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Record W4391873591 · doi:10.1093/jcag/gwad061.179

A179 UNDERSTANDING THE NEED FOR A ZINC DIET TO TREAT ZINC DEFICIENCY IN PATIENTS WITH CELIAC DISEASE

2024· article· en· W4391873591 on OpenAlexaff
Shilpa Tandon, Karen A. Graham, Lindsey Russell, Jane E. Morgan, David Armstrong, M Pinto-Sanchez

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsPopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsZincZinc deficiency (plant disorder)DiseaseMedicineGastroenterologyInternal medicineMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Abstract Background Nutritional deficiencies in celiac disease (CeD) are caused by delayed intestinal healing and a nutrient-lacking gluten-free diet (GFD). At our specialized adult celiac clinic, zinc (Zn) was the most common deficiency present in patients and is clinically treated through Zn supplementation. However, Zn supplements in excess may cause inhibition of other minerals, and gastrointestinal side effects. Alternatively, a Zn diet may be a sustainable option to treat zinc deficiency, however patient preference regarding this treatment method is unknown. Aims To understand patient preference of zinc supplementation compared to a zinc diet to treat Zn deficiency in CeD. We also aim to determine the tolerability and effectiveness of Zn supplements to reduce gastrointestinal and extraintestinal symptoms in the CeD population. Methods This observational prospective pragmatic study was conducted from March 2022-September 2023. Eligible participants had bloodwork indicating plasma Zn levels ampersand:003C 9.4 μ/mol . All participants were prescribed 25 mg per day of Zn gluconate supplements throughout the study. Patients were provided a RedCap link where they completed questionnaires at Visit 1 and at their next clinic appointment in 3-6 months (Visit 2). These surveys included; Celiac Symptom Index (CSI) Questionnaire 2) Extraintestinal Symptoms Visual Analogue Scale (ES-VAS) and 3) Patient Perception Survey (PPS). Continuous data are expressed as Mean (SD), and categorical data is reported as frequencies (%). The Wilcoxon test was used to assess changes in symptoms. Results A total of 42 participants completed the Visit 1 survey, of which 17 participants had their follow up clinic appointment (Visit 2). Out of these 17 participants, 15 were female (88.2%) and the mean age was 33.7 years (+/- 10.6). The mean CSI score at Visit 1 was 35.3 (+/- 10.3) and 33.7 (+/- 13.0) at Visit 2, indicating moderate disease symptoms (p=0.552). The most common extraintestinal symptoms was anxiety (ES-VAS: 5.7), foggy mind (ES-VAS: 4.1), fatigue (ES-VAS: 4.1) and depression (ES-VAS: 3.5). There were no significant changes in extraintestinal symptoms between clinic visits. Out of 42 participants, 15 (35.7%) prefer to treat their Zn deficiency through diet, 26 (59.5%) through supplement, and 1 (2.4%) of participants had no preference. Additionally, 35 (85.4%) participants indicated that they were “likely” to comply to a Zn-diet treatment. Conclusions CeD patients did not experience improvement in gastrointestinal or extraintestinal symptoms on Zn supplementation. However, a portion of CeD patients prefer to treat and are likely to comply with a Zn diet to treat their deficiency. Based on this knowledge, further studies should investigate the efficacy of a Zn diet compared to supplements CeD patients. Funding Agencies CIHR

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)0.004
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.252
Teacher spread0.238 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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