From the Department of Anesthesiology and Intensive Care Medicine, Technical University of Munich School of Medicine and Health, Munich, Germany.
Department of Anesthesia and Intensive Care Medicine, Hessing Foundation, Augsburg, Germany.
Anesth Analg. 2024 Nov 1;139(5):1027-1037. doi: 10.1213/ANE.0000000000007143. Epub 2024 Aug 23.
Patient age is assumed to be an important risk factor for the occurrence of burst suppression, yet this has still to be confirmed by large datasets.
In this single-center retrospective analysis at a university hospital, the electronic patient records of 38,628 patients (≥18 years) receiving general anesthesia between January 2016 and December 2018 were analyzed. Risk factors for burst suppression were evaluated using univariate and multivariable analysis. We measured the incidence of burst suppression as indicated by the burst suppression ratio (BSR) of the Entropy Module, the maximum and mean BSR values, relative burst suppression duration, mean volatile anesthetic concentrations, and mean age-adjusted minimum alveolar concentrations (aaMAC) at burst suppression, and cases of potentially misclassified burst suppression episodes. Analyses were done separately for the total anesthesia period, as well as for the Induction and Maintenance phase. The association with age was evaluated using linear and polynomial fits and by calculating correlation coefficients.
Of the 54,266 patients analyzed, 38,628 were included, and 19,079 patients exhibited episodes with BSR >0. Patients with BSR >0 were significantly older, and age had the highest predictive power for BSR >0 (area under the receiving operating characteristic [AUROC] = 0.646 [0.638-0.654]) compared to other patient or procedural factors. The probability of BSR >0 increased linearly with patient age (ρ = 0.96-0.99) between 1.9% and 9.8% per year. While maximal and mean BSR showed a nonlinear relationship with age, relative burst suppression duration also increased linearly during maintenance (ρ = 0.83). Further, episodes potentially indicating burst suppression that were not detected by the Entropy BSR algorithm also became more frequent with age. Volatile anesthetic concentrations sufficient to induce BSR >0 were negatively correlated with age (sevoflurane: ρ = -0.71), but remained close to an aaMAC of 1.0.
The probability of burst suppression during general anesthesia increases linearly with age in adult patients, while lower anesthetic concentrations induce burst suppression with increasing patient age. Simultaneously, algorithm-based burst suppression detection appears to perform worse in older patients. These findings highlight the necessity to further enhance EEG application and surveillance strategies in anesthesia.
患者年龄被认为是发生爆发抑制的一个重要危险因素，但这仍然需要通过大型数据集来证实。
在这项单中心回顾性分析中，我们对 2016 年 1 月至 2018 年 12 月期间在一家大学医院接受全身麻醉的 38628 名（≥18 岁）患者的电子病历进行了分析。使用单变量和多变量分析评估了爆发抑制的危险因素。我们使用熵模块的爆发抑制比（BSR）、最大和平均 BSR 值、相对爆发抑制持续时间、挥发性麻醉剂浓度的平均值和爆发抑制时的平均年龄校正最小肺泡浓度（aaMAC）以及潜在的分类错误的爆发抑制发作来衡量爆发抑制的发生率。分析分别针对整个麻醉期以及诱导和维持期进行。使用线性和多项式拟合以及计算相关系数来评估与年龄的关系。
在分析的 54266 名患者中，纳入了 38628 名患者，其中 19079 名患者出现 BSR>0 的发作。BSR>0 的患者年龄明显较大，与其他患者或手术因素相比，年龄对 BSR>0 具有最高的预测能力（接受者操作特征曲线下面积 [AUROC] = 0.646 [0.638-0.654]）。BSR>0 的概率随患者年龄呈线性增加（ρ=0.96-0.99），每年增加 1.9%至 9.8%。最大和平均 BSR 与年龄呈非线性关系，而相对爆发抑制持续时间在维持期也呈线性增加（ρ=0.83）。此外，与 Entropy BSR 算法未检测到的潜在爆发抑制发作一样，年龄较大的患者发生的可能性也更高。足以诱导 BSR>0 的挥发性麻醉剂浓度与年龄呈负相关（七氟醚：ρ=-0.71），但仍接近 1.0 的 aaMAC。
在成年患者中，全身麻醉期间爆发抑制的概率随年龄呈线性增加，而较低的麻醉浓度会随着患者年龄的增加而导致爆发抑制。同时，基于算法的爆发抑制检测在老年患者中的表现似乎更差。这些发现强调了在麻醉中进一步加强 EEG 应用和监测策略的必要性。
