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Record W4405040974 · doi:10.4103/jpcc.jpcc_57_24

Nutrition in neonatal and pediatric patients on extracorporeal membrane oxygenation: A survey of current practice in the US and Canada

2024· article· en· W4405040974 on OpenAlexaboutno aff
Jamie Furlong-Dillard, Michael Facciolo, Caroline Ozment

Bibliographic record

VenueJOURNAL OF PEDIATRIC CRITICAL CARE · 2024
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsnot available
Fundersnot available
KeywordsExtracorporeal membrane oxygenationMedicineMalnutritionLife supportMedical nutrition therapyParenteral nutritionEnteral administrationMortality rateIntensive care medicinePediatricsEmergency medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Patients requiring extracorporeal membrane oxygenation (ECMO) are at increased risk of malnutrition due to high rates of protein catabolism, unclear metabolic needs, and safety risks with both parenteral and enteral nutrition (EN). Malnourishment is associated with increased morbidity and mortality, and improved EN and protein intake are associated with decreased 60-day mortality. A standardized practice for nutrition therapy in this population is unestablished. We aim to provide an update on current nutritional practices in pediatric and neonatal patients receiving ECMO support. Subjects and Methods: An online survey was distributed to ECMO medical directors in the US and Canada who had previously participated in survey-based research and those who requested participation during a pediatric ECMO presentation of this study. Each medical director was asked to forward the survey to their center’s registered dietitians (RDs). Results: Of 100 institutions surveyed, 36 physicians and 19 RDs responded yielding a physician response rate of 36% and an RD response rate of 19%. Physicians report “always” providing nutrition parenterally 28% and enterally 17% of the time with 11% of institutions using a protocolized approach. Nutrition therapy aids reduction of morbidity and mortality; however, there is variability in its delivery. Conclusions: Compared to 2015, EN is reported to be less utilized (47% vs. 55%) with less protocol use (11% vs. 38%). These data support the need for the development of a stepwise nutritional support algorithm, which is congruent with the recommendations in the Extracorporeal Life Support Organization Nutrition Guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.346
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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