Peak-to-peak amplitude in neonatal brain monitoring of premature infants

O’Reilly, Deirdre; Navakatikyan, Michael A.; Filip, Marcia; Greene, Deirdre; Marter, Linda J. Van

doi:10.1016/j.clinph.2012.02.087

Cited by 31 publications

(26 citation statements)

References 34 publications

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“…Since the aEEG procedures of commercially available devices are not public, we could only estimate the filters. The subset of methods we analyzed does not comprehensively cover the different algorithms for filter, peak detection, and LMA/UMA estimation [8,12,19,20,21]. This unanalyzed variability, however, only supports our conclusions that different aEEG devices provide different outputs.…”

Section: Discussioncontrasting

confidence: 50%

Are All Amplitude-Integrated Electroencephalogram Systems Equal?

et al. 2017

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Background: Filter and peak detection algorithms implemented in amplitude-integrated electroencephalogram (aEEG) systems are not standardized. New aEEG systems are continuously enriching the market and clinicians are faced with different aEEG devices whose tracings may vary. Objectives: The aim of this work was to determine the role of different aEEG systems on quantitative measurements of the aEEG. Methods: In this observational study, a single-channel aEEG recording (Olympic CFM 6000) with corresponding EEG signal was obtained from 32 infants at a gestational age of 36-44 weeks. The signals were split into 334 episodes of 4 h. New aEEG tracings were generated using the NicoletOne Reader Software and aEEG emulations with varying filter profiles and peak detection settings. The aEEG amplitude margins and automated annotation of continuous normal voltage (CNV) were compared. Results: The output of the Olympic and the NicoletOne systems are very similar but not identical; the Spearman rank correlations of the aEEG amplitude margins exceeded 0.9 and the differences in the lower and upper amplitude margins were 1.55 μV (SD 1.47) and -2.12 μV (SD 1.44) on average (n = 309), respectively. The aEEG emulation showed that the differences between the output of the Olympic and the NicoletOne system could be primarily ascribed to the peak detection algorithm. The differences in output can affect automated analyses with agreement rates in CNV detection of 76% (n = 32, positive) and 92% (n = 32, negative) when comparing the Olympic to the NicoletOne outputs. Conclusions: Commercial aEEG systems have similar but not identical outputs. Care is advised when interpreting automated aEEG classifications across different devices.

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Section: Discussioncontrasting

confidence: 50%

Are All Amplitude-Integrated Electroencephalogram Systems Equal?

et al. 2017

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“…intermittent quiescence (Lombroso, 1985;Olischar et al, 2004Olischar et al, , 2007O'Reilly et al,2012;Selton et al, 2000;Vecchierini et al, 2007), hence the rEEG feature (lower margin) incorporates an age component as well. Likewise, delta 1 power has been shown to decrease with age (Niemarkt et al, 2011;Okumura et al, 2003;Scher et al, 1995).…”

Section: Discussionmentioning

confidence: 99%

“…The novel EEG trend called range EEG (rEEG) is defined as the maximum EEG value minus the minimum EEG value in nonoverlapping 2 s windows (Navakatikyan et al, 2016;O'Reilly et al, 2012). In each 10-min epoch, we computed 7 features of the rEEG transform: the mean, median, upper margin (UM), lower margin (LM), standard deviation, interquartile range and the skewness.…”

Section: Frequency-domain Featuresmentioning

confidence: 99%

Automated classification of neonatal sleep states using EEG

Koolen

Oberdorfer

Rona

et al. 2017

Clinical Neurophysiology

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“…The raw EEG was band pass filtered (0.5–30 Hz) using a zero phase filter and converted into range-EEG (rEEG) [19]. Artefacts in the rEEG were independently visually identified by two of the authors (GG and AMP) blinded to the clinical history of the infant.…”

Section: Methodsmentioning

confidence: 99%

Early biomarkers of brain injury and cerebral hypo- and hyperoxia in the SafeBoosC II trial

et al. 2017

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BackgroundThe randomized clinical trial, SafeBoosC II, examined the effect of monitoring of cerebral oxygenation by near-infrared spectroscopy combined with a guideline on treatment when cerebral oxygenation was out of the target range. Data on cerebral oxygenation was collected in both the intervention and the control group. The primary outcome was the reduction in the burden of cerebral hypo- and hyperoxia between the two groups. In this study we describe the associations between the burden of cerebral hypo- and hyperoxia, regardless of allocation to intervention or control group, and the biomarkers of brain injury from birth till term equivalent age that was collected as secondary and explorative outcomes in the SafeBoosC II trial.MethodsCerebral oxygenation was continuously monitored during the first 72h of life in 166 extremely preterm infants. Cranial ultrasound was performed at day 1,4,7,14, and 35 and at term. Electroencephalogram (EEG) was recorded at 64h. Blood-samples taken at 6 and 64 hours were analysed for the brain injury biomarkers; S100beta, brain-fatty-acid-binding-protein, and neuroketal. All analyses were conducted post hoc.ResultsSignificantly more infants with a cerebral burden of hypoxia within the 4th quartile versus infants within quartile 1–3 were diagnosed with severe intracranial haemorrhage (11/39 versus 11/117, p = 0.003), had low burst rate on EEG (12/28 versus 21/103, p = 0.015), or died (14/41 versus 18/123, p = 0.006), whereas none of these events were significantly associated with cerebral hyperoxia. The blood biomarkers were not significantly associated with the burden of cerebral hypo- or hyperoxia.ConclusionsThe explorative analysis showed that early burden of cerebral hypoxia, but not hyperoxia was significantly associated with low brain electrical activity and severe intracranial haemorrhage while none of the three blood biomarkers were associated with the burden of either cerebral hypo- or hyperoxia.

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Peak-to-peak amplitude in neonatal brain monitoring of premature infants

Cited by 31 publications

References 34 publications

Are All Amplitude-Integrated Electroencephalogram Systems Equal?

Are All Amplitude-Integrated Electroencephalogram Systems Equal?

Automated classification of neonatal sleep states using EEG

Early biomarkers of brain injury and cerebral hypo- and hyperoxia in the SafeBoosC II trial

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