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Preterm EEG: A Multimodal Neurophysiological Protocol
Published on: February 18, 2012
Early Detection of Preterm Intraventricular Hemorrhage From Clinical Electroencephalography
Kartik K Iyer1, James A Roberts, Lena Hellström-Westas
11Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. 2School of Medicine, Faculty of Medicine and Biomedical Sciences, University of Queensland, QLD, Australia. 3Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden. 4Department of Pediatrics, Karlstad Central Hospital, Karlstad, Sweden. 5Department of Pediatrics, Institute for Clinical Sciences, Lund University, Lund, Sweden. 6Metro North Mental Health Service, Brisbane, QLD, Australia. 7Department of Children's Clinical Neurophysiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland. 8Department of Pediatrics, Children's Hospital, University Central Hospital and University of Helsinki, Helsinki, Finland.
Insights
Early detection of intraventricular hemorrhage in extremely preterm infants is possible using bedside electroencephalography (EEG) brain activity measures. This novel EEG analysis can predict hemorrhage before ultrasound confirmation, improving neonatal care.
Area of Science:
- Neonatal Neurology
- Neurodevelopmental Pediatrics
- Medical Technology
Background:
- Intraventricular hemorrhage (IVH) is a frequent complication in extremely preterm infants, often leading to long-term neurodevelopmental deficits.
- Timely intervention is critical for managing IVH, necessitating early and accurate detection methods.
- Current diagnostic tools may not always provide the earliest possible identification of IVH.
Purpose of the Study:
- To identify early brain activity markers predictive of intraventricular hemorrhage (IVH) in extremely preterm infants within the first few postnatal days.
- To assess if quantitative electroencephalography (EEG) measures can preemptively detect IVH occurrence and severity.
- To evaluate the potential of bedside EEG for early IVH diagnosis before ultrasound confirmation.
Main Methods:
- A cross-sectional study involving 25 extremely preterm infants (22-28 weeks gestational age) in a Level III neonatal ICU.
- Quantitative electroencephalography (EEG) was analyzed within the first 72 postnatal hours, focusing on burst activity.
- Cranial ultrasound was performed on postnatal days 1 and 3 to categorize IVH severity (grades 0-4).
Main Results:
- EEG burst shapes in infants with IVH were significantly sharper and less symmetric compared to those without IVH (p < 0.0001 and p < 0.015, respectively).
- Automated EEG analysis, specifically burst symmetry and sharpness, demonstrated high true-positive rates (82% and 88%) and low false-positive rates (19% and 8%) for IVH detection.
- Conventional EEG metrics like interburst intervals and burst counts did not show significant association with IVH.
Conclusions:
- Bedside EEG measures of brain activity can detect intraventricular hemorrhage (IVH) in the early postnatal period, preceding ultrasound findings.
- Novel automated EEG analysis shows promise in preempting IVH occurrence in extremely preterm neonates.
- Early bedside EEG detection of IVH can enhance individualized care, guide therapeutic trials, and deepen the understanding of neonatal brain injury mechanisms.
Objectives:
Intraventricular hemorrhage is a common neurologic complication of extremely preterm birth and leads to lifelong neurodevelopmental disabilities. Early bedside detection of intraventricular hemorrhage is crucial to enabling timely interventions. We sought to detect early markers of brain activity that preempt the occurrence of intraventricular hemorrhage in extremely preterm infants during the first postnatal days.
Design:
Cross-sectional study.
Setting:
Level III neonatal ICU.
Patients:
Twenty-five extremely preterm infants (22-28 wk gestational age).
Measurements And Main Results:
We quantitatively assessed electroencephalography in the first 72 hours of postnatal life, focusing on the electrical burst activity of the preterm. Cranial ultrasound was performed on day 1 (0-24 hr) and day 3 (48-72 hr). Outcomes were categorized into three classes: 1) no intraventricular hemorrhage (grade 0); 2) mild-moderate intraventricular hemorrhage (grades 1-2, i.e., germinal matrix hemorrhages or intraventricular hemorrhage without ventricular dilatation, respectively); and 3) severe intraventricular hemorrhage (grades 3-4, i.e., intraventricular hemorrhage with ventricular dilatation or intraparenchymal involvement). Quantitative assessment of electroencephalography burst shapes was used to preempt the occurrence and severity of intraventricular hemorrhage as detected by ultrasound. The shapes of electroencephalography bursts found in the intraventricular hemorrhage infants were significantly sharper (F = 13.78; p < 0.0001) and less symmetric (F = 6.91; p < 0.015) than in preterm infants without intraventricular hemorrhage. Diagnostic discrimination of intraventricular hemorrhage infants using measures of burst symmetry and sharpness yielded high true-positive rates (82% and 88%, respectively) and low false-positive rates (19% and 8%). Conventional electroencephalography measures of interburst intervals and burst counts were not significantly associated with intraventricular hemorrhage.
Conclusions:
Detection of intraventricular hemorrhage during the first postnatal days is possible from bedside measures of brain activity prior to ultrasound confirmation of intraventricular hemorrhage. Significantly, our novel automated assessment of electroencephalography preempts the occurrence of intraventricular hemorrhage in the extremely preterm. Early bedside detection of intraventricular hemorrhage holds promise for advancing individual care, targeted therapeutic trials, and understanding mechanisms of brain injury in neonates.
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