Cerebral oximetry in cardiac arrest: a potential role but with limitations

Sandroni, Claudio; Parnia, Sam; Nolan, Jerry P.

doi:10.1007/s00134-019-05572-7

Cited by 21 publications

(22 citation statements)

References 14 publications

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“…NIRS techniques have been used to measure the quality of CPR by measuring rSO2, which can be an indicator of the occurrence of ROSC [ 11 ]. Even though rSO2 can directly show the cerebral oxygenation levels, it can be distorted from extracranial blood flow [ 34 ] and might represent systemic circulation rather than cerebral circulation during CPR [ 35 ]. In addition, the relationship between higher rSO2 levels and favorable neurological outcomes remains unclear [ 11 ].…”

Section: Discussionmentioning

confidence: 99%

EEG-Based Prediction of the Recovery of Carotid Blood Flow during Cardiopulmonary Resuscitation in a Swine Model

Kim

Hong

et al. 2021

Sensors

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The recovery of cerebral circulation during cardiopulmonary resuscitation (CPR) is important to improve the neurologic outcomes of cardiac arrest patients. To evaluate the feasibility of an electroencephalogram (EEG)-based prediction model as a CPR feedback indicator of high- or low-CBF carotid blood flow (CBF), the frontal EEG and hemodynamic data including CBF were measured during animal experiments with a ventricular fibrillation (VF) swine model. The most significant 10 EEG parameters in the time, frequency and entropy domains were determined by neighborhood component analysis and Student’s t-test for discriminating high- or low-CBF recovery with a division criterion of 30%. As a binary CBF classifier, the performances of logistic regression, support vector machine (SVM), k-nearest neighbor, random forest and multilayer perceptron algorithms were compared with eight-fold cross-validation. The three-order polynomial kernel-based SVM model showed the best accuracy of 0.853. The sensitivity, specificity, F1 score and area under the curve of the SVM model were 0.807, 0.906, 0.853 and 0.909, respectively. An automated CBF classifier derived from non-invasive EEG is feasible as a potential indicator of the CBF recovery during CPR in a VF swine model.

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Section: Discussionmentioning

confidence: 99%

EEG-Based Prediction of the Recovery of Carotid Blood Flow during Cardiopulmonary Resuscitation in a Swine Model

Kim

Hong

et al. 2021

Sensors

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“…This concludes that there can be undesired contamination of rSO2 with the extracerebral circulation [25][26][27]. Based on current evidence, NIRS may not be recommended as a precise clinical tool for routine cerebral oxygenation monitoring during post-resuscitation ICU care [28,29]. However, there is still ample room for improvement of evidence.…”

Section: Nirs Summarymentioning

confidence: 99%

Cerebral oxygenation monitoring in patients during and after cardiac arrest -- a narrative review of current methods and evidence

2021

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Hypoxic-ischemic brain injury (HIBI) is a leading cause of mortality in post-cardiac arrest (post-CA) patients who successfully survive the initial cardiopulmonary resuscitation (CPR) but later die in the Intensive Care Unit (ICU). Therefore, a key priority of post-resuscitation ICU care is to prevent and limit the impact of HIBI by optimizing the balance between cerebral oxygen delivery and demand. Traditionally, an optimal systemic oxygen balance is considered to ensure the brain’s oxygen balance. However, the validity of this assumption is uncertain, as the brain constitutes only 2%of the body mass while accounting for approximately 20% of basal oxygen consumption at rest. Hence, there is a real need to monitor cerebral oxygenation realistically. Several imaging and bedside monitoring methods are available for cerebral oxygenation monitoring in post-CA patients. Unfortunately, each of them has its limitations. Imaging methods require transporting a critically ill unstable patient to the scanner. Moreover, they provide an assessment of the oxygenation state only at a particular moment, while brain oxygenation is dynamic. Bedside methods, specifically near-infrared spectroscopy (NIRS), brain tissue oxygen tension (PbtO2), and jugular venous oxygen saturation monitoring (SjvO2), have not often been used in studies involving post-CA patients. Hence there is ambiguity regarding clear recommendations for using these bedside monitors. Presently, the most promising option seems to be using the NIRS as an indicator of effective CPR. We present a narrative review focusing on bedside methods and discuss the evidence for their use in adult patients after cardiac arrest.

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“…One of several reasons for the failure to replicate the findings of previous observational studies is the likely considerable heterogeneity in optimal targets among patients. Approximately a third of post-CA patients will lose cerebral autoregulation and are likely to require a higher MAP to preserve cerebral blood flow [9]. rSO 2 has been used to determine optimal MAP in post-CA patients but it is unknown how well rSO 2 correlates with cerebral perfusion pressure (CPP).…”

Section: Oxygenation and Ventilation And Cerebral Perfusionmentioning

confidence: 99%