Therapeutic vs. prophylactic anticoagulation in COVID-19 patients: a systematic review and meta-analysis of real-world studies
Bibliographic record
Abstract
INTRODUCTION: Coagulopathy, in the form of either venous or arterial thromboembolism, is one of the most severe sequelae of coronavirus disease (COVID-19) and has been associated with poorer outcomes. However, the role of therapeutic anticoagulation (tAC) or prophylactic anticoagulation (pAC) in COVID-19 patients has not been definitely established. Therefore, the aim of this systematic review and meta-analysis was to gather all the available real-world data in the field and to provide a reliable effect size of the effect on mortality of tAC compared to pAC in COVID-19 patients. EVIDENCE ACQUISITION: October, 2021. Randomized controlled trials were excluded. Mortality and bleedings were considered as primary and secondary outcomes, respectively. EVIDENCE SYNTHESIS: 10 RWS and 5541 patients were included in the analysis. Overall, tAC was associated with lower mortality (HR=0.62, 95% CI: 0.54-0.71). There was asymmetry at the funnel plot suggesting publication bias, that was not confirmed at the Egger test (P=0.07). For the secondary endpoint, there was a non-statistically significant tendency for more bleedings in patients treated with tAC compared to pAC (RR=1.75, 95% CI: 0.81-3.81). CONCLUSIONS: Our meta-analysis, based on RWS and adjusted estimates of risk, suggests a survival benefit of tAC over pAC in COVID-19 patients in the real world.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".