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Record W1975674098 · doi:10.4236/fns.2015.61002

Assessment of the Nutritional Status of 202 Elderly People Living at Home in Sidi-Bel-Abbès (Western Algeria)

2015· article· en· W1975674098 on OpenAlexaff
Noureddine Menadi, Ghozlane Kelkoul, Ilhem Hassani, Belabbes Merrakchi, Slimane Belbraouet

Bibliographic record

VenueFood and Nutrition Sciences · 2015
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMalnutritionAnthropometryMedicineBody mass indexGerontologyPopulationPublic healthDiabetes mellitusElderly peopleEnvironmental healthInternal medicineEndocrinologyNursing

Abstract

fetched live from OpenAlex

Background: Malnutrition is common for elderly representing a major public health problem with many consequences for the health. Objectives: To assess the nutritional status of a population of elderly living at home. Subjects and Methods: The assessment was conducted from a population of elderly living at home who saw their doctor in the office of a public health centre. For each subject, the anthropometric parameters (weight, height, body mass index (BMI)), biochemical (serum albumin) and Mini Nutritional Assessment (MNA) tools have been measured and calculated. Results: 202 mostly female (56.44%) subjects aged 73.59 ± 5.87 years were included in this study. 78% were suffering from chronic diseases, the most frequent of which was diabetes (32%). 7.43% of the diseased population have BMI < 21, 5.94% experienced undernutrition (MNA < 17) and 68.81% are at risk of malnutrition (MNA: 17 - 23.50). According to serum albumin, 8.91% of the sample is considered to be malnourished. Conclusion: The MNA has proven to be a screening tool more sensitive than other tools (BMI and albumin) in the evaluation of nutritional risk.

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)0.001
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 score0.006
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

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

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 head0.105
GPT teacher head0.386
Teacher spread0.281 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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