颅内压动态波形形态预测脑室炎。

Dynamic Intracranial Pressure Waveform Morphology Predicts Ventriculitis.

机构信息

Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, 177 Fort Washington Ave, 8 Milstein - 300 Center, New York, NY, USA.

Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA.

出版信息

Neurocrit Care. 2022 Apr;36(2):404-411. doi: 10.1007/s12028-021-01303-3. Epub 2021 Jul 30.

DOI:10.1007/s12028-021-01303-3

PMID:34331206

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9847350/

Abstract

BACKGROUND

Intracranial pressure waveform morphology reflects compliance, which can be decreased by ventriculitis. We investigated whether morphologic analysis of intracranial pressure dynamics predicts the onset of ventriculitis.

METHODS

Ventriculitis was defined as culture or Gram stain positive cerebrospinal fluid, warranting treatment. We developed a pipeline to automatically isolate segments of intracranial pressure waveforms from extraventricular catheters, extract dominant pulses, and obtain morphologically similar groupings. We used a previously validated clinician-supervised active learning paradigm to identify metaclusters of triphasic, single-peak, or artifactual peaks. Metacluster distributions were concatenated with temperature and routine blood laboratory values to create feature vectors. A L2-regularized logistic regression classifier was trained to distinguish patients with ventriculitis from matched controls, and the discriminative performance using area under receiver operating characteristic curve with bootstrapping cross-validation was reported.

RESULTS

Fifty-eight patients were included for analysis. Twenty-seven patients with ventriculitis from two centers were identified. Thirty-one patients with catheters but without ventriculitis were selected as matched controls based on age, sex, and primary diagnosis. There were 1590 h of segmented data, including 396,130 dominant pulses in patients with ventriculitis and 557,435 pulses in patients without ventriculitis. There were significant differences in metacluster distribution comparing before culture-positivity versus during culture-positivity (p < 0.001) and after culture-positivity (p < 0.001). The classifier demonstrated good discrimination with median area under receiver operating characteristic 0.70 (interquartile range 0.55-0.80). There were 1.5 true alerts (ventriculitis detected) for every false alert.

CONCLUSIONS

Intracranial pressure waveform morphology analysis can classify ventriculitis without cerebrospinal fluid sampling.

摘要

背景

颅内压波形形态反映顺应性，而脑室炎可降低顺应性。我们研究了颅内压动力学形态分析是否可预测脑室炎的发生。

方法

脑室炎的定义为脑脊液培养或革兰氏染色阳性，需要治疗。我们开发了一个管道，从脑室外引流管中自动分离颅内压波形段，提取主导脉冲，并获得形态相似的分组。我们使用先前验证的临床医生监督的主动学习范例来识别三相、单峰或人工峰的元聚类。元聚类分布与温度和常规血液实验室值结合起来创建特征向量。使用 L2 正则化逻辑回归分类器来区分脑室炎患者和匹配的对照者，并使用 bootstrap 交叉验证的接收者操作特征曲线下面积报告判别性能。

结果

共纳入 58 例患者进行分析。在两个中心发现 27 例脑室炎患者。根据年龄、性别和主要诊断选择 31 例无脑室炎但有导管的患者作为匹配对照者。有 1590 小时的分段数据，包括脑室炎患者 396130 个主导脉冲和无脑室炎患者 557435 个脉冲。在培养阳性之前与培养阳性期间（p < 0.001）和培养阳性之后（p < 0.001），元聚类分布存在显著差异。分类器的中位接收者操作特征曲线下面积为 0.70（四分位距 0.55-0.80），具有良好的判别能力。每 1.5 次真警报（检测到脑室炎）对应一次假警报。