Association between diabetes and venous thromboembolism: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus (DM) plays a vital role in the development of cardiovascular disease. However, its association with venous thromboembolism (VTE) remains unclear, for the published study results are conflicting. We performed a meta-analysis of published cohort studies and case-control studies to assess the role of DM in the formation and prognosis of VTE. METHODS: PubMed and EMBASE databases were searched for articles from the database's establishment until September 15, 2022. Of the 15,754 publications retrieved, 50 studies were identified that met the selection criteria. The New castle-Ottawa Scale was used to evaluate the quality of the literature. Pooled odds ratios (ORs) and 95% confidence intervals were calculated using fixed- or random-effect models. RESULTS: We combined OR using a random-effects or fixed-effects model: patients with DM had an increased risk of VTE (OR 1.27, 95% confidence interval [CI]: 1.15-1.41), which still showed a partial association in studies adjusted by confounding factors (OR 1.20, 95% CI: 1.07-1.35). DM was not significantly associated with VTE when analyzed in studies adjusted by body mass index (OR 1.04, 95% CI: 0.94-1.15). VTE patients with DM had a higher risk of short-term and long-term mortality than those without DM (OR 1.58 [95% CI: 1.26-1.99] for long-term mortality and OR 1.20 [95% CI: 1.19-1.21] for short-term mortality). CONCLUSION: There was no significant association between DM and VTE risk, and body mass index may be a significant confounding factor between DM and VTE risk. However, DM can still lead to an increased risk of long-term and short-term mortality in patients with VTE.
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 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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".