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Record W2126558871 · doi:10.1186/1472-6963-14-s2-p11

Effectiveness of external factors to reduce the risk of dehydration in older people living in residential care: a systematic review

2014· review· en· W2126558871 on OpenAlexaboutno aff
Diane Bunn, Florence O. Jimoh, Stephanie Howard Wilsher, Lee Hooper

Bibliographic record

VenueBMC Health Services Research · 2014
Typereview
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsnot available
FundersUniversity of East AngliaNational Institute for Health and Care Research
KeywordsMedicineNursing researchHealth administrationHealth informaticsPublic healthQuality of Life ResearchDehydrationNursingEnvironmental health

Abstract

fetched live from OpenAlex

Water-loss dehydration, when fluid output exceeds fluid intake, is prevalent in older people living in care homes, due to declining kidney function and poorer thirst sensation exacerbated by increasing comorbidities and impaired mental and physical capacities to obtain a drink. As dehydration is associated with poor health outcomes, effective prevention strategies will improve quality of life. A systematic review, following the Cochrane Collaboration’s guidelines ( http://www.cochrane.org/ ) aimed to identify effective interventions and modifiable factors which improved hydration status and/or fluid intake in older people (≥ 65 years) living in residential care who could drink orally ( http://www.crd.york.ac.uk/Prospero/display_record,asp?ID=CRD42OI2003100 ). Thirteen electronic databases were searched from inception until 30 September 2013 in all languages, with additional searches of key authors, reference lists of reviews and included papers. Using predetermined criteria, two reviewers independently selected studies for inclusion, abstracted data and assessed validity. Searches identified 4328 titles and abstracts after 856 duplicates were removed. 325 full-text papers were obtained and 23 studies included (nineteen intervention and 4 observational studies) from 7 countries. A wide range of interventions and exposures were identified, but the lack of suitable ways of accurately assessing fluid intake and/ or dehydration, as well as paucity of randomisation and allocation concealment resulted in the efficacy of many strategies being unproven. Two observational studies with low risk of bias conducted secondary analyses demonstrating that for-profit ownership in Canada was associated with higher rates of hospital admission for dehydration compared to not-for-profit homes, whilst in the United States (US) there was no difference. Studies at higher risk of bias reported lower rates of dehydration following implementation of the Resident Assessment Instrument (US), eating in a less-institutionalised setting (US, UK), eating with others (US) or use of high-contrast red tableware compared with white (US). No effect was seen for number of residents present in the dining-room, allocation of a permanent seating position, noise level, position of feeding assistants, type of thickening agents used, staff training or staff: resident ratios (Canada, Ireland, US). However, these studies were small so useful effects may have been missed. Multi-component interventions in Germany, Japan, Taiwan and US (including increased availability, attractiveness and choice of drinks, education, assistance with drinking and toileting) were associated with increased fluid intake when between-meals drinks rounds were introduced. There are some promising interventions to improve fluid intake in care homes, but high quality well-powered randomised controlled trials are needed to confirm their efficacy.

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)0.007
metaresearch head score (Gemma)0.032
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: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.008
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
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 head0.068
GPT teacher head0.481
Teacher spread0.414 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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