of 608 patients were included in the study, of which 18% (n = 108) and 9% (n = 52) reported mild and moderate-to-severe PPBCS, respectively. Based on EPOP trajectories, we were able to identify a low (64%, n = 388), resolved (30%, n = 182), and unresolved (6%, n = 38) pain group. Multivariate analysis identified younger age, axillary lymph node dissection, and unresolved EPOP trajectory as independent risk factors for moderate-to-severe PPBCS development. When compared to patients reporting mild PPBCS, moderate-to-severe PPBCS patients experienced significantly more neuropathic pain features, pain-related interference, and delayed opioid cessation.
EPOP trajectories can distinguish between resolved and unresolved acute pain after breast cancer surgery, allowing early identification of patients at risk to develop significant PPBCS.
对急性术后疼痛轨迹进行建模可能会改善对乳腺癌手术后持续性疼痛（PPBCS）的预测。本研究旨在调查术后早期疼痛（EPOP）轨迹对PPBCS发生的预测准确性。
这项观察性研究在一家法国综合癌症中心进行，纳入了2017年12月至2018年11月接受乳腺癌手术的患者。围手术期和随访数据从病历、麻醉和围手术期图表中获取。EPOP定义为术后首24小时内的疼痛强度，并通过疼痛轨迹进行建模。采用K均值聚类方法识别具有相似EPOP轨迹的患者亚组。评估术后24个月内中度至重度PPBCS（数字评分量表≥4）的发生率。
本研究共纳入608例患者，其中分别有18%（n = 108）和9%（n = 52）报告有轻度和中度至重度PPBCS。基于EPOP轨迹，我们能够识别出一个低疼痛组（64%，n = 388）、疼痛缓解组（30%，n = 182）和疼痛未缓解组（6%，n = 38）。多变量分析确定年龄较小、腋窝淋巴结清扫和未缓解的EPOP轨迹是中度至重度PPBCS发生的独立危险因素。与报告有轻度PPBCS的患者相比，中度至重度PPBCS患者经历的神经性疼痛特征、疼痛相关干扰和阿片类药物停用延迟明显更多。
EPOP轨迹可以区分乳腺癌手术后疼痛缓解和未缓解的急性疼痛，从而早期识别有发生显著PPBCS风险的患者。
