Abstract 14569: Direct Oral Anticoagulants in the Treatment of Acute Venous Thromboembolism in Obese Patients: A Systematic Review With Meta-analysis
Bibliographic record
Abstract
Background: Obesity is a real burden and its prevalence is constantly increasing. High body weight is a risk factor for developing venous thromboembolism (VTE). Direct oral anticoagulants’ (DOAC) pharmacokinetics and pharmacodynamics are affected by obesity. Their efficacy and safety in obese (BMI ≥30kg/m 2 ) and morbidly obese (BMI ≥40kg/m 2 ) patients are still unclear in the treatment of VTE. Objectives: To compare the efficacy and safety of DOAC with vitamin K antagonist (VKA)/low molecular weight heparin (LMWH) in the acute treatment of VTE in obese and morbidly obese patients. The primary efficacy outcome was VTE recurrences. The safety outcomes were major bleeding (MB) and clinically relevant non-MB (CRNMB). All-cause mortality was also assessed. Hypothesis: We hypothesized that DOAC would present the same efficacy and safety for the treatment of acute VTE in obese and morbidly obese patients compared to VKA/LMWH. Methods: A systematic literature search (MEDLINE, EMBASE, CENTRAL, Web of Science) was conducted from inception to April 15 th 2020, identifying trials studying DOAC in the treatment of acute VTE in obese patients. Studies were included if one of the outcomes was reported. Two independent reviewers performed the study selection, data extraction, risk of bias assessment and strength of body evidence evaluation using the GRADE methodology. Analyses were conducted using the Mantel-Haenszel method based on a random-effect model. Relative risks (RR) were estimated for the effect measure with 95% confidence intervals. Results: From 1240 citations screened, we included 21 studies (58,590 patients). VTE recurrences was similar with DOAC compared to VKA/LMWH in obese patients (risk ratio (RR): 1.03; 95%CI 0.93-1.15; p=0.55) and morbidly obese patients (RR 1.06; 95CI 0.94-1.19; p=0.35). DOAC was associated with a reduction in MB in obese patients (RR 0.57; 95%CI 0.34-0.94; p=0.03) and morbidly obese patients (RR 0.71; 95%CI 0.50-1.00; p=0.05) compared to VKA/LMWH. In obese patients, no difference was observed in CRNMB with DOAC compared to VKA/LMWH. Conclusion: DOAC is as effective in reducing VTE and is associated with less MB compared to VKA/LMWH in obese and morbidly obese patients.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".