DOI: 10.1542/peds.112.4.855 2003;112;855-861 Pediatrics

Vladimir F. Burdjalov, Stephen Baumgart and Alan R. Spitzer Brain Maturation in Neonates

Cerebral Function Monitoring: A New Scoring System for the Evaluation of

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Cerebral Function Monitoring: A New Scoring System for the Evaluationof Brain Maturation in Neonates

Vladimir F. Burdjalov, MD; Stephen Baumgart, MD; and Alan R. Spitzer, MD

ABSTRACT. Objective. Cerebral function monitoring(CFM), using compressed single-channel amplitude-inte-grated electroencephalogram recorded from 2 biparietalelectrodes, has been shown previously to be a simplebedside tool for monitoring neonatal central nervous sys-tem (CNS) status. As the pattern of the CFM changeswith gestational age, the technique can be used to assessbrain maturation in premature infants. We have devel-oped a new scoring system for the interpretation of neo-natal CFM recordings. The objective of this study was toevaluate CFM tracings at increasing gestational and post-natal ages to develop a scoring system to quantify CFMpattern changes.

Methods. Term and preterm neonates were studiedwith CFM at 12 to 24 hours of life, 48 to 72 hours of life,and then weekly or biweekly until hospital discharge.Each study comprised 8 to 24 hours of continuous CFMrecording. CFM recordings were evaluated using thescoring system for record continuity, presence of cyclicchanges in electrical activity, degree of voltage amplitudedepression, and bandwidth. Each variable was scored foreach recording. All variables were summed to yield atotal score (minimum 0, maximum 13). Total scores werecorrelated with gestational and postconceptional ages.

Results. Thirty infants were studied with gestationalages at birth that ranged from 24 to 39 weeks and birthweights that varied between 450 and 3850 g. A total of 146CFM tracings were analyzed. With advancing gestationaland postconceptional age, scores for each variable as wellas total scores progressively increased with CNS matura-tion. The highest scores were attained at 35 to 36 weeks’postconceptional age, which corresponded to previouslyreported subjective observations performed by visual de-scription of CFM patterns. Of the 4 component variablesthat we analyzed, the most sensitive indicators of CNSmaturity were 1) the presence of a cycling pattern, 2) thecontinuity of the record pattern, and 3) the CFM record-ing bandwidth.

Conclusions. Our proposed scoring system may be avaluable tool to quantify changes during CFM moreobjectively, reflecting variations in CNS activity in new-born infants and allowing for better statistical compari-sons between amplitude-integrated electroencephalo-gram tracings from different patients as well as from thesame patient at different points of time. Pediatrics 2003;112:855–861; amplitude-integrated EEG, brain maturation,cerebral function monitoring, premature neonate.

ABBREVIATIONS. IVH, intraventricular hemorrhage; HIE, hy-poxic-ischemic encephalopathy; CFM, cerebral function monitor-ing; aEEG, amplitude-integrated electroencephalogram; CNS, cen-tral nervous system.

During the past decade, the survival of prema-ture neonates has improved dramatically.1The neonatal population, especially the ex-

tremely low birth weight infant, however, is still atgreat risk for many complications that occur duringthe newborn period that may result in clinicallysignificant neurologic injury, including intraventric-ular hemorrhage (IVH), periventricular leukomala-cia, hypoxic-ischemic encephalopathy (HIE), sei-zures, and meningitis. Ultimately, such problemsmay, in turn, lead to developmental delay and cere-bral palsy.2 These circumstances emphasize the needfor improved surveillance of cerebral function dur-ing this critical period of time.

Cerebral function monitoring (CFM) is a bedside,readily available, user-friendly device for continuousrecording of amplitude-integrated electroencephalo-gram (aEEG) data. The compressed form of this re-cording allows evaluation of baseline brain waveactivity and detection of seizures. CFM recordingsare sampled from two biparietal electrodes that inte-grate electrical activity in the underlying brain re-gions that receive the bulk of cerebral blood flow.Since it was first introduced for continuous cerebralactivity monitoring in adults,3 CFM has been usedincreasingly in some neonatal centers to follow hy-poxic-ischemic brain injury, detect seizures, monitorthe effects of different interventions and events onneonatal cerebral activity, and predict future out-come.4–18 Neonatal aEEG recorded by CFM hasalso been correlated with gestational age and matu-rity of preterm and term infants’ electrical brain ac-tivity.19–23

One of the current problems with evaluating aEEGtracings, however, is that most investigators haveused subjective visual pattern recognition to assessthe record’s continuity, bandwidth, presence of acycling pattern, and the occurrence of epileptiformactivity.13,19–21,23 Various investigators have useddifferent combinations of these descriptive patterns,and there has been no uniform agreement on howbest to analyze the aEEG, particularly in very imma-ture neonates. Furthermore, none of the existingtechniques for interpreting CFM data seems to besuitable for statistical comparisons between different

From the Division of Neonatology, Department of Pediatrics, State Univer-sity of New York at Stony Brook, Stony Brook, New York.Received for publication Sep 27, 2002; accepted Feb 18, 2003.Reprint requests to (A.R.S.) SUNY-Stony Brook, HSC T11-060, Stony Brook,NY 11794-8111. E-mail: aspitzer@mail.som.sunysb.eduPEDIATRICS (ISSN 0031 4005). Copyright © 2003 by the American Acad-emy of Pediatrics.

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tracings, either from different infants or from thesame infant at different postconceptional ages.

We therefore have developed a scoring system forthe interpretation of neonatal CFM recordings. Oursystem incorporates all variables of the neonatalaEEG tracing previously described and grades themaccording to measured changes in the signal patternthat can be readily scored. Our hypothesis was thatnumerical scoring of aEEG tracings at increasingpostconceptional ages would accurately quantify thematurational changes previously described withmore traditional pattern recognition analysis.

METHODS

Study PopulationThis study was conducted in the Regional Perinatal Center of

the neonatal intensive care unit of the State University of NewYork at Stony Brook during the period from January 2000 toFebruary 2002. Thirty patients were enrolled with birth weightsthat ranged from 450 g to 3850 g (median: 862 g) and gestationalages at birth from 24 weeks to 39 weeks (median: 27 weeks).Gestational age was assessed by the last menstrual period and/orby prenatal ultrasonography and was confirmed by physical ex-amination, using the Ballard Scoring System.

Inclusion criteria for study participation were 1) Absence of amajor chromosomal or/and congenital malformation; 2) absenceof HIE, IVH, or periventricular leukomalacia; and 3) absence ofany sedative medication. Cranial ultrasonography was initiallyperformed on all premature infants �34 weeks of gestation in thefirst 3 days of life. Thereafter, studies were done 1 week lateraccording to clinical indications and were repeated at the discre-tion of the attending neonatologist. Infants who demonstrated anyof the previously mentioned abnormalities on any study wereexcluded from aEEG evaluation.

This study was approved by the IRB of the State University ofNew York at Stony Brook. Informed consent was obtained fromthe parents of each patient enrolled in the study.

CFM RecordingsCompressed aEEG recordings were obtained using the Cere-

bral Function Monitor Multi-Trace 2 (Lectromed, Olympic Medi-cal Inc, Seattle, WA). A pair of standard gold-disk EEG electrodeswas attached to the scalp parietal areas in the P3 to P4 positions(International 10-20 System) using Elefix EEG-electrode paste (Ni-hon Kohden, Tokyo, Japan). The electrodes were covered with asmall wad of sterile cotton and secured with Transpore (3M, StPaul, MN) nonocclusive tape to prevent drying of the paste. Areference electrode was similarly placed over the frontal midlineregion of the scalp.

The EEG signal obtained from these electrodes was processedby amplification, a special filtration algorithm to attenuate signalsbelow 2 Hz and above 16 Hz, amplitude and time compression,and rectification. Finally, that compressed aEEG signal was re-corded on heat-sensitive paper, using a semilogarithmic scale, andrun at a speed of 6 cm/h. The CFM was calibrated before each

recording using the manufacturer’s recommended procedure. Pe-riodic recalibration was performed during CFM epochs to becertain that there was no significant baseline drift during thecourse of the study period. Continuous CFM recording was per-formed on each patient for an 8- to 24-hour period, adhering to thefollowing schedule as closely as possible: at 12 to 24 hours of life,at 48 to 72 hours of life, and then weekly or biweekly until hospitaldischarge. On occasion, the clinical status of an individual infantmade recording impossible and the study was then conducted assoon as it was again feasible. For most infants, there was only 1recording during the first week of life. In some infants who had�1 study performed, the best technical CFM tracing that had theleast artifact and fewest interruptions because of intensive careneeds was selected.

CFM Tracing InterpretationFrom each recording, the most stable uninterrupted period of at

least 3 to 4 hours’ duration were chosen for analysis. The follow-ing 4 component variables of the aEEG record were evaluated,categorized, and graded according to the proposed scoring system(Table 1):

1. Record “continuity”: Continuity was assessed by observing theoverall density of the sample tracing. Continuity refers to theappearance of frequent variations in the aEEG electrical activityresponse. High levels of continuity meant that there was con-stant and frequently alternating electrical activity (pen peaksand troughs), so that the recording either appeared very tightlycompressed on the tracing or not. Low levels of continuity hada much reduced number of electrical variations, with greaterseparation of the recording signal peaks and troughs.

2. Presence or absence of “cycling”: Cycling refers to the emer-gence and progression of periods during the CFM epoch ana-lyzed where the peak-to-trough width of the recording wouldexpand and subsequently contract. Cycling was observed asvariations in both amplitude and continuity of electrical activityon aEEG tracings.

3. Amplitude (in �V) of the lower border: The magnitude of theCFM tracing’s lower border (voltage troughs) was estimated asthe average lower microvolt level during the recording epoch.A line drawn though the lower margin of the aEEG bandappeared with half of the microvolt troughs below the line andhalf above. With the emergence of cycling (see above), thenarrowest part of the recording was evaluated.

4. Bandwidth of the aEEG: Bandwidth reflects a combination ofthe voltage span (peak-to-trough) of the tracing and the mag-nitude of the aEEG depression (amplitude of the lower border).The span was calculated as the difference between the upperand lower voltage margins of the tracing’s narrowest part.

Each variable was scored, and the individual component scoreswere summed to determine the total score for each recording. Theminimum possible total score was 0, and the maximum was 13.Individual component variable scores and the total scores from allCFM recordings were subsequently evaluated in relationship toeach infant’s postconceptional age. The weighted R value, orcorrelation coefficient by least-squares method, was calculated asa measure of correlation between scores and postconceptionalage.24 Intercoder reliability for total scores was estimated by ex-

TABLE 1. CFM Scoring System Summarized

Score Continuity Cycling Amplitude ofLower Border

Bandwidth Span and Amplitude of Lower Border

0 Discontinuous None Severely depressed(�3 �V)

Very depressed: low span (�15 �V) and low voltage(5 �V)

1 Somewhatcontinuous

Waves first appear Somewhat depressed(3–5 �V)

Very immature: high span (�20 �V) or moderatespan (15–20 �V) and low voltage (5 �V)

2 Continuous Not definite,somewhat cycling

Elevated (�5 �V) Immature: high span (�20 �V) and high voltage(�5 �V)

3 Definite cycling, butinterrupted

Maturing: moderate span (15–20 �V) and high voltage(�5 �V)

4 Definite cycling,noninterrupted

Mature: low span (�15 �V) and high voltage (�5 �V)

5 Regular and maturecycling

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amining the percentages of scores within �1 and �2 points for atleast 2 readers. One author’s total scores were considered forstatistical analysis (V.F.B.).

RESULTSDuring this study, we analyzed a total of 146 re-

cordings in 30 qualified infants. Seven infants whohad severe IVH or HIE were excluded. The numberof recordings for each patient varied from 1 to 10(median: 4.5). Examples of the tracing analysis areshown in Fig 1.

We observed in the tracing pattern certain matu-rational changes that seemed to correspond to scoresspecific for particular gestational ages. Recordingsdone on younger gestational age infants (24–26weeks) were characterized by discontinuous CFMbackground continuity (continuity scores 0–1); thecomplete absence of or only rudimentary cyclicchanges (cycling scores 0–2), with the first such cy-clical changes being noted at approximately 26weeks of postconceptional age; slightly depressedlower border amplitude (amplitude scores 1–2); anda predominantly broad bandwidth (scores 0–2).

With advancing postconceptional age (27–28weeks), the CFM pattern showed a more continuoustracing (the majority of scores were 1–2, with only 3patients showing scores of 0). Cyclical 20- to 30-minute periods of wider amplitude were intermixedwith periods of narrower bandwidth and began toemerge after 27 weeks of postconceptional age (cy-

cling scores �2). Cycling became more clearly recog-nizable after 29 weeks (scores �3) and were fullyestablished by 34 weeks of postconceptional age(scores �4). There was also a progressive elevation ofthe minimum level of electrical amplitude (majorityof lower border amplitude scores were at 2) andnarrowing of the amplitude’s bandwidth (scoreswere 2–3, with 4 recordings showing a score of 1).

The cyclical periods reached a completely maturepattern after 36 weeks’ postconceptional age (score of5). Also with advancing gestational age, continuityincreased progressively, reaching its maximum by 30to 31 weeks’ postconceptional age. After 27 weeks’postconceptional age, the lower border amplitude ofthe aEEG band remained elevated and bandwidthbecame progressively narrower, with scores of 3 be-tween postconceptional ages of 29 to 34 weeks. Theheight of the aEEG band reached its maximum levelby 35 to 36 weeks’ postconceptional age.

The total score calculated for each recording alsoprogressively increased from 1 to 2 at the earlieststages of maturity and reached its maximum (a scoreof 13) at approximately 39 weeks’ postconceptionalage. The weighted regression of the mean total CFMscore for all variables compared with mean postcon-ceptional age is demonstrated in Fig 2. The progres-sions in individual components of the CFM score areseen in Figs 3 to 5. Lower border amplitude, al-though an integral component of the maturational

Fig 1. The left side of the figure demonstrates aprogressive series of CFM monitor recordings; theright side shows the component score values for therespective studies. There is a maturation of thetracings from A through F in these recordings.Postconceptional age ranges are indicated. Co, con-tinuity of the recording; Cy, presence of cycling; LB,lower border amplitude score; B, bandwidth; T, to-tal score.

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score, had a lower correlation coefficient (R � 0.46,P � .2) and is omitted for brevity. Intercoder reliabil-ity was 82% (14 of 17) for independently scoredrecordings that came within 1 point of each other,whereas 100% of recordings that were independentlyscored were within 2 points.

DISCUSSIONThis study defines a new scoring system for aEEG

evaluation that was devised to assess objectively thedevelopmental maturation of the neurologically un-impaired premature infant. There was a progressiveincrease in both the overall score on the aEEG and

the 4 individual component scores that correlatedclosely to the chronologic and neurodevelopmentalmaturation of these infants. Our own data, as well asmore subjective interpretations from other studies,have shown that the pattern of the neonatal aEEGchanges with advancing gestational and postconcep-tional ages.19–23 The components of the aEEG tracingthat we quantified (record continuity, presence andstage of a cycling pattern, magnitude of tracing de-pression, and bandwidth) have been verified previ-ously.

Of the component variables described on theaEEG, the emergence of a cycling pattern seemed to

Fig 2. Progressive maturation of themean total CFM scores measured be-tween 24 and 39 weeks’ postconcep-tional age. The total number of studiesincluded is 146. There are multipleoverlapping points at intersections ofmean CFM score and postconcep-tional age, with the number of studiesat each point indicated, and the re-gression was accordingly weighted.24

Fig 3. The regression of the cyclingcomponent for the CFM score isshown with postconceptional age (N �146, 30 overlapping weighted means).24

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have the highest correlation with postconceptionalage and could be considered the single best determi-nant of cerebral maturity. This finding might be ex-plained by the emergence and establishment ofsleep-wake cycles as determined by the level of in-tegration of higher central nervous system (CNS)functions.25 aEEG “cycling” has not been correlated,however, with behavioral or sleep states in our studyand may not be analogous to standard EEG interpre-tations of arousal. In contrast, aEEG “continuity”may depend more on the general status of CNSelectrical activity than on maturity, and a continuousaEEG pattern is typically established during earlierstages of development in our study. It should benoted that this finding also differs from standardEEG interpretation of discontinuous versus continu-

ous background continuity with premature CNS de-velopment and may not be analogous.

Inspection of the component variables that wehave described permits the clinician to summarizethe overall integration of an individual infant’s CNSelectrical activity in greater detail. This approachmay facilitate the evaluation of patients for seizuresand other potentially abnormal patterns that maybecome more important in a less healthy prematureinfant population. However, no attempt was made inthe present study to evaluate such abnormal pat-terns.

The EEG is the current standard that reflects thestate of CNS electrophysiologic activity. The EEG,however, is an impractical technology for use as arepetitive, continuous monitoring device in this pop-

Fig 4. The regression of the continuitycomponent for the CFM score is shownwith postconceptional age (N � 146, 30overlapping weighted means).24

Fig 5. The regression of the bandwidthcomponent for the CFM score is shownwith postconceptional age (N � 146, 30overlapping weighted means).24

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ulation of infants. During the past 2 decades, CFMhas gained increasing attention in clinical neonatalresearch, because the aEEG is an easily applicable,readily available, and inexpensive device for contin-uous bedside evaluation of brain activity.3,26 TheaEEG has been shown to have a good correlationwith the standard multichannel EEG in term andcritically ill neonates,14,20,27–29 and it can overcomesome of the disadvantages of the latter as a monitor-ing device. Additional conventional EEG work isrequired, however, to validate observations made inpremature infants with aEEG recordings.

One of the great advantages of CFM is its simplic-ity and the possibility of quick on-line interpretationand analysis of overall brain function. To date, how-ever, there has been no uniform agreement withrespect to the assessment and interpretation of CFMrecordings. On the basis of pattern recognition anal-ysis, various authors have used different assessmentsof the aEEG tracing with some agreement, but therehas not been a consistent approach to the variouscomponents of the recording that seem to changewith increasing gestational age.13,19–21,23 We believethat the current scoring system provides such anapproach.

Last, we urge some caution in using this scoringsystem in the first few days of life. In some infants, adefinitive pattern of aEEG was not established (andcould not be scored) until a few days after birth. Thisfinding may be related to perinatal events and/orprenatal/perinatal interventions, and it requires ad-ditional investigation with respect to its significance.Moreover, our proposed scoring system has someinherent subjectivity within the component vari-ables. Such a detailed scoring system may neverthe-less allow anyone who is interested in the continuousmonitoring of neonatal cerebral status to apply thisscore successfully in the assessment of maturationand CNS integrity. With additional technologic ad-vances, such as digitized aEEG recording and com-puterized calculations of the various measures thatwe have outlined, the problem of subjectivity of scor-ing could potentially be overcome.

CONCLUSIONSCFM seems to be useful for following the normal

maturation of the neonatal brain. Our proposed scor-ing system (although admittedly arbitrary) may be-come a valuable tool to quantify changes duringmaturation, more objectively reflect variations inCNS activity in newborn infants, and allow for betterstatistical comparisons between aEEG tracings fromdifferent patients, as well as from the same patient atdifferent points of time. Future work should definethe aEEG as seen in brain-injured premature neo-nates to better define pattern abnormalities in theseinfants. A different balance or even new componentfactors may prove to be more appropriate when us-ing aEEG to assess acute HIE, when screening forsubtle or cystic white matter injury, or when evalu-ating recovery from injury, as compared with eval-uating maturation.

ACKNOWLEDGMENTSThis investigation was supported with an equipment grant

from Olympic Medical, Inc.We are grateful to all neonatal nursing staff in the neonatal

intensive care unit at SUNY at Stony Brook for invaluable helpand great patience. We also thank Dr Joseph DeCristofaro and DrAnatoliy Ilizarov for advice and encouragement.

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Noted by JFL, MD

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DOI: 10.1542/peds.112.4.855 2003;112;855-861 Pediatrics

Vladimir F. Burdjalov, Stephen Baumgart and Alan R. Spitzer Brain Maturation in Neonates

Cerebral Function Monitoring: A New Scoring System for the Evaluation of

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