Samarani et al. BMC Pediatrics(2020) ARCH ARTICLEOpen AccessComparative study between Fenton andintergrowth 21 charts in a sample ofLebanese premature babiesMarie Samarani1,2, Gianna Restom1,2, Joelle Mardini1,2, Georges Abi Fares1,2, Souheil Hallit1,3*†Marie-Claude Fadous Khalife1,2*†andAbstractBackground: Different charts are used to assess premature growth. The Fenton chart, based on prenatal growth,has been used in the neonates’ intensive care unit (NICU) of the Notre Dame des Secours University Hospital toassess premature newborns’ development. Intergrowth21 is a new multidisciplinary, multiethnic growth chart betteradapted to premature growth. Our objective was to compare both charts Fenton and Intergrowth21 in order toimplement Intergrowth in our unit.Methods: We analyzed 318 files of premature babies born who were admitted to the NICU from 2010 till 2017.Anthropometric data (weight, height and head circumference) converted to percentiles was filled on both chartsfrom birth till 1 month of age.Results: The results of the linear regression, taking the weight at birth as the dependent variable, showed that theFenton scale (R2 0.391) would predict the weight at birth better than the Intergrowth 21 scale (R2 0.257). Thesame applies for height and cranial perimeter at birth when taken as dependent variables. When considering theweight and height at 2 weeks, the results showed that the Intergrowth 21 scale would predict those variablesbetter than the Fenton scale, with higher R2 values higher in favor of the Intergrowth 21 scale for both weight(0.384 vs 0.311) and height (0.650 vs 0.585). At 4 weeks, the results showed that the Fenton scale would predictweight (R2 0.655 vs 0.631) and height (R2 0.710 vs 0.643) better than the Intergrowth 21 scale. The resultsobtained were adjusted over the newborns’ sociodemographic and clinical factors.Conclusion: The results of our study are controversial where the Fenton growth charts are superior to Intergrowth21 before 2 weeks of age and at 4 weeks, whereas Intergrowth 21 charts showed higher percentiles for weight andheight than Fenton charts at 2 two weeks of age. Further studies following a different design, such as a clinical trialor a prospective study, taking multiple ethnicities into account and conducted in multiple centers should beconsidered to enroll a more representative sample of Lebanese children and be able to extrapolate our results tothe national level.Keywords: Growth charts, Percentiles, Premature, Fenton, Intergrowth-21* Correspondence: [email protected]; [email protected]†Souheil Hallit and Marie-Claude Fadous Khalife are last co-authors.1Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik(USEK), Jounieh, LebanonFull list of author information is available at the end of the article The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (, which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication o/1.0/) applies to the data made available in this article, unless otherwise stated.

Samarani et al. BMC Pediatrics(2020) 20:74IntroductionPrematurity is becoming more frequent nowadays especially with the development of artificial fertilizationmethods [1]. In 2016, the Center for Disease Controland Prevention (CDC) declared that around one babyout of 10 is born premature [2, 3]. Newborn’s growthis an important marker and a screening method for anumber of pathologies or deficiencies [4], whichneeds to be tracked through growth charts. The latterwould lead to a better monitoring of the nutritionalstatus, thus, may limit the depth and duration of dietrelated growth restriction and its short- and longterm damages thereafter [3].In fact, many charts have been developed, mostlybased on intrauterine growth and rarely adapted to preterm newborns. Indeed, preterm babies are not fetusesas they no longer live in-utero [ 5]. Regardless of theirapparent independence, they have not acquired thegrowth and survival skills of full-term babies yet andpresent a physiological immaturity. Consequently, whenassessed via common growth charts, these newborns remain under the 10th percentile for a long time and donot catch up with normal growth until the age of two tothree years. For this motive, the actual trend is to supplement this population with a hypercaloric nutrition tocompensate for this extra-uterine growth restriction.Despite this supplementation, most babies fail to reachtheir set growth goals still.Within that scope, alarming studies have shown an association between prematurity and obesity in adulthood,with question marks raised about the link between“overfeeding” the preterm newborns, obesity and cardiovascular complications later in life [6]. In the neonatalpopulation aged between 36 and 50 weeks of unadjustedage, the Fenton chart is considered one of the bestcharts for assessing longitudinal growth [7]. Nevertheless, it showed two weaknesses: it does not reflect theadaptation of the premature newborn to extra-uterinelife and it under- or overestimates newborn’s growth.The most commonly used chart at the Notre Damedes Secours University Hospital Center-Byblos (CHUNDS), is the Fenton chart 2003, which has not been updated till now. Between 2009 and 2014, the Intergrowth21 project has emerged as a successful growthchart and underwent rigorous processes that ensuredthat the data collected in the INTERGROWTH-21stproject is of exceptionally high quality [8]. Intergrowth21 charts are used to create standards for postnatalgrowth of premature infants especially those born before32 gestational weeks [9]. While disagreements on theFenton charts continue, the results of the Intergrowth21st project were awaited with great interest. The “Intergrowth 21st Project” was a prospective multicenter,multi-ethnic study, which included low-risk women,Page 2 of 8non-smokers, with a normal pregnancy history, and nohealth problems that could affect fetal growth [10]. Allmaternal health care and nutritional needs were met.Birth and postnatal growth standards were developedfrom data collected from a cohort of uncomplicatedpregnancies with normal growing fetuses [11]. Thesevery strict selection criteria were mandatory, in order tocreate standards on how the normal growth of healthypremature babies should be.In a recent systematic review, 61 longitudinal referencecharts were identified and compared to the Intergrowth21 chart [9]; assessments made using the Intergrowth-21charts demonstrated a reduction in the diagnosis ofextrauterine growth retardation [9, 12]. Many infantswho were classified as having restricted growth according to the Fenton charts, turned out to have normalpostnatal growth according to the Intergrowth-21charts [12]. Another important point is that, like theWorld Health Organization (WHO) growth standards,the Intergrowth-21 growth standards aim at producinggraphs that describe optimal rather than average growth,which could be used worldwide.Being in a developing country, a local validation beforeadapting Intergrowth-21 charts to our new born infantsis necessary, especially to avoid the misclassification oftheir size, which may have an impact on their nutritionalsupport. For these reasons, the objective of this studywas to check which method (the universal Fenton 2003curves or the Intergrowth-21 curves) used in the neonatology department at CHU-NDS would predict height,weight and cranial perimeter of premature Lebanesebabies better. This study would help us evaluate the difference between both curves in terms of extra- andintra-uterine growth restriction, reflected by weight,height and head circumference at birth and verify laterthe convergence between the intergrowth-21 and theWHO curves of the child health record book around thesixth month of life.MethodsStudy designThis was a retrospective study, conducted at CHU-NDS.Medical records of premature newborns admitted to theneonatal unit over a seven-year period (2010 to 2017),were reviewed. The discretion of names and personal information have been respected. All preterm infants bornalive before 37 weeks of gestation and admitted to theneonatology department within 24 h of birth, were included in the study. Term infants (born at 37 weeks ofgestation or more) were excluded since Intergrowth-21is a growth chart adapted only to preterm babies. Furthermore, excluded were [1] newborns admitted after24 h of birth to the neonatal intensive care unit (NICU)[2], who died during hospitalization [3], who were

Samarani et al. BMC Pediatrics(2020) 20:74transferred to another hospital and [4] who were suffering from a comorbidity that can affect normal growth,such as bronchodysplasia, cardiovascular pathologiesand placental insufficiency or any other prenatal diseasesknown to alter the normal pattern of growth.Data collectionData was collected from files in the medical archive.Weight, height and head circumference of each child atbirth, at 37 weeks of gestation, 2 weeks and 4 weeks oflife were noted, and then marked on the percentilecurves of the Fenton 2003 and Intergrowth 21 charts.Weight and height were measured using a digital babyscale with a rod, whereas head circumference was obtained via a measuring tape; the same measurementmethod was followed for all children. The follow-up dataof each child after discharge were also collected frommedical records of each child’s pediatrician.When the measurements fell on the curves between2 standard lines of percentiles, the value was then approximated to an intermediate value between the twopercentiles. Thus, the 5th, 30th, 70th and 95th percentile were considered if the measurements fell between the following brackets 3rd-10th, 10th–50th,50th–90th and 90th–97th percentile respectively.Values below the 3rd percentile or above the 97thpercentile were reported as 2nd and 98th percentilerespectively. This approximation was made for bothcharts in order to avoid any bias.The data collection took into account other variablessuch as the date of birth of the new born, the length ofstay at the hospital, the need for intubation, transfusion,iron supplementation, the cause of admission to theNICU, consanguinity, medically assisted procreation (Invitro fertilization-IVF) and the delivery method.Statistical analysisStatistical analysis of data was performed using SPSSversion 22 (SPSS Inc., Chicago, IL, USA). Comparisonsof the same baby’s measures according to both chartswere assessed through linear regressions. Multiple linearregressions were conducted taking weight, height andcranial perimeter as dependent variables and taking ineach model one of the charts as an independent variable.The model that had a higher Nagelkerke R2 value wouldpredict the dependent variable more.ResultsOut of a total of 492 medical record extracted, 318(64.63%) newborns aged between 27 and 36 weeks ofgestation met the inclusion criteria. The distribution ofgestational ages showed that 52.8% of the babies wereborn between 34 and 36 gestational weeks, whereas theremaining newborns were under 33 gestational weeksPage 3 of 8(Fig. 1). The most frequent cause of admission to theNICU was multiple pregnancies (32.4%), followed byplacental insufficiency (22%), respiratory distress of different etiologies (22%) and infections (20.1%).The majority of the newborns (98.4%) were admitted to the NICU of the CHU-NDS from maternityward and 1.6% were transferred before birth from another hospital. The mean age of birth was 33.26 2.10 weeks of gestation. Consanguinity was present in11.6% of the cases and caesarean section accountedfor 85.8% of deliveries. Moreover, 29.9% of the babieswere intubated and 78.8% received more than 2 bloodtransfusions during their stay; 49.7% of infants werefed by breast milk and formula milk, 48.1% by formula milk alone and 1.3% were exclusively breastfed.We note that in-vitro fertilization methods accountedfor 24.8% of pregnancies.Difference between the two chartsThe results of the linear regression taking weight at birthas the dependent variable, showed that the Fenton scale(R2 0.391) would predict weight at birth better thanthe intergrowth 21 scale (R2 0.257) (Table 1, Model 1).The same applies for height (Table 1, Model 2) and cranial perimeter (Table 1, Model 3) at birth when taken asdependent variables. In contrast, when consideringweight and height at 2 weeks, the results showed thatthe Intergrowth-21 chart would predict weight (0.384 vs0.311) (Table 1, Model 4) and height (0.650 vs 0.585)(Table 1, Model 5) more than the Fenton chart. Whenconsidering weight and height at 4 weeks, the resultsshowed that the Fenton chart would predict weight(R2 0.655 vs 0.631) and height (R2 0.710 vs 0.643)better than the Intergrowth-21 chart (Table 1, Models 6and 7 respectively).DiscussionGrowth monitoring is an essential tool that reflects theoverall health of neonates, especially preterm infants. Ithelps assess the nutritional status and detect pathological deviations. A meta-analysis, published in 2015, of16 prospective cohorts of premature newborn comparing the 1991 US birthweight reference, the 1999–2000US birthweight reference and the Intergrowth-21st standards, revealed a prevalent reduction of small for gestational age preterm newborn by more than a quarter,with no significant change in the risk of associated neonatal mortality [13]. Conversely, newer results from aretrospective study showed that the incidence of smallfor gestational age preterm newborns was higher withthe Intergrowth 21st standards compared to the Fentonones. The difference between the results of those research [12] prompted us to conduct our study. Growthcurves monitor height, weight, and head circumference

Samarani et al. BMC Pediatrics(2020) 20:74Page 4 of 8Fig. 1 Organizational chart of the studyprogression, therefore a reference chart adopting growthcurves that are applicable for all ethnicities and racesusing anthropometric measures should be used in orderto provide adequate assessment [14]. In our study, acomparison of the weight and height percentiles of thewhole sample showed that before two weeks of age,Fenton growth charts showed better results compared tothe Intergrowth 21; after two weeks of age, Intergrowth21 charts showed higher R2 values for weight and heightthan Fenton charts.The Fenton 2003 growth charts have been adopted inthe NICU of the CHU-NDS so far in order to follow theimprovement of growth in preterm neonates, especiallythose receiving parenteral nutrition according to theinternational nutritional guidelines. In most cases, thesecurves have shown these infants to have growth retardation despite adequate nutrition and introduction ofamino acids, electrolytes and multivitamin complexesvery early; consequently, those babies are exposed to intensive parenteral nutrition for a long period of time,which further delays their discharge from NICU. Themain reason behind this is that Fenton growth charts assessment is based on intrauterine growth standards [15],causing the overfeeding of these newborns to lead toobesity and metabolic syndrome later in life. On anotherhand, the Intergrowth-21 standards aimed at producingcharts that set breastfeeding as the norm to follow anddescribed optimal rather than average growth, whichcould be used worldwide [ 16].Study limitationsOur sample data was difficult to collect after hospitaldischarge since pediatricians do not keep records of theirpatients’ growth in their offices and rely on medical fileskept by the parents. Our study is retrospective that predisposes us to an information bias since we didn’t getthe chance of collecting all the data we need from somefiles. Plus, the effect of the maternal height and weighton the results was not studied and should have been investigated since increased maternal height and weightare correlated with increased infant’s birth weight. Future studies that follow a different design (clinical trialor prospective) should be considered to avoid the bias inanthropometric measurements. A more representativesample of Lebanese children recruited from multiplecenters is warranted to extrapolate the results to thewhole population. Finally, prenatal diseases that couldalter the pattern of growth should be taken intoconsideration.

Samarani et al. BMC Pediatrics(2020) 20:74Page 5 of 8Table 1 Linear regressions of factors associated with the baby’s parameters at birth according to the Fenton and Intergrowth 21chartsModel 1: Dependent variable: Weight at birth.Fenton scaleIntergrowth 21 scaleUnstandardizedBetap-value ConfidenceIntervalIntubation 196.278.001 313.717Gender (females vs males*) 157.258In-vitro fertilization (yes vs no*)Delivery method (C-sectionvs normal*)VariableUnstandardizedBetap-value ConfidenceInterval 78.839 145.980.027 275.295 16.666.004 263.479 51.038 140.141.020 258.511 21.770 398.452 0.001 521.357 275.548 437.977 0.001 573.322 302.631 19.570.793 166.432127.29117.286.836 147.337181.910Any cause of prematurity (yes vs no*) 20.384.378 25.08765.855 8.373.740 58.03041.283Consanguinity (yes vs no*)37.530.642 121.321196.38185.564.337 89.577260.705Breastfeeding (yes vs no*)33.230.068 2.49868.95842.203.0362.69581.712R2 0.391R2 0.257Model 2: Dependent variable: Height at birth.Fenton scaleVariableIntubation (yes vs no*)Intergrowth 21 scaleUnstandardizedBetap-value ConfidenceInterval 1.053.010 1.855 .251UnstandardizedBetap-value ConfidenceInterval 1.188.006 2.036 .341Gender (females vs males*) .993.008 1.730 .256 .575.147 1.353.203In-vitro fertilization (yes vs no*) 1.604 0.001 2.494 .715 1.573.001 2.506 .641Delivery method (C-section vsnormal*) .301.551 1.295.694 .388.463 1.431.654Breastfeeding (yes vs no*).144.249 .101.389.143.273 .114.401.601 .223.383.081.616 .238.400Consanguinity (yes vs no*) .075.895 1.2011.050.332.578 .8421.505Length percentileat birth.065 cause of prematurity (yes vs no*) .080R2 0.368R2 0.305Model 3: Dependent variable: Cranial perimeter at birth.Fenton scaleVariableUnstandardizedBetaIntergrowth 21 scalep-value ConfidenceIntervalUnstandardizedBetap-value ConfidenceIntervalIntubation (yes vs no*).391.021.060.723.194.287 .165.554Gender (females vs males*) .237.127 .542.068.474.010.113.836In-vitro fertilization (yes vs no*) .183.311 .537.172 .071.720 .461.319Delivery method (C-section vsnormal).012.955 .409.433.031.896 .428.489Any cause of prematurity (yes vs no*) .076.247 . .109.172Consanguinity (yes vs no*) .008.972 .478.462.018.943 .493.530Breastfeeding (yes vs no*).009.865 . .043.180Head circumferenceat birth. 0.498R2 0.405

Samarani et al. BMC Pediatrics(2020) 20:74Page 6 of 8Table 1 Linear regressions of factors associated with the baby’s parameters at birth according to the Fenton and Intergrowth 21charts (Continued)Model 4: Dependent variable: Weight at 2 weeks.Fenton scaleVariableIntergrowth 21 scaleUnstandardizedBetap-value ConfidenceIntervalUnstandardizedBetap-value ConfidenceIntervalIntubation (yes vs no*) 164.040.010 287.562 40.517 178.365.003 295.261 61.469Gender (females vs males*) 111.614.063 229.5056.276 35.214.546 149.98579.556In-vitro fertilization (yes vs no*) 353.688.000 487.945 219.430 363.595.000 490.281 236.909Delivery method (C-section vsnormal*) 9.015.917 179.313161.2839.309.909 151.824 170.442Any cause of prematurity (yes vs no*) 36.339.171 15.84688.52547.720.059 1.84997.288Consanguinity (yes vs no*)22.674.801 154.905200.25444.992.597 122.662212.646Breastfeeding (yes vs no*) .757.970 40.73839.223 1.103.954 38.88936.683Weight percentile at 2weeks of age11.378.0007.92714.83011.141.0008.49613.785R2 0.311R2 0.384Model 5: Dependent variable: Height at 2 weeks.Fenton scaleVariableUnstandardizedBetaIntergrowth 21 scalep-value ConfidenceIntervalUnstandardizedBetap-value ConfidenceIntervalIntubation (yes vs no*).673.230 .4481.794.771.128 .2351.777Gender (females vs males*) .579.239 1.562.403 .136.769 1.066.795In-vitro fertilization (yes vs no*) 1.872.028 3.528 .217 1.697.029 3.209 .185Delivery method (C-section vsnormal*) .984.149 2.339.370 .704.261 1.955.547Any cause of prematurity (yes vs no*) .129.570 .588.329 .060.770 .474.354Consanguinity (yes vs no*)1.678.059 .0703.4261.177.143 .4182.772Breastfeeding (yes vs no*) .161.335 .495.173 .149.331 .455.158Length percentileat 2 weeks. 0.585R2 0.650Model 6: Dependent variable: Weight at 4 weeks.Fenton scaleVariableIntergrowth 21 scaleUnstandardizedBetap-value ConfidenceIntervalIntubation (yes vs no*) 349.864.000 511.389 188.338 287.552.001 456.257 118.846Gender (females vs males*) 214.487.006 366.769 62.205 104.602.204 266.91857.714In-vitro fertilization (yes vs no*) 263.235.003 433.325 93.146 316.056.000 490.141 141.971Delivery method (C-section vsnormal*) 49.404.659 270.890172.083 101.449.380 329.711 126.814Any cause of prematurity (yes vs no*) 60.329.079 7.030127.68996.435.00825.542Consanguinity (yes vs no*)72.829.508 144.660 290.31878.345.491 146.491 303.181Breastfeeding (yes vs no*) 10.813.692 64.78543.160 13.781.625 69.60042.038Weight percentile at 4 2 0.655UnstandardizedBetaR2 0.631p-value ConfidenceInterval167.329

Samarani et al. BMC Pediatrics(2020) 20:74Page 7 of 8Table 1 Linear regressions of factors associated with the baby’s parameters at birth according to the Fenton and Intergrowth 21charts (Continued)Model 7: Dependent variable: Height at 4 weeks.Fenton scaleVariableIntergrowth 21 scaleUnstandardizedBetap-value ConfidenceInterval .553.465UnstandardizedBetap-value ConfidenceIntervalIntubation (yes vs no*) 1.278.071 2.668.113Gender (females vs males*) 1.068.055 2.161.024 .559.363 1.784.665In-vitro fertilization (yes vs no*) 1.518.016 2.734 .302 1.096.121 2.493.300Delivery method (C-section vsnormal*) .298.703 1.8591.264 1.735.053 3.494.025Any cause of prematurity (yes vs no*) .215.364 .689.258 .259.325 .783.265Consanguinity (yes vs no*).317.748 1.6602.2941.860.086 .2773.996Breastfeeding (yes vs no*) .127.513 .516.262 .149.490 .580.282Length percentileat 4 weeks. 0.710 2.065.959R2 0.643ConclusionThe results of our study are controversial since the Fenton growth charts showed superiority predicting newborn’s growth in terms of weight, height and cranialperimeter at birth and at 4 weeks compared to theIntergrowth-21 ones, whereas Intergrowth 21 chartsshowed higher percentiles for weight and height at 2 twoweeks of age compared to the Fenton charts. The resultsobtained could have been affected by many factors, including ethnicity that could not be investigated in thisstudy due to its retrospective aspect. Therefore, furtherstudies that take this study’s limitations into account, areneeded.Ethics approval and consent to participateThe study was conducted with the approval of the Ethics Committee ofNotre Dame des Secours university Hospital Byblos. A written informedconsent was obtained from children’s parents.AbbreviationsCDC: Center for Disease Control and Prevention; CHU-NDS: Notre Dame desSecours University Hospital Center-Byblos; IVF: In-vitro fertilization;NICU: neonatal intensive care unit; WHO: World Health OrganizationReceived: 24 December 2019 Accepted: 10 February 2020AcknowledgementsWe would also like to thank Myriam Amm, Juliana Souaiby and HaysamTarabay for their help in the data collection.Authors’ contributionsMCFK conceived and designed the study. MS and GR performed the datacollection and entry. GAF and SH involved to data interpretation andstatistical analysis. MS, GR and JM wrote the manuscript. All authors criticallyrevised the manuscript for intellectual content. All authors read andapproved the final manuscript.FundingNone.Availability of data and materialsThere is no public access to all data generated or analyzed during this studyto preserve the privacy of the identities of the individuals. The dataset thatsupports the conclusions is available to the corresponding author uponrequest.Consent for publicationNot applicable.Competing interestsThere’s nothing the authors have to disclose.Author details1Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik(USEK), Jounieh, Lebanon. 2Pediatrics Department, Notre Dame Des SecoursUniversity Hospital, Byblos, Lebanon. 3INSPECT-LB: Institut National de SantePublique, Epidemiologie Clinique et Toxicologie, Beirut, Lebanon.References1. Liu L, Oza S, Hogan D, et al. Global, regional, and national causes of under-5mortality in 2000-15: an updated systematic analysis with implications forthe sustainable development goals. Lancet. 2016;388(10063):3027–35.2. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: final datafor 2016. Natl Vital Stat Rep. 2018;67(1):1–55.3. Cooke RJ, Ainsworth SB, Fenton AC. Postnatal growth retardation: auniversal problem in preterm infants. Arch Dis Child Fetal Neonatal Ed.2004;89(5):F428–30.4. Schlaudecker EP, Munoz FM, Bardaji A, et al. Small for gestational age: Casedefinition & guidelines for data collection, analysis, and presentation ofmaternal immunisation safety data. Vaccine. 2017;35(48 Pt A):6518–28.5. Malhotra A, Allison BJ, Castillo-Melendez M, Jenkin G, Polglase GR, Miller SL.Neonatal Morbidities of Fetal Growth Restriction: Pathophysiology andImpact. Front Endocrinol (Lausanne). 2019;10:55.6. Parkinson JR, Hyde MJ, Gale C, Santhakumaran S, Modi N. Preterm birth andthe metabolic syndrome in adult life: a systematic review and meta-analysis.Pediatrics. 2013;131(4):e1240–63.7. Fenton TR, Chan HT, Madhu A, et al. Preterm Infant Growth VelocityCalculations: A Systematic Review. Pediatrics. 2017;139(3):e20162045.8. Schanler RJ, Abrahams SA, Hoppin AG. Parenteral nutrition in prematureinfants. Uptodate. 2018. Available from: tion-in-premature-infants.

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The Fenton chart, based on prenatal growth, has been used in the neonates' intensive care unit (NICU) of the Notre Dame des Secours University Hospital to assess premature newborns' development. Intergrowth21 is a new multidisciplinary, multiethnic growth chart better adapted to premature growth.