Individualizing and Optimizing Nutrition to Prevent Metabolic Syndrome and To Improve Neurodevelopment in Preterm and Small for Gestational Age Infants
Phase: NA
Conditions: Infant, Premature, Diseases, Infant, Small for Gestational Age
Sponsor: University of Texas Southwestern Medical Center

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Optimizing Individual Nutrition in Preterm Very Low Birth Weight Infants:  
Randomized Clinical Trial  
  
PI: Luc P. Brion, MD  
Co-Investigators: Charles R. Rosenfeld, MD; Roy Heyne, MD  
Department of Pediatrics  
Funded by CCRAC: Senior Investigator New Direction Award  
Funded by a Grant from the Gerber Foundation   
Funded by George L. MacGregor Professorship (C.R. Rosenfeld)  
FDA application for IDE: waived by the IRB (non-significant risk device)  
Approved by the IRB  STU 102014-056  
 02-14-15  
Revised 10-11-17; 03/27/2018; 4/28/2020 
  
  
1. Introduction and Purpose:   
Background: Insufficient growth before or after birth and insufficient nutrient intake in preterm infants in the 
neonatal intensive care unit (NICU) are associated with growth insufficiency and neurodevelopmental 
impairment at follow-up. Both extremely low gestational age (GA) neonates (ELGANs) and small for 
gestational age (SGA) (weight < 10th percentile for GA) neonates may develop signs suggestive of metabolic 
syndrome during the first 3 years of life. Low birth weight (BW), prematurity and rapid or disproportionate 
weight gain (with increased weight for length) during the first months after birth are associated with signs of 
metabolic syndrome in adults.  
  
In preterm infants fed human milk, milk needs to be fortified to meet nutrient recommendations. Fortification 
can be 1) standard, 2) individualized (adjusted based on daily human milk nutrient analysis and milk volume), 
or 3) optimized (adjusted based on growth rate and serum analyses).   

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The first specific aim will determine whether individualized and optimized nutrition during hospitalization 
results in improved growth in the neonatal intensive care unit (NICU) in extremely low gestational age (GA) 
neonates (ELGANs, <29 weeks) and in small for GA (SGA, birth weight <10th percentile for GA) preterm 
infants compared with optimized nutrition.   
  
The second specific aim will determine whether individualized and optimized nutrition in the NICU improves 
neurodevelopmental outcomes (acquisition of development milestones) and reduces the risk of disproportionate 
growth (i.e., excess fat) in the NICU and findings suggestive of metabolic syndrome in the first 3 years of life.  
  
Hypotheses:   
1. 
Primary hypothesis: In preterm infants (GA <29 weeks or GA <35 weeks and SGA) individualized and 
optimized nutrition will increase velocity of growth (weight gain velocity by 2 g x kg-1 x day-1 and length 
velocity by 0.2 cm per week) from birth to 36 weeks of postmenstrual age (GA plus postnatal age) in 
comparison with optimized nutrition.    
2. 
Secondary hypotheses: Individualized and optimized nutrition will improve neurodevelopmental 
outcome and reduce the risk of disproportionate growth (excess fat) in the NICU and findings suggestive of 
metabolic syndrome in the first 3 years of life.   
  
Primary study endpoint (Aim 1):  
• 
Growth velocity (rate of weight gain [g x kg-1 x day-1] and length velocity [cm x week-1]) from birth to 
36 weeks of PMA (or discharge if patient is discharged earlier than 36 weeks PMA) will be calculated 
using Patel’s geometric method.  
  
Secondary endpoints (Aim 2):  
  
In the NICU:   
• 
Disproportionate growth (abdominal circumference, subscapular skinfold and BMI greater than their 
respective 90th percentiles for age) at 36 weeks of PMA or discharge if patient is discharged earlier than 
36 weeks PMA  
• 
Body composition analysis using air displacement plethysmography (Pea Pod)  
• 
Blood pressure (systolic and mean, calm or sleeping) at 36 weeks PMA and discharge   
• 
Hypertension, defined as systolic blood pressure >99th percentile for PMA for at least 24 hours while 
sleeping or calm  
• 
Blood sample for measurements of cholesterol, fats, cystatin C, adipokines and some blood markers that 
may indicate a higher risk for development of diabetes or metabolic syndrome at discharge or 36 weeks 
of PMA, whatever comes first;  
• 
Bacterial diversity and ratio of Firmicutes to Bacteroidetes (F:B) in stool samples (1) at 28 days of age 
and (2) at 36 weeks or discharge if earlier than 36 weeks  
• 
Body composition analysis using air displacement plethysmography (Pea Pod) at 36 weeks of PMA or 
discharge if patient is discharged earlier than 36 weeks PMA  
At the Follow-up Clinic (Thrive Clinic, Dr. Roy Heyne), a state-of-the-art facility with >95% follow-up 
rate, at 6, 12, & 36 months chronological age & 18-26 months adjusted age (PNA corrected for 
prematurity):   

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• 
Neurodevelopment (Bayley III) scores (cognitive and language composite) at 18-26 months adjusted age   
• 
Findings suggestive of metabolic syndrome: disproportionate growth (excessive fat mass) and high 
systolic blood pressure at each visit at 6 months, 1, 2 and 3 years of age   
• 
Serum levels of cholesterol, fats, cystatin C, adipokines and some blood markers that may indicate a 
higher risk for development of diabetes or metabolic syndrome at 1 and 3 years of age  
• 
Body composition analysis using air displacement plethysmography (Pea Pod) at 6 months of age  
• 
Body composition analysis using Dexascan (Hologic Horizon A) at 1 and 3 years of age  Relationship 
between stool bacterial diversity and F:B ratio, growth and obesity Stopping Rules:  
• 
Less than 10 patients recruited in 12 months  
• 
Mortality in enrolled patients significantly higher than in non-enrolled patients (P<0.01)  
• 
More frequent necrotizing enterocolitis in enrolled patients (P<0.01) 2. Background:  
Purpose: To provide preliminary data for a multicenter randomized trial to test whether individualized and 
optimized nutrition in ELGANS and SGA preterm neonates improves neurodevelopmental outcomes and 
reduces the risk of metabolic syndrome. This could be of major public health significance.   
  
Standard of care: Feeding human milk rather than formula has several advantages for preterm infants including 
decreasing the frequency of necrotizing enterocolitis and infections. However, human milk does not provide 
enough calories or proteins, leading to less growth; therefore, human must be supplemented with human milk 
fortifier, and for some babies, additional protein or fat. The amount of protein and fat in mother’s breast milk 
and donor milk is highly variable, often leading to insufficient growth velocity.1 There are three ways to 
fortifying human milk for preterm infants: (1) Standard, fixed dosage fortification; (2) Adjustable (optimized) 
fortification using growth velocity to modify caloric supplementation and a surrogate for protein sufficiency to 
modify the dosage of protein fortification, and (3) Targeted (customized, individualized) fortification or 
fortification triggered by poor growth and results from human milk analysis. One small randomized trial 
showed that growth of preterm infants in the NICU improved using adjustable supplementation of human milk 
based on weekly BUN levels.2 Other authors have used this approach and observed better growth without any 
toxicity.3-5  At Parkland we have used this approach for more than a decade: adjustment of human milk 
fortification is based on growth velocity and weekly serum BUN and albumin levels; protein intake is increased 
weekly until BUN is greater than 10 mg/dl and albumin is > 3 g/dl.   
  
Targeted individualized supplementation of human milk with fat has been done based on creamatocrit  
(measurement of fat layer after centrifugation); this method was shown inferior to near infrared 
spectrophotomotry,6 which has become the gold standard for human, dairy or animal milk analysis.1 Hair 
showed in a small RCT that targeted supplementation of human milk with fat (human milk cream) based on 
serial measurements of human milk nutrients using near infrared spectrophotometry, increased weight gain and 
linear growth in preterm infants with birth weight 750-1250 grams.7 Several centers have used targeted 
individualized nutrient supplementation successfully. Individualized supplementation was associated with 
improved growth and less gastroesophageal reflux compared to routine supplementation based on assumed 
nutrient contents.8-16  Analysis of donor milk nutrient is standard of care in donor milk banks in the US.17  
  
Rationale for the RCT: There are three ways to fortifying human milk for preterm infants: (1) Standard, fixed 
dosage fortification; (2) Adjustable (optimized) fortification using growth velocity to modify caloric 
supplementation and a surrogate for protein sufficiency to modify the dosage of protein fortification, and (3) 
Targeted (customized, individualized) fortification or fortification triggered by poor growth and results from 
human milk analysis.1 Methods 2 and 3 have been shown by multiple observational studies and each by one 
randomized controlled trial (RCT) to be superior to the first method, but methods 2 and 3 have never been 
compared in an RCT.   

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We plan a RCT to compare standard of care at Parkland (optimized supplementation) with  
individualized supplementation in high-risk infants. This RCT will determine whether growth of preterm at high 
risk for growth insufficiency can be improved by targeted daily supplementation based on (1) serial milk 
analyses in addition to standard of care and (2) the amount of enteral feeding given daily. Patients randomized 
to the control arm will receive standard of care at Parkland, which involves adjustment of human milk 
fortification based on growth velocity and weekly serum BUN and albumin levels; protein intake will be 
increased weekly until BUN (adjusted for creatinine) is greater than 10 mg/dl and albumin is > 3 g/dl. Patients 
in the treatment arm be part of a quality improvement including targeted daily supplementation of human milk 
based on serial milk analyses using near infrared spectrophotometry to meet expected requirements based on 
postmenstrual age and physiologic status; milk intake and fortification will be further adjusted based on growth 
velocity and weekly serum levels of BUN and albumin levels, which will be used as gold standard.   
  
Status of the device: Measurement of nutrients in human milk has been used by several investigators and has 
been shown to improve growth compared with standard fortification. Standard for human milk bank is to 
analyze pooled human milk samples and to provide this information on each milk bottle to the neonatal 
intensive care unit (NICU). However, devices for analyzing human milk samples have not been approved by the 
FDA for analyzing individual mother’s milk for making individual decisions in the neonatal intensive care unit  
(NICU). Three devices are currently available in the US for human milk analysis: The Calais Human Milk 
Analyzer, the SprectraStarTM 2500 XL Neonatal Analyzer (which has now replaced the previous 2400 version) 
and the Foss FT120. We plan to use the SprectraStarTM 2500 XL. This device has been validated in one 
study.18 It is the only device available in the US that was used in a randomized clinical trial, which showed 
improved growth (weight gain and linear growth) in the group in which nutrition was adjusted based on 
readings of human milk composition using this device.7  We believe this device is a non-significant risk device 
because   
1. 
Measurement of nutrients in human milk has been used in several centers to adjust fortification of 
human milk for preterm infants, and has been shown in one randomized trial to improve growth without any 
risk to the infants.  
2. 
Infants randomized to the treatment arm will have growth velocity and BUN and serum electrolytes 
measured regularly, as is done for standard of care, to make sure that adjustment of human milk fortification is 
not exceeding needs for each infant.    
3. 
The Institutional Review Board of Baylor College of Medicine and Affiliated Hospitals and the 
University of Texas Health Science Center at San Antonio have approved a randomized trial that used this 
device and was conducted at Texas Childrens and San Antonio without an IDE (Hair et al, attached).   
  
Status of relevant research:   
Several studies have shown major variability in human milk nutrients. 7-18 The best method for 
measuring nutrients in human milk is near infrared spectrophotometry.1,6 Supplementing human milk based on 
its measured composition has been standard of care in several NICUs for years. Measuring nutrients in human 
milk to provide individualize milk fortification was shown to improve growth (weight gain and linear growth) 
without side effects in a randomized trial at Texas Children’s.7 However, no RCT has been conducted to 
compare individualized targeted supplementation with adjustable optimized supplementation.  
The bowel utilizes a high amount of enterally derived threonine and glutamine, two essential amino 
acids, for its own metabolism and production of mucin;19,20  suggesting that growth might improve by 
discounting enteral contribution to protein intake while providing less than 75 ml x kg-1 x day-1 of enteral 
feeding; such an approach has been used routinely in the Netherlands but has not been tested in a RCT; no 
evidence has been published at this point to show whether this approach improves any of the clinical 
outcomes.21  

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Prenatal and postnatal growth as precursors of metabolic syndrome:  
Metabolic syndrome is defined as the presence of at least three of the following conditions: abdominal 
obesity, a high triglyceride level, a low high-density lipoprotein, high blood pressure and high fasting blood 
sugar. Cardiovascular risk in adults (including signs of metabolic syndrome) is associated with low BW, small 
size for GA and prematurity22-25 and increases with weight gain by 3 years of age.26,27 Some authors found no 
independent association between weight or length at term age and blood pressure in adulthood.28-31 In contrast, 
rapid postnatal weight gain during the first 1.5-3 postnatal months is associated with high systolic blood 
pressure, obesity, or insulin resistance in adults.32-34 Weight gain in excess of linear growth before term 
corrected age and during the next 3 months is associated with abnormal blood levels of cholesterol, body fat 
percentage, waist circumference and acute insulin response in young adults.35 Breastfeeding is associated with 
better brachial artery endothelial function in adult men. 36 Exclusive breastfeeding for the first 2 months is 
associated with less frequent non-insulin-dependent diabetes in adult Pima Indians.37  
In preterm infants, body composition at term age is different than in infants born at term, with a greater 
proportion of fat mass to lean body weight.38 In a population study of ELGANs, the amounts of macronutrients 
(protein, fat and calories) provided in the NICU were independent predictors of growth even after adjusting for 
severity of illness.39 Duncan et al have conducted a cross-sectional study including 3 sets of 40 VLBW infants 
born at Parkland Hospital in 2003-2006 and analyzed at either 1, 2 or 3 years of age.40,41 They observed low 
height and weight z scores for age but increased weight for height, increased ratio of subcutaneous skinfold 
thickness to abdominal circumference, elevated systolic blood pressure and dysfunctional renal regulation and 
hyperfiltration, and elevated leptin level, suggesting leptin resistance. Further studies are needed to determine 
when after birth these occur and whether they predict adult metabolic syndrome.   
Microbiome is associated with health and disease in animals and humans. High ratio of Firmicutes to 
Bacteroidetes (F:B) in stools is associated with obesity and metabolic syndrome in adults.42,43 Developmental 
pattern of the microbiome in infancy is associated with growth rate.44,45 Infants who acquire a profile high in 
Bifidobacterium and Collinsella after 6 months of age have lower adiposity at 18 months of age.45 Addition of 
lactobacillus acidophilus to formula increases weight gain in neonates.46 Several factors affect neonatal 
microbiome. Mother’s own breast milk promotes bacterial diversity in preterm infants compared with formula; 
pasteurized donor human milk moderately increased bacterial diversity.47 Antibiotic exposure in neonates 
reduces stool bacterial diversity and increases risk for obesity.48 However, no data are available about any effect 
of individualization of macronutrient intake affects neonatal microbiome.  
  
Importance of adequate nutrition for growth and neurodevelopment:   
In SGA and preterm infants, insufficient weight gain and linear growth and insufficient macronutrient 
intake in the NICU are associated with growth insufficiency and neurodevelopmental impairment, even after 
adjustment for other morbidities.49-53 However, systematic administration of higher protein intake in the NICU 
than is recommended may not improve, and very high protein intake (6.0–7.2 gm x kg-1 x day-1 of protein), well 
beyond the upper maximum of current practice (5.5), may harm neurodevelopment.54-55  
  
  
  
Gap of knowledge:  
  
Limited information is available regarding the impact of higher protein intake on long-term 
neurodevelopment than is currently recommended.21,56 Further studies are needed to evaluate (1) whether or 
individualizing macronutrient intake to nutrient concentration in human milk is better than adjusting 

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fortification to serum levels of BUN, and (2) whether protein in enteral feeding should be counted in the total 
protein intake when only small amount of enteral feed is provided, to improve growth and neurodevelopmental 
outcome while minimizing the risk for metabolic syndrome in very preterm and SGA infants. No data are 
available about any effect of individualization of macronutrient intake affects neonatal microbiome.   
  
Preliminary Retrospective Data   
Infants <29 weeks GA or < 1000 grams BW, 2008-2012: Parkland Hospital vs. NRN (Table 1):   
At birth, infants at Parkland Hospital had similar weight, greater length and fronto-occipital circumference 
(FOC), and lower ponderal index (PI) [weight in grams x (length in cm)-3 x 100] vs. those in other NRN centers. 
At 36 weeks PMA, they had greater weight, length and PI, suggesting more weight gain but disproportionate fat 
deposition.  
  
Table 1  
  
Parkland Hospital  
Other NRN Centers   
Gestational age (weeks)  
25.3±2.0 (485)**  
25.7±1.9 (8704)  
Age of measurement  
At Birth  
At 36 weeks PMA  
At Birth  
At 36 weeks PMA  
Weight (grams)  
843±283 (485)  
2323±394 (303)**  
834±256 (8699)  
2122±409 (5537)  
Length (cm)  
34.2±2.9 (391)**  
43.5±2.3 (261)**  
33.4±3.5 (8033)  
42.6±3.1 (5135)  
FOC (cm)  
24.1±1.9 (429)**  
30.9±1.5 (283)  
23.7±2.2 (7861)  
30.9±2.0 (5261)  
Ponderal Index  
2.08±0.7 (434)*    
2.83±0.48 (279)**  
2.23±0.69 (8352)  
2.74±0.53 (5328)  
 Table 1. Numbers are mean ± SD (n). * P< 0.01; *** P < 0.001 vs. other NRN Centers, Student t-test. Abbreviations: NRN, Neonatal Research 
Network; PMA, postmenstrual age; FOC, fronto-occipital circumference    
  
  
  
Retrospective data from Parkland Hospital NICU 2004-2013 (vs. Olsen & Holston curves57,58):  
• 
Term infants:  A PI > 90th percentile was observed in 19% of the neonates, twice the expected proportion. 
PI was greater in Hispanics and non-Hispanic Whites vs. other groups (Table 2).  
  
  
  
Table 2  
Race/ethnicity  
Hispanics  
Non-Hispanic Whites  
African Americans  
Asians  
Ponderal index  
2.68±0.39* (2326)  
2.67±0.39* (1710)  
2.61±0.40 (791)  
2.56±0.33 (128)  
Numbers are mean ±SD (n); *P<0.05 vs. African-Americans and Asians, ANOVA followed by Tukey test  
  
• 
Preterm infants < 35 weeks GA born 2004-2013 and discharged home (Table 3):   
Weight gain velocity59 but not linear growth was lower in 29-34 weeks GA with appropriate BW for GA (AGA) 
infants than in SGA or 23-28 weeks GA infants. Growth insufficiency or small FOC at discharge was more 
frequent in SGA vs. AGA infants and in 23-28 weeks GA vs. 29-34 weeks GA infants. Disproportionate 
growth was more frequent in 23-28 weeks GA vs. 29-34 weeks GA infants.   
  
Table 3  
      GA (weeks) and Size for Age  
<29 weeks AGA   
<29 weeks SGA   
29-34 weeks AGA   
29-34 weeks SGA   
P values   
Growth insufficiency at D/C  
    28% (305)  
     94% (17)  
   8% (2784)  
  69% (304)  
***, ***  
Small FOC at D/C  
     5% (325)  
     53% (17)  
   2% (2880)  
  17% (319)  
***, ***  
Disproportionate growth at D/C  
   36% (354)  
     41% (22)  
   5% (2886)  
    5% (320)  
0.96. ***  

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Weight gain velocity (gxkg-1xd-1)  
  13.3±1.9 (470)   
  13.5±2.4 (48)  
   7.4±6.0 (2989)  
  13.1±3.3 (355)  
***,***,***   
Linear growth velocity (cm/week)       1.0±0.2 (459)  
   1.0±0.2 (47)  
   0.8±1.0 (2949)  
   0.9±0.6(354)  
0.46,0.06,0.24  
Change in weight z score#   
-0.42±0.67 (326)  
+0.52±2.31 (17)  
-0.43±0.43 (2893)  
+0.14±0.38 (319)  
***,**, **  
Change in length z score #  
-1.03±0.79 (325)  
-0.84±0.96 (17)  
-0.32±0.76 (2862)  
-0.23±0.79 (319)  
0.15,***, 0.60  
PI at birth  
2.21±0.29 (470)  
2.14±0.21 (48)  
2.36±0.31 (2988)  
2.17±0.30 (356)  
***,**,*   
PI at D/C  
2.90±0.35 (459)  
3.15±0.80 (47)  
2.45±0.29 (2952)  
2.52±0.33 (354)  
***,***,***   
Change in PI (birth to D/C)  
0.69±0.41 (459)  
1.01±0.76 (47)  
0.09±0.40 (2949)  
0.35±0.42 (354)  
***,***, 0.34  
Abbreviations: GA, gestational age; AGA, appropriate for gestational age; SGA, small for gestational age; #, from birth to discharge; D/C, discharge; 
d, days: FOC, fronto-occipital circumference. Continuous variables are presented as mean±SD (number); comparisons include 2-way ANOVA; P 
values are shown as: ***, < 0.001, ** < 0.01, * < 0.05 for SGA vs. AGA; <29 weeks vs. 29-34 weeks; and interaction GA vs. size for age, 
respectively. Categorical variables are presented as % (total N); comparisons were done using logistic regression; p values are shown as ***,    < 
0.001 for comparisons SGA vs. AGA and <29 weeks vs. 29-34 weeks.   
  
In multivariate analyses (n=3809) taking into account GA and BW z score, the presence of a morbidity* 
affecting growth (n=464) was significantly (P<0.001) associated with greater increase in PI from birth to 
discharge and greater odds of growth insufficiency at discharge.     
* chronic lung disease, intestinal obstruction, gastrointestinal surgery, necrotizing enterocolitis, heart surgery, shunt  for hydrocephalus   
  
 VLBW infants : BW ≤ 1500 grams born in 2004-2013 and discharged home (Table 4):  
Table 4  Many patients had growth insufficiency, small FOC and disproportionate growth at discharge.   
  
GA  
Growth 
insufficiency  
Small FOC  
Disproportionate 
growth  
Weight 
gain  
Linear 
growth  
PI at birth  
PI at D/C  
Change in PI  
28.8±2.7  
26% (999)  
7% (1062)  
18% (1113)  
13.5±3.2  
1.0±0.4  
2.19±0.30  
2.75±0.39  
0.56±0.44  
  
3. Concise Summary of the Project:  
  
Study design: Randomized trial: Following parental consent, infants will be double blind randomized with 1:1 
allocation using a stratified permuted block design by computer, using opaque envelopes. Stratification will be 
by GA: 23-286/7 and 29-346/7 weeks.  
  
Hypotheses: This study is designed to test the hypothesis that, in preterm infants with gestational age < 29 
weeks or with gestational age < 35 weeks and small for gestational age, weight gain velocity from birth to 36 
weeks of postmenstrual age will increase by 2 g x kg-1 x day-1 and length gain will increase by 0.2 cm per week 
with individualized nutrient supplementation.  Secondary hypotheses are that individualized nutrition will 
improve growth and neurodevelopmental outcome and reduce the risk of disproportionate growth and metabolic 
syndrome.   
Primary study endpoint (Aim 1):  
• 
Growth velocity (rate of weight gain [g x kg-1 x day-1] and length velocity [cm x week-1]) from birth to 
36 weeks of PMA or discharge (if discharge is earlier than 36 weeks) will be calculated using Patel’s 
geometric method.59   
  
Secondary endpoints (Aim 2):  
  
In the NICU:   

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• 
Disproportionate growth (abdominal circumference, subscapular skinfold and BMI60 greater than their 
respective 90th percentiles for age) at discharge or 36 weeks of PMA (whatever comes first)  
• 
Air displacement plethysmography at discharge: this will be done using the Pea Pod, a noninvasive 
instrument that is FDA approved for measuring fat in neonates and infants. This apparatus measures 
body volume; taking into account body weight and accepted assumptions, the analysis generates the 
percentage of fat and lean body mass. This is the gold standard method for body composition in 
neonates and young infants, for which normative data are available.61,62  
• 
Blood pressure (systolic and mean, calm or sleeping) at 36 weeks PMA and discharge   
• 
Hypertension, defined as systolic blood pressure >99th percentile for PMA63 for at least 24 hours while 
sleeping or calm  
• 
Serum levels of cholesterol, fats, cystatin C, adipokines and some blood markers that may indicate a 
higher risk for development of diabetes or metabolic syndrome at discharge or 36 weeks of PMA, 
whatever comes first; these blood samples will be obtained at the same time as other blood samples for 
clinical indication  
  
At the Follow-up Clinic (Thrive Clinic, Dr. Roy Heyne), a state-of-the-art facility with >95% follow-up 
rate, at 6 months, 12 & 36 months chronological age & 18-26 months adjusted age (PNA corrected for 
prematurity):   
o Body composition using Pea Pod at 6 months of age  
o Neurodevelopment (Bayley III) scores (cognitive and language composite) at 18-26 months 
adjusted age   
o Findings suggestive of metabolic syndrome: disproportionate growth (excessive fat mass) and 
high systolic blood pressure at each visit;   
o Serum levels of cholesterol, fats, cystatin C, adipokines and some blood markers that may 
indicate a higher risk for development of diabetes or metabolic syndrome at 1 and 3 years of age 
(half a teaspoon of blood); these blood samples will be obtained at the same time as other blood 
samples for clinical indication  
  
Measurement of nutrients in human milk: At present there are no Food and Drug Administration (FDA) 
approved devices for the analysis of nutrient content in human milk samples obtained in the NICU. The 
SprectraStarTM Neonatal Analyzer has been validated18 and has been used in a RCT.7 Twice a year, the device 
will be calibrated against control human milk samples purchased from the Ohio Milk Bank and analyzed using 
state-of-the art chemical analysis, and variability will be assessed. The UT Southwestern Institutional Review 
Board (IRB) has classified this device as non-significant risk device.   
Other measurements:  
• 
Maternal pre-pregnancy weight, height, body mass index (BMI), weight gain during pregnancy, placenta 
weight, antenatal and perinatal maternal diseases (e.g., diabetes mellitus, preeclampsia), antenatal steroids, 
intrauterine growth restriction  
• 
GA: best obstetrical estimate (if no prenatal care, new Ballard score)64  
• 
Race/ethnicity, insurance, socioeconomic status, maternal education  
• 
Birth & 36 weeks measurements: weight, FOC, length (obtained on stadiometer within 3 days of birth; up to 
7 days of life in patients who are initially critical and unstable), BMI (using BW and length on stadiometer 
to improve accuracy), abdominal circumference, mid-arm circumference  

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• 
Comparison of relative changes [(36-week measurement – birth measurement)/birth measurement] in 
weight, length and FOC from birth to 36 weeks PMA; change in z score in weight, length and FOC   
• 
Serial measurements of weight, length (using stadiometer for calculating BMI), linear growth estimated 
from the percent change of heel-knee height measurements65 in the critically ill unstable neonate, FOC, arm 
and thigh muscle circumference, abdominal circumference  
• 
At discharge: triceps and subscapular skinfold thickness   
• 
Nutritional tests: weekly BUN adjusted if necessary for renal dysfunction (see study intervention), albumin, 
electrolytes, phosphate, alkaline phosphatase; if the latter two tests suggest osteopenia: bone radiogram; 
vitamin D levels will be considered in severe cases.  
• 
Days without feeding, human milk vs. formula, days to full feeds, days of central line & parenteral nutrition, 
refeeding syndrome, metabolic acidosis, osteopenia of prematurity, micronutrient deficiency (e.g. zinc, 
essential fatty acids, carnitine), mineral deficiency (e.g., magnesium), type and composition of feeding at 
discharge   
• 
Morbidities affecting growth or neurodevelopment, e.g., congenital infection, genetic anomaly, organ 
failure, bronchopulmonary dysplasia, antibiotics66/sepsis, major surgery, intestinal perforation, necrotizing 
enterocolitis, severe intraventricular hemorrhage, periventricular leukomalacia, congenital anomalies, 
systemic steroids   
• 
Cumulative percentage of enteral intake as breast milk in the NICU, which may influence the effect of the 
intervention and glucose, lipid and apolipoprotein metabolism.19  
• 
Stools will be collected and frozen for later analysis of microbiome diversity, Firmicutes:Bacteroidetes ratio 
and metagenomics. Samples will be collected every other week from randomization to discharge.   
• 
Follow-up at 12 and 36 months chronological age and at 18-26 months adjusted age:   
• 
Weight, length, FOC, abdominal circumference, skinfold thickness, two calm blood pressure measurements 
using Doppler amplification with the exact same protocol as previously described,67,68 history of steroids 
and antibiotics at each visit66   
• 
Neurodevelopment (Bayley III) cognitive and language composite scores at 18-26 months   
• 
Serum levels of cystatin C, creatinine, cholesterol (total, LDL, HDL), triglycerides, Leptin, Adiponectin, 
Resistin, IL-6 and TNF alpha at 1 and at 3 years of age (half a teaspoon of blood)  
• 
Whole-body Dexascan to analyze body composition including percentage of fat at 1 and 3 years of age  
   
Procedures: Patients will be randomized to either (a) Optimized and individualized nutrition by adjusting milk 
fortification based on daily measurements of macronutrients in mother’s own milk33,47 or information on milk 
from the milk bank or (b) optimized (standard of care at Parkland), i.e., assuming macronutrient concentration 
in human milk based on available literature and summing enteral and intravenous protein intake. Patients will be 
followed for growth parameters in the neonatal intensive care unit and for growth, neurodevelopment and signs 
suggestive of metabolic syndrome in the low birth weight clinic until 3 years of age.  
  
Maximum number of consented patients; 200; this will allow attrition for comfort care, deaths before 36 weeks 
PMA and withdrawal from the study; we expect to recruit approximately 150 patients into the study with a goal 
of 100 patients reaching endpoint at 36 weeks PMA  
  
Duration of the study: 6 years: recruitment for 2 years, follow-up for 3 years, analysis for 1 year  
  
Reason for removing from the study: comfort care, withdrawal by the parents  
  
4. Study Procedures:   

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Screening:  
  
Screening for potential candidates for the RCT will be done by the investigators who will run the quality 
improvement project that started in May 2015: Optimizing Individual Nutrition in Preterm Very Low Birth 
Weight Infants (STU 102014-045).   
Nutrient intake is decided by the clinical care team with recommendations by dietitians, using published 
data on breast milk composition, published recommendations, weekly rate of growth, feeding tolerance and 
measurements of serum BUN (> 10 mg/dl), albumin (> 3 g/dl), electrolytes, phosphate and alkaline phosphatase 
and bone radiograms as needed. Weight and length at birth were previously obtained by nurses and classified 
using 1963 Lubchenco’s growth curve.69 Size after birth was assessed using the 2003 Fenton’s growth curve,70, 
length curve including crown-heel measurements (obtained by nurses using paper tape or dietitians using a 
stadiometer) and height calculated from heel-knee height, mid-arm circumference and abdominal 
circumference.   
  
New curves have become available on EPIC: weight, length and FOC57 in 2015 and BMI60 in 2016. The 
research team have implemented 2010 Olsen’s curve57 for birth and subsequent measurements up to 39-40 
weeks, 2013 Fenton’s curves71 up to 50 weeks PMA, and WHO curves72 starting at 40-41 weeks), 2015 
Holston’s (BMI)),60 and serial anthropometric measurements to compare growth parameters with expected 
values at each stage. Weight gain velocity will be calculated as described by Patel.59 Linear growth in critical 
unstable infants will be followed using heel-knee height.65 BMI will be calculated using only lengths measured 
on a stadiometer or an infantometer. Nutrition will be optimized using serum BUN goals with adjustment for 
serum creatinine levels compared to normal values for age.4 This approach will be standard care, which will be 
the intervention in any patient entered in the RCT.  
  
Randomization:   
Following parental consent, infants will be double blind randomized with 1:1 allocation using a stratified 
permuted block design by computer, using opaque envelopes in 3 strata: AGA 23-286/7 weeks, SGA 23-286/7 
weeks and SGA 29-346/7 weeks. Twins and multiples will be randomized to the same arm of the study.  
Blinding: Only the dietitian, infant formula technician and a statistician will be aware of the allocation. The 
other members of the research team, the care givers and the parents will not know the allocation.  
  
Study intervention:   
Patients will be randomized to either  
(1) Optimized and individualized nutrition by adjusting milk fortification based on daily measurements of 
macronutrients in mother’s own milk or information on milk from the milk bank    
(2) Or optimized (standard of care at Parkland), i.e., assuming macronutrient concentration in human milk 
based on available literature and summing enteral and intravenous protein intake   
  
Data collection in the NICU will be identical to that for other patients who are part of the QI protocol submitted 
to the IRB: STU 102014-045: Optimizing Individual Nutrition in Preterm Very Low Birth Weight Infants.   
  
Procedures done for research during follow up until 3 years of age include:  
• 
skinfold thickness measurements   
• 
Neurodevelopment exam (Bayley III cognitive and language composite scores) for patients who 
are not enrolled in the NICHD follow-up study (<27 weeks GA)  
• 
(only if parent checks the box on the consent form): half a teaspoon of blood sample; this blood 
will be kept in the freezer at -80 degrees for 10 years for measurement of cholesterol, fats, and 

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11  
some blood markers that may indicate a higher risk for development of diabetes or metabolic 
syndrome.    
• 
(only if parent checks the box on the consent form): whole-body Dexascan to analyze body 
composition including percentage of fat at 1 and 3 years of age. The radiation dose is 
approximately 1% of the Annual US Avg. Natural Background.  
Due to COVID-19 restrictions, the 18-26 months Adjusted Age Follow-up extended up to one year 
from the end of the study window. 
 
5. Criteria for Inclusion of Subjects:  
  
Patients born at Parkland Hospital & Health System  
Gestational age < 29 weeks or gestational age < 35 weeks and small for gestational age   
Maternal plan to breastfeed or to use milk from the milk donor bank From 
birth to 1 week of life  
6. Criteria for Exclusion of Subjects:  
Comfort care only  
Patients with major congenital abnormalities  
Patients who are too unstable for the first 7 days to have an accurate length measurement  
  
7. Sources of Research Material:  
  
• 
NICU database  
• 
Duncan’s database  
• 
Medical records from Parkland NICU on EPIC   
• 
Medical records from the low birth weight clinic (paper records at the clinic or EPIC)  
  
8. Recruitment Methods and Consenting Process:  
  
Potential subjects may be patients of the investigators.  
  
The researchers will check every day whether a baby is born either very preterm (born at less than 29 weeks of 
gestational age, that is about three months before expected due dates) or small for gestational age (weight less 
than the majority [90%] of babies born at same gestational age as your baby) and less than 35 weeks of 
gestational age. They will ask the mother whether she plans to breastfeed her baby or to have her baby receive 
milk from the donor’s milk bank.  
  
Non-English speaking subjects will be consented using informed consent; a Spanish consent will be available.   
  
All research personnel involved in recruitment has been trained in research ethics and is used to openly 
communicate with families in the NICU.  
  
Privacy will be assured by talking with the parents in a private room or using soft voice.   
  
All research personnel involved in recruitment has been trained in research ethics and is used to openly 
communicate with families in the NICU.  

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12  
  
If parents are not available, the patient will not be eligible for consenting.   
  
Parents will be paid $40.00 at each research visit at the low birth weight clinic to reimburse them for parking or 
travel cost. If they stop taking part in this study or are withdrawn by the research team, they will receive 
payment for only the visits they have completed.  For example, if they complete 3 study visits they will be paid 
$120.00.  
  
9. Potential Risks:  
  
Possible side effects include feeding intolerance, high BUN and metabolic acidosis.   
Excessive fortification of milk can cause feeding intolerance (full stomach, more residuals [milk aspirated by 
the nurse] in the stomach before next feeding). Nurses check the baby before each feed and inform the doctor 
about any sign of feeding intolerance; the doctor may decide to adjust the amount of volume of milk and the 
amount of fortification if necessary.   
Excessive protein intake may raise blood urea nitrogen or BUN, and decrease serum bicarbonate concentration. 
Blood urea nitrogen (BUN), creatinine and serum electrolytes are measured weekly. If a high BUN: creatinine 
ratio or a low serum bicarbonate concentration is observed the doctor may decide to decrease the amount of 
protein supplementation.  
Being randomized to the standard arm may, in comparison with the other arm, increase the risk of insufficient 
nutrition, decreased growth and neurodevelopment. If the baby does not grow well enough, the doctor may 
decide to give more calories; this may cause the baby to gain fat.    
Being randomized to individualized nutrition may, in comparison with the other arm, cause excessive weight 
gain.  
If the parent consents to the Dexascan, the additional radiation dose is approximately 1% of the Annual US 
Avg. Natural Background.  
SprectraStarTM 2500 XL Neonatal Analyzer   
Upon submission of the original protocol, this device was considered by the IRB as a non-significant risk 
device. We believe this device is a non-significant risk device because   
1. 
Measurement of nutrients in human milk has been used in several centers to adjust fortification of 
human milk for preterm infants, and has been shown in one randomized trial to improve growth without any 
risk to the infants.  
2. 
Infants randomized to the treatment arm will have growth velocity and BUN and serum electrolytes 
measured regularly, as is done for standard of care, to make sure that adjustment of human milk fortification is 
not exceeding needs for each infant.    
3. 
The Institutional Review Board of Baylor College of Medicine and Affiliated Hospitals and the 
University of Texas Health Science Center at San Antonio have approved a randomized trial that used this 
device and was conducted at Texas Childrens and San Antonio without an IDE (Hair et al, attached).   
  
  
Near infrared (NIR) spectrophotometry has been used to analyze material of solid and liquid states uses 
the wavelength spectrum 1200 to 2400 nm. Commercially available NIR spectrophotometers have been used to 

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13  
measure carbohydrate, fat and protein content in animal milk (cow, sheep, donkey and goat) and human milk. 
These analyzers are used routinely to analyze nutrients in donor’s milk provided to NICUs for preterm  
infants.7,17   
  
The SprectraStarTM 2500 XL Neonatal Analyzer is not approved by the FDA. The SpectraStar 2400 
Near Infrared Analyzer (Unity Scientific, Columbia, MD, USA) has been validated against reference chemical 
analysis of protein, carbohydrate and fat (University of Guelph Laboratory Services, Guelph, Canada) in 42 
samples (32 morning, 5 evening, 3 hind milk and 2 foremilk samples) of human milk by Sauer and Kim.18 
Using these samples, the authors generated a calibration curve, which was tested against a second set of 10 
samples (6 morning, 0 evening, 1 hind milk and 3 foremilk samples) and their reference values. After logistic 
regression analysis, the validation set had a correlation (r2) of 0.91 for carbohydrates, 0.95 for fat and 0.95 for 
protein.   
  
Hair et al have used the SpectraStar 2400 to measure fat content on human milk in a randomized trial 
involving 78 preterm infants with birth weight 750-1250 grams.7 In this trial, they found that the addition of 
milk cream based on results of milk nutrients to calculate individualized supplementation improved weight and 
length velocity. There was no difference in necrotizing enterocolitis, sepsis or death.   
  
Several observational studies have assessed individualized fortification of milk using similar devices 
using near infrared spectroscopy to measure nutrients in human milk for preterm infants in the NICU. These 
studies have shown improved growth without side effects.8-16   
  
  
  
Loss of Confidentiality  
Any time information is collected; there is a potential risk for loss of confidentiality.  Every effort will be made 
to keep your information confidential; however, this cannot be guaranteed.   
Risks of Blood Drawing  
If the parent agrees, the child will have half a teaspoon of blood collected at 3 years of age for the study. Many 
children at this age have blood drawn for routine care; we will try to obtain the research blood sample at the 
same time as blood is drawn for clinical care. Risks associated with drawing blood from your child’s arm 
include minimal discomfort and/or bruising.  Infection, excess bleeding, clotting, and/or fainting also are 
possible, although unlikely.  
Other Risks  
There may possibly be other side effects that are unknown at this time.   
10. Subject Safety and Data Monitoring:  
  
How will risks be minimized or prevented?    
Potential risks and discomforts will be minimized to the greatest extent possible by using procedures such as 
appropriate training of personnel, monitoring, withdrawal of the subject upon evidence of difficulty or adverse 
event; referral for treatment, counseling or other necessary follow-up.  

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14  
Nurses check the baby before each feed and inform the doctor about any sign of feeding intolerance; the doctor 
may decide to adjust the amount of volume of milk and the amount of fortification if necessary.   
Blood urea nitrogen (BUN) and serum electrolytes are measured weekly. If a high BUN (or BUN: creatinine 
ratio) or a low serum bicarbonate concentration is observed the doctor may decide to decrease the amount of 
protein supplementation.  
Many children at 3 years of age have blood drawn for routine care; we will try to obtain the research blood 
sample at the same time as blood is drawn for clinical care.  
  
Type of Research Data or Events to be Monitored:  
  
Study accruals  
Protocol deviations: errors in allocation to study arm  
Protocol violations: error in amount of fortifier or protein supplementation  
Unanticipated problems: NEC, death, sepsis  
Adverse events: feeding intolerance, high BUN (or high BUN: creatinine ratio), low serum bicarbonate 
concentration  
  
Methods and Frequency of Analysis:  
  
Method: review of  
  
report from the database entry   
  
yearly results of the control samples analyses  
 adverse events and unanticipated adverse events   
changes 
in risk/benefits   
  
Frequency: meetings every 6 months after report from the database  
  
Data collection form is attached (spreadsheet)   
  
Person(s) Responsible for Data Monitoring:  
  
Internal DSMC:   
The randomized trial has an internal data safety monitoring committee, which meets every 6 mon and reviews 
the accumulated data. The closed portion of the committee, including Julide Sisman, MD and Larry Brown, MS, 
has access to all data including blinded data, and reviews any potential chart that may raise concern, and makes 
recommendations to the full committee to either stop or continue the study. The rest of the committee, including 
CR Rosenfeld, MD, R Heyne, MD and Maria Caraig, RN, research coordinator, and LP Brion, MD, do not have 
access to blinded data.  
  
Name of the person responsible for submitting reports of unanticipated problems, adverse events, protocol 
deviations and protocol violations to the IRB and sponsor: PI  
  
The PI will send the data safety reports to the IRB.   
  

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15  
Reporting Unanticipated Problems, Adverse Events, Protocol Deviations and Protocol 
Violations:  
• 
PI will report adverse events to the IRB immediately  
• 
PI will report safety reports and DSMC reports to the IRB.   
  
Stopping Rules:  
1. Specific stopping rules:   
• 
Less than 10 patients recruited in 12 months  
• 
Mortality in enrolled patients significantly higher than in non-enrolled patients (P<0.01)  
• 
Necrotizing enterocolitis in enrolled patients more frequent than in non-enrolled patients 
(p<0.01)  
1. Action indicated by the specific stopping rule:   
PI will notify the IRB, all research team members and the funding agency.   
  
Procedures and Time Frames for Communicating Outcomes:  
An open report of the accrual and demographics will be provided to the DSMC by the research team. A closed 
report of mortality and necrotizing enterocolitis will be provided to the DSMC by a statistician.  
The report of the DSMC will be provided to the PI and to the IRB.  
  
Precautions for Maintaining Data Integrity:  
Random selection of data will be checked by the PI and the DSMC for completeness and integrity.   
  
11. Procedures to Maintain Confidentiality:  
  
Identified data are entered by a dedicated Research Nurse (STU 102010-064) or a dietitian into a secure 
computer database. The computer used for this data entry and the database itself are both password-protected 
and can only be accessed by the research nurse and the physicians listed on the protocol. The database will be 
kept on a password-protected subdirectory of a designated UTSW network drive. All the data collection sheets 
are stored in a secure cabinet. Data for study analysis will be de-identified with a link kept on a secure database.  
  
Only members of the research team will have access to the data. Confidentiality will be assured by using 
encrypted electronic devices for transmission of identified information.   
  
Identifiers will be deleted once data on the same patients have been merged across databases. Data 
for study analysis will be de-identified with a link kept on a secure database.   
  
Privacy will be maintained by speaking with the parents in quiet tones with only authorized persons present in a 
private room or behind a screen. Identification of the study subject is done in EPIC.  
  
12. Potential Benefits:  
  
Benefits to the patient:  
There may or may not be direct benefits to the patient. The researchers cannot guarantee that he or she will 
benefit from participation in this research. We do not know which group the baby will be in; it is possible that 
he or she may grow faster if he or she is randomized to individualized nutrition and if measurements of milk 
nutrients inform the nutritionists and infant formula personnel suggest more fortifier may be helpful. It is 

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16  
possible that he or she may have less feeding problems if he or she is randomized to standard nutrition. It is 
possible that the researchers may identify a problem with your baby’s growth or blood pressure; it that is the 
case they will let the mother know. It is possible that being in either arm of the study may reduce the risk for 
neurodevelopmental delay or metabolic syndrome as an adult.  
  
Benefits to the society:  
We hope the information learned from this study will benefit others with prematurity or small size for 
gestational age in the future.  Information gained from this research could lead to better growth and 
neurodevelopment and less metabolic syndrome.  
  
14. Biostatistics:  
  
The primary outcome variable (growth) will be analyzed by intention to treat (i.e., as randomized). Continuous 
variables including the primary outcome will be analyzed using Student’s t-test or analysis of variance and a 
generalized linear model (to determine the effect of the intervention while taking into account co-variates and 
confounding variables). Dichotomous variables will be analyzed using chi-square analysis and by estimating 
relative risk using robust Poisson regression in a generalized estimating equation model. Subgroup analyses will 
be done to compare the 3 strata (AGA 23-28 weeks, SGA 23-28 weeks and SGA 29-34 weeks) and to compare 
SGAs due to insufficient calories (e.g., preeclampsia, low placental insertion) vs. constitutionally small 
neonates (e.g., congenital infection, genetic anomaly, short parents). A probability value <0.05 will be 
considered statistically significant. Secondary outcome variables will be analyzed according to appropriate 
statistical techniques.  
Sample size analysis: Based on the number of patients delivered at Parkland during the last 10 years, we expect 
that 342 (1140x3/10) eligible neonates will be delivered over 3 years. We anticipate enrolling half in the study 
and expect that 2/3 will survive to 36 weeks PMA. Thus we will enroll 150 patients to yield a 100 patients 
available for the primary outcome and to have 80% power using 2-tailed Student t-test (alpha error 0.025) to 
detect an increase in weight gain velocity in the NICU by 2 g x kg-1 x day-1 (standard deviation 3 g x kg-1 x     
day-1) and 95% power (alpha error 0.001) to detect an increase in length velocity by 0.2 cm per week (standard 
deviation 0.2 cm per week), taking into account clustering due to twins and multiples. We will have >80% 
power for both outcomes (alpha error 0.05).   
  
References  
1. Adamkin DH, Radmacher PG. Fortification of human milk in very low birth weight infants (VLBW < 1500 
g birth weight). Clin Perinatol 2014 Jun;41(2):405-21. PMID: 24873840  
2. Arslanoglu S, Moro GE, Ziegler EE. Adjustable fortification of human milk fed to preterm infants: does it 
make a difference? J Perinatol. 2006 Oct;26(10):614-21. PMID: 16885989  
3. Alan S, Atasay B, Cakir U, Yildiz D, Kilic A, Kahvecioglu D, Erdeve O, Arsan S An intention to achieve 
better postnatal in-hospital-growth for preterm infants: Adjustable protein fortification of human milk. Early 
Hum Dev. 2013 Dec;89(12):1017-2 PMID: 24035039  
4. Moro GE, Minoli I, Ostrom M, Jacobs JR, Picone TA, Räihä NC, Ziegler EE. Fortification of human milk:  
evaluation of a novel fortification scheme and of a new fortifier. J Pediatr Gastroenterol Nutr. 1995 
Feb;20(2):162-72. PMID: 7714681  

STU102014-056, Brion, FormA-ResearchProtocol, Mod_20, 06-11-20 
 
17  
5. Arslanoglu S, Moro GE, Ziegler EE, The Wapm Working Group On Nutrition. Optimization of human milk 
fortification for preterm infants: new concepts and recommendations. J Perinat Med. 2010 May;38(3):233-8. 
PMID: 20184400  
6. O'Neill EF, Radmacher PG, Sparks B, Adamkin DH. Creamatocrit analysis of human milk overestimates fat 
and energy content when compared to a human milk analyzer using mid-infrared spectroscopy. J Pediatr 
Gastroenterol Nutr. 2013 May;56(5):569-72. PMID: 23274342  
7. Hair AB, Blanco CL, Moreira AG, Hawthorne KM, Lee ML, Rechtman DJ, Abrams SA. Randomized Trial 
of Human Milk Cream as a Supplement to Standard Fortification of an Exclusive Human Milk-Based Diet 
in Infants 750-1250 g Birth Weight. J Pediatr. 2014 Aug 13. PMID: 25130571  
8. de Halleux V, Rigo J. Variability in human milk composition: benefit of individualized fortification in 
verylow-birth-weight infants. Am J Clin Nutr. 2013 Aug;98(2):529S-35S. PMID: 23824725  
9. Corvaglia L, Aceti A, Paoletti V, Mariani E, Patrono D, Ancora G, Capretti MG, Faldella G. Standard 
fortification of preterm human milk fails to meet recommended protein intake: Bedside evaluation by 
NearInfrared-Reflectance-Analysis. Early Hum Dev. 2010 Apr;86(4):237-40. PMID: 20447779  
10. Corvaglia L, Battistini B, Paoletti V, Aceti A, Capretti MG, Faldella G. Near-infrared reflectance analysis to 
evaluate the nitrogen and fat content of human milk in neonatal intensive care units. Arch Dis Child Fetal 
Neonatal Ed. 2008 Sep;93(5):F372-5. PMID: 18192331  
11. Aceti A, Corvaglia L, Paoletti V, Mariani E, Ancora G, Galletti S, Faldella G. Protein content and 
fortification of human milk influence gastroesophageal reflux in preterm infants. J Pediatr Gastroenterol 
Nutr. 2009 Nov;49(5):613-8. PMID: 19633575  
12. Di Natale C1, Coclite E, Di Ventura L, Di Fabio S. Fortification of maternal milk for preterm infants. J 
Matern Fetal Neonatal Med. 2011 Oct;24 Suppl 1:41-3. PMID: 21883045  
13. Polberger S, Lönnerdal B. Simple and rapid macronutrient analysis of human milk for individualized 
fortification: basis for improved nutritional management of very-low-birth-weight infants? J Pediatr 
Gastroenterol Nutr. 1993 Oct;17(3):283-90. PMID: 8271128  
14. Polberger S, Räihä NC, Juvonen P, Moro GE, Minoli I, Warm A. Individualized protein fortification of 
human milk for preterm infants: comparison of ultrafiltrated human milk protein and a bovine whey 
fortifier. J Pediatr Gastroenterol Nutr. 1999 Sep;29(3):332-8. PMID: 10468001  
15. Polberger S, Lönnerdal B. Simple and rapid macronutrient analysis of human milk for individualized 
fortification: basis for improved nutritional management of very-low-birth-weight infants? J Pediatr 
Gastroenterol Nutr. 1993 Oct;17(3):283-90. PMID: 8271128  
16. Radmacher PG, Lewis SL, Adamkin DH. Individualizing fortification of human milk using real time human 
milk analysis. J Neonatal Perinatal Med. 2013 Jan 1;6(4):319-23. PMID: 24441088  
17. Wojcik KY1, Rechtman DJ, Lee ML, Montoya A, Medo ET. Macronutrient analysis of a nationwide sample 
of donor breast milk. J Am Diet Assoc. 2009 Jan;109(1):137-40. PMID: 19103335  
18. Sauer CW, Kim JH. Human milk macronutrient analysis using point-of-care near-infrared 
spectrophotometry. Journal of Perinatology (2011) 31, 339–343. PMID: 21052045  
19. van der Schoor SR, Wattimena DL, Huijmans J, Vermes A, van Goudoever JB. The gut takes nearly all: 
threonine kinetics in infants. Am J Clin Nutr. 2007 Oct;86(4):1132-8. PMID: 17921393  
20. van der Schoor SR, Schierbeek H, Bet PM, Vermeulen MJ, Lafeber HN, van Goudoever JB, van Elburg 
RM. Majority of dietary glutamine is utilized in first pass in preterm infants. Pediatr Res. 2010 
Feb;67(2):194-9. PMID: 19809373  
21. van Goudoever JB, Vlaardingerbroek H, van den Akker CH, de Groof F, van der Schoor SR. Amino acids 
and proteins. World Rev Nutr Diet. 2014;110:49-63. PMID: 24751621  
22. Barker DJP. The Developmental Origins of Adult Disease. Journal of the American College of Nutrition, 
Vol. 23, No. 6, 588S–595S (2004). PMID: 15640511  

STU102014-056, Brion, FormA-ResearchProtocol, Mod_20, 06-11-20 
 
18  
23. Parkinson JR, Hyde MJ, Gale C, Santhakumaran S, Modi N. Preterm birth and the metabolic syndrome in 
adult life: a systematic review and meta-analysis. Pediatrics. 2013 Apr;131(4):e1240-63. PMID: 23509172 
24. Skilton MR, Viikari JS, Juonala M, Laitinen T, Lehtimäki T, Taittonen L, Kähönen M, Celermajer DS, 
Raitakari OT. Fetal growth and preterm birth influence cardiovascular risk factors and arterial health in 
young adults: the Cardiovascular Risk in Young Finns Study. Arterioscler Thromb Vasc Biol. 2011 
Dec;31(12):2975-81. PMID: 21940950  
25. Kerkhof GF, Breukhoven PE, Leunissen RW, Willemsen RH, Hokken-Koelega AC. Does preterm birth 
influence cardiovascular risk in early adulthood? J Pediatr. 2012 Sep;161(3):390-396.e1. PMID: 22578582 26. 
Belfort MB, Rifas-Shiman SL, Sullivan T, Collins CT, McPhee AJ, Ryan P, Kleinman KP, Gillman MW, 
Gibson RA, Makrides M. Infant growth before and after term: effects on neurodevelopment in preterm infants. 
Pediatrics. 2011 Oct;128(4):e899-906. PMID: 21949135  
27. Vohr BR, Allan W, Katz KH, Schneider KC, Ment LR. Early predictors of hypertension in prematurely 
born adolescents. Acta Paediatr. 2010 Dec;99(12):1812-8. PMID: 20586997  
28. Irving RJ, Belton NR, Elton RA, Walker BR. Adult cardiovascular risk factors in premature babies. Lancet 
2000;355:2135-6. PMID: 10902631  
29. Hack M, Schluchter M, Cartar L, Rahman M. Blood pressure among very low birth weight (<1.5 kg) young 
adults. Pediatr Res 2005;58:677-84. PMID: 16192252  
30. Hovi P, Andersson S, Raikkonen K, Strang-Karlsson S, Jarvenpaa AL, Eriksson JG, et al. Ambulatory blood 
pressure in young adults with very low birth weight. J Pediatr 2010;156:54-9.e1. PMID: 20008427  
31. Keijzer-Veen MG, Finken MJ, Nauta J, Dekker FW, Hille ET, Frolich M, et al. Is blood pressure increased  
19 years after intrauterine growth restriction and preterm birth? A prospective follow-up study in The 
Netherlands. Pediatrics 2005;116:725-31. PMID: 16140714  
32. Fabricius-Bjerre S, Jensen RB, Færch K, Larsen T, Mølgaard C, Michaelsen KF, Vaag A, Greisen G. 
Impact of birth weight and early infant weight gain on insulin resistance and associated cardiovascular risk 
factors in adolescence. PLoS One. 2011;6(6):e20595. PMID: 21655104  
33. Finken MJ, Keijzer-Veen MG, Dekker FW, Frölich M, Hille ET, Romijn JA, Wit JM; Dutch POPS-19 
Collaborative Study Group. Preterm birth and later insulin resistance: effects of birth weight and postnatal 
growth in a population based longitudinal study from birth into adult life. Diabetologia. 2006 
Mar;49(3):478-85. PMID: 16450090   
34. Elks CE, Loos RJ, Sharp SJ, Langenberg C, Ring SM, Timpson NJ, Ness AR, Davey Smith G, Dunger DB, 
Wareham NJ, Ong KK.Genetic markers of adult obesity risk are associated with greater early infancy 
weight gain and growth. PLoS Med. 2010 May 25;7(5):e1000284. PMID: 20520848  
35. Kerkhof GF, Leunissen RW, Hokken-Koelega AC. Early origins of the metabolic syndrome: role of small 
size at birth, early postnatal weight gain, and adult IGF-I. J Clin Endocrinol Metab. 2012 Aug;97(8):2637- 
43. PMID: 22564668  
36. Järvisalo MJ, Hutri-Kähönen N, Juonala M, Mikkilä V, Räsänen L, Lehtimäki T, Viikari J, Raitakari OT. 
Breast feeding in infancy and arterial endothelial function later in life. The Cardiovascular Risk in Young 
Finns Study. Eur J Clin Nutr. 2009 May;63(5):640-5. PMID: 18285807  
37. Pettitt DJ, Forman MR, Hanson RL, Knowler WC, Bennett PH. Breastfeeding and incidence of non-
insulindependent diabetes mellitus in Pima Indians. 1. Lancet. 1997 Jul 19;350(9072): 166-8.PMID: 
9250183  
38. Johnson MJ, Wootton SA, Leaf AA, Jackson AA. Preterm birth and body composition at term equivalent 
age: a systematic review and meta-analysis. Pediatrics. 2012 Sep;130(3):e640-9. PMID: 22891222  
39. Sjöström SE, Öhlund I, Ahlsson F, Engström E, Fellman V, Hellström A, Källén K, Norman M, Olhager E, 
Serenius F, Domellöf M. Nutrient intakes independently affect growth in extremely preterm infants: results 
from a population-based study. Acta Paediatr. 2013 Nov;102(11):1067-74. PMID: 23855971  

STU102014-056, Brion, FormA-ResearchProtocol, Mod_20, 06-11-20 
 
19  
40. Duncan AF, Heyne RJ, Morgan JS, Ahmad N, Rosenfeld CR. Elevated systolic blood pressure in preterm 
very-low-birth-weight infants ≤3 years of life. Pediatr Nephrol. 2011 Jul;26(7):1115-21. PMID: 21399900  
41. Frankfurt JA, Duncan AF, Heyne RJ, Rosenfeld CR. Renal function and systolic blood pressure in verylow-
birth-weight infants 1-3 years of age.  Pediatr Nephrol. 2012 Dec;27(12):2285-91. PMID: 22832668  
42. Remely M, Haslberger AG.The microbial epigenome in metabolic syndrome. Mol Aspects Med. 2017 
Apr;54:71-77. PMID: 27670623  
43. Koliada A, Syzenko G, Moseiko V, Budovska L, Puchkov K, Perederiy V, Gavalko Y, Dorofeyev A, 
Romanenko M, Tkach S, Sineok L, Lushchak O, Vaiserman A. Association between body mass index and 
Firmicutes/Bacteroidetes ratio in an adult Ukrainian population. BMC Microbiol. 2017 May 22;17(1):120. 
PMID: 28532414  
44. White RA1, Bjørnholt JV, Baird DD, Midtvedt T, Harris JR, Pagano M, Hide W, Rudi K, Moen B, Iszatt N, 
Peddada SD, Eggesbø M. Novel developmental analyses identify longitudinal patterns of early gut 
microbiota that affect infant growth. PLoS Comput Biol. 2013;9(5):e1003042. PMID: 23671411  
45. Dogra S, Sakwinska O, Soh SE, Ngom-Bru C, Brück WM, Berger B, Brüssow H, Lee YS, Yap F, Chong 
YS, Godfrey KM, Holbrook JD; GUSTO Study Group. Dynamics of infant gut microbiota are influenced by 
delivery mode and gestational duration and are associated with subsequent adiposity. MBio. 2015 Feb 
3;6(1). PMID: 25650398  
46. Robinson EL, Thompson WL. Effect on weight gain of the addition of Lactobacillus acidophilus to the 
formula of newborn infants. J Pediatr. 1952 Oct;41(4):395-8. PMID: 12991171  
47. Gregory KE, Samuel BS, Houghteling P, Shan G, Ausubel FM, Sadreyev RI, Walker WA. Influence of 
maternal breast milk ingestion on acquisition of the intestinal microbiome in preterm infants. Microbiome. 
2016 Dec 30;4(1):68. PMID: 28034306  
48. Zeissig S, Blumberg RS. Life at the beginning: perturbation of the microbiota by antibiotics in early life and 
its role in health and disease. Nat Immunol. 2014 Apr;15(4):307-10. PMID: 24646587  
49. Stephens BE, Vohr BR. Protein intake and neurodevelopmental outcomes. Clin Perinatol. 2014 
Jun;41(2):323-9. PMID: 24873835   
50. Ehrenkranz RA, Das A, Wrage LA, Poindexter BB, Higgins RD, Stoll BJ, Oh W; Eunice Kennedy Shriver 
National Institute of Child Health and Human Development Neonatal Research Network. Early nutrition 
mediates the influence of severity of illness on extremely LBW infants. Pediatr Res. 2011 Jun;69(6):522-9. 
PMID: 21378596  
51. Ramel SE, Demerath EW, Gray HL, Younge N, Boys C, Georgieff MK. The Relationship of Poor Linear 
Growth Velocity with Neonatal Illness and Two-Year Neurodevelopment in Preterm Infants. Neonatology 
2012;102:19-24. PMID: 22441508  
52. De Jesus LC, Pappas A, Shankaran S, Li L, Das A, Bell EF, Stoll BJ, Laptook AR, Walsh MC, Hale EC,  
Newman NS, Bara R, Higgins RD; Eunice Kennedy Shriver National Institute of Health and Human 
Development Neonatal Research Network. Outcomes of small for gestational age infants born at <27 weeks' 
gestation. J Pediatr. 2013 Jul;163(1):55-60.e1-3. PMID: 23415614  
53. Isaacs EB, Morley R, Lucas A. Early diet and general cognitive outcome at adolescence in children born at 
or below 30 weeks gestation. J Pediatr. 2009 Aug;155(2):229-34. PMID: 19446846  
54. Burattini I, Bellagamba MP, Spagnoli C, D'Ascenzo R, Mazzoni N, Peretti A, Cogo PE, Carnielli VP; 
Marche Neonatal Network. Targeting 2.5 versus 4 g/kg/day of amino acids for extremely low birth weight 
infants: a randomized clinical trial. J Pediatr. 2013 Nov;163(5):1278-82.e1. PMID: 23941670  
55. Goldman HI, Goldman J, Kaufman I, Liebman OB. Late effects of early dietary protein low-birth-weight 
infants.  J Pediatr. 1974 Dec;85(6):764-9. PMID: 4472449  
56. Fenton TR, Premji SS, Al-Wassia H, Sauve RS. Higher versus lower protein intake in formula-fed low birth 
weight infants (Review). Cochrane Database Syst Rev. 2014 Apr 21;4:CD003959. PMID: 24752987  

STU102014-056, Brion, FormA-ResearchProtocol, Mod_20, 06-11-20 
 
20  
57. Olsen IE, Groveman SA, Lawson ML, Clark RH, Zemel BS. New intrauterine growth curves based on 
United States data. Pediatrics. 2010 Feb;125(2):e214-24. PMID: 20100760  
58. Holston A, Stokes T, Olsen C, Choi YS, Curtis J, Higginson J, Adimora C, Hunt CE. Novel noninvasive 
anthropometric measure in preterm and full-term infants: normative values for waist circumference:length 
ratio at birth. Pediatr Res. 2013 Sep;74(3):299-306. PMID: 23797534  
59. Patel AL, Engstrom JL, Meier PP, Jegier BJ, Kimura RE. Calculating postnatal growth velocity in very low 
birth weight (VLBW) premature infants. J Perinatol. 2009 Sep;29(9):618-22. PMID: 1946159  
60. Olsen IE, Lawson ML, Ferguson AN, Cantrell R, Grabich SC, Zemel BS, Clark RH.BMI curves for preterm infants. 
Pediatrics. 2015 Mar;135(3):e572-81. PMID: 25687149  
61. Ellis KJ, Yao M, Shypailo RJ, Urlando A, Wong WW, Heird WC. Body-composition assessment in infancy: 
airdisplacement plethysmography compared with a reference 4-compartment model. Am J Clin Nutr 2007;85:90–5. 
PMID: 17209182  
62. Roggero P, Giannì ML, Amato O, Orsi A, Piemontese P, Cosma B, Morlacchi L, Mosca F. Postnatal growth failure in 
preterm infants: recovery of growth and body composition after term. Early Hum Dev. 2008 Aug;84(8):555-9. PMID: 
18329828   
63. Dionne JM, Abitbol CL, Flynn JT. Hypertension in infancy: diagnosis, management and outcome. Pediatr Nephrol. 
2012 Jan;27(1):17-32. PMID: 21258818  
64. Donovan EF, Tyson JE, Ehrenkranz RA, Verter J, Wright LL, Korones SB, Bauer CR, Shankaran S, Stoll BJ, 
Fanaroff AA, Oh W, Lemons JA, Stevenson DK, Papile LA. Inaccuracy of Ballard scores before 28 weeks' gestation. 
National Institute of Child Health and Human Development Neonatal Research Network. J Pediatr. 1999 Aug;135(2 
Pt 1):147-52. PMID: 10431107  
65. Griffin IJ, Pang NM, Perring J, Cooke RJ. Knee-heel length measurement in healthy preterm infants. Arch Dis Child 
Fetal Neonatal Ed. 1999 Jul;81(1):F50-5. PMID: 10375363   
66. Bailey LC, Forrest CB, Zhang P, Richards TM, Livshits A, DeRusso PA. Association of Antibiotics in Infancy With 
Early Childhood Obesity. JAMA Pediatr. doi:10.1001/jamapediatrics 2014.1539  PMID: 25265089  
67. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and 
Adolescents: The Fourth Report on the diagnosis, evaluation and treatment of high blood pressure in children and 
adolescents. Pediatrics 144:555–576. PMID: 1528627  
68. Duncan AF, Rosenfeld CR, Morgan JS, Ahmad N, Heyne RJ. Interrater reliability and effect of state on blood 
pressure measurements in infants 1 to 3 years of age. Pediatrics. 2008 Sep;122(3):e590-4. PMID 18762  
69. Lubchenco LO, Hansman C, Dressler M, Boyd D. Intrauterine growth as estimated from liveborn 
birthweight data at 24 to 42 weeks of gestation. Pediatrics. 1963 Nov;32:793-800. PMID: 14075621  
70. Fenton TR. A new growth chart for preterm babies: Babson and Benda's chart updated with recent data and 
a new format. BMC Pediatr. 2003 Dec 16;3:13. PMID: 14678563  
71. Fenton TR, Kim JH. A systematic review and meta-analysis to revise the Fenton growth chart for preterm infants. 
BMC Pediatr. 2013 Apr 20;13:59. PMID: 23601190  
72. WHO Child Growth Standards based on length/height, weight and age. Acta Paediatr Suppl. 2006; 450:76– 
85. PMID: 16817681