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Record W3120002515 · doi:10.1016/j.nutos.2020.12.005

Association of serum vitamin D status with development of type 2 diabetes: A retrospective cross-sectional study

2021· article· en· W3120002515 on OpenAlexaff
Hannah Marcus, Muralidhar Varma, Sonal Sekhar Miraj

Bibliographic record

VenueClinical Nutrition Open Science · 2021
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineDiabetes mellitusType 2 Diabetes MellitusCross-sectional studyInternal medicineOdds ratioType 2 diabetesPublic healthRetrospective cohort studyEpidemiologyStatistical significanceEndocrinologyPathology

Abstract

fetched live from OpenAlex

Background and aims Vitamin D deficiency (VDD) has become a growing global public health issue, which is placing increasing burdens on healthcare systems worldwide due to its multifactorial clinical manifestations. However, epidemiological findings pertaining to VDD's link with various disease pathologies, especially type 2 diabetes mellitus (T2DM), remain contradictory. Through a retrospective cross-sectional analysis, this study aimed to contribute towards the construction of a novel framework for understanding the relationship between VDD and T2DM to subsequently inform relevant public health policy. Methods A retrospective cross-sectional analysis of the prevalence of diabetes in both VDD and non-VDD groups was conducted. Data pertaining to various biochemical parameters was obtained from the Kasturba hospital database for 500 patients tested for both serum 25(OH)D and blood glucose levels [i.e. random, fasting, post-prandial, and/or hemoglobin A1c (HbA1C)] between 1st January and 30th April 2018. Results Within the study sample, 117 (41.1%) of patients with VDD had T2DM, whereas 72 (33.5%) of patients without VDD had T2DM. This indicates no association between VDD and T2DM (χ2 = 2.98; p = 0.084). Still, an OR value of 1.4, despite statistical insignificance (95%CI:0.96–2.0, p = 0.084) indicates that there is an approximately 40% greater odds of developing T2DM in VDD patients relative to non-VDD patients. Moreover, the likelihood ratio (LR) is 2.99, which indicates an approximately 3-fold chance of having T2DM as a VDD patient, relative to a non-VDD patient. Conclusions Despite the lack of statistical significance, the findings of this study make important contributions to the existing literature and must be considered in light of their inherent limitations. Taking these into account, it becomes clear that these results should not be extrapolated nor assumed to entirely invalidate the hypothesized link between VDD and T2DM. Rather, such gaps warrant need for further research and more robust study designs to draw sufficiently significant conclusions to justify reforms in clinical practice.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.082
GPT teacher head0.456
Teacher spread0.374 · 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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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