Is diabetes mellitus a risk factor for low bone density: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: This systematic review aimed to investigate whether diabetes mellitus is a risk factor for low bone density, as this might be important and necessary for doctors specialized in treating patients with low bone density. METHODS: PubMed, Embase, CINAHL, and SciELO were searched for cohort, case-control, and cross-sectional studies that investigated the effects of diabetes mellitus on bone mineral density till January 2020. Data screening and extraction are done independently, whereas the methodological quality of the studies was assessed according to the Newcastle-Ottawa Scale (NOS). RESULTS: A total of 14 studies that met the eligibility criteria including 24,340 participants were enrolled. The overall quality of the studies had a scale of over 6 points. The overall odds ratio (OR) regarding the risk of diabetes mellitus in low bone density patients was 1.20 [95% confidence interval (CI)0.80-1.79, P = 0.30], and type 2 diabetes mellitus (T2DM) (OR = 0.69 [0.11, 4.55], P = 0.70). Subgroup analysis revealed that whether females or males, developed or developing countries, T2DM, studies after 2015, and quality over 7 points (all P values > 0.05) showed no significant differences with the risk of low bone density, except type 1 diabetes mellitus (T1DM) (OR = 3.83 [1.64, 8.96], P = 0.002), and studies before 2015 (OR = 1.76 [1.06, 2.92], P = 0.03), and quality below 7 points (OR = 2.27 [1.50, 3.43], P = 0.0001). Funnel plot showed no significant asymmetry. CONCLUSIONS: These findings revealed no relationship between T2DM and low bone density, and also, the evidence between T1DM and low bone density is inadequate, requiring further analysis of well-designed cohort studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.027 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".