Energy and Protein Intake During the Transition from Parenteral to

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Nov 5, 2018 - Total fluid intake for each patient day was normalized to daily ..... We thank Janice Raucci, PharmD, BCPPS, for assistance with devel-.
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Energy and Protein Intake During the Transition from Parenteral to Enteral Nutrition in Infants of Very Low Birth Weight Gustave H. Falciglia, MD, MSc1,2, Karna Murthy, MD, MSc1,2,3, Jane L. Holl, MD, MPH2,4, Hannah L. Palac, MSc4, Yuliya Oumarbaeva, MD5, Donna M. Woods, EdM, PhD1, and Daniel T. Robinson, MD, MSc1,2 Objective To evaluate the association between nutrition delivery practices and energy and protein intake during the transition from parenteral to enteral nutrition in infants of very low birth weight (VLBW). Study design This was a retrospective analysis of 115 infants who were VLBW from a regional neonatal intensive care unit. Changes in energy and protein intake were estimated during transition phase 1 (0% enteral); phase 2 (>0, ≤33.3% enteral); phase 3 (>33.3, ≤66.7% enteral); phase 4 (>66.7, 0, ≤33.3%), phase 3 (>33.3, ≤66.7%), phase 4 (>66.7, 10 mL/kg/d). Fluid restriction and excess non-nutritive fluid intake determinations were chosen because for about 25% of patientdays, infants received less than or equal to 130 mL/kg/d, and for about 25% of patient-days, infants received greater than 10 mL/kg/d of non-nutritive fluids. These values also were associated with less than 100 kcal/kg/d of energy intake (Table I; available at www.jpeds.com). Statistical Analyses For each phase, the number of patient-days, median and IQR for energy, protein, and fluid intake were calculated. Energy, protein, and fluid intake for phases 1-4 were compared with phase 5 (reference category). All statistical comparisons were conducted at the patient-day level and used mixed-effects linear regression to account for repeated measures in the same infant.19 Beta coefficients with 95% CIs are reported in kcal/kg/d or g/kg/d of protein. Two-tailed tests, with P < .05, defined statistical significance. The median parenteral, enteral, and combined energy and protein intakes were graphed by phase of nutrition. The proportion of infants in each phase of nutrition was graphed by age. Bivariable analyses determined significant associations between discrete nutrition delivery practices and energy or protein intake. PN at the NPO and at the intended rate were included in the same models with a reference group of “none.” The definitions of the 5 phases precluded analyses of fortification in phase 1 and of PN and intravenous lipids in phase 5 (nonapplicable). Analyses between intravenous lipids and protein intake were not performed on the basis that intravenous lipids contain no protein. Energy and protein intake were

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the sum of parenteral and enteral intake. Therefore, during phases 2, 3, and 4, bivariable analyses were performed between nutrition delivery practices and parenteral energy or protein intake, and enteral energy or protein intake. Unless otherwise specified, energy and protein intake refer to the combined parenteral and enteral intake. Ten multivariable models described energy and protein intake in the 5 phases. These equations were developed using backward stepwise reduction with a model entry criterion of P < .20. Analyses were adjusted for birth weight and comorbid conditions, as they may affect energy and protein intake, when these adjustments met entry criterion. Collinearity was assessed using variance inflation factors for all final models.

Results Detailed nutritional and fluid data were obtained on 115 infants over 4643 patient-days with a median observation period of 42 (IQR 41, 42) days per patient. Median infant gestational age and birth weight were 28.0 weeks (IQR 25.4, 30.1) and 1060 g (IQR 750, 1300), respectively. In total, 48% of infants were female; 50% were born to mothers who received antenatal steroids, and 82% were admitted by day 1. Patent ductus arteriosus, NEC/SIP, intubation on day 28, and small for gestational age status were present in 48%, 18%, 35%, and 11%, respectively. Among those affected by NEC/SIP, one-half (11/ 21) were diagnosed before admission. Median growth velocities in weight, length, and head circumference were 12.2 g/kg/d

(IQR 10.7, 13.4), 8.6 mm/wk (IQR 7.3, 9.7), and 6.9 mm/wk (IQR: 5.9, 7.8), respectively. The transition period accounted for 39% of all patientdays during the study period (Table II; available at www.jpeds.com). The differences in energy intake between phases 1 through 4 and phase 5 were statistically and clinically significant. Protein intake declined in phases 3 and 4, and these phases were associated with decreased protein intake compared with phase 5. Fluid intake was greatest in phase 5, with a median intake of 150 mL/kg/d. The median energy and protein intake from parenteral, enteral, and combined sources are noted in Figure 1. The proportion of infants in each phase throughout the 6 weeks are described in Figure 2 (available at www.jpeds.com). Of note, 51% and 73% of infants reached phase 5 by days 21 and 42, respectively. Table III describes the results of the bivariable analyses of nutrition delivery practices on energy and protein intake during each phase of nutrition. PN and the presence of a central line were associated with increased energy and protein intake during phases 1, 2, 3, and 4. Intravenous lipids also were associated with increased energy intake. During the transition period, these nutrition delivery practices were associated with increased parenteral energy and protein intake and clinically smaller changes in enteral energy and protein intake (data not shown). Fluid restriction was associated with decreased energy and protein intake, and excess non-nutritive fluid was associated with decreased energy intake. In the unadjusted analyses, fortification was associated with decreased energy and protein intake in phases 2 and 3 but

Figure 1. Parenteral, enteral, and combined intake by phase of nutrition. Medians and IQRs are represented by solid lines and shading, respectively. Energy and Protein Intake During the Transition from Parenteral to Enteral Nutrition in Infants of Very Low Birth Weight FLA 5.5.0 DTD ■ YMPD10109_proof ■ August 29, 2018

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Table III. Bivariable associations between energy or protein intake with nutrition delivery practices Models

Phase 1

Energy intake PN at NPO rate PN at intended rate Intravenous lipids Central line Fortification Fluid restriction Excess non-nutritive fluid Protein intake PN at NPO rate PN at intended rate Central line Fortification Fluid restriction Excess non-nutritive fluid

Phase 2

35 31 24 17

Phase 3

Phase 4

(26, 43) (23, 40) (16, 31) (12, 23) N/A −10 (−13, −7) −13 (−16, −10)

37 37 43 31 −18 −17 −12

(28, 46) (28, 46) (32, 54) (26, 36) (−25, −12) (−19, −14) (−15, −9)

27 31 25 28 −14 −21 −12

(23, 32) (26, 36) (21, 30) (24, 32) (−18, −10) (−25, −18) (−16, −8)

8 5 9 11 10 −23 −6

(4, 11) (1, 9) (6, 12) (7, 16) (7, 13) (−28, −19) (−11, −2)

2.6 (2.4, 2.9) 2.6 (2.3, 2.9) 0.7 (0.5, 1.0) N/A −0.5 (−0.6, −0.4) −0.1* (−0.3, 0.0)

2.7 2.8 1.1 −1.1 −0.4 −0.0*

(2.4, 2.9) (2.5, 3.1) (1.0, 1.3) (−1.3, −0.8) (−0.5, −0.3) (−0.1, −0.1)

1.4 2.0 1.1 −0.3 −0.7 −0.2†

(1.2, 1.6) (1.8, 2.2) (0.9, 1.3) (−0.5, −0.1) (−0.8, −0.5) (−0.4, −0.0)

0.4 0.9 0.7 0.8 −0.8 −0.1*

(0.2, 0.5) (0.7, 1.1) (0.4, 0.9) (0.6, 0.9) (−1.0, −0.5) (−0.4, 0.1)

Phase 5

−11 6 −20 −14

N/A N/A N/A (−13, −9) (4, 8) (−22, −18) (−16, −11)

−0.4 0.5 −0.7 −0.4

N/A N/A (−0.5, −0.3) (0.4, 0.6) (−0.8, −0.6) (−0.5, −0.3)

N/A, not applicable. All associations P < .005 unless noted. Values are beta coefficients in kcal/kg/d and g/kg/d (95% CIs) for energy and protein intake, respectively. *Signifies P > .05. †Signifies P < .05.

increased energy and protein intake in phases 4 and 5 (Table III). Although fortification during phases 2 and 3 was associated with increased enteral energy intake, it also was associated with clinically significant, decreased parenteral energy intake (phase 2: 8 enteral kcal/kg/d [CI 5, 11] and −27 parenteral kcal/kg/d [CI −33, −21]; phase 3: 11 enteral kcal/kg/d [CI 8, 13] and −25 parenteral kcal/kg/d [CI −29, −21]). The same findings were observed with protein intake (phase 2: 0.3 enteral g/kg/d [CI 0.3, 0.4] and −1.4 parenteral g/kg/d [CI −1.6, −1.2]; phase 3: 0.8 enteral g/kg/d [CI 0.7, 0.9] and −1.1 parenteral g/kg/d [CI −1.3, −0.9]). For each phase, multivariable models depict the relative tradeoffs in energy and protein intake associated with nutrition delivery practices (Table IV). For example, during phase 3, centralline access was associated independently with a daily incremental gain in delivered energy (19 kcal/kg/d) and protein (0.7 g/kg/d). Conversely, fluid restriction was associated independently with a daily incremental loss in delivered energy

(−18 kcal/g/d) and protein (−0.5 g/kg/d). Variance inflation factors testing did not demonstrate collinearity between terms in the final model. Findings in the multivariable models were similar to the bivariable analyses with notable exceptions. PN at both NPO and intended rates was not associated with energy intake in phase 4. Throughout the transition period, PN at the intended rate was associated with greater protein intake than at the NPO rate. Fortification was associated independently with increased energy intake in phases 4 and 5 and protein intake during phases 3, 4, and 5. Fortification was no longer associated with decreased energy or protein intake. To address the findings noted with fortification in the unadjusted analysis, infant days with fortification in phases 2 and 3 were compared with infant days without fortification. Infant days with fortification were less likely to have a central line or receive PN after adjusting for remaining practices and total fluid intake. Infant days with fortification also were associated with

Table IV. Multivariable associations between energy or protein intake with nutrition delivery practices Models Energy intake PN at NPO rate PN at intended rate Intravenous lipids Central line Fortification Fluid restriction Excess non-nutritive fluid Protein intake PN at NPO rate PN at intended rate Central line Fortification Fluid restriction Excess non-nutritive fluid

Phase 1

Phase 2

Phase 3

Phase 4

(20, 34) (17, 32) (12, 25) (7, 17) N/A −13 (−15, −10) −18 (−21, −16)

15 (6, 25) 14 (5, 23) 20 (9, 31) 21 (16, 25) Did not meet entry criterion −17 (−19, −15) −14 (−17, −12)

9 (5, 14) 14 (10, 19) 7 (3, 12) 19 (15, 22) Did not meet entry criterion −18 (−20, −15) −10 (−13, −7)

Did not meet entry criterion Did not meet entry criterion 13 (11, 15) 7 (4, 10) 14 (11, 16) −22 (−25, −18) −5 (−8, −2)

2.4 (2.2, 2.7) 2.4 (2.1, 2.7) 0.4 (0.2, 0.5) N/A −0.5 (−0.6, −0.4) −0.3 (−0.4, −0.2)

2.3 (2.1, 2.6) 2.5 (2.2, 2.7) 0.7 (0.5, 0.8) Did not meet entry criterion −0.3 (−0.4, −0.3) Did not meet entry criterion

27 24 18 12

1.2 1.9 0.7 0.5 −0.5 −0.1*

(1.0, 1.4) (1.7, 2.1) (0.5, 0.9) (0.4, 0.7) (−0.6, −0.4) (−0.3, 0.0)

0.5 (0.3, 0.6) 1.0 (0.8, 1.1) 0.4 (0.2, 0.6) 0.9 (0.8, 1.0) −0.6 (−0.8, −0.5) Did not meet entry criterion

Phase 5

−6 5 −20 −12

N/A N/A N/A (−8, −4) (3, 6) (−21, −18) (−14, −10)

−0.2 0.4 −0.7 −0.3

N/A N/A (−0.3, −0.1) (0.4, 0.5) (−0.7, −0.6) (−0.4, −0.2)

All models adjusted for comorbid conditions and birth weight where relevant; all associations P < .005 unless noted. Values are beta coefficients in kcal/kg/d and g/kg/d (95% CIs) for energy and protein intake, respectively. *Signifies P > .05.

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less parenteral protein (in infants receiving PN), less parenteral fat (in infants receiving intravenous lipids), and less parenteral carbohydrates (data not shown).

Discussion We describe the association between nutrition delivery practices and energy and protein intake in infants who were VLBW during the transition from parenteral fluids to full enteral nutrition. The models quantify the trade-offs that need to be considered for each nutrition delivery practice decision. Although PN, intravenous lipids, fortification, and fluid intake vary in concentration and/or volume, they were analyzed dichotomously to simplify the complexity of the trade-offs and because clinicians appear to approach such decisions in a dichotomous manner (eg, should we continue PN today?). The complexity of balancing such trade-offs is highly relevant for infants who are VLBW in the immediate postnatal period and infants made NPO for feeding intolerance or evaluation and management of NEC/SIP.20 The findings of this study suggest the following recommendations to maximize energy and protein intake in VLBW infants: (1) deliver PN and intravenous lipids through phase 3 (≤66.7% enteral) to maximize energy intake; (2) consider PN through phase 4 (33.3% enteral) to maximize protein intake; and (7) limit fluid restriction and excess non-nutritive fluid intake whenever possible. We acknowledge that our suggested approaches prioritize nutrient delivery and are not ideal for competing interests such as the reduction of central-line use. The paradoxical results of fortification in the bivariable and multivariable analyses during phases 2 and 3 were surprising. Infants fortified in phases 2 and 3 received less energy and protein. Gains in enteral energy and protein appear to be negated by larger losses of parenteral energy and protein delivery. These losses are expected to be clinically significant, given that our previous work demonstrated that an increased energy intake of 10 kcal/kg/d over the course of the week was associated with an increased growth velocity of 1.7 g/kg/d.3 The transition phases from parenteral to full enteral feeds represent a dynamic time when energy and protein contribution from each nutrition delivery practice changes. Ideally, clinicians would have easy access to real-time data assessing the energy and protein intake actually received and projected to receive from orders21; however, such a data infrastructure is not widely available.22,23 Even though calculating energy and protein intake does not require advanced mathematics, retrieval of the data to assess the gain or loss in energy and protein from each nutrition delivery practice requires time and effort. This study suggests that an accurate, automated system to compare and contrast the tradeoffs in energy and protein intake with different nutrition delivery practice decisions could substantially assist clinicians. The study attempted to model these

scenarios to help guide clinicians; however, real-time feedback from orders placed within the electronic health record would be optimal. As clinicians attempt to reduce central line– associated infections, early removal of a central line becomes a priority, but without the ability to immediately assess the reduction in energy and protein from the loss of concentrated PN and intravenous dextrose. Similarly, although substantial fluid restriction may be prescribed for bronchopulmonary dysplasia,10 lack of immediate feedback to the clinical team masks its association on receipt of energy and protein. There are several limitations to the analysis. This is a retrospective analysis at a single, referral NICU. Nutrition delivery practices for starting or adjusting PN, feedings or fortification, and their associated outcomes may not be generalizable to all NICUs. The sample size included all infants who were VLBW admitted by 1 week without congenital anomalies to minimize selection bias; however, the findings may not be generalizable to other types of infants in the NICU as a result. Published values were used for the caloric and protein content of human milk, yet these also are known to vary by woman and progression of lactation.24 Documentation errors may have influenced the observed findings: however, daily surveillance of the medical record likely mitigated this limitation and nonsensical differences were reconciled. Lastly, other unknown or unmeasured clinical variables may have affected our results. In conclusion, achieving recommended nutrient intake for infants who are VLBW during the transition from parenteral to enteral nutrition may be hindered by the dynamic association between nutrition delivery practices and energy and protein intake. We speculate that, without more substantive data and computational infrastructure, clinicians are unlikely to be able to accurately ascertain the net association on nutrient intake, resulting from the multiple decisions about nutrition delivery practices. Increased recognition of this important deficit should shift attention and resources to the development and implementation of data and computational infrastructure to facilitate nutritional management of infants who are VLBW. Future research needs to examine optimization of the workflow related to data and computation about nutrition delivery practices by clinicians and the potential association on nutrient intake, as well as specification of the software needed to effectively leverage data in the electronic health record. ■ We thank Janice Raucci, PharmD, BCPPS, for assistance with development of definitions of variables and abstraction of PN details, and Pratyusha Yadavalli, MD, for assistance with data abstraction. Submitted for publication Mar 6, 2018; last revision received May 18, 2018; accepted Jul 3, 2018 Reprint requests: Gustave H. Falciglia, MD, MSc, Ann & Robert H. Lurie Children’s Hospital of Chicago, 225 E. Chicago Ave, Box #45, Chicago, IL 60611. E-mail: [email protected]

Data Statement Data available on request.

Energy and Protein Intake During the Transition from Parenteral to Enteral Nutrition in Infants of Very Low Birth Weight FLA 5.5.0 DTD ■ YMPD10109_proof ■ August 29, 2018

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THE JOURNAL OF PEDIATRICS • www.jpeds.com References 1. Embleton NE, Pang N, Cooke RJ. Postnatal malnutrition and growth retardation: an inevitable consequence of current recommendations in preterm infants? Pediatrics 2001;107:270-3. 2. Martin CR, Brown YF, Ehrenkranz RA, O’Shea TM, Allred EN, Belfort MB, et al. Nutritional practices and growth velocity in the first month of life in extremely premature infants. Pediatrics 2009;124:649-57. 3. Falciglia GH, Murthy K, Holl J, Palac HL, Oumarbaeva Y, Yadavalli P, et al. Association between the 7-day moving average for nutrition and growth in very low birth weight infants. JPEN J Parenter Enteral Nutr 2017;42:80512. 4. Miller M, Vaidya R, Rastogi D, Bhutada A, Rastogi S. From parenteral to enteral nutrition: a nutrition-based approach for evaluating postnatal growth failure in preterm infants. JPEN J Parenter Enteral Nutr 2014;38:489-97. 5. Ehrenkranz RA, Younes N, Lemons JA, Fanaroff AA, Donovan EF, Wright LL, et al. Longitudinal growth of hospitalized very low birth weight infants. Pediatrics 1999;104:280-9. 6. Ainsworth S, McGuire W. Percutaneous central venous catheters versus peripheral cannulae for delivery of parenteral nutrition in neonates. Cochrane Database Syst Rev 2015;(10):CD004219. 7. Bell EF, Acarregui MJ. Restricted versus liberal water intake for preventing morbidity and mortality in preterm infants. Cochrane Database Syst Rev 2014;(1):CD000503. 8. Pallotto EK, Piazza AJ, Smith JR, Grover TR, Chuo J, Provost L, et al. Sustaining SLUG bug CLABSI reduction: does sterile tubing change technique really work? Pediatrics 2017;140:e20163178. 9. Piazza AJ, Brozanski B, Provost L, Grover TR, Chuo J, Smith JR, et al. SLUG bug: quality improvement with orchestrated testing leads to NICU CLABSI reduction. Pediatrics 2016;137:e20143642. 10. Biniwale MA, Ehrenkranz RA. The role of nutrition in the prevention and management of bronchopulmonary dysplasia. Semin Perinatol 2006;30:2008. 11. Murthy K, Dykes FD, Padula MA, Pallotto EK, Reber KM, Durand DJ, et al. The Children’s Hospitals Neonatal Database: an overview of patient complexity, outcomes and variation in care. J Perinatol 2014;34:582-6. 12. 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;29:618-22.

Volume ■■ 13. Quigley M, McGuire W. Formula versus donor breast milk for feeding preterm or low birth weight infants. Cochrane Database Syst Rev 2014;(4):CD002971. 14. Moya F, Sisk PM, Walsh KR, Berseth CL. A new liquid human milk fortifier and linear growth in preterm infants. Pediatrics 2012;130:e92835. 15. Kleinman R, Greer F. eds. Nutritional needs of preterm infants & Appendix D. In: American Academy of Pediatrics Committee on Nutrition: pediatric nutrition handbook. 7th ed. Elk Grove (IL): American Academy of Pediatrics; 2014. 16. Nutrient Data Laboratory of the Beltsville Human on Research Center. USDA Food Composition Databases [Internet]. https://ndb.nal.usda.gov/ ndb/foods/show/299375?manu=&fgcd=&ds=&q=Milk,human,mature ,fluid. Accessed May 1, 2018. 17. Kleinman R. ed. Appendix F4: selected nutrients in human milk. In: American Academy of Pediatrics Committee on Nutrition: pediatric nutrition handbook. 6th ed. Elk Grove (IL): American Academy of Pediatrics; 2009, p. 1265. 18. Cormack BE, Embleton ND, van Goudoever JB, Hay WW, Bloomfield FH. Comparing apples with apples: it is time for standardized reporting of neonatal nutrition and growth studies. Pediatr Res 2016;79:810-20. 19. Robson K, Pevalin D. What is multilevel modelling and why should I use it? In: Steele M, ed. Multilevel modeling in plain language. 1st ed. Los Angeles: Sage; 2016. 20. Lin GC, Robinson DT, Olsen S, Reber KM, Moallem M, DIgeronimo R, et al. Nutritional practices and growth in premature infants after surgical necrotizing enterocolitis. J Pediatr Gastroenterol Nutr 2017;65:1116. 21. Pande PS, Neuman RP, Cavanaugh RR. Key concepts of the Six Sigma system. In: The Six Sigma way. 2nd ed. New York: McGraw Hill Education; 2014. 22. Skouroliakou M, Koutri K, Stathopoulou M, Vourvouhaki E, Giannopoulou I, Gounaris A. Comparison of two types of TPN prescription methods in preterm neonates. Pharm World Sci 2009;31:202-8. 23. Alrifai MW, Mulherin DP, Weinberg ST, Wang L, Lehmann CU. Parenteral protein decision support system improves protein delivery in preterm infants: a randomized clinical trial. JPEN J Parenter Enteral Nutr 2018;42:219-24. 24. Ballard O, Morrow AL. Human milk composition: nutrients and bioactive factors. Pediatr Clin North Am 2013;60:49-74.

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Figure 2. Proportion of infants in each phase of nutrition by age.

Table I. Energy intake associated with fluid intake Fluid intake, mL/kg/d

Median kcal/kg/d

Total fluid intake, mL/kg/d ≤110 >110 and ≤130 >130 and ≤145 >145 and ≤160 >160 and ≤180 >180 Non-nutritive fluid intake, mL/kg/d ≤1 >1 and ≤10 >10 and ≤35 >35

IQR

Beta, P value

58.0 93.1 108.6 121.1 124.2 115.9

42.3, 79.3, 97.9, 113.2, 101.6, 77.8,

77.0 103.3 116.6 125.0 133.2 149.9

−53.9,