1
|
Yao J, Zhang M, Qiu Y. Effect of Combining Intrauterine Cerebral Blood Flow Changes with Electrical Activity on Prognostic Evaluation of Brain Injury. World Neurosurg 2024; 187:e115-e121. [PMID: 38616024 DOI: 10.1016/j.wneu.2024.04.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 04/07/2024] [Accepted: 04/08/2024] [Indexed: 04/16/2024]
Abstract
OBJECTIVES We sought to investigate the value of combining intrauterine cerebral blood flow changes with brain electrical activity examination in evaluating the prognosis of brain injury. METHODS A total of 90 preterm infants were enrolled and divided into 2 groups: the brain damaged preterm infants group (n = 55) and the nonbrain damaged preterm infants group (n = 35). The diagnostic efficacy of combining intrauterine cerebral blood flow changes with electroencephalogram (EEG) activity examination in predicting the prognosis of preterm infants with brain injury was evaluated using T-test. Pearson linear correlation was applied to analyze the relationship between fetal intrauterine cerebral blood flow changes combined with electrical activity examination and the prognosis of brain injury. RESULTS Significant differences were seen in pulse index, the ratio of peak systolic velocity to end diastolic velocity ratio, and other indexes between the 2 groups (P < 0.05). The combined approach of intrauterine cerebral blood flow changes with EEG activity examination demonstrated significantly higher values for area under the curve, sensitivity and negative predictive value compared to using intrauterine cerebral blood flow changes or EEG activity examination alone (P < 0.05). A positive correlation was found between fetal intrauterine cerebral blood flow and electrical activity examination (P < 0.05). CONCLUSIONS Combining the assessment of intrauterine cerebral blood flow changes with cerebral electrical activity examination proved beneficial in diagnosing the prognosis of brain injury and provided an important reference for early clinical intervention.
Collapse
Affiliation(s)
- Juan Yao
- Department of Pediatric, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Man Zhang
- Department of Pediatric, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yu Qiu
- Department of Pediatric, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
| |
Collapse
|
2
|
Wang X, de Groot ER, Tataranno ML, van Baar A, Lammertink F, Alderliesten T, Long X, Benders MJNL, Dudink J. Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants. J Neurosci 2024; 44:e1024232023. [PMID: 38124010 PMCID: PMC10860564 DOI: 10.1523/jneurosci.1024-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 12/23/2023] Open
Abstract
White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.
Collapse
Affiliation(s)
- Xiaowan Wang
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Eline R de Groot
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Maria Luisa Tataranno
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Anneloes van Baar
- Child and Adolescent Studies, Utrecht University, Utrecht 3584 CS, The Netherlands
| | - Femke Lammertink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Thomas Alderliesten
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5612 AZ, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| |
Collapse
|
3
|
Plomgaard AM, Stevenson N, Roberts JA, Hvass Petersen T, Vanhatalo S, Greisen G. Early EEG-burst sharpness and 2-year disability in extremely preterm infants. Pediatr Res 2024; 95:193-199. [PMID: 37500756 PMCID: PMC10798884 DOI: 10.1038/s41390-023-02753-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 06/17/2023] [Accepted: 07/07/2023] [Indexed: 07/29/2023]
Abstract
BACKGROUND Automated computational measures of EEG have the potential for large-scale application. We hypothesised that a predefined measure of early EEG-burst shape (increased burst sharpness) could predict neurodevelopmental impairment (NDI) and mental developmental index (MDI) at 2 years of age over-and-above that of brain ultrasound. METHODS We carried out a secondary analysis of data from extremely preterm infants collected for an RCT (SafeBoosC-II). Two hours of single-channel cross-brain EEG was used to analyse burst sharpness with an automated algorithm. The co-primary outcomes were moderate-or-severe NDI and MDI. Complete data were available from 58 infants. A predefined statistical analysis was adjusted for GA, sex and no, mild-moderate, and severe brain injury as detected by cranial ultrasound. RESULTS Nine infants had moderate-or-severe NDI and the mean MDI was 87 ± 17.3 SD. The typical burst sharpness was low (negative values) and varied relatively little (mean -0.81 ± 0.11 SD), but the odds ratio for NDI was increased by 3.8 (p = 0.008) and the MDI was reduced by -3.2 points (p = 0.14) per 0.1 burst sharpness units increase (+1 SD) in the adjusted analysis. CONCLUSION This study confirms the association between EEG-burst measures in preterm infants and neurodevelopment in childhood. Importantly, this was by a priori defined analysis. IMPACT A fully automated, computational measure of EEG in the first week of life was predictive of neurodevelopmental impairment at 2 years of age. This confirms many previous studies using expert reading of EEG. Only single-channel EEG data were used, adding to the applicability. EEG was recorded by several different devices thus this measure appears to be robust to differences in electrodes, amplifiers and filters. The likelihood ratio of a positive EEG test, however, was only about 2, suggesting little immediate clinical value.
Collapse
Affiliation(s)
- Anne Mette Plomgaard
- Department of Neonatology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Nathan Stevenson
- Brain Modelling Group, QIMR Berghofer Medical Research Institute, Herston, Brisbane, QLD, 4006, Australia
| | - James A Roberts
- Brain Modelling Group, QIMR Berghofer Medical Research Institute, Herston, Brisbane, QLD, 4006, Australia
| | | | - Sampsa Vanhatalo
- BABA Center, Departments of Clinical Neurophysiology and Physiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Gorm Greisen
- Department of Neonatology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
| |
Collapse
|
4
|
Koskela T, Meek J, Huertas-Ceballos A, Kendall GS, Whitehead K. Clinical value of cortical bursting in preterm infants with intraventricular haemorrhage. Early Hum Dev 2023; 184:105840. [PMID: 37556995 DOI: 10.1016/j.earlhumdev.2023.105840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/31/2023] [Accepted: 08/01/2023] [Indexed: 08/11/2023]
Abstract
BACKGROUND In healthy preterm infants, cortical burst rate and temporal dynamics predict important measures such as brain growth. We hypothesised that in preterm infants with germinal matrix-intraventricular haemorrhage (GM-IVH), cortical bursting could provide prognostic information. AIMS We determined how cortical bursting was influenced by the injury, and whether this was related to developmental outcome. STUDY DESIGN Single-centre retrospective cohort study at University College London Hospitals, UK. SUBJECTS 33 infants with GM-IVH ≥ grade II (median gestational age: 25 weeks). OUTCOME MEASURES We identified 47 EEGs acquired between 24 and 40 weeks corrected gestational age as part of routine clinical care. In a subset of 33 EEGs from 25 infants with asymmetric injury, we used the least-affected hemisphere as an internal comparison. We tested whether cortical burst rate predicted survival without severe impairment (median 2 years follow-up). RESULTS In asymmetric injury, cortical burst rate was lower over the worst- than least-affected hemisphere, and bursts over the worst-affected hemisphere were less likely to immediately follow bursts over the least-affected hemisphere than vice versa. Overall, burst rate was lower in cases of GM-IVH with parenchymal involvement, relative to milder structural injury grades. Higher burst rate modestly predicted survival without severe language (AUC 0.673) or motor impairment (AUC 0.667), which was partly mediated by structural injury grade. CONCLUSIONS Cortical bursting can index the functional injury after GM-IVH: perturbed burst initiation (rate) and propagation (inter-hemispheric dynamics) likely reflect associated grey matter and white matter damage. Higher cortical burst rate is reassuring for a positive outcome.
Collapse
Affiliation(s)
- Tuomas Koskela
- Research IT Services, University College London, London WC1E 7HB, UK.
| | - Judith Meek
- Neonatal Intensive Care Unit, Elizabeth Garrett Anderson Wing, University College London Hospitals, London WC1E 6DB, UK; Academic Neonatology, Institute for Women's Health, University College London, London WC1E 6HU, UK.
| | - Angela Huertas-Ceballos
- Neonatal Intensive Care Unit, Elizabeth Garrett Anderson Wing, University College London Hospitals, London WC1E 6DB, UK.
| | - Giles S Kendall
- Neonatal Intensive Care Unit, Elizabeth Garrett Anderson Wing, University College London Hospitals, London WC1E 6DB, UK; Academic Neonatology, Institute for Women's Health, University College London, London WC1E 6HU, UK.
| | - Kimberley Whitehead
- Neonatal Intensive Care Unit, Elizabeth Garrett Anderson Wing, University College London Hospitals, London WC1E 6DB, UK; Department of Neuroscience, Physiology & Pharmacology, University College London, London WC1E 6BT, UK.
| |
Collapse
|
5
|
Wang X, Bik A, de Groot ER, Tataranno ML, Benders MJNL, Dudink J. Feasibility of automated early postnatal sleep staging in extremely and very preterm neonates using dual-channel EEG. Clin Neurophysiol 2023; 146:55-64. [PMID: 36535092 DOI: 10.1016/j.clinph.2022.11.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 10/25/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To investigate the feasibility of automated sleep staging based on quantitative analysis of dual-channel electroencephalography (EEG) for extremely and very preterm infants during their first postnatal days. METHODS We enrolled 17 preterm neonates born between 25 and 30 weeks of gestational age. Three-hour behavioral sleep observations and simultaneous dual-channel EEG monitoring were conducted for each infant within their first 72 hours after birth. Four kinds of representative and complementary quantitative EEG (qEEG) metrics (i.e., bursting, synchrony, spectral power, and complexity) were calculated and compared between active sleep, quiet sleep, and wakefulness. All analyses were performed in offline mode. RESULTS In separate comparison analyses, significant differences between sleep-wake states were found for bursting, spectral power and complexity features. The automated sleep-wake state classifier based on the combination of all qEEG features achieved a macro-averaged area under the curve of receiver operating characteristic of 74.8%. The complexity features contributed the most to sleep-wake state classification. CONCLUSIONS It is feasible to distinguish between sleep-wake states within the first 72 postnatal hours for extremely and very preterm infants using qEEG metrics. SIGNIFICANCE Our findings offer the possibility of starting personalized care dependent on preterm infants' sleep-wake states directly after birth, potentially yielding long-run benefits for their developmental outcomes.
Collapse
Affiliation(s)
- Xiaowan Wang
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anne Bik
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Eline R de Groot
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maria Luisa Tataranno
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.
| |
Collapse
|
6
|
Sensory-based interventions in the NICU: systematic review of effects on preterm brain development. Pediatr Res 2022; 92:47-60. [PMID: 34508227 DOI: 10.1038/s41390-021-01718-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 07/12/2021] [Accepted: 08/17/2021] [Indexed: 11/08/2022]
Abstract
BACKGROUND Infants born preterm are known to be at risk for abnormal brain development and adverse neurobehavioral outcomes. To improve early neurodevelopment, several non-pharmacological interventions have been developed and implemented in the neonatal intensive care unit (NICU). Sensory-based interventions seem to improve short-term neurodevelopmental outcomes in the inherently stressful NICU environment. However, how this type of intervention affects brain development in the preterm population remains unclear. METHODS A systematic review of the literature was conducted for published studies in the past 20 years reporting the effects of early, non-pharmacological, sensory-based interventions on the neonatal brain after preterm birth. RESULTS Twelve randomized controlled trials (RCT) reporting short-term effects of auditory, tactile, and multisensory interventions were included after the screening of 1202 articles. Large heterogeneity was identified among studies in relation to both types of intervention and outcomes. Three areas of focus for sensory interventions were identified: auditory-based, tactile-based, and multisensory interventions. CONCLUSIONS Diversity in interventions and outcome measures challenges the possibility to perform an integrative synthesis of results and to translate these for evidence-based clinical practice. This review identifies gaps in the literature and methodological challenges for the implementation of RCTs of sensory interventions in the NICU. IMPACT This paper represents the first systematic review to investigate the effect of non-pharmacological, sensory-based interventions in the NICU on neonatal brain development. Although reviewed RCTs present evidence on the impact of such interventions on the neonatal brain following preterm birth, it is not yet possible to formulate clear guidelines for clinical practice. This review integrates existing literature on the effect of sensory-based interventions on the brain after preterm birth and identifies methodological challenges for the conduction of high-quality RCTs.
Collapse
|
7
|
Volpe J. Commentary - Cerebellar underdevelopment in the very preterm infant: Important and underestimated source of cognitive deficits. J Neonatal Perinatal Med 2021; 14:451-456. [PMID: 33967062 PMCID: PMC8673497 DOI: 10.3233/npm-210774] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Affiliation(s)
- J.J. Volpe
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Newborn Medicine, Harvard Medical School, Boston, MA, USA
- Address for correspondence: Joseph J. Volpe, M.D., Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, 221 Longwood Avenue, Room 343C, Boston, MA 02115 USA. Tel.: +1 617 525 4145; E-mail:
| |
Collapse
|