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A multi‐center assessment of the nutritional quality of hospital patient menus (393.7)

2014· article· en· W2130273555 on OpenAlexaffabout
JoAnne Arcand, Jaclyn Fraser, Lori Wilkinson, Susan Trang, Katherine Steckham, Heather Fletcher, Heather Oliphant, Mary R. L’Abbé, Roula Tzianetas

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsHamilton Health SciencesHealth Sciences CentreSt. Michael's HospitalMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsDietary Reference IntakeMedicineMalnutritionNutrientVitaminEnvironmental healthChemistryInternal medicine

Abstract

fetched live from OpenAlex

In Canada, there are no widely accepted standards for hospital menu planning. The objective of this study was to evaluate the quality of nutrients and foods served on hospital patient menus. At 3 acute care hospitals in Ontario, Canada (Nov‐Aug 2011), 84 standard menus and 2234 consecutive patient‐selected menus were evaluated in regular and diabetic diets, and 3000 mg and 2000 mg sodium restricted diets. Comparisons were made against the Dietary Reference Intakes (DRI) and Canada’s Food Guide. Energy levels ranged from 1281 ‐ 3007 kcal and 45% of standard menus had < 1600 kcal. Protein ranged from 49 ‐ 159 g and 30% of standard menus had < 60 g. The standard regular menu, the most commonly prescribed, had 1673 ± 362 kcal and 63 ± 9 g protein. Energy and protein levels were highest in diabetic menus. All standard regular and diabetic menus fell within the Acceptable Macronutrient Distribution Range. The proportion of regular standard menus meeting the DRIs were 0% for calcium, sodium, and fibre; 50% for Vitamin C; and 86% for iron. 100% of sodium‐restricted menus fell below the DRI for calcium. Most menus met Milk & Alternatives recommendations, though only 27% met Vegetables and Fruit, 11% met Grain Products, and 8% met Meat & Alternatives recommended servings. These data show that patient menus did not consistently meet recommendations for macronutrient and vitamin and minerals or for the number of Canada’s Food Guide servings, which may contribute to malnutrition. This data supports the need for policies guiding food procurement and menu planning in hospitals.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.401
Threshold uncertainty score0.797

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.374
Teacher spread0.326 · 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 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

Citations1
Published2014
Admission routes2
Has abstractyes

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