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Record W1508861742 · doi:10.1111/nyas.12498

Clinical and economic outcomes of nutrition interventions across the continuum of care

2014· review· en· W1508861742 on OpenAlexaff
M.A.E. de van der Schueren, Marinos Elia, Leah Gramlich, Michael P. Johnson, Su Lin Lim, Tomas Philipson, Azra Jaferi, Carla M. Prado

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2014
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMalnutritionPsychological interventionMedicineHealth careContext (archaeology)Continuum of careClinical nutritionIntensive care medicineHealth economicsEnvironmental healthNursingPublic healthEconomic growthEconomics

Abstract

fetched live from OpenAlex

Optimal nutrition across the continuum of care plays a key role in the short- and long-term clinical and economic outcomes of patients. Worldwide, an estimated one-quarter to one-half of patients admitted to hospitals each year are malnourished. Malnutrition can increase healthcare costs by delaying patient recovery and rehabilitation and increasing the risk of medical complications. Nutrition interventions have the potential to provide cost-effective preventive care and treatment measures. However, limited data exist on the economics and impact evaluations of these interventions. In this report, nutrition and health system researchers, clinicians, economists, and policymakers discuss emerging global research on nutrition health economics, the role of nutrition interventions across the continuum of care, and how nutrition can affect healthcare costs in the context of hospital malnutrition.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.359
GPT teacher head0.558
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations33
Published2014
Admission routes1
Has abstractyes

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