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Record W4396745184 · doi:10.1016/j.clnu.2024.04.039

ESPEN guideline on nutrition and hydration in dementia – Update 2024

2024· article· en· W4396745184 on OpenAlexaff
Dorothee Volkert, Anne Marie Beck, Gerd Faxén Irving, Thomas Frühwald, Lee Hooper, Heather Keller, Judi Porter, Elisabet Rothenberg, Merja Suominen, Rainer Wirth

Bibliographic record

VenueClinical Nutrition · 2024
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsResearch Institute for AgingUniversity of Waterloo
FundersEuropean Society for Clinical Nutrition and Metabolism
KeywordsMedicineGuidelineDementiaGerontologyIntensive care medicineInternal medicinePathologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND & AIMS: Dementia is accompanied by a variety of changes that result in an increased risk of malnutrition and low-intake dehydration. This guideline update aims to give evidence-based recommendations for nutritional care of persons with dementia in order to prevent and treat these syndromes. METHODS: The previous guideline version was reviewed and expanded in accordance with the standard operating procedure for ESPEN guidelines. Based on a systematic search in three databases, strength of evidence of appropriate literature was graded by use of the SIGN system. The original recommendations were reviewed and reformulated, and new recommendations were added, which all then underwent a consensus process. RESULTS: 40 recommendations for nutritional care of older persons with dementia were developed and agreed, seven at institutional level and 33 at individual level. As a prerequisite for good nutritional care, organizations caring for persons with dementia are recommended to employ sufficient qualified staff and offer attractive food and drinks with choice in a functional and appealing environment. Nutritional care should be based on a written care concept with standardized operating procedures. At the individual level, routine screening for malnutrition and dehydration, nutritional assessment and close monitoring are unquestionable. Oral nutrition may be supported by eliminating potential causes of malnutrition and dehydration, and adequate social and nursing support (including assistance, utensils, training and oral care). Oral nutritional supplements are recommended to improve nutritional status but not to correct cognitive impairment or prevent cognitive decline. Routine use of dementia-specific ONS, ketogenic diet, omega-3 fatty acid supplementation and appetite stimulating agents is not recommended. Enteral and parenteral nutrition and hydration are temporary options in patients with mild or moderate dementia, but not in severe dementia or in the terminal phase of life. In all stages of the disease, supporting food and drink intake and maintaining or improving nutrition and hydration status requires an individualized, comprehensive approach. Due to a lack of appropriate studies, most recommendations are good practice points. CONCLUSION: Nutritional care should be an integral part of dementia management. Numerous interventions are available that should be implemented in daily practice. Future high-quality studies are needed to clarify the evidence.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0070.006

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 head0.087
GPT teacher head0.467
Teacher spread0.379 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations83
Published2024
Admission routes1
Has abstractno

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