Efficacy and Safety of Intensified Versus Standard Prophylactic Anticoagulation Therapy in Patients With Coronavirus Disease 2019: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background Randomized controlled trials (RCTs) have reported inconsistent effects from intensified anticoagulation on clinical outcomes in coronavirus disease 2019 (COVID-19). We performed an aggregate data meta-analysis from available trials to quantify effect on nonfatal and fatal outcomes and identify subgroups who may benefit. Methods We searched multiple databases for RCTs comparing intensified (intermediate or therapeutic dose) vs prophylactic anticoagulation in adults with laboratory-confirmed COVID-19 through 19 January 2022. We used random-effects meta-analysis to estimate pooled risk ratios for mortality, thrombotic, and bleeding events (at end of follow-up or discharge) and performed subgroup analysis for clinical setting and dose of intensified anticoagulation. Results Eleven RCTs were included (N = 5873). Intensified vs prophylactic anticoagulation was not associated with a mortality reduction up to 45 days (risk ratio [RR], 0.93 [95% confidence interval {CI}, .79–1.10]). There was a possible signal of mortality reduction for non–intensive care unit (ICU) patients, although with low precision and high heterogeneity (5 studies; RR, 0.84 [95% CI, .49–1.44]; I2 = 75%). Risk of venous thromboembolism was reduced (RR, 0.53 [95% CI, .41–.69]; I2 = 0%), with effect driven by therapeutic rather than intermediate dosing (interaction P = .04). Major bleeding was increased with intensified anticoagulation (RR, 1.73 [95% CI, 1.17–2.56]) with no interaction for dosing and clinical setting. Conclusions Intensified anticoagulation has no effect on mortality among hospitalized adults with COVID-19 and is associated with increased bleeding risk. The observed reduction in venous thromboembolism risk and trend toward reduced mortality in non-ICU settings requires exploration in additional RCTs. Clinical Trials Registration. CRD42021273449 (PROSPERO).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".