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Inflammatory Indices and Their Associations with Postoperative Delirium
The Journals of Gerontology Series A: Biological Sciences and Medical Sciences ( IF 4.3 ) Pub Date : 2024-11-22 , DOI: 10.1093/gerona/glae285 Gabrielle E Mintz, Edward R Marcantonio, Jeremy D Walston, Simon T Dillon, Yoojin Jung, Shrunjal Trivedi, Xuesong Gu, Tamara G Fong, Michele Cavallari, Alexandra Touroutoglou, Bradford C Dickerson, Richard N Jones, Mouhsin M Shafi, Alvaro Pascual-Leone, Thomas G Travison, Sharon K Inouye, Towia A Libermann, Long H Ngo, Sarinnapha M Vasunilashorn
The Journals of Gerontology Series A: Biological Sciences and Medical Sciences ( IF 4.3 ) Pub Date : 2024-11-22 , DOI: 10.1093/gerona/glae285 Gabrielle E Mintz, Edward R Marcantonio, Jeremy D Walston, Simon T Dillon, Yoojin Jung, Shrunjal Trivedi, Xuesong Gu, Tamara G Fong, Michele Cavallari, Alexandra Touroutoglou, Bradford C Dickerson, Richard N Jones, Mouhsin M Shafi, Alvaro Pascual-Leone, Thomas G Travison, Sharon K Inouye, Towia A Libermann, Long H Ngo, Sarinnapha M Vasunilashorn
Background Although the pathogenesis of delirium is poorly understood, increasing evidence supports a role for inflammation. Previously, individual inflammatory biomarkers have been associated with delirium. Aggregating biomarkers into an index may provide more information than individual biomarkers in predicting certain health outcomes (e.g., mortality); however, inflammatory indices have not yet been examined in delirium. Methods Four inflammatory markers, C-reactive protein, Interleukin-6, Soluble Tumor Necrosis Factor Alpha Receptor-1, and Chitinase-3 Like Protein-1 (CHI3L1), were measured preoperatively (PREOP) and on postoperative day 2 (POD2) in 548 adults aged 70+ undergoing major noncardiac surgery (mean age 76.7 [standard deviation 5.2], 58% female, 24% delirium). From these markers, four inflammatory indices were considered: 1) quartile summary score, 2) weighted summary score (WSS), 3) principal component score, 4) a well-established inflammatory (LASSO-derived) index associated with mortality. Delirium was assessed using the Confusion Assessment Method (CAM), supplemented by chart review. Generalized linear models (GLM) with a log-link term were used to determine the association between each inflammatory index and delirium incidence. Results Among the inflammatory indices, WSS demonstrated the strongest association with delirium: participants in WSS quartile (Q)4 had a higher risk of delirium vs. participants in Q1, after clinical variable adjustment (relative risk [RR], 95% confidence interval [CI] for PREOP: 3.07, 1.80-5.22; and POD2: 2.65, 1.63-4.30). WSS was more strongly associated with delirium than the strongest associated individual inflammatory marker (PREOP CHI3L1 [RR 2.45, 95% CI 1.53-3.92]; POD2 interleukin-6 [RR 2.39, 95% CI 1.50-3.82]). Conclusions A multi-protein inflammatory index using WSS provides a slight advantage over individual inflammatory markers in their association with delirium.
中文翻译:
炎症指标及其与术后谵妄的相关性
背景 尽管对谵妄的发病机制知之甚少,但越来越多的证据支持炎症的作用。以前,单个炎症生物标志物与谵妄有关。将生物标志物聚合到一个指数中可能提供比单个生物标志物更多的信息来预测某些健康结果(例如死亡率);然而,尚未检查谵妄的炎症指数。方法 在 548 名 70+ 接受大型非心脏手术的成年人 (平均年龄 76.7 [标准差 5.2],58% 女性,24% 谵妄)中测量 C 反应蛋白、白细胞介素-6、可溶性肿瘤坏死因子 α 受体-1 和几丁质酶-3 样蛋白-1 (CHI3L1) 四种炎症标志物。从这些标志物中,考虑了四个炎症指数:1) 四分位数总分,2) 加权总分 (WSS),3) 主成分评分,4) 与死亡率相关的公认炎症(LASSO 衍生)指数。使用混淆评估方法 (CAM) 评估谵妄,并辅以图表审查。使用带有对数链接项的广义线性模型 (GLM) 来确定每个炎症指数与谵妄发生率之间的关联。结果在炎症指标中,WSS 与谵妄的相关性最强:经过临床变量调整后,WSS 四分位数 (Q)4 的参与者发生谵妄的风险高于第一季度的参与者(相对风险 [RR],PREOP 的 95% 置信区间 [CI]:3.07,1.80-5.22;和 POD2:2.65,1.63-4.30)。WSS 与谵妄的相关性比最强的相关个体炎症标志物更强 (PREOP CHI3L1 [RR 2.45,95% CI 1.53-3.92];POD2 白细胞介素-6 [RR 2.39,95% CI 1.50-3.82])。 结论 使用 WSS 的多蛋白炎症指数在与谵妄的相关性方面略优于单个炎症标志物。
更新日期:2024-11-22
中文翻译:
炎症指标及其与术后谵妄的相关性
背景 尽管对谵妄的发病机制知之甚少,但越来越多的证据支持炎症的作用。以前,单个炎症生物标志物与谵妄有关。将生物标志物聚合到一个指数中可能提供比单个生物标志物更多的信息来预测某些健康结果(例如死亡率);然而,尚未检查谵妄的炎症指数。方法 在 548 名 70+ 接受大型非心脏手术的成年人 (平均年龄 76.7 [标准差 5.2],58% 女性,24% 谵妄)中测量 C 反应蛋白、白细胞介素-6、可溶性肿瘤坏死因子 α 受体-1 和几丁质酶-3 样蛋白-1 (CHI3L1) 四种炎症标志物。从这些标志物中,考虑了四个炎症指数:1) 四分位数总分,2) 加权总分 (WSS),3) 主成分评分,4) 与死亡率相关的公认炎症(LASSO 衍生)指数。使用混淆评估方法 (CAM) 评估谵妄,并辅以图表审查。使用带有对数链接项的广义线性模型 (GLM) 来确定每个炎症指数与谵妄发生率之间的关联。结果在炎症指标中,WSS 与谵妄的相关性最强:经过临床变量调整后,WSS 四分位数 (Q)4 的参与者发生谵妄的风险高于第一季度的参与者(相对风险 [RR],PREOP 的 95% 置信区间 [CI]:3.07,1.80-5.22;和 POD2:2.65,1.63-4.30)。WSS 与谵妄的相关性比最强的相关个体炎症标志物更强 (PREOP CHI3L1 [RR 2.45,95% CI 1.53-3.92];POD2 白细胞介素-6 [RR 2.39,95% CI 1.50-3.82])。 结论 使用 WSS 的多蛋白炎症指数在与谵妄的相关性方面略优于单个炎症标志物。