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Enteral feeding

2002· article· en· W4232688943 on OpenAlexaff
Khursheed N. Jeejeebhoy

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2002
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsParenteral nutritionMedicineEnteral administrationIntensive care medicineMalnutritionGlutamineAspiration pneumoniaMedical nutrition therapyPneumoniaInternal medicine

Abstract

fetched live from OpenAlex

In this review, topics with scientific strength, topical interest, and controversy were selected. Over the past 50 years, malnutrition has become increasingly recognized as a cause of increased morbidity and mortality in hospital patients. From 1970 to 1980, parenteral nutrition was advocated as the most appropriate form of nutritional therapy for hospital patients. Since then, parenteral nutrition has been replaced by enteral nutrition as the best way of delivering nutrients to hospital patients. The timing of enteral nutrition has been debated. Should it be instituted early, within the first 24 hours? In addition, enteral nutrition containing immune-enhancing nutrients such as arginine, omega-3 fatty acids, glutamine, and nucleotides has been advocated for critically ill patients. The relative merits of enteral versus total parenteral nutrition continue to be debated. Questions about possible complications related to enteral nutrition have been raised. Patients are at risk of nosocomial pneumonia from aspiration and at risk of bowel ischemia because enteral nutrition increases intestinal oxygen consumption. Steroids are often used to treat Crohn disease, but because of undesirable side effects, various techniques have been used to reduce steroid dependency. Enteral nutrition has been advocated as a way of reducing steroid dependency. Finally, enteral nutrition is routinely used to feed demented patients and those in a vegetative state. It is not clear whether this practice alters outcome or quality of life.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.248
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.081
GPT teacher head0.352
Teacher spread0.271 · 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

Citations6
Published2002
Admission routes1
Has abstractyes

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