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52

PEDIATRICS

Vol. 76 No. 1 July1985

Stability

in Waking-Sleep

States

in Neonates

as a Predictor

of Long-Term

Neurologic

Outcome

Cesare

T. Lombroso,

MD, PhD,

and Yoichi

Matsumiya,

PhD

From the Seizure Unit and Division of Neurophysiology, Department of Neurology, The

Children’s Hospital, and Department of Neurology, Harvard Medical School, Boston

ABSTRACT. Thirty-three full-term neonates were ranked

blindly on a scale ranging from the least to the highest

“risk” for future neurologic complications on the basis of

available perinatal biographies, tests, and examinations

performed during the newborn period. Four prolonged

polygraphic-behavioral recordings were obtained one

week apart beginning at ten days after birth. Five waking

and sleep states were scored in each session as

percent-ages of total observation time, giving a total of 20 scores

for each baby to be subjected to analysis of variance. These measures also provided individual profile

consist-ency or variability in maintaining waking-sleep states

over the selected period of postnatal time. The whole

cohort, except three infants who could not be followed

adequately, was then reexamined periodically over a

pe-nod ranging from 3 to 4 years (±6 months) for neurologic

and developmental assessments. Except for two scores

that produced a low level of statistical significance (P <

.05), the other 18 scores were found to be not associated

with long-term outcomes. Even the first two scores were

not satisfactory discriminators for the outcome of the

individual babies. However, when coefficients of

concord-ance (W) were computed from each individual baby

pro-file, significant statistics (P < .001) emerged to indicate

good correlations between high or low W values in the

newborn period and long-term outcomes. All 17 newborns

who had W scores greater than 0.9 were found to be

normal at follow-up regardless of the poor ranking given

several of them during the newborn period. Among the

13 newborns who had W scores less than 0.9, 11 had a

poor clinical outcome at follow-up, though several had

been ranked initially as falling within the least “risk”

group. Pediatrics 1985;76:52-63; newborns at risk,

wak-ing-sleep profiles, neurologic assessment.

Neonatal EEGs provide noninvasive diagnostic

clues and have been shown by many to be a powerful

Received for publication May 6, 1983; accepted Aug 14, 1984. Reprint requests to (C.T.L.) Seizure Unit, The Children’s Hos-pital, Boston, MA 02115.

PEDIATRICS (ISSN 0031 4005). Copyright © 1985 by the American Academy of Pediatrics.

tool to suggest short- and long-term outcomes.’2

In our investigations during the past two decades,

we classified newborn polygraphic EEG recordings

according to the presence or absence of (1)

abnor-malities in background EEG activities, (2) ictal

abnormalities, and (3) abnormalities in the

orga-nization of “states” (for a definition of “states,” see

references 12 to 17) and in some specific EEG

maturational indices.12’18’19 We were able to

estab-lish their consistency or inconsistency by serial

tests during the newborn period and to correlate

them with clinical outcomes in prospective studies.

We obtained some significant statistical

correla-tions between these groups of recordings and

long-term outcomes in various cohorts of infants “at

high risk.”

These correlations, however, refer to groups of

babies, not to individuals. Whereas we might

pre-dict what outcome awaits a group of babies at high

risk, we are often unable to determine how an

individual baby might fare. The purpose of the

present study was to seek new strategies for

obtain-ing more individual long-term prognosis.

Neonates with known anomalies in their CNS

show deviations in the duration of their sleep

states or in some specific components of the

lat-ter.’2’4”8’2025 We thought that we might enhance

our ability to predict individual outcome by

system-atically measuring for a period of postnatal life a

baby’s consistency in maintaining its states.

Most investigations have dealt with the more

easily qualifiable and quantifiable sleep states and

the transitions between them. We chose to include

waking states as well. Although these have been the

subject of fewer controlled studies, we assumed that

their inclusion might more fully demonstrate how

predetermined inborn schedules interact with, and

are modified by, exogenous and endogenous factors.

Kleitman,26 Prechtl et al,’3 and Wolff’5 were some

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ARTICLES 53

of the early authors to include waking states in

their studies, they established some of the

taxon-omy, and they reached some conclusions about

waking-sleep organization and about how it could

be influenced by morbidity.

MATERIALS

AND METHODS

Population

Thirty-three full-term newborns were studied;

three were eliminated from the study because they

were lost at follow-up. We studied a population of

babies that were waiting for adoption and, hence,

they were kept at their nurseries for a longer time

than usual. Selection depended on the availability

of required information and access. The scope of

the study was described to appropriate guardians.

Care was taken to stress that this was an

investi-gative endeavor and that the only benefits to the

babies were inherent in their being followed

regu-larly and, if abnormal signs or symptoms developed,

appropriate measures were to be taken. The

gesta-tion, age, sex, and prenatal, perinatal, and postnatal

status of each infant are shown in the Table.

Rating

of Population

To minimize selection biases and to avoid the

risk in arbitrarily assigning each infant to discrete

categories (“normal,” “at risk,” “at high risk,” etc),

we adopted a method of rank order. Three pediatric

neurologists were given the information shown in

the Table except for the long-term outcomes listed

in the column on the right (a single-blind design).

They were asked to project by a ranking method

the degree of future risk for neurodevelopmental

deficits for each subject, considering the given data

on the prenatal, perinatal, and postnatal biography,

tests, and clinical status. Their task was to arrange

the series of neonates in a scale ranging from the

infant thought to be at “the least risk” to the one

considered to be at “the highest risk.” Then the

whole population was arranged in a serial order,

assigning number 1 to the subject rated as being

least at risk progressively to the one considered to

be most at risk. There was a good agreement among

the three raters (r = .70). As shown in the Table,

the subjects are arranged according to the sum of

the three ranked values given by the three raters so

that the first subject in the list (baby 1) received

the best combined rank (least risk) and was given

a new rank of 1, and the last one (baby 29) received

the worst combined rank (highest risk) and was

given a new rank of 30. The new ranking order

based on the combined ranks is shown in the

col-umn on the left. Within the group of newborns

ranked at low risk, the EEG findings obtained

within the first week after birth were normal except

for five infants: in one newborn there was an

ex-cessive number of apneic episodes of “central type”

during non-rapid eye movement (NREM) sleep,

with some rolandlic isolated sharp waves; in two

infants there were dysmaturity indices of a

tran-sient nature189; two newborns had excessive

ro-landic and/or multifocal spikes, with otherwise

nor-ma! background and sleep states. Within the group

of newborns ranked at progressively higher risk,

genera! and neurologic examinations during the

newborn period, however, revealed no unequivocal

evidence of obvious, severe CNS impairment such

as persistent and marked hypotonia, continuing

seizures, or evidence of persistent brainstem

dys-function. Three infants actually had borderline

neurologic assessments, but they were classified as

at risk because of their morbid histories. The

neu-rologic examinations utilized the techniques of

Amiel-Tison, modified according to states (see

Lombroso,8 Prechtl’6). EEG findings were

abnor-ma! initially in 13 babies, but six of these infants

subsequently

had normal EEG findings. Abnormal

EEG findings showed only in four infants some of

the patterns that, in previous studies, suggested

profound CNS compromise.’’2

TESTING

AND FOLLOW-UP

Polygraphic recordings, with behavioral

obser-vations by a technologist well trained in

interpret-ing neonatal EEGs, were performed during seven

consecutive hours at about i-week intervals, four

times after birth. The recordings were obtained in

the same surroundings in the nursery and at the

same time of day. Although previous routine EEGs

had been obtained in several infants during their

first week of life, the initial session for this study

was begun at the second week of life. The routines

of feeding, cuddling, and diaper changing were

maintained; but patting, rocking, and use of

paci-fiers and of toys were discouraged during the

re-cording sessions. None of the infants or their

moth-ers were receiving drugs at the time the

investiga-tion began. Some of the babies had received

pheno-barbital or Dilantin, but in all babies the drugs were

discontinued within 1 week after birth, and blood

levels at the time ofthe po!ygraphic recordings were

less than values known to influence states.

Five states were selected for scoring (modified

from the scales of Wolff15 and of PrechtP6): state

1-awake, active, and crying; state 2-awake,

ac-tive, but quiet; state 3-awake, quiet, possibly

drowsy; state 4-rapid eye movement (REM), or

active sleep; and state 5-NREM, or quiet sleep.

(The criteria for scoring these states were: state

i-eyes open, moving, crying or fussing, EEG

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3 yr, nl; DQ 110 3.5 yr, nl; DQ 98

4 yr, ni; DQ 108

8 mo, satisfactory; 18 mo, walked, language devel delay; 3.6 yr, mild diparesis, abn gross & fine coord, Neg CT scan, DQ 70

2.9 yr, ni; DQ 90

3.2 yr, nl; DQ 100

8 mo onset IS with hypsar, neg w/

U, Rx ACTH, cessation IS; 2.9

yr, mild quadriplegia; DQ 60 1.2 yr, F#{176}T/C convulsions; not walking; HC 25%; 3.0 yr,

nonfo-cal szs (tonic/atonic/myoclonic); extrapyramidal signs moderate;

DQ 76

2.8 yr, ni; DQ 112

3.7 yr, nl; DQ 108

3.4 yr, ni; DQ 110

1.8 yr, onset Rt focal szs; NE, nl;

DQ 84; 3.0 yr, szs controlled by

DPH; NE Rt hemiparesis; DQ 80

3.6 yr, severe diparesis, language devel delay, HC 10%, EEG abn;

DQ 85

2.9 yr, ni; DQ 96

2.6 yr, HC 50%, neg CT scan,

EEG; (mild global delay); DQ <

88

3.1 yr, ni; DQ 105

2.9 yr, nl; DQ 110

54

TABLE. Data for 30 Infants Ranked According to Future Risk for Neurodeveloprnental Deficits (Least Risk

[Infant 1] to Most Risk [Infant 30])*

Infant’s Infant Gesta- Sex Prenatal, Perinatal, and Outcome

Rank No. tional Postnatal Status

of Age

Risk (wk)

1 1 40 F Neg P & Del; Neg NE & EEG

2 2 41 M Neg P & Del; SIB 12%; Rx with lights; Neg NE & EEG

3 11 40 F Neg P & Del; wt 1,350 g; Neg NE & EEG

4 23 40#{189} F URI with fever at 6 mo; LF Del; SIB 18%;

Rx Pb, lights x 5 d; Neg sepsis w/u, NE,

sono, ECG, EEG, CSF

5 10 39 M Multiple misc; Neg P & Del; pH 7.2; Neg

w/u, NE & EEG

6 20 39 M Bleed 7 mo; Neg Del; ? szs 4th d; Neg w/u,

CSF, sono, CT scan, EEG, NE

7 13 39#{189} M Neg P & Del; IAA; EEGs “transient dysma-turity”

8 21 39 F Neg P & Del; Mild meconium stain; Apgar:

7 at 1 mm and 8 at 5 mm; SIB 17%; Rx with lights; NE some jitteriness, ? szs;

EEG wnl; Neg sono, NE except

jitteri-ness

9 6 39 F Neg P & Del; PRM; Neg sepsis w/u; PDA

& RDS 5 d; Neg NE, EEG, sono

10 22 38 M Neg P & Del; pulmonary hypertension,

re-solved 10th d; Neg CT scan, BAEP, CEP,

EEG; NE jitteriness, obligatory TNR, no

tracking, ? blink to light

11 7 40 F Neg P & Del; apnea 1 wk; Neg w/u; EEG

central-type apnea; Neg sepsis w/u, CSF,

NE, CT scan; EEG abn (absent NREM

& excess F sharp transients)

12 30 38#{189} M Neg P & Del; Apgar: 6 at 1 mm and 8 at 5 mm; PDA; mild RDS; several apneic spells 3rd d; Neg EEG, ECG,

pneumo-gram, sepsis w/u, chemistries, BS; NE

slight jitteriness 48 h, responsive, good

tone, Moro, suck, placing, eye tracking;

NE at discharge wn! with slight increase

DTR LE

13 3 39 F Neg P; brief decel ht monit; pH 7.2; RDS; 2

szs 3rd d; Rx Pb x 7 d; Neg w/u, NE,

sono; EEG abn (focal ictal discharge, nl

bkgd)

14 18 40 F Neg P; prolonged 2nd stage labor; marked

late meconium; pH 6.9; resusc at 3 mm &

off 24 h later; Neg NE, sono 7th d; EEG

abn (some burst suppression in NREM)

15 4 41 M Maternal DM; LF Del; resusc at 6 mm with

resp assist 4 d; NE floppy w/clonus; Neg

w/u & sono, but BS 20 mg/dL; no known szs; NE moderate hypotonia with brisk

DTR, good Moro, suck; Neg sono, BAEP;

EEG abn (brief low-frequency ictal

dis-charge)

16 17 39 F Mild late preeclampsia; CS; BW 2,100 g;

few apneas, nonictal, resolved 6th d; Neg

sepsis w/u & CSF; NE mild hypotonia,

depressed suck; Neg sono; EEG excessive

rolandic spikes

17 16 40 M Neg P; Del pelvic disproportion; fetal

dis-tress; CS; resusc at 10 mm with resp

as-sist 1 wk; RDS; apnea (nonictal) 2 wk; Neg CT scan, sono; NE mild hypotonia, lethargy, poor suck, obligatory TNR;

EEGs “transient dysmaturity”

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TABLE-Continued

Infant’s Infant Gesta- Sex Prenatal, Perinatal, and Outcome

Rank No. tional Postnatal Status

of Age

Risk (wk)

18 5 38 F Moderate ethanol in P; LF Del; jitteriness 3 3.2 yr, nl; DQ > 90

d; DIC; renal failure resolved 4th d; NE

floppy, poor suck; EEG abn 3rd d; Neg

NE, EEG, BAEP, CT scan 6th d

19 8 39 M Neg P; decel ht monit; pH 6.9; resusc at 5 3.0 yr, quadriparesis w/Lt

hemi-mm with resp assist 10 d; mu!tifoca! szs 2 paresis, EEG abn; DQ < 80

d; Rx Pb & DPH; Ca 5, BS 18 mg/dL;

Rx Pb & DPH discontinued 8th d; no

recurrence of szs; Neg sono, ECG, NE;

EEG abn (ictal multifocal discharge 2nd

d; wnl 5th d)

20 14 38 F Moderate toxemia; Abr plac; CS; Rt pneu- 2.6 yr, global devel delay, CT scan mothorax; resusc at 7 mm; PDA; Ca 6.6; bilateral mild atrophy; DQ < 80 3 clonic szs; Rx Pb, Ca & glucose; NE

hypertonic, mild obligatory TNR, good suck, Moro, eye tracking, but lethargic;

EEG abn (poor state differentiation)

21 12 41 F Bleed 3rd T; Preeclampsia; Del late, 2.8 yr, HC 3%, hemiparesis, TIC

marked meconium; pH 7.1; fever & Esch- szs, CT scan Rt hemisphere

atro-erichia coli; Neg CSF, CT scan; RDS; phy, EEG abn; DQ < 70 dysmorphic features; apnea ? ictal; EEG

abn; NE lethargic, hypotonic, poor

plac-ing, Moro, & suck, clonus, plantar

flex-ors; Neg EEG 6th d

22 24 41 F Vaginal bleed 3rd mo; fetal distress; HF 3.0 yr, very mild quadriparesis,

Del; resusc at 4 mm with resp assist 1 EEG nl; DQ 90

wk; PDA; sepsis; ? meningitis; CSF

pleo-cytosis (TP 150); multifocal szs x 2 wk;

Neg CT scan; NE mildly floppy, DTR nl,

poor Moro, good eye movement; Neg

EEG, BAEP, CEP

23 15 39 F Neg P; Del breech, heavy meconium; decel 1.4 yr, delayed motor; 3 yr, very

ht monit; pH 7; DIC; renal failure; HBP; mild hemiparesis; DQ 100

CT scan and sono Rt cerebellar

hemor-rhage & mild ventricular dilation; clonic

szs 3rd d; Rx Pb 6 d; NE lethargy;

unsus-tamed bilateral clonus; repeat CT scan

mild hydrocephalus; EEG abn; Neg NE &

EEG 10th d

24 19 38#{189} M Gestational DM, bleed 6th mo; nuchal cord 3.2 yr, severe TIC szs; global devel

X2; fetal distress; pH 6.9; resusc with delay, EEG abn; DQ <60

resp assist X 5 d; SIB 15%; NE

hypo-tonia, lethargy, clonus; Neg CT scan,

CSF, BAEP; EEG abn (burst

suppres-sion) 1st d, 5th d borderline

25 26 38#{189} M Eclampsia 6th mo (BP 200/95; 1 T/C sz, 1.5 yr, nl except ? language devel

Rx conservative); Labor decel ht monit; delay; 3.1 yr, nl; DQ 104

MF Del; umbilical cord; pH 6.9; heavy

meconium; Apgar: 2-5-5 at 1-5-10 mm;

Resusc at 11 mm with resp assist 38 h; sepsis w/u pos blood culture E coli; LP

neg; sono Neg; apneic episodes ? szs;

EEG abn 4th d, nl 7th d; NE at discharge

2 wk later hypotonia, asymmetrical

Moro, poor suck, poor placing,

hyperac-tive DTR LE>UE, clonus sustained Rt

foot

26 9 38#{189} M Neg P & Del; 1 tonic sz at 46 h; LP blood 2.9 yr, nl; DQ 108

CT scan & sono grade II IVH; Rx

con-servative (no hydrocephalus); NE

hyper-tonic 4th d, exaggerated TNR, poor suck,

central apneas; Neg BAEP, CEP; EEG

abn (“marked dysmaturity”); NE still

hy-pertonic 8th d, scissoring, clonus, no placing, asymmetrical TNR, Moro; EEG

still mild dysmaturity 8th d

55

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8 mo,

nh,

mii diplegia; 2.3yr, nl;

DQ 92

3.5 yr, ni; DQ 96

1 yr, one febrile convulsion, NE, nl; 3.6 yr, nl; DQ 98

1.8 yr, onset Rt focal szs, NE, nl;

DQ 84; 3.0 yr, szs controlled with

DPH, NE, Rt hemiparesis; DQ

80

TABLE-Continued

56

Infant’s Infant Gesta- Sex Prenatal, Perinatal, and Outcome

Rank No. tional Postnatal Status

of Age

Risk (wk)

27 28 41 M Bleed 5th mo; NegL& Del; BW 2,650 g;

Apgar: 5 at 1 mm and 7 at 5 mm; focal sz

at i5 h; Nl electrolytes and BS; Neg sep-tic w/u; LP slight pleocytosis, TP 90, sugar 50; 2nd LP neg; szs persisted de-spite good Pb & DPH levels; CT scan

edema & ? Rt F infarct, 2nd CT scan Rt

F atrophy; EEG x 3 1st 2 wk abn (poor states; ictal runs Lt F-P in 1st EEG, 2nd

EEG better states, dysmature indices;

asymmetrical with decreased voltage Rt F); NE at discharge marked hypertonicity w/bilateral clonus, poor Moro,

asymmet-rical TNR, poor visual responses

28 27 39 F Neg P; Long Del (no monitor); CS; severe meconium stain; Umb cord; pH 7; Apgar: 3 at 1 mm and 6 at 5 mm; szs multifocal at 12 h; Ca 6.8; BS 20 mg/dL; szs for 10 d despite good Pb & DPH levels, then szs discontinued; Neg w/u; NE at discharge floppy, lethargic, brisk DTRS with clonus

poor tracking with nl doll’s responses,

poor suck & placing; 3 EEGs 1st d to

13th d abn (persistent dysmaturity

indices, nl states, persistent Rt & Lt

spikes C-P-O)

29 25 40 F Neg P; long 1st stage labor, ruptured

mem-brane, CS at 12 h; Apgar: 1 at 1 mm and

3 at 5 mm; pH 6.8; Resusc 5 mm; focal szs at 6 h; Ca 6, BS 15 mg/dL; Rx Cat,

glucose, Pb (10 mg/kg x 3 d); szs

discon-tinued; EEG abn 2nd d; Neg sono, LP;

CT scan 5th d ? edema; 2nd EEG abn

7th d; NE lethargy, hypotonic, poor suck,

poor Moro, brisk DTR, poor tracking,?

doll’s responses; Neg BAEP, vestibular test

30 29 42#{189} M Neg P; Del lost fetal heart monitor, CS;

Umb cord; pH 6.2; BW 3,840 g; Apgar: 3

at 1 mm and 3 at 5

mm;

Resusc at 5 mm

with resp assist; RDS; LP marked

xan-thochromia in 3 tubes; Hct 29; Sono IVH

grade 3; myoclonic sz, apnea, & posturing 26th h; EEG abn (ictal t discharge, Lt

P-0, poor states); szs persisted 4 d despite

good level Pb, then discontinued with

di-azepam; 2nd LP xanthochromia; TP 200,

S 60; Off resp assist 10th d; NE at

dis-charge (2 wk) marked hypotonia,

de-pressed sensorium, poor Moro, suck, &

placing; frequent vomiting; EEG abn

(ab-sent NREM, excess spikes awake &

REM over P-T with Pos sharp waves Lt

C

* Abbreviations used are: abn, abnormal; Abr plac, abruptio placenta; ACTH, adrenocorticotropic hormone; BAEP,

brainstem auditory evoked potentials; bkgd, background; BS, blood sugar; BW, birth weight; C, central; CEP, cerebral evoked potentials; coord, coordination; CS, cesarean section; CSF, cerebrospinal fluid; CT, computed tomography;

decel ht monit, decelerated heart monitor; Del, delivery; devel, developmental; DIC, disseminated intravascular

coagulation; DM, diabetes mellitus; DPH, diphenylhydantoin; DQ, developmental quotient; DTR, deep tendon reflexes;

F, frontal; HBP, high blood pressure; HC, head circumference; HF, high forceps; hypsar, hypsarrhythmia; IAA, internal

aortic arch; IS, infantile spasms; LE, lower extremities; LF, low forceps; LP, lumbar puncture; Lt, left, MF, mid

forceps; misc, miscarriage; NE, neurologic examination; Neg, negative; ni, normal; NREM, non-rapid eye movement;

0, occipital; P, pregnancy, PDA, patent ductus arteriosus; Pos, positive; PRM, premature ruptured membranes; RDS,

respiratory distress syndrome; REM, rapid eye movement; resp assist, respiratory assistance; resusc, resuscitated; Rt, right; Rx, therapy; SIB, serum indirect bilirubin; sono, ultrasound scan; szs, seizures; T, temporal; T/C, tonic/clonic; TNR, tonic neck reflex; TP, total protein; UE, upper extremities; URI, upper respiratory tract infection; wnl, within

normal limits; w/u, work-up.

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ARTICLES

57

mostly obscured by artifact; state 2-eyes open, not

crying or fussing, moving and responsive to visual

stimuli, EEG with continuous irregular background

with mixed frequencies from fi to t5, voltages of 20

to 100 ;zV, no clear gradients, often

electromy-ographic (EMG) artifact and eye movements; state

3-eyes open, but rarely moving or responsive to

visual stimuli, not crying or fussing, EEG similar

to state 2, but with intermittent frontoposterior

gradient, with higher voltages and slower

frequen-cies in anterior gradients; state 4 or REM

sleep-eyes closed, intermittent phasic body/limb

move-ments, grimacing, smiling, sucking, clusters of eye

movements, irregular respiration, lowered EMG

tonic activity, EEG similar to that of state 2 during

the initial or first REM period, in subsequent REM

periods showing continuous, lower-voltage (20 to

50 tV) background with prevailing f, t frequencies;

state 5 or NREM sleep-eyes closed, quiescence of

body, limbs, face, and eye movements except for a

rare startle or a rare slow eye movement, regular

respiration, increased tonic EMG activity, EEG

either discontinuous with bursts of higher-voltage

(50 to 200 V) t5, t waves with some sharp transients

separated by decreased mixed-frequency

back-ground (20 to 50 j.tV, four- to ten-second duration)

or with more continuous and higher-voltage (50 to

200 V) background with prevailing frequencies in

the #{246},0 range. These two EEG patterns are called,

respectively, “trace alternant” and “continuous

slow wave” patterns, and they occur in NREM sleep

in variable percentages, the trace alternant

prevail-ing at birth and progressively decreasing with the

continuous slow wave progressively increasing

dur-ing the first 4 to 6 weeks after birth. For a more

detailed description of both states and

accompany-ing EEG patterns, see Parmelee and Stern,14

Wer-ner et al,17 and Lombroso.’2 In some epochs during

sleep in which babies had closed eyes and, hence,

were considered to be asleep, the other criteria for

defining REM or NREM were incomplete. This

represents what has been called “transitional sleep

state.” For the purpose of our analysis, we

elimi-nated these epochs from our scoring. In this

popu-lation, such epochs never exceeded more than 5%

of the total sleep recorded.)

Times spent by each infant in each one of these

five states were scored as percentages of the total

recording periods at each ofthe four sessions. Thus,

we obtained for each baby a total of 20 scores that

could be subjected to various analyses of variance

between the normal and at risk groups. Further, for

each infant, it was feasible to establish the degree

of variability for each selected

state

from session to

session; this resulted in an individual profile of the

stability or instability of the selected states (profile

consistency). All babies were reexamined at

6-month intervals (±2 weeks) by the same observer

(C.T.L.), and a final neurologic reevaluation was

performed at periods varying from 2 years 4 months

to 4 years. In some, a computed tomographic (CT)

scan was repeated. All obtained full developmental

evaluations at the end of the study (Table).

RESULTS

AND ANALYSIS

The clinical outcomes for the whole group are

summarized in the Table. In the first analysis, we

examined whether any scores of particular states at

any of the weekly recording sessions offered

mdi-vidual prognostic clues. Of the 20 scores obtained

(five awake-sleep states times four recording

ses-sions), two statistical significances were found

be-tween the normal and abnormal outcomes.

Awake-Quiet percentages between the normal and

abnor-ma! populations in the first week recordings are

shown in Fig 1. A statistically significant difference

is present

at this

time

(P < .05). However, if we

take the normal mean, -2 SD, as a criterion for

“normality,” only 2/il babies in the abnormal

group had values outside the criterion, whereas all

the others had values within the criterion. If the

abnormal mean, +2 SD, is used as a criterion for

“abnormality,” only 3/19 in the normal group had

values outside the criterion. The other group

com-parison that showed statistical significance was

NREM in the second week (P < .05). The group

with normal outcome had a higher NREM

percent-age than the abnormal group, but the

discrimina-tory power of the mean ±2 SD was similarly poor.

Thus, it became clear that this type of intergroup

analysis was not particularly promising to refine

our “group-prognostications.”

We noted that there was a genera! tendency for

the normal group to show approximately the same

percentages of sleep-waking states at different

re-cordings, whereas the risk group exhibited higher

variability. Hence, we proceeded to analyze the

consistency profiles of the individual babies and

their long-term clinical outcomes.

Two examples, one chosen as the best case of

state consistency throughout the four separate

ses-sions and the other chosen as an extreme example

of state variability, are shown in Fig 2.

The consistency measurement of a given subject

on the state profile over the four repeated

obser-vations is expressed by an index

W,

which is a

coefficient of concordance derived from an analysis

of variance applied to the 20 points (five states

times four repetitions) in a given individual data

matrix. Because these points are in a percentage

form, ie, the length of time spent in each state

divided by the total observation time, the totals of

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1ST WEEK ? BORDERLINE

U ABNORMAL

10

5

p <

0.05

- 2SD

W0.9965

#2

INITIALLY: NORMAL

60 - OUTCOME: NORMAL

-I

% 40

-20

-0

60

% 40

20

0

the repetition rows ofthis analysis are always 100%,

which makes the sum of squares (55) for the

repe-tition (SSr) to zero. Hence, the total 55 (SSt) is

composed of the 55 between states (SSs) and the

55 within

states

(SSe).

If each

repetition

produces

the same percentage to a given state that every

other repetition produces, and if the same is

re-peated in the other four states, the SSe becomes

zero, and SSs =

SSt,

which

is a case

of the perfect

concordance. As the degree of lack of concordance

increases, the SSr decreases, while SSe increases.

The

W

is defined as SSr/SSt and is a parametric

equivalent to Kendall’s method, which used a

non-parametric technique.27 It is obvious that when the

profiles between the four recordings approach

iden-tity, W approaches the value of 1 (SSr = SSt); and

if the state percentages are distributed as if

ran-domly assigned, W approaches the value of 0 (SSr

U = 0).

I P III IV V The results of this analysis for the entire cohort

of neonates are summarized in Fig 3. The babies

are lined up in the abscissa from the most normal

(baby 1) to the highest risk (baby 29), using the

combined ranking method described earlier. In

gen-era!, there is a weak association between initial

normality or abnormality and good or bad

long-term outcomes. However, there are many

excep-tions (see the Table). For example, baby 13, whose

initial neonatal findings were benign, developed

infantile spasms with hypsarrhythmia in his EEG

at 8 months, with quadriparesis and a

developmen-tal quotient of 60 at 2.9 years; baby 21, located close

to the normal end in the newborn period, developed

I AWAKE, CRY IV ASLEEP. REM

II AWAKE, QUIET V ASLEEP. NON-REM

AWAKE - QUIET

U NORMAL OUTCOME

58

WAKING-SLEEP

STATES

IN NEONATES

r.:j#{149}

+ 2SD

#{149}1

;‘I

.

. normaI mean (x)

;:

I:0rmaI

mean

(y)

___

Fig 1. One of two examples in which statistically significant value was found when

comparing outcomes. At first week of testing, percentage scores in Awake-Quiet state were

significantly different between normal and abnormal outcomes (P < .05). However, this

is a group difference. Taking normal mean -2 SD values as criterion, only two abnormal outcomes could be identified; the other nine values were within 2 SD. Taking abnormal

mean +2 SD, three normal outcome values were outside of this criterion.

I I I I I

I Ii III IV V

#19

INITIALLY: AT RISK

- OUTCOME: ABNORMAL 3

O.73O1 f\ I i

- /, %,#{149}_

, ..

.4 %% 2

- //41 4

III AWAKE, DROWSY

Fig 2. Two examples of state profiles. Percentage time

spent in each awake-sleep state is plotted on vertical axis;

horizontal axis shows five awake-sleep states. Solid,

dot-ted, coarse, broken, and fine broken lines represent

mea-sures obtained on first, second, third, and fourth sessions,

respectively. Top, Profile ofneonate with highest W value

is shown; bottom, profile of neonate with lowest W value is shown.

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LONG TERM OUTCOME

#{149}

ABNORMAL

? BORDERLINE

1.00

0.90

0.80

0.70

121212 2 3 1 11 112112 2222

121 30 031627 038476 584245998 759

PROFILE CONSISTENCY

ARTICLES

59

>-C)

z

w

U)

Cl)

z

0

C)

z

II

0

0 0

.(

II

0 0

U NORMAL

NORMAL TO BORDERLINE TO AT RISK

ASSESSMENT IN NEWBORN PERIOD

Fig 3. Assessment of profile consistency in newborn period. State profile consistency is expressed by W on vertical axis. On horizontal axis, baby who was thought to have least risk (baby 1) was placed at left end, and other neonates were arranged according to their ranking for increasing risk obtained through single-blind method. Thus, baby rated as

having highest risk (baby 29) is located at extreme right. With two exceptions (babies 16

and 20), high W values (>90) are associated with normal outcomes, whereas low W values

(<.90) are associated with abnormal outcomes. Two borderline cases (babies 4 and 24) also had relatively high W values.

nonfebrile seizures and at age 3 years had

my-oclonic, tonic, and atonic epilepsy, with

extrapyr-amidal signs and a developmental quotient of 76;

baby 23, who received the fourth highest rank in

normality during the newborn period, was

motori-cally delayed with mild diparesis and a

developmen-tal quotient of

70 at 3.6 years.

Babies

30 and 3, who

are located slightly to the left of the midpoint in

the scale (hence, ranked as relatively normal

new-borns) also had poor outcomes. A!! five infants had

shown low-consistency profiles during their

neo-natal period. All others who were normal at final

assessment had shown good state consistency with

the exception of baby 20. Baby 16, ranked at some

risk initially, had a low consistency profile, but a

good outcome. Conversely, babies 26, 9, 28, 25, and

29 were initially considered to have high risks, but

were found to be neurologically intact on follow-up.

As shown in Fig 3 and detailed in the Table, these

five babies had demonstrated high state consistency

profiles in spite of their low initial ranking, hence,

rated at significant risk for future outcome. Baby

24 at 3 years had some motor deficits, but normal

development; baby 4 was questionably

compro-mised. They had been ranked initially within the

at-risk group; both, however, showed consistent

state profiles, and their final clinical outcome may

be considered as borderline, at worst.

In summary, all 17 babies who had the 17 highest

w

values were found to be normal later (including

the two borderline ones), whereas among the 13

babies who had the lowest 13

W

values, 1 1 were

found to be abnormal and two normal at final

assessment (P < .001). The results are shown in

Fig 4 (right columns). Hence, compared with the

future risk predictions by the neurologists on the

basis of prenatal, perinatal, and postnatal clinical

information (Fig 4, left columns), the profile

con-sistency method (W) appears to be vastly superior

for long-term prognosis.

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1

10

20

30

BORN PERIOD RANKED

.

I

I

.

I

N

0 N N

A

A

I N

I

!

I

I’

I

I

I

I

II

I C H

1

I

w

I

ABNORMAL NORMAL

.

.

ABNORMAL NORMAL

ASSESSMENT IN

NEW-RANKED

60

WAKING-SLEEP

STATES

IN NEONATES

N

A

N

K

S

LONG TERM OUTCOME

Fig 4. Assessment of long-term outcome. In two columns on right, all babies’ values are

aligned from highest W (top) to lowest W (bottom). There is clear correlation between

high W values and normal outcomes and, conversely, correlation between low W values

and abnormal outcomes. Two dots with question mark are borderline cases. In contrast

with these positive correlations, prognostic profiles suggested by clinical assessment during

newborn period often proved to be wrong. This is indicated by entirely overlapping

distributions of dots in columns on left. Baby who was thought to be least at risk is ranked

at top of column, and one thought to be most at risk is ranked at bottom.

DISCUSSION

Early investigators who demonstrated the

recur-rence of relatively homogenous, short and simple

cycles of wakefulness-sleep states in the human

newborn were already aware that these states are

sensitive to exogenous and endogenous factors. In

1967, Parmelee et al alluded to the lability of sleep

cycles in grossly abnormal babies. Deviations in

sleep states or in some of their components have

been

described by other investigators.’3”20’22’23’33

These included most heterogenous groups of

patho-logic

conditions:

asphyxia;

Down

syndrome;

hypo-thyroidism; stress; heroin-addicted mothers or

mothers with diabetes or toxemia; kernicterus;

gen-era! sepsis; seizures; surgical problems with no

evi-dence of CNS involvement.

These studies dealt with sleep states only.

Be-cause full-term, normal neonates spend about 60%

to 70% oftheir time in sleep during their first weeks

of life, it is natural that investigations focused

mainly on sleep states. This was especially true of

investigations using serial EEG recordings.

A major

problem

confronting observations on

sleep states is that they use “group” rather than

“individual” measures. For example, normal

full-term newborns during their first 4 weeks of life

spend nearly half of their total sleep time in REM

and slightly less time in NREM. These are average

percentages; in fact, they may vary 20% to 30% in

either direction between babies. Hence, reliable

normal values, even values that are only for sleep

states, show marked individual fluctuations, often

overlapping with those obtained in impaired

new-borns. Further, different values are reported

ac-cording to whether these states were scored by

simple observation or by polygraphy, and, hence,

they may vary from study to study according to

predefined criteria set by individual investigators.

Not only do we deal with large normal standard

deviations, but we know also that these sleep states

can be influenced, even if transiently, by several

variables.’2 For example, there are reports stating

that newborns with seizures exhibit decreased REM

sleep time. Yet these reports do not include

infor-mation about use of anticonvulsants. It is known

that diazepam or phenobarbital prolong NREM

sleep at the expense of REM.’2 Even greater

van-abilities may be expected in the waking states in

which so many more interactions take place with

hard-to-control environmental stimuli.

Thus, in our attempt to evaluate degrees of

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ARTICLES

61

bility in wakefulness-sleep state organization as a

possible predictive measure for at-risk newborns,

we were confronted by several problems. We could

not find published data on a cohort of normal babies

that included polygraphic recordings in both

wak-ing and sleep over a period of time after birth.

Although sleep patterns of normal infants from

birth to several months have been carefully

stud-ied,16’3436 these do not include waking states nor do

they focus on neurologic clinical correlates. No data

covering a sufficiently long period of waking-sleep

recordings and long-term clinical correlations are

available for at-risk neonates. There are, of course,

exceptions for babies already known to have severe

CNS disorders and who show aberrations in their

sleep-state cycling. These have been described

an-ecdotally in neonates known to have congenital

brain malformations and in infants with

hypothy-roidism, phenylketonuria, or severe kernicterus and

in “other grossly abnormal babies.* Once we

ex-dude this population of clearly affected neonates,

there remains a large group of infants in whom

either biographic events or neurologic and other

examinations suggest less clear risk factors. This

population, comprising our group, rarely has those

constellations of abnormal parameters that would

reliably indicate long-term clinical outcome.

Experimental studies of Waite et a!39 suggested

that sleep stability in newborn rabbits appeared to

have high predictability in terms of their normal

development. Our pilot study, begun in 1973, of two

small groups of full-term human neonates

consid-ered, respectively, as normal or at risk suggested

that this strategy of studying individual

waking-sleep state stability over time was promising.4#{176}

Tho-man et a!41 studied a sample of 22 “healthy

full-term babies” by measuring percentages of six

be-haviora! states between the second and fifth week

after birth. Their conclusions were that infants with

most stable state consistency developed better than

those with least stable state consistency. Their

follow-up covered about 30 months, and their main

correlations were with developmental scales. Some

deviant cases were found, and some clinical

corre-lates appear obscure, such as those of a baby with

the lowest profile consistency developing an

aplas-tic anemia at 30 months. Our pilot study4#{176}and the

present one differ in terms of populations and

methodologies from that of Thoman et al,41 but

there is general agreement in that quantitative

in-dices of stability over time in behavioral states

demonstrate a generally positive correlation with

later clinical outcomes.

A ranking scale from normal to highest risk was

*References 3, 4, 11, 20-23, 30, 37, 38.

used in our study to minimize bias. It became

evident that the at-risk population tended to cluster

around extreme values. This suggested that the

individual state consistency profile over time,

sub-mitted to Mann-Whitney U-test, would provide a

clear difference between the groups. Indeed, this

difference emerged (P < .01, Fig 3). Five babies

ranked within the lowest risk cluster, exhibited

some of the lowest consistency profiles and, on

long-term follow-up, had clearly poor clinical

out-comes. Eight neonates who were ranked by the

blind scores within the group at risk had, instead,

good profiles and fared well on follow-up. Some of

these babies had worrisome neonatal problems,

from hypoxic-ischemic states with early seizures,

to meningitis, to intraventricular hemorrhage as

well as abnormal findings on neurologic

examina-tions and tests during the newborn period.

Inter-estingly, three newborns ranked at moderate to

high risk (babies 3, 8, and 15) had borderline or

normal findings on neurologic assessments at

dis-charge, but showed poor state consistency profiles

and were neurologically impaired when reexamined

at age 3 years. Some deviant cases should be pointed

out: within the least-risk group, baby 20 had a low

consistency quotient, but at 3.2 years was normal.

Conversely, one infant ranked within the greater

risk range (baby 16) developed into an essentially

normal toddler, but had a low quotient.

There was a high statistical difference between

the normal and abnormal outcomes (P < .01). If

values for the two babies with normal outcome but

with low W-va!u#{234}s are excluded, the mean values

for the normal and abnormal groups became .9851

and .8738, respectively (P < .001). The standard

deviations are .0102 and .0740, respectively. Thus,

if the normal mean +2 SD is used as the normal

criterion

(W

= .9647), ii infants with normal values

and two infants with borderline values are within

this criterion. Therefore, with this criterion,

pre-dictability of the future normalcy is 82.6% (19/23).

If normal and borderline cases are combined, such

predictability rises to 91.3%, with two

false-nega-tive cases (8.7%).

One might say that because the distribution of

these data points is more Poisson in type, normal

mean +2 SD would not be appropriate as criterion

values. However, because with the exceptions of

babies 20 and 16, there is a clear separation between

the two groups, any criterion values between .96

(the lowest value for normal outcome) and .91 (the

highest value for abnormal otucome) are probably

good for discriminating purposes.

We recognize that our study did not control a

number of variables that might be relevant,

partic-ularly with regard to the waking states. Our

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62

WAKING-SLEEP

STATES

IN NEONATES

graphic data indicate a period of total sleep greater

than that reported by direct observation. We do not

dispute the question raised by WolW2 of whether

polygraphic recordings are necessarily superior to

careful visual observation of the waking-sleep

be-havioral states of these infants. We think that, as

far as sleep states are concerned, the availability of

other parameters offered by polygraphy is, indeed,

a better method for both qualification and

quanti-fication of sleep states. Regarding the waking

states, however, polygraphy is of doubtful value. As

we mentioned in the introduction, the study of

consistency in the various waking states may

ac-quire greater value in detecting subtle dysfunctions

of the developing CNS, as they may offer more

information on how pre-determined biologic

sched-ules may be modified by organic as well as by

environmental variables.

CONCLUSION

This investigation was focused on the proposition

that prolonged and repeated measurement of the

ability of a baby to maintain fairly constant state

organization might indicate that baby’s neurologic

outcome. It is clear that the data reported in this

study with relatively small numbers of neonates

will require further confirmation and refinement in

design. Meanwhile, the results obtained appear

en-couraging and, if confirmed, we would have

avail-able an economical tool for prognostic profiles of

newborns at risk. Parents and/or other observers

could, in fact, be trained to recognize and score

these waking-sleeping states, without the need of

the more expensive polygraphic recording, and thus

prolonged profiles of state consistency or variability

could be obtained by simple observation.

ACKNOWLEDGMENTS

We thank Drs Karl Kuban and Shozo Nakano,

De-partment of Neurology, Harvard Medical School, and Dr

Ritsuko Sawa, Department of Pediatrics, Jichi Medical

School (Japan), who helped in assessment of neonates.

We also thank Dr Russel M. Church, Department of

Psychology, Brown University, for his advice on

statis-tical procedures.

REFERENCES

1. Monod N, Dreyfus-Brisac C: La trace paroxystique ch#{232}zle nouveau-ne. Rev Neurol 1962;106:129-130

2. Lombroso CT: Neonatal seizure states, in Proceedings IX

International Congress of Pediatrics. Tokyo, University of Tokyo Press, 1965, pp 38-59

3. Rose AL, Lombroso CT: Neonatal seizure states: A prospec-tive study in 137 full-term babies. Pediatrics 1970;45:404-425

4. Monod N, Pajot N, Guidasci 5: The neonatal EEG: Statis-tical studies and prognostic value in full-term and preterm

babies. Electroencephalogr Clin Neurophysiol 1972;32:529-544

5. Prechtl HRF, Theorell K, Blair AW: Behavioral state cy-clase in abnormal infants. Dev Med Child Neurol 1973; 15:606-615

6. Dreyfus-Brisac C, Monod N: Neonatal status epilepticus, in Leiry G (ed): Handbook EEG Clinical Neurophysiology (Vol. 7B). Amsterdam, Elsevier Biomedical Press, 1975, pp 6-23 7. Engel RCH: AbnormalEiectroencephalogram in the Neonatal

Period. Springfield, IL, Charles C Thomas Publishing Co, 1975

8. Lombroso CT: Convulsive disorders in newborns, in Thomp-son RA, Green JR (eds): Pediatric Neurology and Neurosur-gery. New York, Spectrum, 1978, pp 205-239

9. Ellingson RI: The EEGs of premature and full-term new-borns, in Daly DD, Klass DW (eds): Current Practice in

Clinical Electroencephalography. New York, Raven Press,

1979, p 149

10. Tharp BR: Pediatric electroencephalography, in Aminoff M (ed): Electrodiagrtosis in Clinical Neurology. London, Churchill Livingstone Inc, 1980, pp 67-117

11. Watanabe K, Miyasaki 5, Hara K, et al: Behavioral state cycles, background EEGs and prognosis of newborns with perinatal asphyxia. Electroencephalogr Clin Neurophysiol 1980;49:618-625

12. Lombroso CT: Neonatal electroencephalography, in Neider-meyer E, Lopes da Silva P (eds): Electroencephalography: Basic Principles, Clinical Applications and Related Fields.

Baltimore, Urban & Schwarzenberg, 1982, pp 599-637 13. Prechtl HFA, Weinman H, Akiyama Y: Organization of

physiological parameters in normal and neurologically ab-normal infants: Comprehensive computer analysis of poly-graphic data. Neuropaediatrie 1969;1:101-129

14. Parmelee AH Jr, Stern E: Development of states in infants, in Clemente CD, Purpura DP, Mayer FE (eds): Sleep and

the Maturing Nervous System. New York, Academic Press,

1972, pp 200-214

15. Wolff PH: The causes, controls and organization of behavior in the neonate, in Psychological Issues. New York, Interna-tional University Press, 1966, vol 17

16. Prechtl HFR: The behavior status of the newborn infant (a review). Brain Res 1974;76:185-212

17. Werner 55, Stockard JE, Bickford R: Atlas of Neonatal Electroencephalography. New York, Raven Press, 1977 18. Lombroso CT: Neurological observations in diseased

new-borns. Biol Psychiatry 1975;10:527-558

19. Lombroso CT: Quantified electroencephalographic scales in 10 preterm healthy newborns followed up to 40-53 weeks CA by serial polygraphic recordings. Electroencephalogr Clin Neurophysiol 1979;46:460-473

20. Monod N, Eliet-Flescher J, Dreyfus-Brisac C: Le Sommeil du nouveau-ne pathologique: Analyse des etudes polygraph-iques. Biol Neonate 1976;11:216-247

21. Schutz MA, Schulte FJ, Akiyama Y, et al: Development of electroencephalographic sleep phenomena in hypothyroid infants. Electroencephalogr Clin Neurophysiol 1968;25:351-358

22. Schulte FJ, Hinze G, Schrempf G: Maternal toxemia, fetal malnutrition, and bioelectric brain activity of the newborn, in Clemente CD, Purpura DP, Mayer FE (eds): Sleep and

the Maturing Nervous System. New York, Academic Press,

1972, pp 419-439

23. Theorell K, Prechtl HFR, Vos JE: A polygraphic study of normal and abnormal newborn infants. Neuropaediatrie 1974;5:279-316

24. Lombroso CT: Seizures in the newborn period, in Vinckler PJ, Bruyn GW (eds): Handbook of Clinical Neurology. Am-sterdam, Elsevier Biomedical Press, 1974, vol 15, pp 189-218

25. Guilleminault C, Sonquet M: Sleep study and related pa-thology, in Korobkin R, Builleminault C (eds): Advances in

Perinatal Neurology. New York, SP Medical & Scientific

Books, 1979, pp 225-247

26. Kleitman N: Sleep and Wakefulness, ed 2. Chicago, Univer-sity of Chicago Press, 1963

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27. Edwards AL: Statistical Methods for the Behavioral

Scien-tists, ed 6. New York, Rinehart, 1958

28. Parmelee AH Jr, Wenner WH, Akiyama Y, et al: Electro-encephalography and brain maturation, in Minkowski A (ed): Regional Development of the Brain in Early Life. Ox-ford, Blackwell, 1967, pp 459-480

29. Dreyfus-Brisac C: The electroencephalogram of the prema-ture infant and full-term newborn, in Kellaway P, Petersen I (eds): Neurological and Electroencephaiographie Studies in Infancy. New York, Grune & Stratton mc, 1964, pp 186-207

30. Petre-Quadens 0: Contribution

a

l’#{233}tudede la phase dite parodoxale du sommeil, thesis. Acta Neurol Psychiat BeIg

1969;69:769-898

31. Petre-Quadens 0: Sleep in mental retardation, in Clemente CD, Purpura DP, Mayer FE (eds): Sleep and the Maturing

Nervous System. New York, Academic Press, 1972, pp

383-417

32. Schulman C: Alterations ofthe sleep cycle in heroin addicted and “suspect” newborns. Neuropaediatrie 1969;1:89-100 33. Emde RN, Metcalf DR: An electroencephalographic study

of behavioral rapid eye movement states in the human newborn. J Nerv Ment Dis 1970;150:370-376

34. Parmelee AH Jr, Wenner WH, Schulz HR: Infant sleep patterns from birth to 16 weeks of age. J Pediatr 1964; 65:576-582

35. Dittrichov#{224} J: Development of sleep in infancy, in Robinson

RI (ed): Development in the Fetus and Infant: Brain and

Early Behavior. New York, Academic Press, 1969, pp 193-204

36. Ellingson RJ, Peters JF: Development of EEG and daytime sleep patterns in trisomy-21 infants during the first year of life: Longitudinal observations. Electroencephalogr Clin Neurophysiol 1980;50:457-466

37. Monod N, Guidasci S: Sleep and brain malformation in the neonatal period. Neuropaediatrie 1976;7:228-249

38. Parmelee AH Jr, Stern E: Development of states in infants, in Clemente CD, Purpura DP, Mayer FE (eds): Sleep and

the Maturing Nervous System. New York, Academic Press,

1972, p 221

39. Waite SP, DeSantis DS, Thoman EB, et al: The predictive validity of early sleep development on later behavioral char-acteristics in the rabbit. BiOI Behav 1977;2:249-261

40. Lombroso CT: Some aspects of EEG polygraphy in new-barns at risk from neurological disorders, in Buser PA, Cobb

WA, Okuma T (eds): Kyoto Symposia (EEG Suppl No 36).

Amsterdam, Elsevier Biomedical Press, 1982, pp 652-663 41. Thomas EB, Denenberg VH, Sievel J, et al: State

organi-zation in neonates: Developmental inconsistency indicates risk for developmental dysfunction. Neuropediatrics 1981;12:45-54

42. WolffPH: Organization ofbehavior in the first three months of life, in: Early Development, Research Publications of Association for Research in Neurological and Mental Dis-eases (ARNMD). New York, 1973, vol 51, chap 7, pp 132-153

GROWTH

HORMONES

The days when we thought we knew how to use human growth hormone

(hGH) are over: the prospect of growth-hormone-releasing hormone (GHRH)

and genetically engineered biosynthetic hGH in unlimited quantities raises a

new set of questions. . . . The comfortable situation which we enjoyed when we

thought we were using a safe preparation for clear clinical indications with a

reasonably assured outcome has been shattered. We do not know who needs

GH and we do not know what will happen when we give it to normal short

children. We have about two years to find the answers to these questions before

hGH is available in large quantities and consumer pressure begins to rise.

Submitted by Student

From Editorial: Who needs growth hormones? (Lancet 1984;2:1189-1190).

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1985;76;52

Pediatrics

Cesare T. Lombroso and Yoichi Matsumiya

Outcome

Stability in Waking-Sleep States in Neonates as a Predictor of Long-Term Neurologic

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Pediatrics

Cesare T. Lombroso and Yoichi Matsumiya

Outcome

Stability in Waking-Sleep States in Neonates as a Predictor of Long-Term Neurologic

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Figure

Fig 3.Assessmentalsoandexpressedrankinghaving(<.90)riskofprofileconsistencyinnewbornperiod.StateprofileconsistencyisbyWonverticalaxis.Onhorizontalaxis,babywhowasthoughttohaveleast(baby1)wasplacedatleftend,andotherneonateswerearrangedaccordingtotheirforincreasingriskobtainedthroughsingle-blindmethod.Thus,babyratedashighestrisk(baby29)is locatedat extremeright.Withtwoexceptions(babies1620),highW values(>90)areassociatedwithnormaloutcomes,whereaslowW valuesareassociatedwithabnormaloutcomes.Twoborderlinecases(babies4and24)hadrelativelyhighW values.
Fig 4.Assessmentat topdistributionswithnewbornhighandof long-termoutcome.In twocolumnson right,all babies’valuesarealignedfromhighestW(top)tolowestW(bottom).Thereis clearcorrelationbetweenW valuesandnormaloutcomesand,conversely,correlationbetweenlowW valuesabnormaloutcomes.Twodotswithquestionmarkareborderlinecases.Incontrastthesepositivecorrelations,prognosticprofilessuggestedby clinicalassessmentduringperiodoftenprovedtobewrong.Thisisindicatedbyentirelyoverlappingof dotsin columnson left.Babywhowasthoughtto be leastat riskis rankedof column,andonethoughtto be mostat riskis rankedat bottom.

References

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To further investigate the role of Ng in cell growth and differentiation, we compared the ex- tracellular-signal regulated kinase 1/2 (ERK1/2) ac- tivity in Ng expressed cells

So the present study was carried out to assess nutritional status of children aged six months to five years based on measurement of mid upper arm

based diet containing 6.7% ethanol feeding to mice with impaired TGF-β signaling through constitutive disruption of β2-spectrin and/or Smad3.. Unexpectedly,

Correlation between pulmonary function tests and inflammatory markers in familial mediterranean

Binary logistic regression analysis showed that, after adjusting for the risk factors which were significantly associated with CKD in univariate analysis, factors

This study will analyze the impact of farmer’s adoption on mobile internet using the model developed by Nabhani (2015A), a model that predicts that business performance will be