To investigate the association of serum osteocalcin with cognitive functional status in patients with type 2 diabetes: A systematic review with meta-analysis
Bibliographic record
Abstract
BACKGROUND: To systematically evaluate the correlation between serum osteocalcin levels and cognitive function status in type 2 diabetes mellitus (T2D) patients. METHODS: This review was conducted according to the PRISMA guidelines, and was developed and submitted to PROSPERO (CRD42022339295). We comprehensively searched PubMed, EMBASE, Web of Science, Scopus, ProQuest, and Chinese Databases (China National Knowledge Infrastructure, Wan Fang, Chinese Science and Technology Periodical Database, and China Biology Medicine) up to 1 June 2023. 3 investigators performed independent literature screening and data extraction of the included literature, and 2 investigators performed an independent quality assessment of case-control studies using the Newcastle-Ottawa-Scale tool. Data analysis was performed using Review Manager 5.4 software. For continuous various outcomes, mean difference (MD) or standardized MD with 95% confidence intervals (CIs) was applied for assessment by fixed-effect or random-effect model analysis. The heterogeneity test was performed by the Q statistic and quantified using I2, and publication bias was evaluated using a funnel plot. RESULTS: 9 studies with T2D were included (a total of 1310 subjects). Meta-analysis results indicated that cognitive function was more impaired in patients with lower serum osteocalcin levels [MD = 9.91, 95% CI (8.93, -10.89), I2 = 0%]. Serum osteocalcin levels were also significantly different between the 2 groups of T2D patients based on the degree of cognitive impairment [MD = -0.93, 95% CI (-1.09, -0.78), I2 = 41%]. It summarized the statistical correlation between serum osteocalcin and cognitive function scores in patients with T2D at r = 0.43 [summary Fisher's Z = 0.46, 95% CI (0.39, -0.50), I2 = 41%). After sensitivity analysis, the heterogeneity I2 decreased to 0%, indicating that the results of the meta-analysis are more reliable. CONCLUSION SUBSECTIONS: Based on a meta-analysis of included studies, we concluded that there is a moderately strong positive correlation between serum osteocalcin levels and patients' cognitive function in T2D. An intervention to increase serum osteocalcin levels can contribute to delaying and improving cognitive decline in patients with T2D.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".