aEEG(Amplitude Integrated EEG) in Neonates

A comprehensive approach on aEEG in Neonates..

1. NEUROMONITORING IN NICU (a EEG & NIRS) Presenter Dr R K Shwetabh Moderator Dr Sushil Kumar Asst Professor

2. Specific Learning Objectives Introduction Mechanism Indications Uses Research Limitations aEEG NIRS

3. Introduction

4. Introduction Neuromonitoring is the continuous screening and assessment of neurologic status at the bedside Bedside neurological examination traditionally been used Often insufficient for diagnosis, prognosis and complete characterisation Electroclinical dissociation of seizures Any derangement in structural or functional integrity changes electrical properties This can be picked up by proximately placed electrodes and analyzed

5. In What Situations It Is Useful To Monitor Neonates ? Useful In Neonates With Perinatal Asphyxia. Helps to assess the severity of insult early, take treatment decisions, monitor response and prognosticate. To detect and treat neonatal seizures. Monitor effect of drugs. Also Helpful In : Seizures or clinical scenario mimicking seizure disorders Apnea / Hypertension / Tachycardia Significant neurological disorders Congenital brain malformations / vascular lesions Post cardiac arrest Inborn error of metabolism Urea cycle disorders / Hypoglycaemia / Hypocalcaemia.

6. Tools for neuromonitoring aEEG and cEEG NIRS Head ultrasound Computed tomography head Doppler head ultrasound Plasma brain injury markers: under research Somatosensory evoked potentials Pupillometry Multimodal brain monitoring

7. Amplitude Integrated EEG

8. Electrophysiology Of EEG An EEG reflects the summation of electrical activity arising from EPSP(Excitatory Post Synaptic Potential) and IPSP(Inhibitory Post synaptic Potential) of pyramidal neurons mainly: The supra granular and infragranular cortical layers and depends also partially on thalamic input to the granular layer (layer iv) The graph displays the difference in electrical voltage between two different recording locations (y-axis) over time (x-axis). Approximately 6 cm 2 of cortex must be activated to create enough electrical activity to be visible on a scalp EEG.

9. Why continuous monitoring? Early identification of risk for brain injury Neurologic symptoms may not be overt Any early diagnosis of the compromised brain function will lead to better interventions and outcomes

10. Why a EEG? 11

11. Signal Processing

12. Simplified Approach Raw EEG Specialized band pass filter Rectification Smooth data Time compression semi-logarithmic amplitude compression 6cm aEEG =1 hr EEG

13. Semi logarithm

14. The Lectromed CFM by Lectromed UK The Olympic CFM 6000 by Olympic Medical / Natus USA The CFAM4 by RDM ltd UK Different Brands

15. The BRM3 by BrainZ and GE NicoletOne from Natus Medical

16. Neurosoft EEG

17. Placement Of Electrodes Usually the Signal Is Recorded From Two Electrodes Placed On Either Side Of The Head. A Third Electrode Acts As A Ground Electrode The optimal location is P3/P4

18. LEFT RIGHT

19. Types Of Electrodes 1.Cup Electrodes: These Require Meticulous Preparation Before Application . 2. Low Impedance Needle Electrodes : Small needle electrodes placed subdermally and secured with a tape. They have low impedance, are not dislodged easily and can be retained for several days .

20. Electrode positions (Tips) Interelectrode distance may influence amplitude Do not place over fontanels/sutures Do not apply over edema/hematoma abrasions Do not touch bedding Optimal number/positions of electrodes not known Can be covered by a handband

21. Why biparietal? Bi parietal placement of electrodes is recommended, as it overlies the apex of vascular watershed region of brain and is appropriate location for detecting abnormalities in diffuse encephalopathy. Bi parietal electrode has advantage that it avoid muscle and movement artifacts and also avoid hindrance in nursing procedures.

22. Why only biparietal?

23. Conductive paste and gel.. Rs 1665( Aamzon )   Strips away the top layer of skin and moistens the underlying skin layer - L owers the skin impedance with minimal skin irritation and patient discomfort. Rs 1280 ( Aamzon )

24. Impedance A measure of the quality of electrode contact and lead motion artifect Anything that gets between the sensor ( hydrogel or low impedance needles) and “impedes” or interferes with the devices ability to read the brain signal (hair, dry skin, vernix ) Want it as low as possible The display of low(10 kV) equal and stable impedance ensures optimal recording. Ideal is 5kV Can be used to detect lead motion artifact

25. Impedance

26. Impedance-Loose ends

27. Basics of Graphics….

28. Upper and Lower Margin…

29. Gestation and a EEG

30. Gestation and aEEG

31. Progression according to gestation…

32. Abnormal EEG background features & outcomes

33. 369 Extremely preterm neonates/10 year period 339 aEEG –EEG features was extracted, comprising nine qualitative parameters and 330 quantitative metrics. Quantitative and qualitative analysis of preprocessed aEEG –EEG signals 2-3 years/5-7 years outcome The machine learning-based regression models showed significant but relatively weak predictive performance (ranging from r=0·13 to r=0·23) for nine of 13 outcomes The machine learning-based classifiers exhibited acceptable performance in identifying infants with intellectual impairments from those with optimal outcomes at age 5–7 years, achieving balanced accuracies of 0·77 (95% CI 0·62–0·90; p=0·0020) for full-scale intelligence quotient score and 0·81 (0·65–0·96; p=0·0010) for verbal intelligence quotient score.

34. 60 preterm neonates  < 32 weeks of gestation. All cases were monitored by aEEG within the 1st 72 h of life for at least 4 h, and then brain MRI and aEEG were done at term equivalent age (TEA) of 40 weeks.  aEEG showed that 83.3% of the cases had continuous normal background activity at TEA, and MRI showed that 75% of the cases were normal. Comparing between non-affected and affected groups as categorized by Bayley scale regarding aEEG and MRI findings, there was greatly statistically significant difference between the two groups ( P  < 0.001). Brain MRI showed higher sensitivity and accuracy than aEEG . Brain MRI at TEA is more sensitive and accurate than aEEG to predict the neurodevelopmental outcome. aEEG at TEA is more predictor for neurodevelopmental outcome than at birth. The combination of both aEEG and brain MRI at TEA gives more prediction about the degree of affection in neurodevelopmental outcome in preterm infants

35. a EEG in SGA babies

36. Sleep Wake Cycling Sleep–wake cycling (SWC) in the aEEG is characterized by smooth cyclic variations, mainly of the minimum amplitude (i.e. lower border). Periods with broader bandwidth represent more discontinuous activity during quiet sleep ( trace alternant in full-term infants), and the narrower parts of the trace correspond to more continuous background during wakefulness or active sleep. Lower >5 microV and upper>10 microV

37. SLEEP WAKE CYCLING No SWC No cyclic variation of the aEEG background Imminent/immature SWC Some, but not fully developed, cyclic variation of the lower amplitude, but not developed as compared with normative gestational age representative data Developed SWC Clearly identifiable sinusoidal variations between discontinuous and more continuous background activity, with cycle duration>20 min

38. SWC is considered to reflect brain integrity. SWC can be seen from the gestational age of 29 weeks. The presence, time of onset and quality of SWC are influenced by the hypoxic-ischemic insult to which the newborns were exposed and good neuro -developmental outcome is associated with early onset and normal SWC Importance of SWC..

39. a EEG Classification( Hellström- Westas )

40. Continuous Normal Voltage(CNV) CONTINUOUS: Maximum amplitude(upper margin) > 10 mcV Minimum amplitude(lower margin) > 5 mcV

41. DISCONTINUOUS Maximum amplitude(upper margin) > 10 mcV Minimum amplitude(lower margin) < 5 mcV Variability of lower margin + Discontinuous Normal Voltage

42. BURST SUPPRESSION PATTERN:Burst >100mcV Maximum amplitude(upper margin) > 10 mcV (> 25mcV) Minimum amplitude(lower margin) < 5 mcV (0-1mcV) Variability of lower margin – absent BS+ denotes burst density>100 bursts/h BS-means burst density<100 bursts/h Burst Suppression

43. Low Voltage Low Voltage Maximum amplitude(upper margin) < 10 mcV Minimum amplitude(lower margin) < 5 mcV

44. Isoelectric FLAT TRACE Maximum amplitude(upper margin) < 5 mcV Minimum amplitude(lower margin) < 5 mcV

45. Just remember 2 values 10 & 5 In 1 st box: Both are happy happy .. …both have values above 10 & 5 In 2 nd box : upper margin is happy with 10 but not the lower margin . In 3 rd box no one is happy .

46. The two common aEEG classifications and scoring systems described by Hellström- Westas and Burdjalov are valuable tools to predict neurodevelopmental outcome when performed within the first 72 h of life. Both aEEG classifications are useful to predict chance of survival. The classification by Hellström- Westas can also predict long-term outcome at corrected age of 2 years.

47. Normal EEG in Full Term and Preterm Neonate Continuous Wavy Pattern Both maximum and minimum amplitude is above 5 micro volts Normal SWC – Sleep wake cycle Narrow in awake state and broad in quiet sleep Term Discontinuous Pattern Also called Trace Discontinu Minimum voltage may be less 5 uvolts Some times confused with burst suppression Low voltage is generally not as low as in BS Pre term

48. EEG in Preterm Neonate Discontinuous Pattern Also called Trace Discontinu Minimum voltage may be less 5 uvolts Some times confused with burst suppression Low voltage is generally not as low as in BS

49. Seizure and aEEG Neonatal seizures are often subtle or subclinical. EEG monitoring is superior to clinical signs for identification of neonatal seizures. The limited number of electrodes makes the aEEG method easy to use for clinical routine monitoring in the NICU. Continuous EEG monitoring with a reduced number of electrodes detects around 80% of seizures, and at least 90% of infants with seizures Majority of neonatal seizures are relatively brief ( 1-3 min) Preterm infants tend to have shorter seizures than term infants.

50. Seizure Characteristic Neonatal seizures are often classified as a)electroclinical, i.e. electrographic changes with clinical symptoms b)electrographic, i.e. ‘occult’ or clinically silent. Electroclinical ‘uncoupling’ is common i.e. the clinical seizures cease while electrographic (subclinical) seizures persist after administration of antiepileptic drugs. Clinical identification of seizures by clinical observation alone is unreliable in newborn infants. All infants with clinically suspected seizures should have a standard EEG record

51. Neonates at risk for developing seizure Perinatal asphyxia and hypoxic–ischemic encephalopathy; Infants with clinically suspected seizures; Severely ill infants (RDS, sepsis) who require ventilation and/or inotropes; Infants with meningitis, unspecified encephalopathy, or cerebral malformations Infants with severe cardiac malformations or congenital diaphragmatic hernia; Infants with severe hypoglycemia or metabolic disease; Infants requiring ECMO treatment; Infants who receive paralyzing agents while being on mechanical ventilation

52. Electrographic identification of seizure A seizure pattern in the EEG is characterized by repetitive, stereotyped waveforms with a definite onset, peak, and end (crescendo-decrescendo appearance). No specific criteria as regards minimum duration of a seizure, although 10 s has been considered largely Briefer runs of repetitive waveforms, often called epileptiform activity, are not uncommon in ill newborns. It is possible that shorter periods of repetitive activity, 5–10 s, should also be assessed as seizures since this type of activity has been associated with adverse neurologic sequelae.

53. Seizure Identification Usually seen as an abrupt rise in the minimum amplitude and a simultaneous rise in the maximum amplitude Often followed by a short period of decreased amplitude

54. Seizure Identification Single seizure A solitary seizure Repetitive seizures Single seizures appearing more frequently than at 30 minute intervals. Status epilepticus Continuously ongoing seizure activity for>30 minutes.

55. Different aEEG Of Seizure

56. Effect of Phenobarbitone

57. Ten studies 433 patients For the detection of individual seizures, when " aEEG with raw trace" was used, median sensitivity was 76% (range: 71-85), and specificity 85% (range: 39-96). When " aEEG without raw trace" was used, median sensitivity was 39% (range: 25-80) and specificity 95% (range: 50-100). Studies included in the systematic review showed aEEG to have relatively low and variable sensitivity and specificity. On the available evidence, aEEG cannot be recommended as the mainstay for diagnosis and management of neonatal seizures. There is an urgent need of well-designed studies to address this issue definitively.

58. 2023 73 term and preterm newborns who underwent EEG monitoring using amplitude-integrated electroencephalography ( aEEG ). Neurological development until around 18 months of age, with 59 patients remaining in the long-term study. A total of 22% of patients with NS developed epilepsy, 12% cerebral palsy, 19% severe neurodevelopmental disabilities, and 8.5% died within the first 18 months of life. aEEG background pattern is a strong predictor of unfavorable neurological outcomes, with an odds ratio of 20.4174 ( p  < 0.05) Early EEG monitoring in the NICU provides valuable insights into predictors of unfavorable neurological outcomes in newborns who experienced NS.

59. aEEG in Hypoxic ischemia

60. aEEG in Perinatal Asphyxia In asphyxiated full-term infants, the aEEG can accurately predict outcome in 80% of the infants at 3 h and in 90% of the infants at 6 h postnatally The early aEEG background in asphyxiated infants correlates with the degree of neurone -specific enolase in the cerebrospinal fluid, and with cerebral glucose metabolism later in the neonatal period. Combining neurologic examination with aEEG performed < 12 h after birth further increases predictive accuracy from 75 to 85%. A negative relationship has been found between EEG amplitude measures, Sarnat grades, and MRI abnormality scores.

61. aEEG in Perinatal Asphyxia Term asphyxiated infants, a CNV background/continuous background pattern with normal amplitude within the first hours of life, is predictive of good outcome . Discontinuous patterns such as BS and electrocerebral inactivity (i.e. flat), or extremely low-voltage patterns, are predictive of poor outcome (death or severe handicap ). Most asphyxiated infants with an early BS aEEG background have a poor neurologic outcome. In order to assess recovery of the background activity and time for onset of sleep–wake cycling, Aeeg recordings should be continued for a minimum of 48–72 h.

62. aEEG in Perinatal Asphyxia

63. Recovery in Perinatal Asphyxia The electrocortical background normalizes and becomes CNV in most full-term infants within 1–2 weeks following a severe hypoxic–ischemic insult. IBI is the EEG feature that correlated best with outcome A predominant IBI of more than 30s is associated with a 100% probability of severe neurologic disability or death, and an 86% risk for development of epilepsy Good outcome is associated with earlier onset of sleep–wake cycling and normal pattern by 36 HOL. Presence of seizures in aEEGs of asphyxiated infants have not been as clearly associated with outcome

64. aEEG in Perinatal Asphyxia

65. 2016

66. Inclusion criteria studies including data of neonates with HIE, treated or not with TH, monitored with aEEG and with neurodevelopmental follow-up of at least 12 months 403 articles and 17 studies   aEEG´s background activity, as recorded during the first 72 hours after birth, has a strong predictive value in infants with HIE treated or not with TH.

67.  Studies comparing aEEG (6, 24, 48 or 72 h) in term encephalopathic babies undergoing therapeutic hypothermia, with neurodevelopmental outcome at 1 year or more. 9 studies 520 neonates   The pooled sensitivity and specificity for an abnormal trace at 6 h of age to predict adverse outcome were 96% (95% CI 91 to 98%) and 39% (95% CI 32 to 46%).  Conclusion: A persistently abnormal aEEG at 48 h or more is associated with an adverse neurodevelopmal outcome. The positive prognostic value of 6 h aEEG is poor and good outcome may occur despite abnormal aEEG . Conversely, a normal 6 h aEEG has a good negative predictive value although do not exclude adverse outcomes.

68. Seventy-four infants were recruited by using the CoolCap criteria Outcomes assessed by using the Bayley Scales of Infant Development II at 18 months. The aEEG was recorded for 72 hours. Patterns and voltages of aEEG backgrounds were assessed.   The positive predictive value of an abnormal aEEG pattern at the age of 3 to 6 hours was 84% for normothermia and 59% for hypothermia. Moderate abnormal voltage background at 3 to 6 hours of age did not predict outcome. The recovery time to normal background pattern was the best predictor of poor outcome (96.2% in hypothermia, 90.9% in normothermia). Never developing SWC always predicted poor outcome. Time to SWC was a better outcome predictor for infants who were treated with hypothermia (88.5%) than with normothermia (63.6%).

69. Page 97

70. Objective : To evaluate the predictive ability of aEEG for abnormal neurological outcomes in neonatal encephalopathy or neonates with encephalopathy. Methods : Neonates above 35 weeks of gestation admitted to NICU in a tertiary care hospital with a diagnosis of encephalopathy were enrolled. Clinical characteristics severity of encephalopathy and seizures were recorded. Amplitude integrated recording was started at admission and continued till recovery of trace to normal or for 10 days. The primary outcome was death or abnormal neurological status at 3–6 months of age. An abnormal aEEG trace was observed in 51 (76.1%) infants with NE. For adverse neurological outcomes at an age average of 4.5 months of age, aEEG had a sensitivity, specificity, NPV, and PPV of 100, 54.2, 100, and 77.5, respectively. Conclusions : Clinical staging and aEEG has good predictive ability to detect an adverse neurological outcome. aEEG improves the ability to predict abnormal outcome in babies with moderate encephalopathy. Early recovery of aEEG abnormality correlates with better neurodevelopmental outcomes.

71. Page 99

72. Advantages & Disadvantages Associated : Allows continuous, real time prolonged monitoring of cerebral activity. Allows identification of seizures Easy to use and interpret. Potentially enhances newborn care by allowing early decisions on initiating and tailoring therapy. 1.Because of the few number of electrodes used, it Cannot Be Used To Detect Focal Abnormalities. 2. Can Miss Seizure Activity Of Shorter Duration. 3.It does Not Give Information About EEG Frequency.

73. aEEG for selection of cooling Trials Cool Cap(2005) TOBY trial(2009) neo.nEURO.network (2010)

74. 102 COOL CAP trial Methods:  234 term infants with moderate to severe neonatal encephalopathy and abnormal amplitude integrated electroencephalography ( aEEG ) were randomly assigned to either head cooling for 72 h, within 6 h of birth, with rectal temperature maintained at 34-35 degrees C (n=116), or conventional care (n=118). Primary outcome was death or severe disability at 18 months. Examined in two predefined subgroup analyses the effect of hypothermia in babies with the most severe aEEG changes before randomisation -- ie , severe loss of background amplitude, and seizures--and those with less severe changes. Predefined subgroup analysis suggested that head cooling had no effect in infants with the most severe aEEG changes (n=46, 1.8; 0.49-6.4, p=0.51), but was beneficial in infants with less severe aEEG changes (n=172, 0.42; 0.22-0.80, p=0.009).

75. 104 aEEG was performed with a cerebral function monitor (MT2-5330 system [ Lectromed , Letchworth, Hertfordshire, England]), and standard EEG was performed according to the International 10 –20 classification. Classification of the aEEG and EEG results was based on the reports by al Naqeeb et al and Lamblin et al,respectively , and yielded 2 subgroups, that is, moderately abnormal aEEG /EEG findings associatedwith mild/moderate encephalopathy and suppressed aEEG /EEG findings associated with severe encephalopathy. This classification was used for adjustment and subgroup analysis.

76. 105 Continuous aEEG data of term neonates with HIE were reviewed for background pattern and aEEG cycling from start of monitoring through rewarming. Infants were classified by overall background evolution pattern. Adverse outcomes were defined as death or severe magnetic resonance imaging injury, as well as developmental outcomes in a subset of patients. 80 infants receiving therapeutic hypothermia met the inclusion criteria. Background evolution pattern seemed to distinguish outcome groups more reliably than background pattern at discrete intervals in time (LR: 43.9,  p  value < 0.001 ). Infants who did not reach discontinuous background by 15.5 HOL, cycling by 45.5 HOL, and normalization by 78 HOL were most likely to have adverse outcomes . Evolution of aEEG in term neonates with HIE may be more useful for predicting outcome than evaluating aEEG at discrete intervals in time.

77. 26 studies 1458 infants Predicting outcome between 18m-3 years  MRI within 2 weeks of birth performed best on sensitivity 0.85 (95%  CI  0.79-0.89), specificity 0.72 (95%  CI  0.66-0.77), and AUC 0.88 Multichannel EEG (Electroencephalogram) demonstrated the sensitivity 0.63 (95%  CI  0.49-0.76), specificity 0.82 (95%  CI  0.70-0.91), and AUC 0.88, aEEG (amplitude-integrated electroencephalography) background pattern pooled sensitivity, specificity and AUC were 0.90 (95%  CI  0.86-0.94), 0.46 (95%  CI  0.42-0.51), and 0.78 SEPs (Somatosensory evoked potentials), pooled sensitivity and specificity were 0.52 (95%  CI  0.34-0.69), 0.76 (95%  CI  0.63-0.87), and AUC 0.84, respectively .  MRI and neurophysiological tests (aEEG or EEG) were promising predictors of adverse outcomes, while SEPs need high-quality studies to confirm the findings

78. Hemorrhagic and ischemic lesions in the preterm The aEEG /EEG at all gestational ages should normally contain at least 100 bursts/h. aEEG /EEG changes associated with hemorrhagic or ischemic brain damage: a) Increased discontinuity, i.e. increased IBI and/or decreased amplitude (voltage) during the IBI (i.e. BS pattern instead of tracé discontinu ); b) Presence of epileptic seizure activity, often subclinical; c)Loss of sleep–wake cycling; Recovery within 1–2 weeks, chronic stage changes may persist and are best evaluated with standard EEG 108

79. Bilirubin encephalopathy

80. Methods: 114 neonatal hyperbilirubinemia patients 62 (54.38%) males Age of patients undergoing aEEG examination 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 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.

81. Miscellaneous conditions Most aEEG /EEG changes due to metabolic diseases, CNS infections, or malformations are non-specific. The most common aEEG findings include overall background depression and loss of sleep–wake cycling, and the presence of seizures. BS is often present in non- ketotic hypergly cinemia , hemi megalencephaly , and Ohtahara syndrome. A standard EEG should be recorded early in all infants with cerebral symptoms due to metabolic disturbances, including hypoglycemia, infections, and cerebral malformations

82. Artifact Electrical activity other than the brain’s electrical activity (monitors, IV pumps, ventilators, etc.) Live EEG signal is used as a point of reference to confirm suspected brain activity OR to distinguish artifact

83. HFO causing artifact

84. Limitations Does not give information about EEG frequency Activity <2 Hz or > 15 Hz is not recorded by the CFM trace. Focal abnormalities in the EEG may not be identified Prone to artifacts and effects of medication

85. Common Pitfalls In Interpretation Of aEEG If Background Activity Appears Elevated, It May Be Due To: Handling of the baby Muscle activity (more for frontal electrodes) High frequency ventilation Status epilepticus Gasp artifact ECG artifact Cannot detect a short, focal or low amplitude seizures. If Background Activity Appears Depressed, It May Be Due To: Severe scalp edema Deep sedation Leads too close to each other.

86. How to avoid errors in interpreting aEEG trace ? To accurately interpret aEEG : Mark any care/procedures/movements or other events on the record. Review drugs and other therapies given to the neonate. Look at the simultaneous EEG display. Also look for simultaneous clinical events. To ensure good aEEG recording: Place the electrodes carefully. Check for impedance while placing electrodes and regularly thereafter. The impedance indicates the contact between the electrode and the patient. A loose contact or high impedance reduces the quality of the record. Keep the impedance <10 W, ideally close to zero

87. Conclusion Role of aEEG in assessing and monitoring of encephalopathic neonates is well established May help in identifying seizures and assessing the response to treatment The aEEG tracing should be analysed along with raw EEG trace Step Wise Reading aEEG Is Important For Correct Interpretation. Always Check Whether The Reading Is Accurate Or There Is Any Pitfall.

88. Quiz… Q 1 Where are the electrodes applied?? P3/F3 P4/F4

89. Q 2 DISCONTINUOUS PATTERN

90. Question 3 BURST SUPRESSION PATTERN

91. Question 4 BURST SUPRESSION WITH SEIZURES

92. Question 5 STATUS EPILEPTICUS

93. Question 6

94. Question 7