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Deficiencies in Nutritional Intake in Patients with Diabetic Foot Ulcers

2017· article· en· W2584425836 on OpenAlexvenueno aff
Haiyan Min Maier, Jasminka Ilich Ernst, Bahram H. Arjmandi, Jeong Su Kim, Maria T. Spicer

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetic footMedicineFoot (prosody)Diabetes mellitusInternal medicineEndocrinologyGastroenterologyPhilosophy

Abstract

fetched live from OpenAlex

Aims: This study examined the dietary and anthropometric components of diabetic patients with or without diabetic foot ulcers (DFU). Methods: Eighty-two adult subjects were recruited in Tallahassee, FL (USA) and categorized into one of three groups: subjects without diabetes, patients with Diabetes Mellitus (DM) but not foot ulcers, and patients with DFU. Twenty-four hour food recalls, foot ulcer history and blood samples were collected from each subject. Dietary intake was evaluated with Food Processor. Biomarkers of inflammation and oxidative stress were measured with ELISA kits. Results: DFU subjects in this study were mostly overweight or obese. DFU had inadequate intakes in protein, fiber, vitamin B1, B2, B3, B6, C, D, and E; calcium, magnesium, phosphorus, potassium, selenium, and zinc. They had excessive intakes in saturated fat, trans fat, and sodium. Conclusions: Malnutrition is very common in the DM and DFU subjects. Protein and vitamin supplementation may be beneficial in prevention and management of DM as well as DFU.

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)0.000
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 score0.010
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.293
Teacher spread0.262 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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