Obesity as a Risk Factor for Venous Thromboembolism Recurrence: A Systematic Review
Bibliographic record
Abstract
Background and Objectives: Venous thromboembolism (VTE) encompasses Deep Venous Thrombosis (DVT) and Pulmonary Embolism (PE). The duration of anticoagulant therapy following a VTE event partly relies on the risk of recurrent VTE which depends on the clinical setting where VTE occurred and the VTE risk factors present. Obesity is considered a minor risk factor and studies in the literature have provided conflicting results on whether obesity influences the development of recurrences. The aim of the present study is to assess the effect of obesity on VTE recurrence in patients that suffered from a previous VTE event. Materials and Methods: We conducted systematic research for English language studies in Medline, Scopus and ProQuest databases in order to identify publications that assess the risk of VTE recurrence in obesity. Inclusion criteria were: 1. Diagnosis of VTE, 2. Definition of obesity as a body mass index ≥30 kg/m2, 3. Report of the risk of obesity on VTE recurrence, 4. Adult human population. We did not include case reports, review studies or studies that assessed other forms of thrombosis and/or used other definitions of obesity. We used the Newcastle-Ottawa scale to address the quality of the studies. Results: Twenty studies were included in the analysis, of which 11 where prospective cohort studies, 6 were retrospective cohort studies, 1 was a cross-sectional study, and 2 were post-hoc analysis of randomized clinical trials. Obesity was significantly associated with recurrences in 9 studies and in 3 of them the association was significant only in females. Conclusions: There is heterogeneity between the studies both in their design and results, therefore the effect of obesity on VTE recurrence cannot be adequately estimated. Future randomized clinical studies with appropriately selected population are needed in order to streamline the effect of obesity on VTE recurrence.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".