Early-Life Predictors of Fetal AlcoholSpectrum DisordersWendy O. Kalberg, MA, LED,a Philip A. May, PhD,a,b,c David Buckley, MA,a Julie M. Hasken, MPH,b

Anna-Susan Marais, B Cur Nursing,c Marlene M. De Vries, MSW,c Heidre Bezuidenhout, MBChB, DCH, MSc,d

Melanie A. Manning, MD,e Luther K. Robinson, MD,f Margaret P. Adam, MD,g Derek B. Hoyme, MD,h Charles D.H. Parry, PhD,c,i

Soraya Seedat, MBChB, MMed, FC Psych, PhD,c Amy J. Elliott, PhD,j,k H. Eugene Hoyme, MDc,k,l,m

abstractBACKGROUND AND OBJECTIVES: Fetal alcohol spectrum disorders (FASD) comprise the continuum ofdisabilities associated with prenatal alcohol exposure. Although infancy remains the mosteffective time for initiation of intervention services, current diagnostic schemes demonstratethe greatest confidence, accuracy, and reliability in school-aged children. Our aims for thecurrent study were to identify growth, dysmorphology, and neurodevelopmental features ininfants that were most predictive of FASD at age 5, thereby improving the timeliness ofdiagnoses.

METHODS: A cohort of pregnant South African women attending primary health care clinics orgiving birth in provincial hospitals was enrolled in the project. Children were followedlongitudinally from birth to 60 months to determine their physical and developmentaltrajectories (N = 155). Standardized protocols were used to assess growth, dysmorphology,and development at 6 weeks and at 9, 18, 42, and 60 months. A structured maternal interview,including estimation of prenatal alcohol intake, was administered at 42 or 60 months.

RESULTS: Growth restriction and total dysmorphology scores differentiated among children withand without FASD as early as 9 months (area under the receiver operating characteristiccurve = 0.777; P , .001; 95% confidence interval: 0.705–0.849), although children whowere severely affected could be identified earlier. Assessment of developmental milestonesrevealed significant developmental differences emerging among children with and withoutFASD between 18 and 42 months. Mothers of children with FASD were significantlysmaller, with lower BMIs and higher alcohol intake during pregnancy, than mothers ofchildren without FASD.

CONCLUSIONS: Assessment of a combination of growth, dysmorphology, and neurobehavioralcharacteristics allows for accurate identification of most children with FASD as early as9 to 18 months.

WHAT’S KNOWN ON THIS SUBJECT: Drinking during pregnancy results ina continuum of disabilities in exposed offspring, fetal alcohol spectrumdisorders. Although early infant intervention positively influences long-termdevelopmental outcome of at-risk children, current diagnostic criteriareveal highest accuracy and reliability in school-aged children.

WHAT THIS STUDY ADDS: Growth, dysmorphic features, andneurobehavioral characteristics in infancy can predict which children are atgreatest risk of being assigned fetal alcohol spectrum disorder diagnosesat age 5, thereby aiding in timely diagnosis and initiation of interventionservices in early life.

To cite: Kalberg WO, May PA, Buckley D, et al. Early-LifePredictors of Fetal Alcohol Spectrum Disorders.Pediatrics. 2019;144(6):e20182141

aCenter on Alcoholism, Substance Abuse, and Addictions, University of New Mexico, Albuquerque, New Mexico;bNutrition Research Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; dDivision ofMolecular Biology and Human Genetics, Departments of Biomedical Sciences and cPsychiatry, Faculty of Medicineand Health Sciences, Stellenbosch University, Stellenbosch, South Africa; eDepartments of Pathology andPediatrics, School of Medicine, Stanford University, Stanford, California; fDepartment of Pediatrics, School ofMedicine, State University of New York at Buffalo, Buffalo, New York; gDepartment of Pediatrics, School ofMedicine, University of Washington, Seattle, Washington; hDepartment of Pediatrics, School of Medicine andPublic Health, University of Wisconsin–Madison, Madison, Wisconsin; iAlcohol, Tobacco, and Other Drug ResearchUnit, South African Medical Research Council, Cape Town, South Africa; jAvera Research Institute Center forPediatric and Community Research, Sioux Falls, South Dakota; kDepartment of Pediatrics, Sanford School ofMedicine, University of South Dakota, Sioux Falls, South Dakota; lSanford Children’s Genomic MedicineConsortium, Sanford Health, Sioux Falls, South Dakota; and mDepartments of Pediatrics and Medicine, College ofMedicine, University of Arizona, Tucson, Arizona

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Fetal alcohol spectrum disorders(FASD) encompass a range ofdeleterious effects of maternalalcohol consumption duringpregnancy. Together, they comprisethe most common environmentallyinduced category of intellectualdisability in the world, potentiallyaffecting 1% to 6.5% of school-agedchildren (10–65 per 1000) in theUnited States.1–4 Although the mostsevere end of the FASD continuum(fetal alcohol syndrome [FAS]) occursin 0.2% to 0.9% of live births (2–9per 1000) in the United States,3 it ismuch more common elsewhere.5 Forexample, in some communities in theWestern Cape Province of SouthAfrica, 9.3% to 12.8% of children(93–128 per 1000) have documentedFAS, whereas the full gamut of FASDaffects 18.2% to 25.9% of children(182–259 per 1000).6,7

Although several diagnostic schemesare used to assign diagnoses in theFASD continuum, the parameters setforth by the Institute of Medicinehave been employed most extensivelyin international population-basedstudies.8,9 These diagnostic guidelinesrecently were updated as theCollaboration on Fetal AlcoholSpectrum Disorder Prevalence(CoFASP) Consensus ClinicalDiagnostic Guidelines for FASD10

(Table 1).

Many consequences of FASD arelifelong, and behavioral and learningdifficulties constitute a significantburden. Neuroscience has revealedthat the neural plasticity of youngbrains is positively enhanced byintervention through early infantstimulation and augmentednutrition.11,12 Although identificationand referral of at-risk children withinthe first few months of life may becrucial for initiating effective earlyintervention services, diagnosis of thecontinuum of FASD in infants is rarelyattempted. Such diagnosticinattention may be explained bya lack of phenotypic specificity in thenewborn13 and by the higher

confidence, accuracy, and reliability ofdiagnoses in school-agedchildren.9,10,14–17

In the current study, we seek toidentify discriminating features ofFASD in early life, which will lead toimproved timeliness of diagnosis. Ouraims for the study include comparingand contrasting young children withFASD with typically developingchildren on (1) growth patterns, (2)dysmorphic features, and (3)measures of temperament anddevelopment, thereby identifyingfeatures in infants that can mostaccurately predict a diagnosis ofFASD at age 5.

METHODS

An international multidisciplinaryteam of experienced investigators ledthe study, which was conducted overan 8-year period (2008–2015).Dysmorphology and developmentalassessments were completed on eachstudy child at 6 weeks (time point 1[T1]) and at 9 (time point 2 [T2]), 18(time point 3 [T3]), 42 (time point 4[T4]) and 60 months of age (timepoint 5 [T5]).

Two regional communities in theWestern Cape Province of SouthAfrica with a high prevalence ofdocumented FASD (comprising 5towns and their surrounding ruralareas) housed the project.6,7,18–21 Theprovince’s population encompassesa diverse racial makeup (mixed race,50%; black, 33%; white, 16%; andIndian or Asian, 1%).22 Theproportion of women who drinkheavily during pregnancy in the 2rural agricultural study communitiesis 23.7%.23 By 20 weeks’ gestation,52.5% of pregnant women receiveprenatal care, and most womenschedule their first antenatal visit inthe second trimester.24

The Faculty of Medicine and HealthSciences Research Ethics Committeesat Stellenbosch University and theUniversity of New Mexico approvedall study procedures and data

collection tools. As an incentive andreimbursement for their time,participating women and childrenreceived a grocery store voucher ateach clinic visit.

Screening for Prenatal AlcoholExposure and Selection ofParticipants

Trained research staff recruitedpregnant women and their indexstudy children from primary healthcare clinics and hospitals, explainedthe study to prospective participants,and, after obtaining consent,conducted screening interviews thatincluded the 10-item Alcohol UseDisorders Test (AUDIT).25,26 Womenwith a history of drinking within thelast year were advised about thedangers of drinking during pregnancyand counseled to stop drinking. Thescreened women reported thecomplete gamut of drinking behavior,ranging from abstinence to heavydrinking. The modal pattern ofdrinking occurred in binges of $3standard drinks per day (14 g ofabsolute alcohol) on weekends.Initially, any woman who visiteda primary health care clinic forantenatal care and who agreed toparticipate was recruited. Afterdelivery, the children of enrolledwomen were evaluated at T1, T2, andT3. Once several hundred childrenwere recruited and had been followedthrough T3, a subset for thelongitudinal study was selected. Thecriteria for inclusion in thelongitudinal cohort includedcompletion of testing at all 3 timeperiods and maternal AUDIT scores.8 or ,7. Of the 199 childreninitially enrolled in the study, mothersof 105 reported AUDIT scores .8(52.8%), and mothers of 94 (47.2%)reported AUDIT scores ,7. Of thewomen whose AUDIT scores were.8, 44 (42%) scored between 8 and14, and 61 (58%) scored .15. Of thewomen whose AUDIT scores were,7, 52 (55%) scored 0, and 42 (45%)scored between 1 and 7. Therefore,

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the cohort reflected a representativerange of maternal drinking by design.

Comparison of Excluded Subjectsand Study Participants

One mother-child dyad dropped outimmediately (before T1), and anadditional 44 were later excludedfrom analysis because of insufficientdata. Of the 44 children who wereexcluded from the study, 23 werediscussed at a case conference afterT5 and were found to haveinsufficient data for inclusion: 18because of lack of developmentaltesting and 5 because both testingand prenatal alcohol exposure datawere missing. An additional 21children were not available and weretherefore not examined by thedysmorphologists at T5, 9 of whomwere last examined at T4 and 12 of

whom were last evaluated at T3.There were no statistically significantdifferences (on t tests, P , .05)between the 44 children withinsufficient data and those withcomplete data sets when comparedon height, weight, occipitofrontal(head) circumference (OFC), totaldysmorphology score, or BayleyScales of Infant Development, ThirdEdition (BSID-III) cognitive percentileat T3, T4, or T5. A total of 155children completed the entireprotocol with a complete data set andare included in this analysis. Becauseof the complexity of the project, thenumber of children seen at each timeperiod was variable (Fig 1).

The children were assessed on 3domains: (1) growth (height, weight,and OFC), (2) dysmorphology, and (3)

development. A structured maternalinterview was also performed on allparticipants. After completion of thestudy, data were analyzed todetermine which morphometricmeasures, dysmorphic features,developmental skills, or combinationthereof was most predictive ofa definitive FASD diagnosis at age 5.

Maternal Interviews

Structured maternal interviews wereused to gather information aboutmaternal age, ethnicity, physical traits(height, weight, OFC, BMI), gravidity,parity, time of pregnancy recognition,and drinking before and duringpregnancy by trimester.

Dysmorphology Assessments

Expert US clinical geneticists anddysmorphologists assigned diagnoses

TABLE 1 Updated Diagnostic Guidelines for FASD

CoFASP Consensus Clinical Diagnostic Guidelines for FASD

Prenatal Alcohol Exposure FAS FacialFeaturesa

Growth Restrictionb Deficient BrainGrowthc

NeurobehavioralImpairment(,3 y)d

NeurobehavioralImpairment(.3 y)e

StructuralBirth

Defectsf

FASWith confirmed or

unconfirmed alcoholexposure

X X X X X —

PFASWith confirmed alcohol

exposureX — — X X —

With unconfirmed alcoholexposure

X X (or deficient braingrowth)

X (or deficient heightand/or weight)

X X —

ARNDg

With confirmed alcoholexposure

— — — N/A X —

Alcohol-related birth defectsWith confirmed alcohol

exposure— — — — — X

Adapted from Hoyme HE, Kalberg WO, Elliott AJ, et al. Updated clinical guidelines for diagnosing fetal alcohol spectrum disorders. Pediatrics. 2016;138(2):e20154256. N/A, not applicable; X,required; —, not required.a The characteristic pattern of facial anomalies is defined by the presence of $2 of the following: (1) short palpebral fissures (#10th percentile), (2) thin vermilion border (rank of 4 or 5on racially normed lip-philtrum guide), and (3) smooth philtrum (rank of 4 or 5 on racially normed lip-philtrum guide).b Prenatal and/or postnatal growth deficiency: height and/or weight #10th percentile on sex-specific population-normed growth curves.c Deficient brain growth, morphogenesis, and/or neurophysiology is characterized by $1 of the following: (1) OFC #10th percentile, (2) structural brain abnormalities, and (3) recurrentnonfebrile seizures.d Affected children must display evidence of developmental delay $1.5 SD below the mean.e Children should be assessed for global, cognitive, and behavioral deficits. Global impairment: general conceptual ability, performance IQ, visual IQ, or spatial IQ$1.5 SD below the mean;cognitive deficit: $1.5 SD below the mean in 1 domain (executive function, specific learning impairment, memory impairment, or visual spatial impairment); behavioral impairmentwithout cognitive impairment: behavioral deficit in 1 domain $1.5 SD below the mean in areas of self-regulation (mood or behavioral regulation impairment, attention deficit, or impulsecontrol).f One or more major malformations demonstrated in animal models and human studies to be related to prenatal alcohol exposure, including cardiac defects (eg, atrial septal defects,ventricular septal defects, aberrant great vessels, conotruncal heart defects), musculoskeletal defects (eg, radioulnar synostosis, vertebral segmentation defects, large joint con-tractures, scoliosis), renal anomalies (eg, aplastic, hypoplastic, or dysplastic kidneys; “horseshoe” kidneys; ureteral duplications), eye anomalies (eg, strabismus, ptosis, retinal vascularanomalies, optic nerve hypoplasia), and/or hearing impairment (eg, conductive or neurosensory hearing loss).g For ARND, 2 domains of impairment are required for either cognitive deficit without behavioral impairment or behavioral impairment without cognitive deficit.

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using the CoFASP diagnosticguidelines for FASD.10 The guidelinesset forth a structured, empiricallybased dysmorphology assessment

scheme and weighted numericalscoring system for quantifyinggrowth restriction and minoranomalies common among children

exposed to alcohol. Dysmorphologyexaminations adhered toa standardized protocol at each ageinterval (T1–T5). US or South African

FIGURE 1Consolidated Standards of Reporting Trials chart for the longitudinal study. aAfter 44 subjects were excluded because of incomplete data, 155 childrencompleted the entire battery.

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dysmorphologists, pediatricians, orspecially trained research staffconducted the examinations. All staffwere trained in the CoFASPdiagnostic methodology10 by theexpert US dysmorphologists.Examiners were blinded to eachchild’s prenatal alcohol exposurehistory and to the results of anyprevious study assessments at eachtime interval.

Developmental Assessments: Birthto 42 Months

Specially trained research staffadministered the Brazelton NeonatalBehavioral Assessment Scale (BNBAS-3). Assessment of each infant’s abilityto regulate his or her state wasa focus of this study.27 Self-regulation(including general irritability, abilityto maintain attention, and generalstate maintenance) was hypothesizedto be more difficult for children whowere prenatally exposed to alcohol.Specific items on the BNBAS-3explored aspects of the child’s state,affect, and temperament.28

Sanctioned trainers instructed staffmembers on administration of theBSID-III. The BSID-III,29 designed totrack attainment of developmentalmilestones and abilities, was used toassess infant and toddlerdevelopment from 1 to 42 months ofage across 5 domains (cognitive,language, motor, social-emotional,and adaptive abilities). Cognitive,language, and motor skills wereassessed directly with the child,whereas social-emotional skills werederived from responses of theprimary caregiver to a questionnaire.Composite standard scores werederived for cognitive, language,motor, and social-emotional skills.29

Assessment Tool Used for Children at60 Months of Age

The Kaufman Assessment Battery forChildren, Second Edition (KABC-II)30

was used to measure processing andcognitive abilities of children at T5.This tool provides a mental

processing index (MPI) that de-emphasizes acquired knowledge,instead focusing on sequential andsimultaneous processing, learningability, and planning ability. TheKABC-II was chosen because it hasbeen validated for use in previousSouth African and other Africanresearch initiatives.31,32 TwoAfrikaans-speaking clinicalpsychologists who were blinded toalcohol exposure historyadministered the assessment.

Data Collection

During the initial clinical assessmentat T1, a dysmorphology examination,BNBAS-3 assessment, and BSID-IIItesting were completed. The BSID-IIIwas administered at assessmentpoints T1 to T4, and the KABC-II wascompleted at T5. USdysmorphologists provided 2 physicalexaminations, 1 at T4 and 1 at T5.Children who were born before 36weeks’ gestation were consideredpre-term, and all developmentaltesting was scored on the basis of thechild’s adjusted age for prematurityuntil 24 months. Interexaminerreliability data are not available forthe present investigation but havebeen sound in previous studies thatwere conducted by using thismethodology.18,19

All dysmorphology data weresystematically collected and recordedon a standard dysmorphologychecklist,9,10 and developmentaltesting followed standardizedprocedures. After the data werecollected, they were entered intoExcel databases, quality assured, andexported into a master database inSPSS (version 22; IBM SPSS Statistics,IBM Corporation, Armonk, NY]).33

Data Analysis

Data from the 155 children diagnosedproduced a data set formultiple–repeated-measures analysisof variance (ANOVA) to comparechanges in scores over the 5 timepoints on the basis of the final

diagnoses assigned. Categoricaldiagnoses assigned at caseconferences included FAS, partialfetal alcohol syndrome (PFAS),alcohol-related neurodevelopmentaldisorder (ARND), or not FASD. Nochildren met diagnostic criteria foralcohol-related birth defects.9,10 Noother genetic or malformationsyndromes were identified. Finaldiagnoses were assigned by the USdysmorphologists ina multidisciplinary case conferenceon the basis of the data gathered atT5 (psychological and behavioralassessments, growth, anddysmorphology examinations) and onthe basis of alcohol exposureinformation obtained from thequestionnaire responses provided atboth the initial screening and fromthe full maternal interview completedat either T4 or T5. At the time ofassignment of the final diagnosis,diagnosticians were blinded to anyother data previously gathered or topreliminary diagnoses assigned atearlier time points.

SPSS was used for all data analyses.33

A repeated-measure ANOVA was usedto measure differences betweenrelated population means over timebecause the primary longitudinalstudy aim was to identify factorsearly in a child’s life that wouldpredict a later FASD diagnosis. Inaddition, a receiver operatingcharacteristic (ROC) analysis wasemployed to strictly define the timeperiod when diagnostic prediction, byusing the dysmorphology score,achieved significance. The nullhypothesis was that the means ofFASD groups and the childrenwithout FASD would be equalover time.

RESULTS

Maternal Characteristics

In Table 2, the following arecompared between mothers who gavebirth to children with FASD and thosewho did not: (1) age, (2) growth

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parameters, (3) educational level, (4)race, (5) gravidity, (6) parity, (7) andself-reported drinking behaviorbefore and during pregnancy.34,35

Mothers of children diagnosed withFASD at age 5 demonstratedsignificantly higher gravidity (3.5 vs2.6) than did mothers of childrenwithout FASD. Self-reported drinkingbefore and during pregnancyrevealed significant differences indrinking during pregnancy (especiallyin the second and third trimesters)between mothers who had childrenwith FASD and those who did not. ByFASD diagnosis, the percentages ofwomen who reported drinking duringpregnancy were 90% for FAS, 100%for PFAS, 100% for ARND, and 51.4%for non-FASD. A comparison of othertraits between mothers who drankduring pregnancy and those who didnot revealed significant differences inheight (P , .001), weight (P = .006),OFC (P = .010), BMI (P = .024),number of years of education (P ,.001), gravidity (P = .002), and parity(P = .003). The mothers of childrenexposed to alcohol were significantlyshorter and lighter, had smaller OFCsand BMIs, and demonstrated highergravidity and parity.

Dysmorphology

Table 3 presents a comparison ofstudy children at age 5 who werediagnosed with FASD with thosechildren who were not. Childrendiagnosed with FAS, PFAS, or ARNDdemonstrated significantly highertotal dysmorphology scores thanthose without FASD. No significantdifference was observed between theFASD and non-FASD groups on length ofgestation, sex, or age at the Bonferroni-adjusted value of 0.005 at age 5.

As is the case with any medicalcondition, sound clinical judgmentwas exercised in assigning diagnosesin the FASD continuum. Among thedifferential diagnoses consideredwere genetic disorders or conditionsarising from other teratogens.Additionally, because OFC, growth,

and many cognitive and behavioralcharacteristics display moderate tohigh degrees of heritability, whensuch information was available aboutthe family, these data wereconsidered in final diagnostic

decisions. In the children includedin the final analysis, all otherapparent diagnoses, genetic orotherwise, were ruled out on thebasis of the clinical impression ofthe dysmorphologists.

TABLE 2 Maternal Characteristics

Mothers of ChildrenWith FASD(n = 79)

Mothers of ChildrenWithout FASD(n = 76)

P

Age at interview, y, mean (SD) 32.5 (7.9) 29.3 (7.1) .01Height, cm, mean (SD) 154.5 (5.7) 158.7 (7.6) ,.001Weight, kg, mean (SD) 55.4 (15.8) 70.2 (19.2) ,.001OFC, cm, mean (SD) 54.2 (2.4) 55.2 (2.3) .010BMI, mean (SD) 22.9 (5.8) 27.7 (7.6) ,.001Number of years of school, mean (SD)a 8.2 (2.1) 9.8 (2.2) .001Race, %Mixed race 97.5 90.8 —

Black 2.5 9.2 —

White 0.0 0.0 .07Gravidity, mean (SD) 3.5 (1.6) 2.6 (1.6) .002Parity, mean (SD) 3.2 (1.7) 2.4 (1.3) .003Spontaneous abortions, mean (SD) 0.3 (0.6) 0.2 (0.5) .25Induced abortions, mean (SD) 0.0 (0.1) 0.1 (0.2) .17Stillbirths, mean (SD) 0.1 (0.2) 0.0 (0.3) .55Week of pregnancy recognition, mean(SD)

12.6 (5.4) 12.8 (6.2) .81

Drinking during pregnancy, % yes 94.9 51.4 ,.001Usual number of drinks per drinking day,mean (SD)First trimesterb 8.3 (9.3) 5.9 (4.9) .14Second trimesterb 7.4 (10.0) 3.8 (4.4) .04Third trimesterb 5.3 (10.4) 1.8 (3.9) .02

—, not applicable.a FASD: n = 50; not FASD: n = 42.b Among drinkers only in the specific time period.

TABLE 3 Child Age, Sex, Growth, and Dysmorphology Comparisons

FASD(n = 79)

Not FASD(n = 76)

Pa

Weeks’ gestation at birth, mean (SD) 38.0 (2.7) 37.8 (3.4) .70Child’s age at T5, mo, mean (SD)b 58.8 (7.3) 56.4 (6.5) .03Sex, % male 40.5 43.4 .71Height percentile at T5, mean (SD)c 14.3 (17.0) 34.4 (26.6) ,.001Height z score at T5, mean (SD) 20.4 (0.7) 0.4 (1.1) ,.001Weight percentile at T5, mean (SD)c 10.4 (16.2) 33.5 (30.1) ,.001Weight z score at T5, mean (SD) 20.4 (0.6) 0.5 (1.2) ,.001BMI percentile at T5, mean (SD)c 23.4 (25.8) 41.4 (31.3) ,.001BMI z score at T5, mean (SD) 20.3 (0.9) 0.3 (1.1) ,.001OFC percentile at T5, mean (SD)c 8.8 (15.4) 30.2 (26.4) ,.001OFC z score at T5, mean (SD) 20.5 (0.7) 0.5 (1.1) ,.001PFL percentile at T5, mean (SD)c 11.4 (12.4) 26.5 (15.7) ,.001PFL z score at T5, mean (SD) 235 (0.8) 0.4 (1.0) ,.001Philtrum ranking at T5, mean (SD) 3.5 (0.9) 2.8 (0.7) ,.001Vermilion ranking at T5, mean (SD) 3.6 (0.9) 2.9 (0.8) ,.001Total dysmorphology score at T5, mean (SD) 14.2 (5.0) 7.0 (3.8) ,.001

PFL, palpebral fissure length.a Bonferroni-adjusted significance level = 0.005.b Senior dysmorphologist examinations used for analysis.c Centers for Disease Control and Prevention percentiles.

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The total dysmorphology score hasproven to be a useful anddiscriminating tool in evaluatingindividuals for potential FASD(Table 4). Figure 2 reveals thetrajectories of weight, OFC, anddysmorphology scores for childrenwith FASD and those without FASD atage 5. Children with FASD weighedless and demonstrated smaller OFCsat all time points. The children withFASD at age 5 also displayedsignificantly higher dysmorphologyscores throughout early life comparedwith those children without FASD.ROC analysis was performed toquantify the level of discriminationprovided by the dysmorphology scoreby time period. The analysis revealedthat the area under the curve (AUC)(discrimination value) was 0.772 at

T1 (95% confidence interval [CI]:0.695–0.848), 0.777 at T2 (seebelow), and 0.839 at T3 (95% CI:0.705–0.849), each of which wasstatistically significant (P , .001).The ROC value at 9 months (T2) isillustrated in Fig 3, and the AUC of0.777 (P , .001; 95% CI:0.705–0.849) is both statisticallysignificant and robust in light of otherfindings at T2 and later time periods.Data used to classify each of the

specific FASD diagnosesindependently are illustrated in Fig 4.This classification reveals that thedysmorphology score clearlydiscriminates between children withFASD and those without FASD at9 months of age because each of thespecific FASD diagnostic group linesbecome separated by totaldysmorphology score alone.Moreover, the total dysmorphologyscore was also highly discriminating

TABLE 4 Dysmorphology Scoring System (aWeighted Score Based on Analysis ofthe Frequency of Growth Restrictionand Minor Anomalies in 370 ChildrenWith FAS)

Feature Score

OFC #10% 3Growth deficiencyHeight #10% 2Weight #10% 1

Short PFL (#10%) 3Smooth philtrum 3Thin vermilion 3Hypoplastic midface 2Epicanthal folds 2Decreased IPD or ICD (#25%) 2Flat nasal bridge 2Altered palmar crease 2Fifth-finger clinodactyly 2Long philtrum ($90%) 2Anteverted nares 2Camptodactyly 2Ptosis 1“Railroad track” ears 1Heart murmur or confirmed CHD 1Strabismus 1Limited elbow supination 1Hypoplastic nails 1Prognathism 1Hypertrichosis 1Total possible score 41

Adapted from Hoyme HE, Kalberg WO, Elliott AJ, et al.Updated clinical guidelines for diagnosing fetal alcoholspectrum disorders. Pediatrics. 2016;138(2):e20154256.CHD, congenital heart disease; ICD, intercanthal distance;IPD, interpupillary distance; PFL, palpebral fissure length.

FIGURE 2Weight, OFC, and total dysmorphology score over time.

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between children diagnosed with FASand those without FASD from T1 toT5 (Fig 4, Supplemental Table 6).These data indicate that making anydiagnosis of FASD versus non-FASDat 9 months of age throughdysmorphology score alone is morestrongly supported than doing so atan earlier age. Additionally, data fromthe post hoc analysis in SupplementalTable 6 also support this finding. AtT3 (18 months), children with FASare significantly discriminated fromboth those without FASD and thosewith ARND on the dysmorphologyscore. Furthermore, at T4 (42months), the dysmorphology scorealso discriminated children with PFAS

from those without FASD. Finally, thepost hoc analysis (SupplementalTable 6) reveals that the differencesbetween each of the specific FASDdiagnoses are significant at T5(60 months).

BNBAS-3 Results

BNBAS-3 data at 6 weeks wereexplored to see if self-regulationwould be lower for infants exposed toalcohol during pregnancy. Infantswhose mothers were abstinent duringpregnancy were compared withinfants whose mothers drank duringthe first trimester of pregnancy. Thiscomparison revealed significantdifferences on the examiner’s

emotional response variable betweenchildren who were exposed to alcoholduring the first trimester ofpregnancy and those who were notexposed. There was also a significantdifference between the children whowere exposed and the children whowere unexposed on the cost ofattention and examiner facilitationvariables only (SupplementalTable 7).

Scores From the BSID-III and theKABC-II

Cognitive scores from the BSID-IIIwere analyzed on the basis of theassigned FASD diagnostic categoriesat T5; they began to differentiateamong the groups between 9 and18 months of age (Fig 5), especiallythose with FAS. The BSID-III did notdiscriminate among specific FASDdiagnostic groups in a clinicallyinterpretable way at any age(although the ROC analysis revealedsignificant discrimination [P = .003]of FASD versus non-FASD at18 months [AUC = 0.628; 95% CI:0.544–0.711]). By T5, when assessedby using the KABC-II, the variousFASD groups continued to showincreasing decline in overall cognitiveabilities, as would be expected. Thechildren with FAS were the mostdifferent from subjects without FASD(Table 5). Additional BSID-III testingresults are presented in SupplementalTable 8 for all testing domains at eachtime period by diagnostic category.Significant differences amongdiagnostic categories began toemerge over T3 (18 months) and T4(42 months).

KABC-II Scores Compared byDiagnostic Categories at 60 Months

The KABC-II overall MPI globalscores, the simultaneous visualprocessing scores, and the learningscores were significantly lower forchildren with FAS, PFAS, and ARNDwhen compared by ANOVA withthose for the children who did nothave FASD (Table 5). Pairwisedifferences (individual diagnostic

FIGURE 3ROC analysis: AUC for accuracy of the total dysmorphology score in discriminating children withFASD from children without FASD at T2 (9 months of age) evaluation.

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groups), were also significantly lowerfor each of the 3 FASD diagnosticgroups than for those without FASDfor global, simultaneous visualprocessing, and learning percentileranks. Any percentile score equal toor less than the eighth percentilewould place the child’s skills $1.5SDs from the mean. All global andvisual processing scores fell .1.5 SDsbelow the mean. The percentile-rankmean scores on the MPI and visualprocessing subtests range from 2.5%to 6.2%, which fall in the borderlinerange of ability for children diagnosedwith FAS, PFAS, and ARND. Thelearning domain scores were alsosignificantly lower for children withFASD, although the percentile scoresfell in the average range. Interestingly,

however, the short-term memoryscores were not significantly differentbetween children who were affectedand those who were not.

DISCUSSION

This study reveals the accuracy ofusing dysmorphology assessments forFASD diagnostic purposes in childrenunder the age of 3, especially inconjunction with appropriatebehavioral evaluations. Suchassessments progressively discriminateamong specific FASD diagnostic groups,from 18 to 60 months (when theKABC-II can discriminate each of theFASD diagnostic groups from oneanother). These early signs frombehavioral testing reveal significant

potential, especially when coupled withexpert dysmorphology evaluations, forguiding surveillance of children whomay be at risk for a specific FASDdiagnosis because of prenatal alcoholexposure.

Our data indicate that dysmorphicfeatures differentiate betweenchildren with FASD and unaffectedchildren as early as 9 months of age,although children with FAS who areseverely affected can be identifiedearlier with a significant degree ofprobability.36,37 Data from thedysmorphology examinations revealthat the specificity of facial featuresobserved in FAS and PFAS beginsto differentiate among diagnosticcategories within the FASDcontinuum at 9 months but do somost clearly from 18 monthsonward. Growth restriction, a clearcriterion needed for a diagnosis ofFAS, is evident at 9 months as well,if not before.

Assessment of early behavioral anddevelopmental milestones and ROCanalysis revealed significantdevelopmental differences betweenchildren with FASD and those withoutFASD between 18 and 42 months ofage. The results of the BNBAS-3 at T1revealed that infants prenatallyexposed to alcohol have significantlymore difficulty maintaining a state ofattention (cost of attention). Infantswho are frailer or those who havea known developmental issue mayhave greater difficulty maintaininga state of attention.29 When an infanthas such difficulty, the clinician mayobserve shallow or irregularbreathing; motor disorganization andexhaustion displayed by flailing,hyper- or hypotonicity, jerkiness, orcomplete shut down into a sleepingstate; or state overload displayed bycrying, hiccups, yawns, regurgitating,or gagging. When an infant exhibitsthese traits, the examination becomesmore difficult to complete or facilitate(examiner facilitation), and theexaminer may experience more stress

FIGURE 4Total dysmorphology score over time by diagnosis at 60 months (5 years); error bars:6 1 SE; N = 94(total number of children seen at all 5 time points); repeated measures analysis, within subjectseffect, time: F = 24.263, P , .001; repeated measures analysis, within subjects effect, time 3 group:F = 2.370, P , .002; repeated measures analysis, between subjects effect, group: F = 21.338, P ,.001; Mauchly’s test of Sphericity has been violated: x2(9) = 17.118, P = .047.

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when conducting the assessment(examiner’s emotional response).

Children who were prenatallyexposed to alcohol did not score ashighly on the KABC-II (MPI globalscore) at 60 months and had the mostdifficulty in the visual processing

subtests. Conceptual thinking andoverall cognitive deficits were reported

in the earliest studies of children with

FASD.38,39 Although children who were

affected scored significantly lower on

the learning cluster, their scores were

still in the average range.

Attrition of 44 children because ofincomplete data (of 199 entering theevaluation protocol) did not skew theresults. There were no statisticaldifferences (P , .05) in height,weight, OFC, total dysmorphologyscore, or BSID-III cognitive percentileat T3, T4, or T5 among those witha diagnosis of FASD or non-FASD whowere discussed at case conferenceand those excluded because ofinsufficient data or not beingassessed at T5. Of the 44 childrenwho were excluded from analysis, 23were discussed in detail ata multidisciplinary case conference at60 months of age and determined tohave insufficient data for finalanalysis in the study. Eighteen weredetermined to have insufficient databecause of the lack of testing (KABC-II), and none were found to haveinsufficient data because of a lack ofalcohol exposure information. Fivehad insufficient data because bothtesting and alcohol exposureinformation were missing. Twenty-one individuals were not evaluated bythe dysmorphologists at T5. Of the 21not evaluated at T5, 9 were lastassessed at T4, and 12 were lastassessed at T3.

Other investigators previously haveattempted to determine features inearly infancy that are most predictiveof FASD as the child with alcoholexposure grows older. Coles et al40

used neonatal microcephaly (OFC lessthan the fifth percentile), pre- orpostnatal growth deficiency, and level

FIGURE 5Cognitive percentile scores over time; error bars: 6 1 SE; the BSID-III was used in T1 to T4; the KABC-II was used in T5; N = 57 (total number of children seen at all 4 time points); repeated measuresanalysis, within subjects effect, time: F = 8.687, P , .001; repeated measures analysis, within subjectseffect, time3 group: F = 1.340, P = .198; repeated measures analysis, between subjects effect, group: F =0.174, P = .971; Mauchly’s test of Sphericity has been violated: x2(5) = 22.736, P , .001.

TABLE 5 KABC-II Global Percentile Rank, KABC-II Simultaneous or GV Percentile Rank, and KABC Sequential Number Recall or GSM Perentile RankCompared by Diagnostic Groups

FAS(n = 34)

PFAS(n = 13)

ARND(n = 18)

Not FASD(n = 64)

P

Mean (SD) Mean (SD) Mean (SD) Mean (SD)

KABC-II global percentile rank 4.6 (4.8) 6.2 (10.2) 6.0 (6.6) 19.1 (18.5) ,.001a,b,c

KABC-II simultaneous or GV percentile rank 2.5 (3.8) 5.1 (9.7) 2.7 (3.0) 16.0 (20.7) ,.001a,b,c

KABC-II sequential or GSM percentile rank 15.9 (17.6) 20.5 (18.7) 18.4 (16.0) 25.6 (22.0) .12KABC-II learning or GLR (Atlantis) percentile rank 29.2 (26.1) 23.1 (19.7) 30.7 (22.4) 50.4 (26.3) ,.001a,b,c

GLR, long-term storage and retrieval; GSM, short term memory; GV, visual processing.a Post hoc comparisons are significantly different between FAS and not FASD.b Post hoc comparisons are significantly different between PFAS and not FASD.c Post hoc comparisons are significantly different between ARND and not FASD.

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of self-reported maternal alcohol useduring pregnancy to predict whichinfants at 6 or 12 months would be athighest risk for developmental delay.Stoler and Holmes41 employeda standardized facial assessmentscale to attempt to differentiatenewborns exposed to alcohol fromnewborns not exposed to alcohol ina blinded fashion. The facialassessment differentiated the groupsto some extent; however, individualdiagnoses were not assigned anddevelopmental follow-up was notattempted. Thus, the predictive valueof their facial assessment scale interms of developmental outcome inindividual children with alcoholexposure was not evaluated. Carteret al42 demonstrated that growthtrajectory in infancy and childhood isa marker of which heavily alcohol-exposed infants are at greatest risk ofcognitive developmental deficits, withthose displaying prenatal growthrestriction, persistent postnatally, atgreatest risk. Mesa et al43 recentlypublished results of a study in whichcardiac-orienting responses wereused as an early scalable biomarker ofalcohol-related neurodevelopmentalimpairment. The study revealed thatthe cardiac-orienting response at6 months was more predictive ofdevelopmental delay on the 12-monthBSID-III testing than the 6-monthBSID-III score.43 Although furtherwork is needed to determine thelong-term predictive accuracy of thistechnique, cardiac-orientingresponses may be an early and

straightforward way to determineindividual risk for laterdevelopmental delay.

Although diagnoses at the moresevere end of the FASD continuummay be suspected in early infancy, noaccepted diagnostic criteria forinfants and preschool-aged childrenwith FASD currently exist. Thus, suchdiagnoses are, by definition,preliminary until morecomprehensive neurobehavioraltesting can be accomplished whenchildren reach school age. However,lack of defined and accepteddiagnostic criteria for FASD in infancyshould not deter referral of infantsexposed to alcohol for appropriatediagnostic services. Children withprenatal alcohol exposure (especiallythose demonstrating developmentaldelay or behavioral concerns or thosewho are in foster care) should beevaluated at any age. Even withouta definitive FASD diagnosis, suchchildren may benefit from specificinterventions and therapies.

CONCLUSIONS

Although any child with prenatalalcohol exposure falls into an at-riskcategory for developmentaldisabilities, in the current study, wehave established that determinationof a diagnosis within the FASDcontinuum is possible earlier inchildhood than has previously beenappreciated. Assessment ofa combination of growth, dysmorphic

features, and neurobehavioralcharacteristics allows for accurateidentification of most children withFASD as early as 9 to 18 months.

ABBREVIATIONS

ANOVA: analysis of varianceARND: alcohol-related

neurodevelopmental disorderAUC: area under thecurveAUDIT: Alcohol Use Disorders TestBNBAS-3: Brazelton Neonatal

Behavioral AssessmentScale

BSID-III: Bayley Scales of InfantDevelopment, ThirdEdition

CI: confidence intervalCoFASP: Collaboration on Fetal

Alcohol SpectrumDisorder Prevalence

FAS: fetal alcohol syndromeFASD: fetal alcohol spectrum

disorderKABC-II: Kaufman Assessment

Battery for Children,Second Edition

MPI: mental processing indexOFC: occipitofrontal (head)

circumferencePFAS: partial fetal alcohol

syndromeROC: receiver operating

characteristicT1: time point 1T2: time point 2T3: time point 3T4: time point 4T5: time point 5

Ms Kalberg is a co–principal investigator for the Oxnard Foundation–funded portion of this project and conceptualized and designed the study, helped design the

neurodevelopmental assessment protocol for enrolled infants and children, drafted the initial manuscript, and serves as the first author; Dr May is the principal

investigator of the National Institute on Alcohol Abuse and Alcoholism–funded studies in South Africa on which this article is based and substantially contributed to

the conception and design of the study as well as to the analysis and interpretation of data gathered and revised the manuscript critically for important intellectual

content, including all statistical analyses and epidemiological designs and analyses; Mr Buckley and Ms Hasken make up the data analysis group for the fetal

alcohol spectrum disorders team collaboration and supervised the acquisition, storing, and analysis of sensitive subject data, produced the tables and figures for

the manuscript, and revised the manuscript critically for important intellectual content; Ms Marais and Ms De Vries are the local South African project managers of

the present longitudinal cohort study and substantially contributed to the conception and design of the study as well as to the acquisition, analysis, and

interpretation of data and revised the article critically for important intellectual content; Drs Bezuidenhout, Manning, Robinson, Adam, and Derek B. Hoyme

substantially aided in the conception and design of the study, extensively contributed to data acquisition by providing dysmorphology examinations of all children in

the current study, extensively contributed to the analysis and interpretation of data by assigning final diagnoses to all subjects in multidisciplinary case

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conferences throughout the project, and revised the article critically for important intellectual content; Drs Parry and Seedat are the South African coinvestigators

of the National Institute on Alcohol Abuse and Alcoholism–funded studies on which this article is based and actively participated in the conception and design of the

study (including providing critical input about and liaison with the local South African communities in which subjects were recruited), participated in the vital

analysis and interpretation of data, and revised the article critically for important intellectual content; Dr Elliott assisted with the design of the current

investigation (specifically with substantial planning of the neurodevelopmental assessment protocol for infants and children in the study), trained the South African

staff in the administration of the neurodevelopmental tests performed, participated in the analysis and interpretation of the neurodevelopmental data gathered,

and critically revised the manuscript for important intellectual content; Dr H. Eugene Hoyme is a coprincipal investigator for the Oxnard Foundation–funded portion

of the current study and conceptualized and designed the study, analyzed and interpreted the growth and dysmorphology data acquired, reviewed the manuscript

critically for important intellectual content, and performed the final edits of the manuscript; and all authors approved the final manuscript as submitted and agree

to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated

and resolved.

DOI: https://doi.org/10.1542/peds.2018-2141

Accepted for publication Sep 12, 2019

Address correspondence to H. Eugene Hoyme, MD, Sanford Children’s Genomic Medicine Consortium, Sanford Health, 1305 W 18th St, Route 6744, Sioux Falls, SD

57117-5039. E-mail: gene.hoyme@sanfordhealth.org

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2019 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

FUNDING: Funded by National Institute on Alcohol Abuse and Alcoholism grants R01 AA11685 and R01/UO1 AA01115134. Funding was also provided by the Oxnard

Foundation (Newport Beach, CA). Funded by the National Institutes of Health (NIH).

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

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