Early single‐channel aEEG/EEG predicts outcome in very preterm infants

Wikström, Sverre; Pupp, Ingrid Hansen; Rosén, Ingmar; Norman, Elisabeth; Fellman, Vineta; Ley, David; Hellström‐Westas, Lena

doi:10.1111/j.1651-2227.2012.02677.x

Cited by 151 publications

(177 citation statements)

References 24 publications

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“…Early EEG grade alone demonstrated low sensitivity (50%) and high specificity (89%), highlighting the possible limitation of the EEG grades for the prediction of death or long term neurodevelopmental delay. These results are consistent with other studies which demonstrated sensitivities of 25-61% (12,16). Although many studies have shown EEG grading to be predictive of long term outcome, none have shown that simple quantitative features of the readily-available SpO 2 and HR have similar-if not better-performance at predicting 2-y outcome.…”

Section: Discussionsupporting

confidence: 82%

“…Tyson et al (11) demonstrated that a five-factor model which consists of GA, BW, gender, exposure to antenatal corticosteroids, and singleton vs. twin birth, performed better than GA alone for the prediction of outcome in a cohort of preterm infants between 22-25 wk GA. Our AUC results showed an improvement from both these two predictive models (10,11). Also for our study, the sensitivity, specificity, and OR values showed similar values or improvements to previous studies in which EEG or aEEG was evaluated as one predictor or the only predictor (13,15,16). However, studies that examined serial EEG recordings or used Articles a larger cohort size had better sensitivity or specificity values (12,14).…”

Section: Discussionsupporting

confidence: 64%

“…Other studies have shown that the amplitude integrated EEG (aEEG) can predict long-term outcome, with specificity ranging from 73 to 89% and sensitivity ranging from 56 to 87% (15)(16)(17). To date, however, no standardized method for the accurate prediction of long-term outcome in very preterm infants has been successfully translated into clinical practice.…”

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confidence: 99%

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Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring

et al. 2016

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Background: Preterm infants are at risk of adverse outcome. The aim of this study is to develop a multimodal model, including physiological signals from the first days of life, to predict 2-y outcome in preterm infants. Methods: Infants <32 wk gestation had simultaneous multichannel electroencephalography (EEG), peripheral oxygen saturation (SpO 2 ), and heart rate (HR) monitoring. EEG grades were combined with gestational age (GA) and quantitative features of HR and SpO 2 in a logistic regression model to predict outcome. Bayley Scales of Infant Development-III assessed 2-y neurodevelopmental outcome. A clinical course score, grading infants at discharge as high or low morbidity risk, was used to compare performance with the model. results: Forty-three infants were included: 27 had good outcomes, 16 had poor outcomes or died. While performance of the model was similar to the clinical course score graded at discharge, with an area under the receiver operator characteristic (AUC) of 0.83 (95% confidence intervals (CI): 0.69-0.95) vs. 0.79 (0.66-0.90) (P = 0.633), the model was able to predict 2-y outcome days after birth. conclusion: Quantitative analysis of physiological signals, combined with GA and graded EEG, shows potential for predicting mortality or delayed neurodevelopment at 2 y of age.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionsupporting

confidence: 64%

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Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring

et al. 2016

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“…In term infants with perinatal hypoxic-ischemic encephalopathy, aEEG background pattern characteristics and changes in cycling activity provide prognostic information on neurodevelopmental outcome (3). Recent studies demonstrated that early aEEG pattern can predict both short-and long-term outcome in the preterm (4,5). Normal aEEG background pattern in preterm infants (6) differs, however, from that in the term infants (7), and interpretation of its tracing is problematic because it is strongly influenced by brain maturation (6,7).…”

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confidence: 99%

Impact of perinatal factors on continuous early monitoring of brain electrocortical activity in very preterm newborns by amplitude-integrated EEG

et al. 2014

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Background: Amplitude-integrated electroencephalogram (aEEG) is increasingly used for neuromonitoring in preterms. We aimed to quantify the effects of gestational age (GA), postnatal age (PNA), and other perinatal factors on the development of aEEG early after birth in very preterm newborns with normal cerebral ultrasounds. Methods: Continuous aEEG was prospectively performed in 96 newborns (mean GA: 29.5 (range: 24.4-31.9) wk, birth weight 1,260 (580-2,120) g) during the first 96 h of life. aEEG tracings were qualitatively (maturity scores) and quantitatively (amplitudes) evaluated using preestablished criteria. results: A significant increase in all aEEG measures was observed between day 1 and day 4 and for increasing GA (P < 0.001). The effect of PNA on aEEG development was 6.4-to 11.3-fold higher than that of GA. In multivariate regression, GA and PNA were associated with increased qualitative and quantitative aEEG measures, whereas small-for-GA status was independently associated with increased maximum aEEG amplitude (P = 0.003). Morphine administration negatively affected all aEEG measures (P < .05), and caffeine administration negatively affected qualitative aEEG measures (P = 0.02). conclusion: During the first few days after birth, aEEG activity in very preterm infants significantly develops and is strongly subjected to the effect of PNA. Perinatal factors may alter the early aEEG tracing and interfere with its interpretation.

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“…In fact, in the preterm newborn the predominant aEEG background pattern is discontinuous [3] ; the aEEG trace evolution early after birth is influenced by the time of extrauterine exposure [4][5][6] , and the cyclical character is less defined than in term newborns [2,6,7] . Previous work has focused on the changes on aEEG in association with brain abnormalities in preterms, identifying voltage suppression and the absence of cycling activity [9][10][11] as markers of poor short-and long-term outcome [12] . A better knowledge on the evolution of maturational patterns of aEEG in preterms may improve early detection of brain abnormalities and outcome prediction.…”

Section: Introductionmentioning

confidence: 99%

Delayed Cyclic Activity Development on Early Amplitude-Integrated EEG in the Preterm Infant with Brain Lesions

et al. 2012

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Background: Maturation of amplitude-integrated electroencephalogram (aEEG) activity is influenced by both gestational age (GA) and postmenstrual age. It is not fully known how this process is influenced by cerebral lesions. Objective: To compare early aEEG developmental changes between preterm newborns with different degrees of cerebral lesions on cranial ultrasound (cUS). Methods: Prospective cohort study on preterm newborns with GA <32.0 weeks, undergoing continuous aEEG recording during the first 84 h after birth. aEEG characteristics were qualitatively and quantitatively evaluated using pre-established criteria. Based on cUS findings three groups were formed: normal (n = 78), mild (n = 20), and severe cerebral lesions (n = 6). Linear mixed models for repeated measures were used to analyze aEEG maturational trajectories. Results: 104 newborns with a mean GA (range) 29.5 (24.4-31.7) weeks, and birth weight 1,220 (580-2,020) g were recruited. Newborns with severe brain lesions started with similar aEEG scores and tendentially lower aEEG amplitudes than newborns without brain lesions, and showed a slower development of the cyclic activity (p < 0.001), but a more rapid increase of the maximum and minimum aEEG amplitudes (p = 0.002 and p = 0.04). Conclusions: Preterm infants with severe cerebral lesions manifest a maturational delay in the aEEG cyclic activity already early after birth, but show a catch-up of aEEG amplitudes to that of newborns without cerebral lesions. Changes in the maturational aEEG pattern may be a marker of severe neurological lesions in the preterm infant. brain lesions started with similar aEEG scores and tendentially lower aEEG amplitudes than newborns without brain lesions, and showed a slower development of the cyclic activity (p ! 0.001), but a more rapid increase of the maximum and minimum aEEG amplitudes (p = 0.002 and p = 0.04). Conclusions: Preterm infants with severe cerebral lesions manifest a maturational delay in the aEEG cyclic activity already early after birth, but show a catch-up of aEEG amplitudes to that of newborns without cerebral lesions. Changes in the maturational aEEG pattern may be a marker of severe neurological lesions in the preterm infant.

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Early single‐channel aEEG/EEG predicts outcome in very preterm infants

Cited by 151 publications

References 24 publications

Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring

Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring

Impact of perinatal factors on continuous early monitoring of brain electrocortical activity in very preterm newborns by amplitude-integrated EEG

Delayed Cyclic Activity Development on Early Amplitude-Integrated EEG in the Preterm Infant with Brain Lesions

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