Association of serum vitamin D status with development of type 2 diabetes: A retrospective cross-sectional study
Bibliographic record
Abstract
Summary: 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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".