Reply: Neural substrates of vulnerability to post-surgical delirium with prospective diagnosis.
Reply: Neural substrates of vulnerability to post-surgical delirium with prospective diagnosis.
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答复：具有前瞻性诊断的术后谵妄易感性的神经基础。
DOI：
10.1093/brain/aww150
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
SAGESStudyGroup
中科院分区：
文献类型：
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作者：
Cavallari,Michele;Guttmann,CharlesRG;Jones,RichardN;Inouye,SharonK;Alsop,DavidC;SAGESStudyGroup
先生，在研究大脑微结构异常和术后谵妄之间的联系时，我们没有关于特定大脑网络的先验假设。通过这种无偏见的方法获得的我们的研究结果支持了这样的假设，即参与认知和行为任务的神经网络之间的连接受损易在手术压力下发生谵妄（Cavallari et al.，2016年）。具体来说，我们发现，术前扩散异常的连接和节点的大脑网络参与注意（如额顶叶控制网络，小脑），记忆（如海马），唤醒（如基底前脑），和协调活动（如丘脑，胼胝体）易患术后谵妄。基于脑血管或多发性硬化症病变在关键部位的病例报告，先前已经假设了这些网络损伤的潜在致病作用（Ross，1991; Sanders，2011）（综述参见Alsop et al.，2006），以及最近对谵妄的功能性MRI和扩散张量成像（DTI）研究（Choi等人，2012; Morandi等人，2012; Shioiri等人，2010年）。我们的研究结果支持在一个更大的，前瞻性队列的无痴呆老年人谵妄的连接障碍假说，谵妄的措施，调查其神经相关性的选择可以显着影响的能力，以检测协会，可能有助于阐明其复杂的病理生理。尽管在临床实践中有用，但由于与分类相关的变异性信息的内在损失，诸如谵妄发生的二分测量可能不是理想的（Altman，2006; Rothman等人，2008）和潜在的亚综合征或部分形式的错误分类。由于连续测量更好地反映了谵妄作为一种谱系障碍的内在本质，其特征是无症状、亚综合征和完全谵妄综合征之间的连续体，因此我们决定在主要分析中使用谵妄严重程度作为主要结局指标。在我们的分析中，峰值CAM严重程度（CAM-S）评分定义为所有日常医院评估的最高CAMS评分，无论患者是否谵妄，用于指示谵妄的严重程度。因此，我们的主要发现与谵妄严重程度相关的弥散异常具有独立于谵妄状态分类的诊断标准的优势。使用谵妄严重程度作为主要结局使我们能够利用整个样本，因为所有研究参与者都有每日CAM评级;因此，诊断的图表审查方法不适用于该分析。
Sir, In investigating the association between microstructural brain abnormalities and postoperative delirium we had no a priori hypotheses regarding specific brain networks. Our findings, obtained through such an unbiased approach, supported the hypothesis that impaired connectivity across neural networks involved in cognitive and behavioural tasks predisposes to delirium under the stress of surgery (Cavallari et al., 2016). Specifically, we found that presurgical diffusion abnormalities in connections and nodes of brain networks involved in attention (eg frontoparietal control network, cerebellum), memory (eg hippocampus), arousal (eg basal forebrain), and coordinated activities (eg thalamus, corpus callosum) predisposed to postsurgical delirium. A potential pathogenic role of damage to those networks had been previously hypothesized (Ross, 1991; Sanders, 2011) based on case reports of cerebrovascular or multiple sclerosis lesions in strategic locations (for a review see Alsop et al., 2006), as well as on more recent functional MRI and diffusion tensor imaging (DTI) studies of delirium (Choi et al., 2012; Morandi et al., 2012; Shioiri et al., 2010). Our findings support the dysconnectivity hypothesis of delirium in a larger, prospective cohort of dementia-free older individuals.The choice of delirium measures to investigate its neural correlates can significantly impact the ability to detect associations that may help elucidate its intricate pathophysiology. Although useful in clinical practice, dichotomous measures, such as delirium occurrence, may not be ideal due to the intrinsic loss of information on variability associated with categorization (Altman, 2006; Rothman et al., 2008) and potential misclassification of subsyndromal or partial forms. As continuous measures better reflects the intrinsic nature of delirium as a spectrum disorder, characterized by a continuum between no symptoms, subsyndromal, and the full delirium syndrome, we decided to use delirium severity as the main outcome measure in our primary analysis. Peak CAM-Severity (CAM-S) score, defined as the highest CAMS score of all daily hospital assessments regardless of whether or not the patient was delirious, was used to indicate delirium severity in our analyses. Therefore, our main finding of diffusion abnormalities associated with delirium severity has the advantage of being independent from the diagnostic criteria applied to classify delirium status. The use of delirium severity as the main outcome allowed us to utilize the entire sample since all the study participants had daily CAM ratings; thus, the chart review approach for diagnosis did not pertain to this analysis.