Comparative Effectiveness of Energy Doses in Critical Illness
Phase: PHASE2
Conditions: Critical Illness
Sponsor: Emory University

Comparative effectiveness of energy doses in critical illness 
 
Short title: The Energy Dose Study 
 
Principal Investigator: Thomas Ziegler, M.D. 
 
Protocol Version Date:  6/2/2014 
 
NCT Number: NCT01369147 
 
 
 
 
 
Abstract: 
Protein and/or energy deficits are associated with increased rates of hospital infection, skeletal 
muscle weakness, impaired wound healing, and prolonged convalescence in ICU patients. To 
prevent or treat malnutrition, enteral nutrition (EN) and/or parenteral nutrition (PN) are routinely 
given worldwide to a significant proportion of ICU patients. Optimal caloric requirements in 
critically ill patients are unknown due to a lack of rigorous randomized clinical trials. The 
comparative efficacy of energy doses in critically ill patients is unknown and clinical 
recommendations are conflicting and controversial; this issue is the focus of our study. 
We have designed this pilot, single-center Randomized Clinical Trial (RCT) to prospectively 
compare, for the first time, the clinical efficacy of different energy doses in ICU patients requiring 
PN due to intestinal failure/dysfunction. A total of 60 patients will be studied (20 per energy dose 
group) to generate critical preliminary data needed to inform subsequent appropriately powered 
Phase III multicenter trials. 
The primary aim of this study is to perform a controlled, double-blind, prospective, randomized, 
intent-to-treat Phase II clinical trial to test the efficacy of three specific energy doses [0.6, 1.0 
and 1.3 x measured REE (resting energy expenditure), respectively], given for 28 consecutive 
days during the ICU course, on 28-day total hospital-acquired infections (primary endpoint), 
Blood Stream Infections (BSI), and other important clinical outcomes in medical/surgical ICU 
patients requiring specialized parenteral ± enteral feeding. We would also determine, in these 
subjects A) the impact of cumulative and mean daily 28-day energy deficits [energy intake-
measured REE] on clinical outcome endpoints; and B) the practical utility of estimated REE 
determined by Harris-Benedict equation versus measured REE across different energy doses. 
We would also like to determine the impact of administered energy dose and energy deficits on 
global metabolomic patterns over time and their association with key clinical outcomes.  
This study will allow us to generate needed data on the effect of energy dose and energy 
deficits on global metabolomic patterns over time that may be associated with key clinical 
outcomes in ICU patients. This exploratory research is also needed to develop new methods 
that evaluate the metabolic responses to nutrition support and their potential relationships to 
clinical outcomes. 
 

 
 
Background: 
 
The increasing rate of hospital-acquired infection and sepsis are major causes of morbidity and 
mortality in intensive care unit (ICU) patients 1, 2 . The enormous impact of critical care-related 
illness demands that we find cost-effective therapies to improve outcome that can be rapidly 
implemented. Malnutrition is also very common in critically ill patients and is associated with 
increased hospital-acquired infections and mortality in ICU patients 3-13. Protein and/or energy 
deficits are associated with increased rates of hospital infection, skeletal muscle weakness, 
impaired wound healing, and prolonged convalescence in ICU patients 12, 14-17 3, 34-37. To prevent 
or treat malnutrition, enteral nutrition EN and/or PN are routinely given worldwide to a significant 
proportion of ICU patients 3-13 . Unfortunately, very few well-designed RCTs on the clinical 
efficacy of specialized nutrition support modalities in critical illness have been 
performed 18, 19. Observational studies indicate that initial nutritional goals in ICU settings are 
infrequently achieved; recent surveys show that both underfeeding, and, to a lesser extent, 
overfeeding, are common in ICU settings 5, 7, 20-22. Unfortunately, rigorous, prospective studies to 
determine effects of different energy doses have not been performed 5, 7, 12 . The comparative 
efficacy of energy doses in critically ill patients is thus unknown and clinical recommendations 
are conflicting and controversial; this issue is the focus of our application. Given the changes in 
the methods of ICU nutritional support during the past 5-10 years, including tighter blood 
glucose control 23, 24 and the use of overall lower caloric loads than in previous decades (when 
“hyperalimentation” was the norm), there is a clear need for further CER studies of different 
modalities of nutrition support based on current ICU clinical care practices 25-31. Energy (calorie) 
needs in adult patients in the ICU often vary considerably because of day-today changes in 
clinical conditions 9, 32, 33. However, optimal caloric requirements in critically ill patients are 
unknown due to a lack of rigorous RCTs. The resting energy expenditure (REE), or basal 
metabolic rate, is best determined using serial bedside metabolic cart measurements (indirect 
calorimetry), but technical issues (e.g. air leaks, high inspiratory oxygen concentration) can 
cause inaccuracies 3, 32, 33 . REE can also be estimated using standard equations, most 
commonly the Harris-Benedict equation (HBE), which incorporates the patient's age, gender, 
weight, and height 3, 10, 12. Unfortunately, the HBE may over- or underestimate REE in critically ill 
patients 3, 32, 33 . 
 
Current clinical practice guidelines, which are not evidence-based, suggest that an adequate 
energy goal for most adult ICU patients is approximately equivalent to measured or estimated 
REE x 1.0-1.3, given the minimal physical activity of ICU patients and the known complications 
of excess caloric doses, including hyperglycemia 8-10, 12 . In observational and retrospective 
(unblinded) studies, administration of both adequate energy doses (typically via the intravenous 
route well as “hypocaloric” feeding (typically as enteral feeds given at less than prescribed 
amounts) have each variously been associated with improved ICU outcomes in prolonged stay 
(> 4-5/days) ICU patients, particularly with regard to hospital-acquired infections, sepsis, and 
other complications 6, 11, 34, 35. Villet et al showed that less negative (i.e. more positive) ICU 

energy balance was associated with lower rates of hospital infections, less time on mechanical 
ventilation, decreased ICU length of stay (LOS) and lower total complication rates 11. Dvir et al 
found that daily mean negative ICU energy balance (energy intake – REE by indirect 
calorimetry) was strongly associated with increased rates of respiratory failure, sepsis, renal 
failure and pressure ulcers and total ICU complications 6. In marked contrast, Krishnan et al 
performed an unblinded descriptive, cohort study in medical ICU patients receiving PN, EN or 
EN+PN and showed that death rates varied as a function of the mean daily energy intake 34. 
The patients in the lowest tertile of mean daily caloric intake in relation to a goal of 25 
kcal/kg/day had the lowest mortality rates compared to the higher tertile energy intake groups. 
Further, Rubinson et al performed a prospective, unblinded cohort study in 138 clinically 
matched medical ICU patients and found that patients whom received an average of < 6 
kcal/kg/day (lowest quartile of intake) had significantly more bloodstream infections (BSI) than 
patients in the 2nd to 4th quartile groups for energy intake 35. This study suggested that there 
might be a threshold of energy intake needed to decrease BSI in medical ICU patients, but that 
higher levels of caloric intake do not influence this morbidity index.  
 
Unfortunately, in all trials concerning ICU energy dose and outcomes, a major design flaw is 
that the amino acid/protein and micronutrient intake has also varied between groups, 
especially when enteral feeds were employed 34. Also, blood glucose levels in the study 
groups, a known risk factor for ICU morbidity and mortality, were either not reported 6, 11, 35 or 
were higher than levels now considered appropriate for ICU patients (<150-180 mg/dL) 36. 
Thus, the true impact of energy dose per se on clinical outcomes in ICU patients is 
unknown at the present time. Studies to help better define energy dosing are also potentially 
important to guide clinicians to avoid complications related to overfeeding and refeeding 
syndromes, common in ICU settings 12, 37-39. Phase III, adequately powered, double-blind, 
intent-to-treat RCTs are needed, with design informed by pilot data such as we will 
generate in this project, to better define calorie requirements associated with improved 
outcomes in ICU patients. 
 
Recent discussions have emphasized the utility of metabolomic methods for nutrition research 
40, 41. Metabolomics analysis represents a novel approach to study integration of 
metabolic responses to specialized nutrition support 42, 43. We, under the direction of Co-I 
Dr. Dean Jones, have focused on high-resolution liquid chromatography mass spectroscopy 
(LC-MS) method. Metabolic profiles can be analyzed using our established bioinformatics 
methods to identify metabolic patterns and potential metabolic biomarkers of energy 
insufficiency and response to the different ICU energy dose regimens 44. The proposed 
studies will allow us to generate needed data on the effect of energy dose and energy 
deficits on global metabolomic patterns over time that may be associated with key 
clinical outcomes in ICU patients. Future studies could focus on nutritional strategies based 
on the specific identity of plasma metabolites that may be associated with improved outcomes. 
The fractal analysis-derived Hurst exponent has recently received attention because it provides 
a means to interpret biological signals generated by healthy biological systems or pathological 
states with one numerical value 45-49. Hurst exponent data is related to a variety of physiologic 
states and to outcome measures in Parkinson’s disease, obstructive sleep apnea and sudden 

cardiac death 45-49. Fractal analysis of metabolomic data will allow us to test whether the 
Hurst exponent is related to clinical outcomes and/or response to nutritional 
interventions in the ICU patients we propose to study.  
 
Emerging data strongly suggest that microbes of the intestine (the microbiota) play a key 
role in host metabolism, immune/inflammatory processes and disease pathophysiology 
50-52. The intestinal microbiome (genome of the gut microbiota) is shaped by both environment 
(e.g. diet) and host genetics; and, vice versa, the gut microbiota itself appears to regulate a wide 
spectrum of host immune, inflammatory and metabolic responses 53. Human data on the 
impact of nutrition support during critical illness on the gut microbiome are limited. 
Despite limited evidence, there is a suspected interplay between critical illness and the gut 
microbiome, which warrants further exploration in the setting of nutrition support 54-58. Nelson et 
al utilized 16S rRNA pyrosequencing to characterize stool of hospitalized patients and observed 
perturbations in gut microbiota following infection 59. It is acknowledged that the microbiome 
plays an integral role in health maintenance, and that modifications of the gut microorganisms 
may influence outcomes in critically ill patients.       
 
Hypothesis:  
 
1) Adequate energy administration (defined as 1.3 x REE) will result in a lower 28-day total 
hospital-acquired infection rate compared with ICU patients receiving lower energy doses. 
 2) Differences in energy intake will result in global changes in metabolic patterns that 
themselves are associated with clinical outcomes in the ICU patients studied.  
 
Specific Aims: 
 
1) To perform a controlled, double-blind, prospective, randomized, parallel group, intent-to-treat 
Phase II clinical trial to test the efficacy of three specific energy doses [0.6, 1.0 and 1.3 x 
measured REE (metabolic cart), respectively], given for 28 consecutive days during the ICU 
course, on 28-day total hospital-acquired infections (primary endpoint), BSI, and other important 
clinical outcomes in medical/surgical ICU patients requiring specialized parenteral ± enteral 
feeding. 
2)  In Aim 1 subjects to: a) examine the impact of cumulative and mean daily 28-day energy 
deficits [energy intake-measured REE] on clinical outcome endpoints; and b) to estimate the 
agreement for REE as determined by the HBEand the measured REE across different energy 
doses. 
3) To determine the impact of administered energy dose and energy deficits on global 
metabolomic patterns, human microbiome, and handgrip strength over time and their 
association with key clinical outcomes in Aim 1 subjects.  
 
Study Procedures: 
 
A total of 60 subjects will be enrolled in this intent-to-treat trial at Emory University Hospital 
(EUH) and EUH-Midtown. Patients admitted to either a medical or surgical (non-neurological) 

ICU within the previous 168 hours and who are expected to survive and remain in the ICU for at 
least 96 hours after entry are eligible. Patients enrolled in this study are also those deemed to 
likely require central venous parenteral nutrition (PN) for 7+ subsequent days after entry on a 
clinical basis. Patients who meet the following eligibility criteria will be approached: 
Inclusion criteria: 1) A signed informed consent is in place on the patient’s chart; 2) The patient 
is at least 18 but not more than 90 years of age at time of ICU admission; 3) The patient has a 
body mass index (BMI) > 40 kg/m2; 4) The patient has been admitted to either a medical or 
surgical (non-neurological) ICU and is expected to survive and remain in the ICU for at least 72 
hours after entry;  5) There is central venous access for administration of the study PN; 6) The 
patient’s primary physician(s) will allow the investigative team to manage the study PN and 
enteral feedings during the current hospitalization; and 7) The patient is expected to require total 
or partial central venous PN for 7 or more subsequent days after entry on a clinical basis (e.g. 
following massive small bowel ± colonic resection, the presence of high output fistulae or 
perforated small bowel, with demonstrated intolerance to EN or when EN may be 
contraindicated, as with severe diarrhea or emesis, partial or complete bowel obstruction, 
severe gastrointestinal bleeding and severe hemodynamic instability, such as with escalating 
vasopressor requirements). 
 
Exclusion criteria:  1) The patient is pregnant; 2) The patient has unresuscitated clinical sepsis 
[defined as unstable blood pressure despite vasopressor support and mean arterial pressure 
(MAP) < 60 mm Hg on at least 3 consecutive readings within a 3-hour period during the 24 
hours prior to study entry; 3); 3) The patient was admitted to the ICU following trauma or burns; 
4) The patient has significant renal dysfunction (defined as serum creatinine > 2.5 mg/dL or 
deemed to have significant acute kidney injury by the primary physicians) and is not receiving 
continuous renal replacement therapy (CRRT) or intermittent hemodialysis; 5) The patient has 
previously undergone an organ transplantation; 6) the patient has a current malignancy or is 
currently receiving an active regimen of chemotherapy and/or radiotherapy to treat a previously 
diagnosed malignancy≠; 7) the patient has a history of HIV/AIDS; 8) The patient has received 
any investigational drug within 60 days prior to study entry; and 9) The patient is unable or 
unwilling to participate in study procedures such as longitudinal blood draws and administration 
of study nutrient formulations. 
 
≠ † Patients with malignant metastasis and terminal untreatable carcinoma will be excluded. 
 
If the patient meets criteria, we will consent the patient’s legally authorized representative 
(LAR), as potential study subjects will be mechanically ventilated and probably sedated. 
 
Randomization of study subjects: A research team member will calculate the APACHE II score. 
Treatment assignments will be stratified according to clinical center and on the basis of illness 
severity (APACHE II score, either ≤ 15 or > 15). The treatment assignments will be generated 
by the Emory-based DCC with the use of a pseudo-random-number generator with randomly 
permutated blocks that will be used to ensure balance between the numbers of subjects 
assigned to the REE x 0.6, 1.0 or 1.3 groups, respectively. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Data Collection:  Baseline data collected will include APACHE II score, and clinical and 
demographic data. The following will be collected during the course of the study: 
 
A) Measured resting energy expenditure (MREE; per metabolic cart) will be determined on 
the baseline day before 2 pm. The goal energy dose composition of PN for all three 
energy doses for each enrolled subject is calculated by the blinded research team 
members. The metabolic cart-derived REE will be used to determine basal energy 
expenditure (REE) and thus the initial energy dosing 5, 10, 12. MREE will be determined at 
baseline and 5x weekly (M-F before 2 pm; see Aim 2) using a state-of-the-art metabolic 
Study Schema: Controlled, randomized, double-blind, prospective, parallel-group, 
intent-to-treat Aim 1 clinical trial to test the efficacy of three energy doses [0.6, 1.0, 
and 1.3 x measured REE (MREE), by metabolic cart, respectively], given for 28 
consecutive days during the ICU and post-ICU course in critically ill medical and 
surgical patients requiring parenteral nutrition (PN) ±enteral nutrition (EN) at Emory 
University. The primary endpoint is total hospital-acquired infections after entry; 
secondary endpoints are bloodstream infections, ventilator-free days, and ICU and 
28-day hospital length of stay and mortality. Aim 2 examines the effect of cumulative 
and mean daily measured 28-day energy deficits after entry on Aim 1 clinical outcome 
endpoints and relationships between estimated REE (Harris-Benedict equation) at 
study entry. Aim 3 explores the impact of energy dose and cumulative and mean 
daily 28-day energy deficits on global metabolomic patterns, microbiome, and 
strength over time and in association with key clinical outcomes in Aim 1.  
      Plasma (metabolome), microbiome, and strength analysis      
Study Day 
Double-blind PN with transition to double-blind EN as tolerated 
  
1.3 x REE 
1.0 x REE 
0.6 x REE 
Nosocomial infections and other clinical outcomes 
0 
3 
7 
14 
21 
28 
MREE 
(M-F) 
MREE 
(M-F) 
MREE 
(M-F) 
MREE 
(M-F) 
Randomization 

cart and standard methodologies by a study team respiratory technician with prior 
experience and expertise in clinical indirect calorimetry. In the event that the metabolic 
cart is not available, the most recent measurements will be used. The nutrition will not be 
adjusted if the MREE is <10% changed from the reading the day before. 
 
B) Longitudinal SOFA scores of organ dysfunction/failure: Sequential organ failure 
assessment (SOFA) scores will be calculated in the morning of each ICU day 60. The 
baseline Apache II score on the day of ICU admission will also be calculated in all 
patients. 
 
C) Blood sampling for metabolomics analysis (Aim 3): Baseline and serial study blood for 
processing as below will be drawn between 0800 and 1000 h. at the baseline day and 
study days 3, 7, 14, 21 and 28. A total of 28 mL of blood will be drawn at baseline and 
days 7, 14, 21 and 28 of study. A total of approximately 150 mL of blood will be obtained 
for analysis during the first 28 days after entry.  
 
D) Assessment and monitoring of blood glucose concentrations: Three blood glucose data 
points (the initial AM blood glucose sent to the hospital laboratory, and one 
representative laboratory or fingerstick blood glucose level obtained at a time point 
between 1400-1660 h and again between 2200-2400 h) ± 1 hour window. 
 
E) Assessment and monitoring of nosocomial infections: New hospital infections will be 
diagnosed based on standardized CDC criteria exactly as currently performed in Dr. 
Ziegler’s multicenter NIH U01 study (updated by CDC in 2009). All infections will be 
adjudicated by review of pertinent data in a blinded fashion by Infectious Disease Co-I 
Dr. Henry Blumberg. 
 
F) Stool sampling for microbiome analysis (Aim 3): Stool samples, when available, will be 
collected by the primary nurse at baseline and study days 3, 7, and 14, within 24 hours 
of the specific study day. The sample will be placed in a vial and frozen for later analysis 
by colleagues at the University of Chicago. The date, time, and consistency of stool will 
be collected for each sample.     
 
G) Handgrip strength test for overall strength assessment (Aim 3): If patients are deemed 
alert and able by study team, a Jamar Hydraulic Hand Dynamometer (Sammons Preston 
Rolyan, Chicago, IL) will be used to measure handgrip strength on the day subjects 
leave the ICU, then 3 and 7 days after ICU discharge. If the subject is consented before 
surgery and subsequent ICU admission, a handgrip measurement will be taken during 
pre-op. At each time point, the subject will be asked to squeeze the handheld 
dynamometer as hard as they can for 3 seconds, and they will be asked to repeat this 3 
times, with a 1-minute rest between measurements.    
 
Serial data entry via case report forms (CRFs): The investigators will monitor all study subjects 
daily during the ICU stay and after discharge to the general ward and enter data into 

standardized CRFs. The primary endpoint is total nosocomial infection rate during the 28-day 
study period. Secondary Aim 1 post-entry endpoints to be monitored include: 1) 28-day hospital 
mortality; 2) Rate of new nosocomial blood stream infections (BSIs) during the initial 28 days; 3) 
Rate of new nosocomial infections during the initial 28 days; 4) mean ICU SOFA score; 5) ICU 
ventilator-free days at day 28; 6) ICU and total hospital length of stay. 
 
Hospital nutrition support - Administration of double blind parenteral and enteral nutrition: 
Briefly, the nutritional goals are to provide total daily calorie (kcal) intake [from PN + dextrose-
containing IV fluids (> 500 mL/day) + propofol/clevidipine + any enteral feedings) at 0.6, 1.0 or 
1.3 x baseline MEE (per metabolic cart). We will then serially adjust total PN/EN energy dosing 
based on real-time serial cart REE measurements during the ICU stay, as indicated by the 
energy dose group to which the patient is randomized. The total amino acid/protein intake goal 
is 1.2 g/kg/day. Dextrose will initially comprise 70% of PN non-amino acid kcal and IV fat (30% 
Intralipid) 30% of PN non-amino acid kcal daily, adjusted as clinically indicated. The 1.0 x REE 
energy dose study group will serve as the control group in this CER study. Study PN will be 
continued only if deemed indicated by the investigators and the primary physicians. Daily intake 
of study PN volume (mL), PN dextrose (g), PN lipid emulsion (g), intake of study tube feeding 
volume, and daily PN and enteral (oral or tube feeding) volumes will be calculated and entered 
into the CRFs daily for the initial 28 days after entry, beginning on day 1. 
 
Study subjects will receive a maximum of 28 days of double blind study PN ± EN. Subjects will 
be transitioned from PN to enteral feeds as soon as tolerated and clinically indicated. Study PN 
will be discontinued when enteral intake of ≥ 50% of energy requirements is achieved for ≥ 48 
hr. The amount of PN administered will be decreased as a function of actual enteral nutrient 
intake to maintain daily goals. The 24-hr daily study PN will be prepared under sterile laminar air 
flow hood conditions by the unblinded research pharmacist and pharmacy technician at each 
site. The study EN will be made in the Metabolic Kitchen or in the compounding area of the 
pharmacy. 
 
For study PN, the energy dose will be altered via proportional changes in the administered PN 
carbohydrate and lipid doses in isovolemic PN using established double-blind methods of our 
research team in Dr. Ziegler’s ongoing Phase III trial U01 DK069322  The method employs use 
of three written orders by the blinded research team members to account for three possible 
energy doses per randomization (either 0.6, 1.0 and 1.3 x REE, respectively) given as 
isovolemic PN solutions. The PN dose will be written for each 24-hr period taking into account 
calories provided as lipid emulsion in the sedative propofol (1.1 kcal/mL) or clevidipine (2 
kcal/mL), and any dextrose-containing IV fluid orders exceeding 500 mL/day. The lipid emulsion 
will be a conventional soybean-oil based product (30% Intralipid, Baxter, Deerfield, IL). The PN 
bag labels will state that study dextrose and study lipids are provided, but will not list the specific 
amount of each. Labeling of all other PN constituents will be per standard IV Pharmacy 
procedures. Additional details on study PN and EN nutrient formula preparation by the 
unblinded pharmacist and technician, blinding procedures, and strategies to prepare PN, EN, 
and combined PN+EN feeds that a) achieve our planned energy intake goals (0.6, 1.0 and 1.3 x 
measured REE by metabolic cart) and b) are isonitrogenous.  

Clinical management guidelines: The care for the ICU subjects at both EUH and EUH-M 
hospital study sites are standardized per uniform Emory Healthcare ICU guidelines for ventilator 
weaning, use of antibiotics, sedation, blood glucose control/insulin administration pathways, etc. 
The investigators, working closely with the primary clinical teams, will attempt to maintain 
morning blood glucose levels between 150-180 mg/dL in the ICU and ≤ 200 mg/dL in the less-
controlled setting of the general surgical ward 23, 24.   
 
Determination of energy deficit: Energy intake from PN ± EN (tube feeds + any oral diet) will be 
determined as outlined in Aim 1 each day for the initial 28-days of study. MREE will be 
determined by metabolic cart 5x week (Monday through Friday) before 2 pm. Any PN or EN 
being administered will be continued uninterrupted during MREE determinations. The 5 daily 
cart measurement results (kcal/day) for each study week will be averaged and that mean daily 
value used as the daily measured energy requirement for all 7 days of that week. The daily 
energy deficit will be calculated by subtracting the calculated mean daily MREE during each 
study week from the actual daily energy intake. The cumulative and mean daily ICU and 28-day 
energy deficits will be determined. Metabolic cart measurements will not be performed on any 
given day in patients whom are in isolation due to resistant microorganism infection 
(contraindicated), or if the patient requires a fraction of inspired oxygen of < 60%, has a 
requirement for positive end-expiratory pressure of > 12 cm H2O, or has a documented leak in 
the ventilator or chest tube systems (precluding accurate cart measurements) 32, 33. The 
estimated REE by the HBE(outlined in detail in Table 3 of reference 3 61) will be calculated on 
the baseline day using most recent available pre-ICU dry body weight. 
 
High-resolution metabolomics analysis: Plasma samples will be obtained at baseline and on 
days 3, 7, 14, 21 and 28 after entry (please see study schema above). Metabolomic profiles at 
the specific analysis time-points will be compared to compare subjects: 1) within the three study 
energy doses; 2) whom develop a nosocomial infection or a BSI versus those who do not; and 
3) who die compared to those who are alive at 28 days. Samples will be analyzed in triplicate 
with a Thermo LTQ-Velos Orbitrap high-resolution mass spectrometer (≥ 50,000 resolution) 
following extraction with acetonitrile containing an internal standard mixture and separation on 
anion exchange and C18 columns. Validated extraction methods (apLCMS and xMSanalyzer) 
44, 62 will be used to provide a mass/charge ratio (m/z) feature table of detected ions, 
characterized by relative retention time and accurate mass. The mass spectrometer will be set 
to collect data from m/z ratio 85 to 2000 daltons over a 10-minute chromatography period.  
Internal stable isotopic standards are spiked into every sample so that the relative retention time 
and accurate mass provide unambiguous denotation of an ion even if the chemical is 
unidentified 63; relevant reference samples are included preceding and following each block of 
20 samples for long-term quality assurance. Electrospray ionization will be used in the positive 
ion mode for detection. When necessary, tandem mass spectrometry will be used to positively 
identify metabolites of interest, with a metabolite defined as any chemical in a biological system.  
 
Stool sampling and gut microbiome analysis: On study days 0, 3, 7, and 14 the primary nurse 
will collect a small sample of stool (± 24-hr window of each study day). All specimens will be 
collected into sterile containers, processed, and stored at -80°C as previously outlined 64. The 

gut microbiota in all fecal samples will be identified using established next generation DNA 
sequencing of 16S rRNA libraries, performed by our collaborator Dr. Eugene Chang of the 
University of Chicago (6, 18, 66). Briefly, 50 mg of frozen fecal sample will be homogenized in 
extraction buffer and 0.1-mm-diameter zirconia/silica beads are added prior to lysing of 
microbial cells on a Mini-Beadbeater-8 cell disrupter. After overnight incubation at 55°C, 
extraction with phenol: chloroform: isoamyl alcohol, and precipitation with ethanol will be 
performed. Isolated DNA is dissolved in Tris-EDTA buffer and stored at -80°C. The 16S rRNA 
gene sequences are amplified from DNA samples using barcode-labeled primers for the V3–V4 
region of the 16S rRNA encoding gene (Escherichia coli positions 338–806), as outlined 65-67. 
The Shannon diversity index and distinctive peak numbers (richness) of the OTUs in the 
microbiome libraries between baseline (day 0) and serial fecal samples (days 3, 7, and 14) will 
be compared as previously outlined 65, 67, 68. These representative sequences are aligned using 
PyNAST and taxonomy assigned to them using the RDP Classifier. The PyNAST-aligned 
sequences will also be used to build a phylogenetic tree with FastTree and unweighted UniFrac 
distances then computed between all samples for additional ecological analyses, including 
principal coordinates analysis (PCA) 65-67.  
 
Adverse Event (AE) Reporting: 
 
The subjects enrolled in this trial are initially critically ill subjects deemed to require both PN and 
prolonged ICU care. Such individuals are known to have a high morbidity and mortality rate. No 
AEs specifically due to the study nutrient formulations are expected. However, we will closely 
monitor the clinical course of all subjects daily and record conventional serious adverse events 
(SAEs) and unexpected and expected AEs, as well as note significant clinical or surgical events 
as narrative data. For the purposes of study reporting, an SAE is any of the events below: 
1. Death 
2. Re-hospitalization after study PN or tube feeding discontinuation 
3. Documented pulmonary aspiration of study tube feeds during study tube feed 
administration 
4. New cancer diagnosis 
5. Congenital anomaly/disorder 
 
When any of the above events occur, an SAE form in the subject’s CRF binder is filled out and 
faxed to the DCC. The DCC will in turn report these events to the DSMB and NIDDK. These 
events will also be reported to each site’s IRB per their local reporting requirements. 
All other serious, unexpected or unanticipated problems that are potentially related to study PN 
or tube feeding will be reported to the IRB, per local reporting guidelines, and the DCC. 
Operationally, this means that if: 1) in the opinion of the PI, was there a causal relationship 
between the intervention and the serious event (i.e., there is a reasonable possibility that the 
event may have been caused by the study drug intervention); and 2) the serious event was 
unexpected (i.e., not identified in nature, severity or frequency in the current IRB approval 
research protocol or informed consent document). Code responses in terms of relation to study 
PN will be as: definitely related, possibly related, unsure, probably not related and definitely not 
related). SAEs and AEs need to be reported up to and including 30 days after study drug 

discontinuation. Ongoing SAEs and AEs must be followed until resolved. A 30-day post-study 
drug follow-up SAE/AE form will be included in subject monitoring.  
 
Expected Adverse Events: There are no expected AEs that are likely to be due to the study PN 
or tube feeding. Major AEs common in ICU subjects receiving PN and tube feeding will be 
identified and reported to the DCC and DSMB. The following expected AEs would be 
reported during the 28-day study: 
1.   Clinically significant pulmonary aspiration  
2.   Pneumothorax 
3.   Development of worsening renal function with serum creatinine ≥ 5.0 mg/dL or requiring new 
initiation of renal replacement therapy 
4.   Development of severe hepatic dysfunction (serum total serum bilirubin ≥ 15.0 mg/dL) 
5.   Hyperglycemia > 250 mg/dL 
6.   Hypoglycemia < 50 mg/dL (from blood draws and laboratory analysis) 
 
The adverse event data will be compiled by the DCC and reported to the DSMB twice a year. 
This trial will employ an NIH-approved data and safety monitoring board (DSMB) and a 
comprehensive AEs reporting plan to minimize risks to the subjects. 
 
Potential Risks: A total of approximately 150 mL of blood will be obtained for analysis during the 
first 28 days after entry. A total of 28 mL of blood will be drawn at each of the baseline and days 
3, 7, 14, 21 and 28 of study. Although most of the early blood draws (e.g. baseline and days 3, 7 
and 14) are likely to be via an already-indwelling arterial catheter or less likely a central or 
peripheral venous catheter required for clinical purposes, pain and bruising, and much less 
likely, infection could occur with venipuncture. Lightheadedness and fainting can also occur with 
drawing blood.  
 
Indirect calorimetry to measure resting energy expenditure (MREE) is a routine ICU test and 
performed over a 30-minute period using a metabolic cart (to collect expired air for 
measurement by the machine), which is connected to the mechanical ventilator tubing in 
patients on mechanical ventilation. Manipulation of the tubing for this connection on a Monday-
to-Friday basis (5x/week) carries an extremely small risk of infection. In patients not on the 
ventilator, the measurement is done while the patient is lying quietly in bed by placing a large 
plastic see-through hood over the head of the patient to collect the expired air. This could cause 
a sense of claustrophobia in some patients, but is typically very well tolerated.  
 
Administration of PN has well-known complications that can be classified as mechanical (e.g. 
pneumothorax with central line insertion), infectious (e.g. PN-associated infection) and 
metabolic (e.g. hyperglycemia, electrolyte disturbances, increased serum liver function tests).  
 
Administration of tube feedings can result in nausea, emesis, pulmonary aspiration, pneumonia, 
diarrhea, a variety of mechanical complications associated with the placement of feeding tubes 
and metabolic complications similar to that seen with PN. However, these modes of feeding will 

be given only as indicated per standard clinical care guidelines and a central venous catheter 
will be inserted only if indicated per clinical care by the primary physicians. 
 
The only significant difference in nutrient administration is that a different caloric dose will be 
given to individual patients, depending on the randomization; either 40% below the estimated 
REE using the standard HBE (i.e. 0.6 x estimated REE), 100% of the REE (i.e. 1.0 x estimated 
REE), or 30% above the estimated REE (i.e. 1.3 x estimated REE). There is no a priori risk to 
any of these energy doses and the limited data to date are conflicting as to whether one dose 
confers any risk or morbidity versus another (there are no data to suggest that ICU mortality 
would be different at any of these three energy doses vs. the others). Further, this range of 
energy doses is routinely given to adult ICU patients throughout the world. This is due to the 
lack of consensus on appropriate energy dosing for specialized nutrition support. The total 
amino acid/protein and fluid amounts in each of the three energy-dose groups is designed to be 
similar between groups (please see research plan).  
 
Tighter blood glucose control, generally using insulin drip therapy, is the standard of care for 
ICU subjects as several studies now show that control to levels in the range of < 180 mg/dL 
decreases ICU morbidity and mortality, although the exact goals for blood glucose remain 
controversial in surgical ICU patients. Recent data from the NICE-SUGAR trial suggest that 
maintaining blood glucose levels < 180 mg/dL may be an appropriate goal in ICU patients. 
However, uncertainty persists with regard to surgical ICU patients, whom may benefit from 
lower levels, based primarily on earlier data from the large Leuven study (some centers suggest 
levels lower than 140-150 mg/dL or lower in such patients). Risk of hypoglycemia is theoretically 
increased using this approach but with careful blood glucose monitoring (routine in ICU subjects 
on insulin infusion), this rarely occurs. Blood glucose control goals will be liberalized (≤200 
mg/dL) when the subject is in the less-controlled environment of the general surgical ward. 
 
Protections Against Risk:  Aseptic procedures for central venous catheter (CVC) insertion and 
line/site maintenance will be followed per identical standard operating procedures (SOPs) in 
place at the study sites [Emory University Hospital (EUH) and Emory University Hospital-
Midtown]. These include a mandatory checklist for physicians or physician assistant placement 
of CVC that includes documentation of site attempts and type of catheter placed (subclavian 
vein preferred as first choice of site unless contraindicated). Other required components include 
use of ultrasound guidance when possible, mandatory performance of CVC placement bundle 
components (SOPs for optimal hand hygiene, patient positioning, and maximal sterile barriers, 
including cap, mask and sterile gown and gloves for operators during procedure, large sterile 
drape and maintenance of sterile field) and notations regarding emergent or elective CVC 
insertion and tolerance of the procedure. Following line placement, the CVC dressing is 
changed by primary registered ICU nurses every 7 days or sooner as clinically indicated using 
chlorhexidine gluconate skin prep and a chlorhexidine gluconate-containing Biopatch (Ethicon, 
Johnson and Johnson, Somerville, NJ) with an occlusive dressing. The non-genital skin of the 
ICU patient is also washed every 24 hr with chlorhexidine gluconate skin prep. 
 

We will incorporate conventional ICU insulin administration and tight blood glucose monitoring 
guidelines. All study personnel will closely communicate with the study patient’s primary 
physicians and ICU care staff regarding nutrition support orders and transition from PN to EN 
and oral diet. Standard aseptic procedures for all blood drawing will be followed. 
 
Confidentiality: All subject records will be kept in locked file cabinets in the P.I.’s/coordinator’s 
research offices and at the Emory-based Data Coordinating Center (DCC) and will be 
accessible only to the P.I. and the investigative team. Subject identification numbers will code all 
data. The master list connecting the codes to identifying information will be secured in the DCC. 
All data maintained in the computerized database will be accessible only with a login and 
protected password. After the study is completed, all data will be kept according to NIH and 
FDA regulations in a locked file.  
 
Data and Safety Monitoring Board (DSMB): The Data and Safety Monitoring Board (DSMB) will 
act in an advisory capacity to the National Institute of Diabetes, Digestive and Kidney Diseases 
(NIDDK) to monitor subject safety and evaluate the efficacy of the intervention being studied in 
this clinical trial funded by the NIDDK. The DSMB will be appointed by the PIs upon study 
funding, and approved by NIDDK program staff. The DSMB will be composed of at least two 
experienced clinical nutrition support investigators not otherwise participating in the study and 
not affiliated with Emory. A biostatistician not otherwise participating in the study will also be 
named to the DSMB. The DSMB will meet twice yearly, and as needed, and will receive blinded 
and unblinded reports on study progress prepared by the DCC. 
 
Statistical Analysis: 
 
Continuous variables will be summarized with standard descriptive statistics and represented 
graphically with displays such as scatterplots, box plots, line plots and histograms, while 
categorical variables (adverse events) will be described by frequency tables. 
 
For Aim 1: The primary analyses of the data will be performed according to subjects’ original 
treatment assignment (i.e., intention-to-treat analyses) and the inclusion of all data from all 
subjects randomized in the final analysis. Rates of infection (i.e., BSI and total nosocomial 
infections) per 1000 hospital days will be estimated overall and for each of the 3 energy doses.  
Confidence intervals (95%) for the incidence rates will be estimated using an exact method 
based on the Poisson distribution. 
 
Additionally incidence rates of infection will be estimated by performing a generalized estimating 
equations (GEE) Poisson regression analysis of the counts, implemented using SAS Proc 
Genmod, using an exchangeable correlation structure for the repeated counts within subject.  
The incidence rate ratio (IRR) is the ratio of the incidence density in one group to that of another 
group. Results by each baseline covariate will be presented as the IRR and the 95% confidence 
interval (CI). This GEE model can also accommodate time-dependent covariates such as daily 
blood glucose levels measured before an infection and total 28-day energy (cumulative deficit or 
as a time-dependent covariate). 

 
Twenty-eight day mortality will be summarized as a proportion plus the 95% confidence interval 
(overall and for each treatment group). The 28-day mortality will be compared between 
treatment groups using a chi-square or Fisher’s exact test. The potential association of each of 
the categorical prognostic factors (gender, race, high or low Apache score, clinical center) with 
mortality will also be evaluated using a Chi-square test or Fisher's exact test. Baseline 
continuous prognostic factors (age, SOFA score, blood glucose) will be compared by treatment 
group using the Wilcoxon rank-sum test. Odds ratios will be calculated to measure the degree of 
association. All statistical tests will be 2-sided. Factors significant to at least a value of P ≤ 0.20 
in the univariable analyses will be used in multivariable logistic regression analyses. Forward 
and backward stepwise selection will be used if necessary to choose prognostic variables for a 
multivariable logistic regression model. The odds ratio and its 95% confidence interval will be 
calculated for each factor in the presence of others in the final model. 
 
Days on mechanical ventilation, length of ICU stay and hospital length of stay will be 
summarized with percentiles (25th, 50th and 75th) and the median absolute deviation. These 
secondary outcomes will be compared between the 3 treatment groups using the Kruskal-Wallis 
test. Repeated-measures analyses of daily SOFA scores and laboratory measures such as 
blood glucose will be analyzed with a means model with SAS Proc Mixed (version 9, mixed 
linear models) providing separate estimates of the means by time on study (days 0, 3, 7, 14, 21, 
and 28) and treatment group (energy dose: 0.6, 1.0 and 1.3 x REE). An unstructured variance-
covariance form among the repeated measurements will be assumed for each outcome and 
estimates of the standard errors of parameters will be used to perform statistical tests and 
construct 95% confidence intervals. T-tests will be used to compare the pairwise differences 
between the model-based treatment means (least-squares means) at each time point. Statistical 
tests will be 2-sided. The model-based means are unbiased with unbalanced and missing data, 
so long as the missing data are non-informative (missing at random). A dropout process is 
assumed to be missing at random if; conditional on the observed data, the dropout is 
independent of the unobserved measurements. 
 
For Aim 2: The agreement between the study entry HBE and the initial REE, as well as  the 
mean daily serial MREE by metabolic cart, will be summarized using graphical methods and by 
calculating the 95% limits of agreement estimated by the mean difference ± 1.96 standard 
deviation of the differences. Bland and Altman (1999)63 extend the limits of agreement approach 
to data with repeated measurements (i.e., serial REE measurements). To investigate whether 
the relationship between mean daily serial REE and entry HBE is altered by the mean daily 
caloric dose administered, regression methods will be used (i.e., analysis of covariance, 
ANCOVA). ANCOVA analyses will also be stratified by location (ICU versus the floor). 
 
For Aim 3: The data processing will be performed as follows: 1) Feature detection conducted by 
systematic re-extraction with multiple parameter settings that optimize sensitivity and reliability; 
2) Sample quality and feature consistency evaluation; 3) Feature overlap detection between 
datasets; 4) Statistical analysis includes false discovery rate (FDR; typically with q=0.05) to 
identify significantly different features between the two groups while correcting for multiple 
comparisons; hierarchical cluster analysis (HCA) to visualize differences between groups as 

well as between time points and to  identify clusters of highly correlated features that can be 
mapped to biological pathways; 5) Characterization of features and biological pathways utilizing 
multiple chemical databases (KEGG) metabolic pathways 
(http://www.genome.jp/kegg/tool/color_pathway.html), MetaCore (www.genego.com; Carlsbad, 
CA), and MetaCyc (http://www.metacyc.org).69 We will utilize Metaboanalyst 2.0 70 for the time 
series analysis to detect metabolic changes throughout the study period and two-way ANOVA to 
determine the impact of varying energy doses on global metabolomics patterns. Once important 
features have been identified, we have the ability to positively identify the chemical names of 
known metabolites by MS/MS analysis. 
 
There is very little data available to inform an adequate power calculation for microbiome 
analysis; thus a formal power analysis was not completed. Samples will be compared by 
repeated-measures analyses using a mixed linear model for analysis of specific microbial phyla 
over time within subjects and for changes from baseline over time within and between the 
individuals. Both absolute effects and percent (%) change from baseline values will serve to 
correct for individual heterogeneity. If a specific parameter follows a non-normal distribution, an 
appropriate transformation will be used to ensure normality of the data. Pearson correlation 
coefficient will be used for association studies (e.g. SRB microbiota/microbiome changes with 
dsrA gene expression) 67.   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
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