Variation in Neonatal Nutrition Practice and Implications: A Survey of Australia and New Zealand Neonatal Units

McLeod, Gemma A.; Farrent, Shelley; Gilroy, Melissa; Page, Denise; Oliver, Colleen; Richmond, Fiona; Cormack, Barbara

doi:10.3389/fnut.2021.642474

Cited by 8 publications

(4 citation statements)

References 79 publications

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“…PDHM and MOM are often fortified to meet premature infants' nutrient requirements. Standard fortification is based on a reference value for milk protein content, 28 usually 0.8–1.3 g/100 mL in Australia 29 . Our study provides additional information for clinicians making decisions around fortification of PDHM in Australian NICUs.…”

Section: Discussionmentioning

confidence: 96%

Macronutrient content of pasteurised donor human milk: Variability between batches from single‐donor pools at an Australian milk bank

Walter,

Clifford,

Sulfaro

et al. 2023

J Paediatrics Child Health

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AimThis study aimed to characterise the between‐batch variability of pasteurised donor human milk (PDHM) produced from single‐donor pools at Australian Red Cross Lifeblood's milk bank and identify key donor characteristics that predict macronutrient content.MethodsMacronutrient content from 200 batches of PDHM was measured using a mid‐infrared human milk analyser (Miris, Uppsala, Sweden). Linear mixed models were used to study the impact of stage of lactation and gestational age on macronutrient content. Coefficients of determination (R2) were calculated to estimate the impact of the individual donor on overall variability.ResultsMacronutrient content of PDHM varied considerably, with between‐batch variations of 2.8 and 6.4‐fold for protein and fat content, respectively. Mean crude protein content was 1.16 g/100 mL, ranging from 0.7 to 1.96 g/100 mL. Mean fat content was 3.85 g/100 mL, ranging from 1.46 to 9.39 g/100 mL. Stage of lactation was identified as a predictor for protein content and gestational age at birth for fat content. Individual donor effect explained 55 and 35% of the variance for fat and protein content, respectively.ConclusionsThis study highlights the variation in macronutrient content in PDHM at an Australian milk bank. Variability could be reduced through the implementation of targeted multiple‐donor pooling using the key donor characteristics identified in this study along with the measurement of macronutrient content of individual donors at the time of first donation. However, the clinical benefit of a reduction in between‐batch variation, achieved through multiple‐donor pooling, would need to be assessed to justify additional efforts associated with PDHM processing changes.

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Section: Discussionmentioning

confidence: 96%

Macronutrient content of pasteurised donor human milk: Variability between batches from single‐donor pools at an Australian milk bank

Walter,

Clifford,

Sulfaro

et al. 2023

J Paediatrics Child Health

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“…One limitation of this approach is that the feed recommendations generated by the NRO engine were based solely on the participating site's clinical guidelines [51]. As a result, the applicability of these recommendations may be limited to the specific practices and protocols followed at the site [52]. Therefore, caution should be exercised when generalizing these findings to other clinical settings.…”

Section: Discussionmentioning

confidence: 99%

An Ontology and Rule-Based Clinical Decision Support System for Personalized Nutrition Recommendations in the Neonatal Intensive Care Unit

Kaur,

Jain,

McAdams

et al. 2023

IEEE Access

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Premature neonates hospitalized in the neonatal intensive care unit (NICU) have high nutritional needs to ensure optimal growth and development. Monitoring adherence to neonatal nutritional guidelines and providing personalized nutritional recommendations are essential for promoting their health. However, ensuring consistent adherence to these guidelines is challenging. To address this, we developed a clinical decision support system using an ontology and rule-based approach to offer personalized nutrition recommendations for preterm infants in the NICU. The Nutrition Recommendation Ontology (NRO) was developed, incorporating 121 classes, 366 axioms, and 157 semantic rules based on standard nutrition guidelines and retrospective data from 601 NICU patients, using a cumulative 8460 patient-days data collected from a single center between 2019-2021. While the ontology represented the conceptual knowledge, the rules encoded the procedural knowledge. The integrated NRO-based system serves as a reasoning engine, enabling the generation of patient-specific feeding recommendations and assisting in identifying deviations from established guidelines. To validate its efficacy, the NRO system was tested on 10 sample case studies and achieved 98% accuracy, as assessed by a panel of neonatologists. Our findings indicate that the NRO-based clinical decision support system can provide accurate personalized nutrition recommendations and assess guideline adherence in the NICU. With further real-world validation, we anticipate that this approach could significantly improve nutrition delivery, prevent malnutrition, and ultimately improve outcomes for preterm infants. INDEX TERMS Premature neonates,Ontology, clinical decision support,semantic,nutrition management I. INTRODUCTION A PPROPRIATE nutrition is essential for the growth, development, metabolism, and immunity of preterm neonates [1], [2]. Inadequate nutrition in premature neonates hospitalized in the neonatal intensive care unit (NICU) is associated with long-term adverse outcomes such as decreased growth and impaired neurodevelopment [3], [4]. Due to immature gastrointestinal tracts, premature neonates at <34 weeks gestational age are unable to tolerate full enteral nutrition after birth and therefore require parenteral nutri-

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“…Nutrition interventions for preterm infants vary widely among hospitals. 4,5 There is no consensus about optimal nutrition for preterm infants because of large variability in methodology, approach, and reporting of published studies. 6 Hence, evidencebased nutrition guidelines are needed to enable health practitioners to make the best nutrition care decisions for preterm infants.…”

Section: Introductionmentioning

confidence: 99%

“…Nutrition interventions for preterm infants vary widely among hospitals 4,5 . There is no consensus about optimal nutrition for preterm infants because of large variability in methodology, approach, and reporting of published studies 6 .…”

Section: Introductionmentioning

confidence: 99%

Nutrition guidelines for preterm infants: A systematic review

Meiliana,

Alexander,

Bloomfield

et al. 2023

J Parenter Enteral Nutr

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Background:There is no consensus on optimal nutrition for preterm infants, leading to substantial practice variation. We aimed to assess the quality of nutritional guidelines for preterm infants, the consistency of recommendations, and the gaps in recommendations.Methods:We searched databases and websites for nutritional guidelines for preterm infants before first hospital discharge, which were endorsed, prepared, or authorised by a regional, national, or international body, written in English, and published between 2012‐2023. Two reviewers independently screened articles and extracted the recommendations. Four reviewers appraised the included guidelines using AGREE II.Results:7051 records were identified, and 27 guidelines included, 26% of which were high in quality. Most guidelines lacked stakeholder involvement and rigour of development. We found considerable variation in recommendations, many of which lacked details of certainty of evidence and strength of recommendation. Recommendations for type of feed and breastmilk fortification were consistent among high quality guidelines, but recommendations varied for intakes of almost all nutrients and monitoring of nutritional adequacy. Different guidelines gave different certainty of evidence for the same recommendations. Most gaps in recommendations were due to very low certainty of evidence.Conclusions:Future development of nutritional guidelines for preterm infants should follow the standard guideline development method and ensure the rigorous process including stakeholders involvement to improve the reporting of strength of recommendation, certainty of evidence, and gaps in recommendation. Evidence is needed to support recommendations about macro and micronutrient intakes, breastmilk fortification, and markers on adequacy of intake of different nutrients.This article is protected by copyright. All rights reserved.

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Variation in Neonatal Nutrition Practice and Implications: A Survey of Australia and New Zealand Neonatal Units

Cited by 8 publications

References 79 publications

Macronutrient content of pasteurised donor human milk: Variability between batches from single‐donor pools at an Australian milk bank

Macronutrient content of pasteurised donor human milk: Variability between batches from single‐donor pools at an Australian milk bank

An Ontology and Rule-Based Clinical Decision Support System for Personalized Nutrition Recommendations in the Neonatal Intensive Care Unit

Nutrition guidelines for preterm infants: A systematic review

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