Venous thromboembolism prevention in intracerebral hemorrhage: A systematic review and network meta-analysis
Bibliographic record
Abstract
INTRODUCTION: To summarize and compare the effectiveness of pharmacological thromboprophylaxis to pneumatic compression devices (PCD) for the prevention of venous thromboembolism in patients with acute intracerebral hemorrhage. METHODS: MEDLINE, PUBMED, EMBASE, and CENTRAL were systematically searched to identify randomized and non-randomized studies that compared each intervention directly to each other or against a common control (hydration, anti-platelet agents, stockings) in adults with acute spontaneous intracerebral hemorrhage. Two investigators independently screened the studies, extracted data, and appraised risk of bias. Studies with a high risk of bias were excluded from our final analysis. The primary outcome was the occurrence of venous thromboembolism (proximal deep vein thrombosis or pulmonary embolism) in the first 30 days. RESULTS: 8,739 articles were screened; four articles, all randomized control trials, met eligibility criteria. Bayesian network meta-analysis was performed to calculate risk estimates using both fixed and random effects analyses. 607 patients were included in the network analysis. PCD were associated with a significant decrease in venous thromboembolism compared to control (OR: 0.43, 95% Credible Limits [CrI]: 0.23-0.80). We did not find evidence of statistically significant differences between pharmacological thromboprophylaxis and control (OR: 0.93, 95% CrI: 0.19-4.37) or between PCD and pharmacological thromboprophylaxis (OR: 0.47, 95% CrI: 0.09-2.54). CONCLUSION: PCDs are superior to control interventions, but meaningful comparisons with pharmacotherapy are not possible due to a lack of data. This requires further exploration via large pragmatic clinical trials. TRIAL REGISTRATION: PROSPERO: CRD42018090960.
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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 | 0.022 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.010 | 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".