Epicardial adipose tissue in type 1 diabetes mellitus: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot surrounding the myocardium and evidence suggests its potential role in the development of cardiovascular complications in type 1 diabetes mellitus (T1DM). This systematic review and meta-analysis aimed to: (1) quantify EAT measurements (thickness and volume) in patients with T1DM, and (2) compare EAT measurements between T1DM patients and healthy controls. Methods A comprehensive literature review was conducted using a systematic search strategy to identify studies that measured EAT thickness or volume in T1DM patients in PubMed, Embase, Cochrane Library, Web of Science, and CINAHL. Studies were included if they: (1) involved patients with T1DM, (2) reported EAT measurements using imaging techniques, and (3) were published in English. Case reports and reviews were excluded. Two independent reviewers performed study selection, data extraction, and quality assessment. Study quality was evaluated using the Newcastle–Ottawa Scale (NOS). Statistical heterogeneity was assessed using I2 statistics. Meta-analysis was performed using a random effect model. Results A total of nine studies involving 285 and 233 participants measuring thickness and volume with T1DM were included. The pooled mean EAT thickness was 5.81 mm (95%CI: 4.30, 7.32 mm), and the pooled mean EAT volume was 56.84cm3 (95%CI: 34.05, 79.63cm3). Significant heterogeneity was observed between the volume and thickness of EAT among people with T1DM (I2 = 99% for volume and 95% for thickness). Subgroup analysis revealed a mean difference of 2.12 mm (95%CI: 0.82, 3.43 mm) in EAT thickness between T1DM and control groups. Conclusions Our findings indicate increased EAT measurements in T1DM patients compared to healthy individuals, suggesting EAT’s potential involvement in T1DM-related cardiovascular issues.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".