Sleep-wake cycle on amplitude-integrated EEG and neuroimage outcomes in newborns

Sleep state organisation of moderate to late preterm infants in the neonatal unit

BACKGROUND

Sleep supports neurodevelopment and sleep architecture reflects brain maturation. This prospective observational study describes the nocturnal sleep architecture of healthy moderate to late preterm (MLP) infants in the neonatal unit at 36 weeks post menstrual age (PMA).

METHODS

MLP infants, in the neonatal unit of a tertiary hospital in Ireland from 2017 to 2018, had overnight continuous electroencephalography (cEEG) with video for a minimum 12 h at 36 weeks PMA. The total sleep time (TST) including periods of active sleep (AS), quiet sleep (QS), indeterminate sleep (IS), wakefulness and feeding were identified, annotated and quantified.

RESULTS

A total of 98 infants had cEEG with video monitoring suitable for analysis. The median (IQR) of TST in the 12 h period was 7.09 h (IQR 6.61-7.76 h), 4.58 h (3.69-5.09 h) in AS, 2.02 h (1.76-2.36 h) in QS and 0.65 h (0.48-0.89 h) in IS. The total duration of AS was significantly lower in infants born at lower GA (p = 0.007) whilst the duration of individual QS periods was significantly higher (p = 0.001).

CONCLUSION

Overnight cEEG with video at 36 weeks PMA showed that sleep state architecture is dependent on birth GA. Infants with a lower birth GA have less AS and more QS that may have implications for later neurodevelopment.

IMPACT

EEG provides objective information about the sleep organisation of the moderate to late preterm (MLP) infant. Quantitative changes in sleep states occur with each week of advancing gestational age (GA). Active sleep (AS) is the dominant sleep state that was significantly lower in infants born at lower GA. MLP infants who were exclusively fed orally had a shorter total sleep time and less AS compared to infants who were fed via nasogastric tube.

Developmental characteristics of early electroencephalography in preterm neonates: Differences between twins and singletons

BACKGROUND

To analyze the early electroencephalography (EEG) development of twins and singleton preterm neonates using 5 measurement indicators.

METHODS

On the 1st and 7th days after birth, EEG monitoring was performed on 102 preterm neonates (62 males, median gestational age 33.15 weeks, IQR 31.00-35.75). The minimum amplitude, maximum amplitude, maximum interburst intervals (IBI), total duration of trace discontinue (TD), maximum duration of single TD, and the Burdjalov score of amplitude-integrated electroencephalography (aEEG) were used to evaluate EEG recordings.

RESULTS

The minimum amplitude of EEG increases with gestational age (GA), while the maximum amplitude decreases, the maximum IBI decreases, and the total duration of TD and the maximum duration of single TD decrease (all p < 0.05). Burdjalov score did not differ significantly between the 1st and 7th days (p = 0.075). There is no significant difference between twins and singleton preterm infants in the five EEG measurement indicators (p > 0.05 for all).

CONCLUSION

The five EEG measurement indicators can better reflect preterm infants' brain maturation than the Burdjalov score in aEEG. There were no statistical differences in brain maturation between twin and singleton preterm infants.

Prophylactic Low-Dose Paracetamol Administration for Ductal Closure and Amplitude-Integrated Electroencephalography in Preterm Infants

INTRODUCTION

Prophylactic low-dose paracetamol administration is used to induce closure of the ductus arteriosus in preterm infants. In our recent study we found no impairment on microstructural maturation processes in the brain of preterm infants at term-equivalent age following prophylactic low-dose paracetamol administration. We now assessed amplitude-integrated electroencephalography (aEEG) signals in preterm infants with and without exposure to prophylactic low-dose paracetamol administration.

METHODS

Infants <32 gestational weeks born between 10/2014 and 12/2018 received prophylactic paracetamol (10 mg/kg intravenously every 8 h until echocardiography after at least 72 h) and form the paracetamol group; infants born between 02/2011 and 09/2014 formed the control group. Four single parameters (continuity, cyclicity, amplitude of lower border, bandwidth span) together with their sum (Burdjalov total score) and presence of sleep-wake cycles were compared between the groups.

RESULTS

Included in the study were 338 infants. Two-hundred and seventeen infants received prophylactic paracetamol and 121 formed the control group. The paracetamol group showed a significantly higher number of sleep-wake cycles per hour and a significantly higher total scores compared to the control group (p < 0.05).

CONCLUSION

Paracetamol exposure has been regarded critically with respect to safety in preterm infants in recent years. We found no impairment on amplitude-integrated electroencephalography signals in preterm infants receiving low-dose prophylactic paracetamol compared to controls. Growing awareness and greater availability of data may encourage the clinicians to administer prophylactic paracetamol for ductal closure in preterm infants. The clinical relevance of our findings has to be evaluated in long-term follow up studies on neurodevelopmental outcome.

Amplitude-integrated electroencephalography improves the predictive ability of acute bilirubin encephalopathy

BACKGROUND

To establish a clinical prediction model of acute bilirubin encephalopathy (ABE) using amplitude-integrated electroencephalography (aEEG).

METHODS

A total of 114 neonatal hyperbilirubinemia patients in the Beijing Chaoyang Hospital from August 2015 to October 2018 were enrolled in this study. There were 62 (54.38%) males, and the age of patients undergoing aEEG examination was 2-23 days, with an average of 7.61±4.08 days. Participant clinical information, peak bilirubin value, albumin value, hyperbilirubinemia, and the graphic indicators of aEEG were extracted from medical records, and ABE was diagnosed according to a bilirubin-induced neurological dysfunction (BIND) score >0. Multivariable logistic regression was used to establish a clinical prediction model of ABE. Furthermore, decision curve analysis (DCA) was performed to evaluate the model's predictive value.

RESULTS

According to the BIND score, there were a total of 23 (20.18%) ABE cases. The multivariable logistic regression analysis showed that the value of bilirubin/albumin (B/A), presence of hyperbilirubinemia risk factors, number of sleep-wake cycling (SWC) within 3 hours, widest bandwidth, duration of SWC, and type of SWC were significantly associated with ABE. A clinical prediction model was developed as: p=ex/ (1+ex), X=0.278+0.713*B/A+2.602*with risk factors (with risk factors equals 1) - 1.500*SWC number within 3 hours + 0.219*the widest bandwidth-0.065*the duration of one SWC + 1.491* SWC (mature SWC equals 0, immature SWC equals 1). The area under the curve (AUC) was 0.85 [95% confidence interval (CI): 0.75-0.94], which was significantly higher than the AUC only based on conventional clinical information of B/A (AUC: 0.58, 95% CI: 0.45-0.72). The DCA also showed good predictive ability compared to B/A.

CONCLUSIONS

A clinical prediction model can be established based on the patients' B/A, presence of risk factors for hyperbilirubinemia, number of SWC within 3 hours, widest bandwidth, duration of 1 SWC, and the type of SWC. It has good predictive ability and may improve the diagnostic accuracy of ABE.

Evaluation of maturity of sleep states in preterm infants using conventional and amplitude-integrated electroencephalography

OBJECTIVE

To determine whether sleep state maturity can be estimated accurately using conventional electroencephalography (cEEG) or amplitude-integrated electroencephalography (aEEG) features concerning sleep in neurologically unimpaired preterm infants.

METHODS

A total of 51 preterm infants were monitored with cEEG-polygraphy and simultaneous aEEG. Sleep state maturity of EEG corresponded to specific postmenstrual age (PMA). PMA on cEEG was blindly estimated according to cEEG patterns (indicated as background continuity, frequencies, and voltages) as well as developmental markers in specific states. PMA on aEEG was blindly estimated based on the cycling score (cycling representing sleep state transitions) according to a pre-established scoring system.

RESULTS

A total of 51 EEGs recorded between 32 and 37 weeks PMA were analysed. A significant relationship between estimated PMA (ePMA) and actual chronological PMA (cPMA) was shown by linear regression both on cEEG (r = 0.93, β = 0.98, 95% confidence interval (CI) 0.87-1.09, p < 0.001) and aEEG (r = 0.85, β = 0.83, 95% CI 0.69-0.98, p < 0.001). The estimation gap (defined as ePMA minus cPMA) was between -2 and +2 weeks both on cEEG and aEEG. The percentage of estimation gap between -1 and +1 weeks was 96% for cEEG, which was higher than the estimate of 88% for aEEG.

CONCLUSION

Estimated maturity of sleep state was well correlated with cPMA both on cEEG and aEEG. PMA corresponding to state maturity could be estimated within two weeks of actual cPMA using either of these two tools. However, cEEG had higher accuracy compared with aEEG in the evaluation of sleep state maturity.

Prognostic value of amplitude-integrated EEG in neonates with high risk of neurological sequelae

OBJECTIVE

To determine the efficacy and the prognostic value of amplitude-integrated electroencephalography (aEEG) in term and near-term neonates with high risk of neurological sequelae.

METHODS

Infants of ≥35 weeks of gestation diagnosed with neonatal encephalopathy or with high risk of brain injury were included. All eligible infants underwent aEEG within 6 h after clinical assessment. The infants were followed up 12 months to evaluate neurological development.

RESULTS

A total of 250 infants were eligible, of which 85 had normal aEEG, 81 had mildly abnormal aEEG, and 84 had severely abnormal aEEG. Of these infants, 168 were diagnosed with different neonatal encephalopathies, 27 with congenital or metabolic diseases, and 55 with high risk of brain injury. In all, 22 infants died, 19 were lost to follow-up, and 209 completed the follow-up at 12 months, of which 62 were diagnosed with a neurological disability. Statistical analysis showed that severely abnormal aEEG predicted adverse neurological outcome with a sensitivity of 70.2%, a specificity of 87.1%, a positive predictive value of 75.6%, and a negative predictive value of 83.7%.

INTERPRETATION

aEEG can predict adverse outcomes in high-risk neonates and is a useful method for monitoring neonates with high risk of adverse neurological outcomes.

Amplitude-integrated EEG in infants with neonatal abstinence syndrome

BACKGROUND

To describe amplitude-integrated encephalogram (aEEG) characteristics of neonates with neonatal abstinence syndrome (NAS).

METHODS

This is a prospective observational study. Newborns exposed to prenatal opioids and their gestational matched controls were included. A single-channel aEEG was obtained using Olympic 6000 CFM monitor. The background activity (continuous/discontinuous), the amplitudes (μV) and the presence of sleep-wake cycle (SWC) were documented.

RESULTS

A total of 59 infants, 23 with NAS and 36 controls were enrolled. All aEEG were completed within 48 hours of life prior to initiation of treatment. Birth weight and gestational age were similar in both groups. An aEEG was abnormal (discontinuous pattern and/or absent SWC) in 78 % (18/23) of infants with NAS versus only 25% in control group (9/36), [OR 10.8, CI (2.7-46.5) P < 0.001]. 61% of infants with NAS had discontinuous pattern [OR 7.8, CI (2-32) P = 0.001] and 39% had absence of sleep-wake cycle [OR 7.1, CI (1.4-39.4) P = 0.007].

CONCLUSIONS

A majority of infants with NAS have abnormal aEEG activity.