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Customized growth charts: rationale, validationand clinical benefits

Jason Gardosi, MD, FRCOG; Andre Francis, MSc; Sue Turner, BSc, RM; Mandy Williams, MSc, RM

ccurate standards for antenatal

Appropriate standards for the assessment of fetal growth and birthweight are central togood clinical care, and have become even more important with increasing evidence thatgrowth-related adverse outcomes are potentially avoidable. Standards need to be evi-dence based and validated against pregnancy outcome and able to demonstrate utilityand effectiveness. A review of proposals by the Intergrowth consortium to adopt theirsingle international standard finds little support for the claim that the cases that itidentifies as small are due to malnutrition or stunting, and substantial evidence that thereis normal physiologic variation between different countries and ethnic groups. It is

A surveillance of fetal growth areessential for early recognition of the fetuswho is at risk in an unfavorable intra-uterine environment. Standards are alsoimportant after delivery, to assess the ne-onate’s risk of immediate and long-termmorbidity and for audit, benchmarking,and epidemiologic investigations.

possible that the one-size-fits-all standard ends up fitting no one and could be harmful ifimplemented. An alternative is the concept of country-specific charts that can improvethe association between abnormal growth and adverse outcome. However, such stan-dards ignore individual physiologic variation that affects fetal growth, which exists in anyheterogeneous population and exceeds intercountry differences. It is therefore morelogical to adjust for the characteristics of each mother, taking her ethnic origin and herheight, weight, and parity into account, and to set a growth and birthweight standard foreach pregnancy against which actual growth can be assessed. A customized standardbetter reflects adverse pregnancy outcome at both ends of the fetal size spectrum andhas increased clinicians’ confidence in growth assessment, while providing reassurancewhen abnormal size merely represents physiologic variation. Rollout in the UnitedKingdom has proceeded as part of the comprehensive Growth Assessment Protocol(GAP), and has resulted in a steady increase in antenatal detection of babies who are at riskbecause of fetal growth restriction. This in turn has been accompanied by a year-on-yeardrop in stillbirth rates to their lowest ever levels in England. A global version of customizedgrowth charts with over 100 ethnic origin categories is being launched in 2018, and willprovide an individualized, yet universally applicable, standard for fetal growth.

Key words: birthweight, customized chart, fetal growth, GROW, LGA, maternal size,perinatal, SGA, stillbirth

One Size Does Not Fit AllA series of recent publications by theIntergrowth 21 project promote the useof a single universal standard for fetalgrowth and birthweight.1-3 The datawere derived from educated, affluent,clinically healthy women with adequatenutritional status in 8 countries. Theauthors call the standard “multiethnic”because it included different pop-ulations, with the implication that it istherefore suitable to be applied to mul-tiple ethnic groups. The authorsconsidered differences to be marginaland likely to be due to socioeconomic orother nonphysiologic factors and arguedfor the adoption of a single, prescriptive,universally applicable standard.

At the time of writing, there has stillbeen no evidence presented to suggestthat Intergrowth improves the identifi-cation of fetuses or neonates at anincreased risk of adverse outcome. To the

From the Perinatal Institute, Birmingham, UK.

Received Nov. 8, 2017; revised Dec. 4, 2017;accepted Dec. 6, 2017.

All authors are employees of the PerinatalInstitute, a not for profit organization whichderives income from the provision of supportservices to healthcare organizations, includingthe ‘Growth Assessment Protocol’ reviewed inthis article.

Corresponding author: Jason Gardosi, MD.jgardosi@perinatal.org.uk

0002-9378/$36.00ª 2017 Elsevier Inc. All rights reserved.https://doi.org/10.1016/j.ajog.2017.12.011

contrary, there is evidence of significantvariation between different populationsand individuals and mounting evidenceagainst a one-size-fits-all approach:First, their “multiethnic” concept ischallenged by studies that have shownsubstantial ethnic variation, even inselected low-risk populations, that sup-port the notion that observed differencesare physiologic, not pathologic. Thisevidence has included analyses of data-bases of birthweight4-6 and prospectiveevaluation of growth curves in differentethnic groups in the National Institute ofChild Health and Human Developmentfetal growth studies.7

Second, there is mounting evidenceagainst the utility and safety of the

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Intergrowth standard by investigatorswho applied it to their own local popu-lation.8-10 The concept of a universalstandard has also been challenged fromthe perspective of developmental originsand fetal adaptive responses, becausemany biologic and cultural factors caninfluence fetal growth that should not beviewed as abnormal.11

The recently published World HealthOrganization (WHO) standard forfetal growth used similar methods tothat of Intergrowth, selecting low-riskpregnancies from 10 countries.12 Theyfound differences in growth betweencountries and between individualmaternal characteristics such as height,weight, and parity and concluded that

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FIGURE 1Effect of mean birthweight shift on SGA/LGA rate

Proportion of cases at SGA/AGA or AGA/LGA limit that need to be reclassified, in a population with a

birthweight distribution with standard error 382.6 g, if average birthweight varies by 200 g (64%

reclassified) and 400 g (90% reclassified), respectively (see examples in text). Adapted from Gardosi

J, Francis A. A customized standard to assess fetal growth in a US population. Am J Obstet Gynecol

2009;201:25.e1-7.28 With permission.

AGA, appropriate-for-gestational age; LGA, large-for-gestational-age; SGA, small-for-gestational-age.

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such variation needs to be taken intoaccount.

Intergrowth’s own tables showedintercountry differences, despite theirselection of low-risk, well-nourishedmothers. For example, in Table 1 in thearticle of Villar et al,2 the term birth-weight for mothers from Italy is 3.3 kgand from the United Kingdom 3.5 kg,which is a 200-g difference that is unlikelyto be explained by variation in nutritionalstatus or socioeconomic deprivation be-tween 2 Western European countries. Inany average term birthweight distribu-tion, a shift by 200 g results in >60% ofsmall-for-gestational-age (SGA) or large-for-gestational-age (LGA) cases beingmisclassified (Figure 1). For Indianmothers, the mean Intergrowth birth-weight was 2.9 kg, which is 400 g less thanthe average for their whole population(3.3 Kg); a shift by 400 g would reclassify90% of SGA or LGA cases (Figure 1).

A multinational study of 1.2 millionterm pregnancies by Francis et al,13

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published in this issue of AJOG,confirmed significant differences inmeanbirthweights and hence SGA rates be-tween ten country cohorts using theIntergrowth birthweight standard, andshowed that these were not due to path-ological factors as represented by stillbirthrates; instead, the different SGA ratesmerely reflected physiological variation,throwing further doubt on the utility ofIntergrowth as an international standard.The potential adverse effect of applying

the wrong standard in internationalcomparisons becomes all too apparent ina recent publication in which the Inter-growth standard was applied to low andmiddle income country data from theChild Health Epidemiology ReferenceGroup (CHERG).14 They reported that34% of births in India were SGA (<10thIntergrowth percentile) while only 5%and 6% were SGA in their Eastern Asiaand Northern Africa populations,respectively. Such high SGA rates areunlikely to be explained bymalnourished,

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stunted, or socioeconomically disadvan-taged pregnancies in India; and the lowSGA rates in Northern Africa are unlikelyto be explained by anything other thanthat the standard ismisleading. Applied atlocal level, such findings may result inunnecessary antenatal investigations andinterventions, postnatal overfeeding tocompensate for presumed growthrestriction, parental anxiety, and thepossibility that real SGA and its associatedrisk is ignored; conversely, in populationsthat are assigned a low SGA rate, thestandard will put babies at risk becausereal SGA may be missed.

Defining the Growth PotentialCustomized charts adjust for constitu-tional or physiologic variation andexclude pathologic factors that affectgrowth, thereby defining an optimizedstandard that represents the growthpotential of each individual fetus.15,16 Asa result, they improve the prediction ofbirthweight in an uncomplicated preg-nancy and improve the identification ofabnormal growth.

An alternative method for definingfetal growth potential is the DetereRossavik model of IndividualizedGrowth Assessment to specify expectedthird-trimester size trajectories and birthcharacteristics from second-trimestermeasurements of several anatomicparameters.17 This approach seeks toaddress the problems that are inherentwith a population standard by using eachfetus as its own control. Analysesrecently have been extended to a largerdatabase of 119 longitudinally scannedpregnancies with normal neonatal out-comes,18 but the model has not beenapplied widely in clinical settings. Oneconceptual concern19 is that the fetuscould already be affected by intrauterinegrowth restriction in the secondtrimester, which is known to increase therisk of adverse outcomes early20 or late21

in pregnancy. Use ofmeasurements fromsuch a fetus could project an individualcurve that does not reflect the truegrowth potential and, by normalizing thepathologic factors, be less likely to allowidentification of abnormal growth.

In the customized model, the variablesfor adjustment are derived from

FIGURE 2Comparison of proportionality curves

Derived from Hadlock FP, Harrist RB, Martinez-Poyer J. In utero analysis of fetal growth: a sono-

graphic weight standard. Radiology 1991;181:129-33; Stirnemann J, Villar J, Salomon LJ, et al.

International estimated fetal weight standards of the INTERGROWTH-21st Project. Ultrasound Obstet

Gynecol 2017;49:478-86; and Kiserud T, Piaggio G, Carroli G, et al. The World Health Organization

Fetal Growth Charts: a multinational longitudinal study of ultrasound biometric measurements and

estimated fetal weight. PLOS Med 2017;14:e1002220, according to method described previously.16

WHO, World Health Organization.

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birthweights of normally formed fetuseswho were delivered at the end ofuncomplicated pregnancies at term. Thephysiologic variables that significantlyaffect birthweight are consistent in manycohort studies and are quantified throughmultivariable analysis: fetal sex, maternalheight, weight in early pregnancy, parity,and ethnic origin. Adjustment formaternal height and weight is madewithin normal body mass index (BMI)limits only.16 Pathologic factors that areknown at the beginning of pregnancyinclude hypertension, diabetes mellitus,smoking, and low and high BMI. Socialdeprivation may appear in the univariateanalysis but does not tend to remain sig-nificant after adjustment for other fac-tors, such as smoking and abnormalBMI.22 The model adjusts for the physi-ologic but not pathologic variables, andresults in a constant that represents anexpected optimal birthweight at the endof an uncomplicated pregnancy.

Sets of coefficients have now beenderived from suitable databases frommore than 25 countries and publishedfor populations in the UnitedKingdom,16 Sweden,23 Australia,24 NewZealand,25 France,26 Spain,27 UnitedStates,28 and Ireland,29 with others inpreparation. International comparisonshave demonstrated remarkable between-country similarities in the growth po-tential that a baby of a standard mothercan expect to reach at the end of anuncomplicated pregnancy. For example,a nulliparous mother of (Anglo-) Euro-pean origin with a height of 163 cm andearly pregnancy weight of 64 kg would,after an uncomplicated pregnancy, beexpected to give birth to a baby whoweighs 3453 g in the United States, 3456g in the United Kingdom, 3464 g inAustralia, and 3464 g in New Zealand.28

In practice, maternal characteristicsare entered into a software program(GROW; Gestation Network; Birming-ham, UK, www.gestation.net) to calcu-late an individually adjusted termoptimal weight for 40.0 weeks (280 days)gestation. This predicted weightendpoint is then combined with a stan-dard proportionality function16 to pro-vide a gestation-related optimal weight(GROW) curve. We used the standard

Hadlock estimated fetal weight (EFW)curve30 and converted it from a fetalweight-by-gestation curve to a percent ofterm weight-by-gestational age curve,with the Hadlock 40-week weightassigned 100%. This allows any termoptimal weight to be substituted for100%, thereby specifying the expectedweight for gestational age trajectory(GROW curve) up to that predictedendpoint. We have since compared theproportionality curve based on Had-lock30 with ones based on the 2 recentlypublished EFW curves by Intergrowth3

and WHO.12 As Figure 2 shows, the re-sults are remarkably similar, despite thefact that the underlying curves originatefrom different studies, and suggest thatthe proportionality method is a robustway to outline the growth trajectory tothe term optimal weight.

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The use of a fetal-, rather than aneonatal, weight-based standard helpsto highlight the association betweenfetal growth restriction and pretermbirth16,31 because the standard isderived from normal term pregnancies;the prevalence of SGA in pretermbabies tends to be hidden by the use ofa neonatal curve that is derived frompreterm birthweights that are abnormalby definition. The normal rangearound the GROW curve is derivedfrom the standard error of the multipleregression model and the term optimalweight that together give a coefficientof variation (CV) of 11%; the 90th and10th percentile limits are then reachedby �1.28�CV, or �14% of the termoptimal weight.16

It is worth noting that the use ofterm weight with a fetal weight-derived

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FIGURE 3Birthweight prediction

R square of model, with gestational age-controlled residuals of birthweight within mid tertile of the

distribution. Stepwise addition of variables (sex, parity, ethnicity, maternal height, maternal weight).

Data source: West Midlands singleton births 2009-2013; n¼131,570.

mat, maternal.

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proportionality function makes theGROW curve a standard that can beapplied to assess fetal as well asneonatal weight.

ValidationOne test of the customized method is toassess the correlation between predictedand actual birthweight in normal preg-nancy, according to the number ofphysiologic variables entered. Themultivariable regression provides an R2

of the model; although this has beenshown to increase by 50% when adjust-ment is made for maternal variables(from R2¼0.18 to 0.29),32 the overallcorrelation is still poor. However,because the model is not designed topredict pathologic factors, but optimalweight free from pathology, it is moreappropriate to assess the additionalcontribution of each physiologic variablewithin the mid tertile of the distribution,where most growth-related pathologicfactors are likely to have been excluded.33

This analysis shows that the R2 valuerises stepwise with each variable entered,to an R2 of 0.76, which indicates that,

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together, these factors account for 76%of normal variation within this centralpart of the birthweight distribution(Figure 3).More clinically relevant is the effect of

adjustment of the standard on thecut-offs for LGA and SGA. The effect ofcustomization at the LGA end has beenexamined by relatively few studies todate. Larkin et al,34 Cha et al,35 andGonzalez et al,36 who studied a cohortwith diabetes mellitus, all found that thecustomized model identified previouslyunrecognized LGA populations whowere at risk of intrapartum morbidity.Sjaarda et al37 found hitherto unidenti-fied pregnancies at risk because of LGA ifthe model was adjusted to excludematernal weight. Constantine et al38

compared fully customized withpartially customized LGA that wasadjusted for ethnicity and sex only andfound both methods to be associatedsimilarly with adverse outcomes; how-ever, primary outcome cases (a com-posite of neonatal outcomes that areassociated with fetal overgrowth andgestational diabetes mellitus) had a

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significantly higher average percentileand a 50% higher LGA rate (19.3% vs13.2%) when the fully customized LGAstandard was used.38

At the SGA end of the spectrum, anumber of studies have shown thatcustomized SGA was associatedmore closely with pathologic outcomesthan various local or national stan-dards.23,39-44 Typically, customizedassessment resulted in an additionalgroup being identified as SGA, whichwasalso associated significantly withincreased perinatal mortality risk. A sys-tematic review found that both custom-ized and population-based SGA hadhigher rates of adverse outcomes, but thereported point estimates for customizedSGA tended to be higher and, in theinstance of fetal death, were more thandouble that for population-based SGA,albeit with overlapping 95% confidenceintervals (95%CI): customized, 7.8 (95%CI, 4.2e12.3), vs population based, 3.3(95% CI, 1.9e5.0).45

Application of the fetal weightebasedproportionality curve in the optimalitymodel, as explained earlier, results inmore preterm babies being identified asSGA.31,46,47 Hutcheon et al48 suggestedthat this is the main advantage of thecustomized growth chart, and adjust-ment for individual variation had littleadditional effect. Using a Swedish dataset,they compared a customized model withthe Hadlock curve adjusted for sex onlyand reported similar relative risks of SGAfor stillbirth and neonatal death. How-ever, this conclusion has been questionedon several grounds.32,33 Although theauthors claimed to use our originalmethod for customizing percentiles, theirmodel adjusted for maternal size only inwide categories rather than continuousvariables, which would have blunted theeffect. They also did not identify andexclude pathologic factors to allowcustomized percentiles to reflect the fullgrowth potential. Even so, althoughrelative risk values were similar, theircomparative tables still suggest that5e10% more deaths were identified bytheir modified customization method.

Carberry et al49 looked at term birth-weight in an Australian cohort andfound no advantages in a customized

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SGA over a locally derived populationstandard. The study has added interestbecause it assessed outcome throughperinatal morbidity indices and neonatalbody fat with the use of air displacementplethysmography. However, informationon maternal and pregnancy characteris-tics for customization was based mostlyon maternal recall. In a large database inScotland, partial customization(maternal height and parity) wascompared with an unspecified popula-tion standard at term,50 and the in-vestigators found that this model did notimprove association of SGA with still-birth and infant death. It is uncertainwhether the results were affected by anabsence of maternal weight and ethnicityvariables or by the missing data onmaternal height. Also, the analysisused the Net Reclassification Index, thestatistical reliability of which has beenquestioned.51

Mikolajczyk et al52 analyzed WHOGlobal Survey data from 24 low- andmiddle-income countries and comparedthe association between pregnancy out-comes and SGA defined by either thestandard Hadlock fetal weight curve orthe use of the proportionality fetalweight equation,16 adjusted by country-specific average term birthweight, orstepwise increasing the adjustment up toa fully customized model including sex,maternal height and weight, and parity.The data posed challenges that includeddating of pregnancies, and maternalweight was obtained mostly at the end ofpregnancy or in labor. However, the in-vestigators showed clearly that adjust-ment by country average weight was themain improvement over the single(Hadlock) weight standard and thatadditional adjustment, even for sex ofthe neonate, added no demonstrableadvantages.

Analysis within Maternal SubgroupsIt is possible therefore that, in fetuseswho have survived to term, fetal growthdeficit is more subtle and not markedenough to demonstrate differences in thecohort as a whole, even if the method issound and all variables for custom-ization are available. Instead, their ben-efits become apparent with analysis of

the effect of customization on the con-stituent subgroups of any heterogeneousmaternity population.We undertook such analyses32 in the

same Swedish birth registry dataset asthat referenced above,23 applyingcustomized and uncustomized standardswith the same fetal weightebased pro-portionality curve. We first looked atparity and found customized SGA to bebetter aligned to perinatal mortality risk;the uncustomized standard showed anexaggerated SGA rate for nulliparouswomen that did not reflect a rise inmortality rate. Although first pregnan-cies can have more complications, suchas preeclampsia and prolonged labor,increased clinical awareness and appro-priate management should not have torely on defining more babies as SGA ifthey are not, and can lead to unnecessaryinvestigations and interventions.In the same study,32 we analyzed SGA

rates in 4 BMI groups (<20, 20-25,25-30, �30 kg/m2). Perinatal mortalityrates were directly proportional to BMI;SGA defined by customized percentilesalso increased with BMI and was well-aligned with the perinatal mortalitytrend. In contrast, uncustomized SGArates were statistically different from themortality risk, being very high in thinmothers and low in obese mothers. Thisfinding contradicts previously held as-sertions, which were based on data fromthe same Swedish register of births, thatobesity was protective of SGA.53 In fact,population-based percentiles obscurethe fact that a baby may be relativelysmall compared with its growth poten-tial. Application of the customizedstandard identifies that obese mothershave an increased risk of having agrowth-restricted baby.32,54

We also looked at maternal size groupspredefined according to height andweight, within a subgroup of pregnancieswith normal BMI (20-25 kg/m2; ie, sym-metrically small and largemothers).Here,the perinatalmortality ratewas similar forall groups, and customized SGA rateswere correspondingly similar; but thepopulation-based standard showed a highSGArate for smallmothers and a lowSGArate for large mothers and hence did notreflect the perinatal mortality trend.32

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We repeated this assessment after thepublication of the Intergrowth fetalweight standard,3 applying it to a previ-ously described English database22 usingstillbirth as the outcome. The resultsshow again good alignment betweenmaternal size groups and stillbirth riskwhen SGAwas customized but not whenthe Intergrowth standard is applied(Figure 4). The clinical implication isthat small mothers with normally smallbabies may be subjected to unnecessaryinvestigations, interventions, and anxi-ety and that large mothers are reassuredfalsely when being assessed with the useof a one-size-fits-all chart that does nottake individual variation into account.

Customized charts reduce false-positive diagnoses of SGA whenultrasound estimated fetal weight mea-surements are plotted on customized vsuncustomized fetal weight curves.55 Thisbecomes most apparent in our multi-ethnic population, a large proportion ofwhich are of South Asian origin. It was afrequent clinical observation that scanmeasurements that were plotted on theprevalent Hadlock EFW chart30 returnedmany SGA results. In ourWest Midlandsdatabase, 56% of these scans would notplot as SGA on the customized GROWchart. This group had the same risk forperinatal death as the non-SGA group(relative risk, 1.2; 95% CI, 0.5e3.0),which confirmed that an uncustomizedstandard applied in this subgroup resultsin the majority of cases identified as SGAare false positives.56

Clinical ApplicationThe use of customized percentiles isrecommended by the Royal College ofObstetricians and GynaecologistsGuidelines57 for the assessment ofbirthweight and antenatal surveillance offetal growth. Customized percentile cal-culators are freely available via theGestation Network (www.gestation.net)that is administered by the PerinatalInstitute and have been or are currentlyin use by over 300 clinicians and re-searchers in 30 countries. They can beapplied in case-by-case assessment ofneonatal weight or in spreadsheet formatto analyze whole databases for audit orresearch. A global version of the GROW

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FIGURE 4Maternal size, small-for-gestational-age and stillbirth risk

Stillbirth rate and smallness for gestational age according to Intergrowth-21st and GROW standards

equalized for<10th percentile cases by Intergrowth¼7.7%. Data source: West Midlands database

2009-2013; singleton, normally formed, n¼62,652. Maternal size groups defined in 4 weight and

corresponding height ranges to remain within body mass index range of 20-25 kg/m2: (1) small:

weight,<57 kg; height, 148e167 cm; (2) below average: weight, 57.0e60.3 kg; height, 153e171

cm; (3) above average: weight, 60.3e65.0 kg; height, 157e174 cm; (4) big: weight, �65.0 kg;

height, 161e180 cm.BMI, body mass index; GROW, gestation-related optimal weight; IG21, Intergrowth21; SGA, small for gestational age.

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percentile calculator was recentlyreleased and includes coefficients forover 100 ethnic or country of origingroups.

For antenatal surveillance, customizedGROW charts are produced at thebeginning of pregnancy, once the ex-pected date of delivery is confirmed bythe ultrasound dating scan. The chart iseither printed out at the beginning ofpregnancy or can be displayed electroni-cally, either as a stand-alone GROWapplication or integrated with the hospi-tal’s maternity information system. Itdisplays the calendar dates for each weekof gestation on the X axis and has 2 Yaxesfor plotting fundal height measurement

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in centimeters and for EFW in grams.Individual parameters (head circumfer-ence, abdominal circumference, femurlength) are not plotted because (1)there are no validated coefficients forindividual adjustment or customization,(2) EFWs are more meaningful for themother and clinician in the assessmentof small as well as large babies, and (3)accuracy of EFW and antenatal identifi-cation of SGA and LGA can be auditedthrough birthweight as a gold standard,whereas no such standards exist forindividual ultrasound measurement.Although abdominal circumference isthe main component in determiningEFW, the latter has been shown to be

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able to detect additional at-risk casescompared with abdominal circumfer-ence alone.58 Serial EFW measurementhas also been found to be as good as orbetter than serial abdominal circumfer-ence in the prediction of adverseoutcome.59

GROW charts provide not only theoptimal predicted birthweight endpointfor that pregnancy but also the slope ofthe normal growth curve that will leadto this point, together with upper andlower limits that can be set at 90th and10th or 95th and 5th percentiles. Theweight of the fetus at any point in thethird trimester can be assessed withinthe customized limits for that preg-nancy. In pregnancies with suspectedSGA and normal umbilical arteryDoppler, customized assessment of fetalsize was a better predictor of adverseoutcome than growth velocity.60 Yet,serial measurements are also importantand can be evaluated with reference tothe predicted customized slope of theGROW curve. The measurements maybe within normal limits; however, if thetrajectory is slower than that predicted,action in terms of further investigationsor expedited delivery has to beconsidered.61

Currently, the slope of the curve isassessed visually, but the application ismoving towards digital quantification.The concept of a fetus’ growth trajectory‘crossing percentile lines’ is insufficientbecause it ignores the time element (ie,the period over which the growth deficithas extended). In a serially scannedcohort of Dutch primiparous women,fetal weight gain was significantly slowerin pregnancies that required admission tothe neonatal intensive care unit (20 g/d)than if the pregnancy was uncomplicated(24 g/d).62 In time, there will be moreinformation on antenatal growth velocityand outcome on which to base recom-mendations, and the next version ofGROW will link growth trajectories thatare adjusted for each pregnancy withaction prompts and decision support.

GROW charts are provided as part ofthe Growth Assessment Protocol (GAP),a comprehensive program that includeshands-on and remote training sup-ported by e-learning, competency

FIGURE 5Detection of small for gestational age

Trend of antenatal detection rate of newborn infants with SGA birthweight (<10th customized

percentile). Baseline rates, GAP user average, and average for top ten performing units are shown.

GAP, Growth Assessment Protocol; GUA, GAP user average; SGA, small for gestational age.

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assessment, and evidence-based proto-col templates for local adaptation. In theUnited Kingdom, GAP has been imple-mented in just under 80% of hospitals(www.perinatal.org.uk/gap-uptake.aspx),generating customized charts for>600,000 pregnancies each year. Inthe Netherlands, the Royal MidwiferyAssociation has licensed a Dutch versionof GROW for their membership, andNew Zealand has recently commenced aMaternal Fetal Medicine Network andhealth ministry recommended nationalroll-out. Individual clinicians and in-stitutions in a number of countries havealso commenced implementation.

Antenatal Detection of SGAAlthough there has been progress withbiomarkers and uterine artery Dopplerto screen for preeclampsia and earlyonset intrauterine growth restriction(IUGR), the majority of growth restric-tion is late in onset, with the growth ofthe fetus outstripping placental functionand reserve, the prediction of which hasbeen poor.61 Therefore, the emphasis hasto be on surveillance and on raisingawareness of the importance of fetal riskcaused by IUGR. A fetus that is SGA bycustomized percentiles has a 7-foldincreased risk of intrauterine death.22

Surveillance protocols are based onearly pregnancy risk assessment, withalgorithms that identify 36% of ourpopulation as being at significantlyincreased risk of SGA and stillbirth.63

This leads to 2 main care pathways: (1)low risk, which in health systems withwell-established midwifery services ismonitored with serial fundal heightmeasurements, and (2) increased risk,which requires serial ultrasound scansthroughout the third trimester. Acontrolled study has shown that trainingin standardized fundal height measure-ment and plotting on customized chartssignificantly increased antenatal detec-tion of SGA and LGA fetuses whilereducing false-positive diagnoses.64

Detection of SGA in high-risk preg-nancies is proportional to the number ofthird-trimester scans, which are usuallyperformed only 2e3 times and only upto 34e36 weeks gestation, because ofchronic shortages in ultrasound

resources in the National Health Service(NHS).65 In a nonresearch environ-ment, a routine or indicated scan at36 weeks gestation has only a 36%chance to predict SGA birthweight,66

which is likely to be due to thefact that most customized i.e. non-constitutional SGA at term is due to lateonset IUGR.Antenatal detection of SGA has

been established as an auditable keyperformance indicator and is facilitatedby the GROW application. Trained staffenter details of the outcome of preg-nancy, and the software then calculatesthe customized birthweight percentileand referral, detection and falsepositive rates. The results are availablethrough automated local reports andprovide benchmarking and trend anal-ysis. The audit is not mandated, but itsuptake has increased steadily becauseclinicians and managers realize theadvantages of monitoring serviceimprovements.Maternity units are required to un-

dertake a baseline audit before imple-mentation of GAP and are oftensurprised how low their detection ratesare, averaging 18.7% (95% CI,

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16.8e20.5), which in fact is similar tohistoric published reports of 15e16% inlow-risk populations.67,68 Figure 5 shows,against this baseline, the quarterly trendin detection rates for the last 2 years inunits that have established routine post-natal audit. There was a gradual, overallrise to 42.0% (95% CI, 41.1e43.0),which represents a 2.5-fold increase frombaseline, and a more pronouncedimprovement to 56.0% (95% CI,53.0e58.9) for the top 10 performingunits. These centers can be characterizedas most engaged with the protocol,training, and audit program, whichhighlights that performance is effortrelated.

Software is also available to undertakemissed case audit, which facilitates morefocused and structured investigationsinto reasons that newborn SGA cases aremissed, such as a lack of referral, poorscan quality, or system issues such asshortages in ultrasound services or a lackof up-to-date protocols for surveillanceor management. A limitation of suchroutine audits is that it cannot evaluateinstances of growth restriction thatoccur without the fetus falling below theSGA cut-off limit.

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FIGURE 6Trend in stillbirth rates in England

Stillbirth rates (per 1000) in England: ONS.75 The rate remained similar over a 10-year period (2000,

5.26; 2009, 5.29) and averaged 5.35; the fall to 4.35 by 2016 following the implementation of the

GAP program represented a 19% drop (P<.01).

CI, confidence interval; GAP, Growth Assessment Protocol; ONS, Office of National Statistics.

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Reducing Avoidable StillbirthsThe effect of any composite interventionis difficult to assess as perinatal death,and other ‘hard’ outcome measures arerelatively rare. Randomized trials, usu-ally the gold standard, are not veryfeasible, (1) because of the large numbersrequired to have sufficient power, (2)because the relative simplicity of a ran-domized, controlled trial design is chal-lenged by the large learning component,competency assessment, and need toraise overall awareness; and (3) ran-domized assessment, individually or inclusters, requires clinical equipoise thatcannot be guaranteed if a method isalready recommended on the basis ofobservational evidence and clinicalguidelines, such as those in place fromthe Royal College of Obstetricians andGynaecologists.57

The relevant model therefore is“evaluation in practice,” which is arigorous before-and-after assessment ofthe impact of wide-ranging imple-mentation, as was undertaken in thesuccessful “back to sleep” campaign forsudden unexplained deaths in infancy69

and which was never investigated by a

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randomized, controlled trial. Stillbirthrates are a suitable measure of the effectsof such a program. Nine-tenths of fetaldeaths occur antenatally, and one-half ofall normally formed stillbirths (countedin the United Kingdom from 24 weeksgestation) are SGA, even after adjust-ment for delay between fetal death andassessment of weight at delivery,70,71

although an additional unknown num-ber are IUGR without being SGA.Traditionally, two-thirds of stillbirthsused to be categorized as “unexplained”and, by implication, unavoidable; how-ever, a new classification of ‘relevantconditions’ rather than ‘causes’ and in-clusion of a category of SGA defined bycustomized percentiles found that themajority of such unexplained deathswere in fact SGA and, by implication,IUGR.71 Confidential case reviews byindependent panels have furthermoreshown that, at least two-thirds of SGAdeaths are associated with substandardcare.72 Such findings helped to prioritizestillbirth as a potentially avoidableoutcome; they also led to better expla-nations given to grieving parents whowere trying to come to terms with their

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loss and assisted clinicians in planningsubsequent pregnancies and to improveantenatal services overall.

Customized charts are considered acentral component of this program,because they give clinicians more confi-dence when assessing whether the situ-ation is reassuring or calls for action.Fetal weights that plot as SGA or are ona slow trajectory on customized growthcurves are less likely to be consideredconstitutionally small, and manage-ment recommendations in nationalguidelines57 are further encouragementto adopt a proactive clinical approach.

According to the aforementioned ob-servations, it is estimated that up to two-thirds of normally formed stillbirths areSGA or IUGR and that two-thirds ofthese are considered to have had sub-standard care that was likely to havecaused or contributed to fetal death; thiswould make >40% of stillbirths poten-tially avoidable. Therefore, in healthsystems where one-half of pregnancieswith SGA or IUGR are identified ante-natally, a 20% reduction in stillbirthrates should be achievable with increasedawareness, education, and the appro-priate evidence-based protocols.

The Growth AssessmentProtocol (GAP)GAP was commenced in the WestMidlands, a health region with one ofthe highest perinatal mortality rates inthe United Kingdom. Its implementa-tion led to the first ever drop in still-birth rates to below the nationalaverage, and further analysis foundthat this reduction was confined topregnancies with SGA/IUGR.73 Subse-quently, implementation extended to 2additional health regions, whichtogether demonstrated a significantreduction in stillbirth rates, while theyremained the same in regions that didnot take up GAP.74 Although this wasan evaluation in practice rather than atrial, examination of Bradford Hillcausality criteria confirmed that thereduction in stillbirths was attributableto the implementation of GAP.74

Since then, there has been a nationalroll-out of the program and, to date,includes almost 80% of all Hospital

ajog.org Expert Reviews

Trusts and Health Boards across theUnited Kingdom. GAP has led to a year-on-year reduction in stillbirth rates (perthousand) in England to 4.35 by 201675,their lowest ever level, which representsa 19% drop from the preceding 10-yearaverage (2000e2009) of 5.35 (Figure 6).Scotland also implemented GAP in 12(86%) of its 14 Health Boards as part ofa nationally commissioned program,while also benefitting from an ongoingnational maternity quality improve-ment program; its own 10-year(2000e2009) average stillbirth rate of5.41 dropped similarly by 20% to 4.31by 2016.76

Ongoing work includes the develop-ment and provision of electronic toolsto facilitate routine audit, risk assess-ment, auto-plotting of measurements,and decision support, which promptevidence-based referral protocols andmanagement pathways. Hitherto coun-try specific, the global version ofcustomized antenatal GROW chartswith over 100 ethnic/country of origincategories will be launched in 2018 toprovide an individualized, yet univer-sally applicable, standard for fetalgrowth. -

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