Gonçalves Maria C B, Khera Tanvi, Otu Hasan H, Narayanan Shilpa, Dillon Simon T, Shanker Akshay, Gu Xuesong, Jung Yoojin, Ngo Long H, Marcantonio Edward R, Libermann Towia A, Subramaniam Balachundhar
From the Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Harvard Medical School, Boston, Massachusetts.
Anesth Analg. 2025 Feb 1;140(2):476-487. doi: 10.1213/ANE.0000000000007293. Epub 2025 Jan 10.
Delirium after cardiac surgery is common, morbid, and costly, but may be prevented with risk stratification and targeted intervention. In this study, we aimed to identify protein biomarkers and develop a predictive model for postoperative delirium in older patients undergoing cardiac surgery.
SomaScan analysis of 1305 proteins in the plasma from 57 older adults undergoing cardiac surgery requiring cardiopulmonary bypass was conducted to define delirium-specific protein signatures at baseline (preoperative baseline timepoint [PREOP]) and postoperative day 2 (POD2). Selected proteins were validated in 115 patients using the Enzyme-Linked Lectin Assay (ELLA) multiplex immunoassay platform. Proteins were combined with clinical and demographic variables to build multivariable models that estimate the risk of postoperative delirium and bring light to the underlying pathophysiology.
Of the 115 patients, 21 (18.3%) developed delirium after surgery. The SomaScan proteome screening evidenced differential expression of 115 and 85 proteins in delirious patients compared to nondelirious preoperatively and at POD2, respectively ( P < .05). Following biological and methodological criteria, 12 biomarker candidates (Tukey's fold change [|tFC|] >1.4, Benjamini-Hochberg [BH]- P < .01) were selected for ELLA multiplex validation. Statistical analyses of model fit resulted in the combination of age, sex, and 3 proteins (angiopoietin-2; C-C motif chemokine 5; and metalloproteinase inhibitor 1; area under the curve [AUC] = 0.829) as the best performing predictive model for delirium. Analyses of pathways showed that delirium-associated proteins are involved in inflammation, glial dysfunction, vascularization, and hemostasis.
Our results support the identification of patients at higher risk of developing delirium after cardiac surgery using a multivariable model that combines demographic and physiological features, also bringing light to the role of immune and vascular dysregulation as underlying mechanisms.
心脏手术后谵妄很常见，病情严重且成本高昂，但可通过风险分层和针对性干预加以预防。在本研究中，我们旨在识别蛋白质生物标志物，并为接受心脏手术的老年患者开发术后谵妄的预测模型。
对57例接受需要体外循环的心脏手术的老年患者的血浆进行1305种蛋白质的SomaScan分析，以确定术前基线（术前基线时间点[PREOP]）和术后第2天（POD2）的谵妄特异性蛋白质特征。使用酶联凝集素测定（ELLA）多重免疫分析平台在115例患者中对选定的蛋白质进行验证。将蛋白质与临床和人口统计学变量相结合，建立多变量模型，以估计术后谵妄的风险，并揭示潜在的病理生理学机制。
115例患者中，21例（18.3%）术后发生谵妄。SomaScan蛋白质组筛查显示，与术前和POD2时未发生谵妄的患者相比，发生谵妄的患者分别有115种和85种蛋白质表达存在差异（P <.05）。根据生物学和方法学标准，选择12种生物标志物候选物（Tukey倍数变化[|tFC|]>1.4，Benjamini-Hochberg[BH]-P <.01）进行ELLA多重验证。模型拟合的统计分析结果显示，年龄、性别和3种蛋白质（血管生成素-2；C-C基序趋化因子5；金属蛋白酶抑制剂1；曲线下面积[AUC]=0.829）的组合是谵妄表现最佳的预测模型。通路分析表明，与谵妄相关的蛋白质参与炎症、神经胶质功能障碍、血管生成和止血过程。
我们的结果支持使用结合人口统计学和生理特征的多变量模型来识别心脏手术后发生谵妄风险较高的患者，同时也揭示了免疫和血管调节异常作为潜在机制的作用。
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