DOACs vs LMWHs in hospitalized medical patients: a systematic review and meta-analysis that informed 2018 ASH guidelines
Bibliographic record
Abstract
Venous thromboembolism (VTE) is a relatively frequent complication in hospitalized patients, especially in those with risk factors. The benefit of using direct oral anticoagulants (DOACs) for prevention is controversial. This systematic review was performed as part of the American Society of Hematology (ASH) guidelines on VTE, developed in partnership with McMaster University. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Epistemonikos were used as data sources from date of inception to November 2019. We included randomized trials in patients hospitalized for an acute medical disease, evaluating any DOACs vs other pharmacological prophylaxis, and included 3 trials with low risk of bias. We analyzed the effects of DOACs vs low-molecular-weight heparins (LMWHs) at 2 different time points: at the end of the short-term treatment phase (both drugs given for the same period of time) and at the end of the extended prophylaxis period (extended DOACs vs a shorter course of LMWHs). We observed that the use of DOACs did not reduce the risk of pulmonary embolism or symptomatic deep venous thrombosis (DVT) in comparison with LMWHs. However, the risk of major bleeding was slightly increased. Additionally, we observed that the benefit of DOACs previously reported was largely based on the reduction of asymptomatic DVT and was not apparent when only symptomatic events were considered. The use of DOACs in hospitalized medical patients slightly increases the risk of major bleeding with no appreciable benefit over LMWHs.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".