Anticoagulation Versus Antiplatelets in Spontaneous Cervical Artery Dissection: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: It is uncertain whether antiplatelets or anticoagulants are more effective in preventing early recurrent stroke in patients with cervical artery dissection. Following the publication of the observational Antithrombotic for STOP-CAD (Stroke Prevention in Cervical Artery Dissection) study, which has more than doubled available data, we performed an updated systematic review and meta-analysis comparing antiplatelets versus anticoagulation in cervical artery dissection. METHODS: The systematic review was registered in PROSPERO (CRD42023468063). We searched 5 databases using a combination of keywords that encompass different antiplatelets and anticoagulants, as well as cervical artery dissection. We included relevant randomized trials and included observational studies of dissection unrelated to major trauma. Where studies were sufficiently similar, we performed meta-analyses for efficacy (ischemic stroke) and safety (major hemorrhage, symptomatic intracranial hemorrhage, and death) outcomes using relative risks. RESULTS: We identified 11 studies (2 randomized trials and 9 observational studies) that met the inclusion criteria. These included 5039 patients (30% [1512] treated with anticoagulation and 70% [3527]) treated with antiplatelets]. In meta-analysis, anticoagulation was associated with a lower ischemic stroke risk (relative risk, 0.63 [95% CI, 0.43 to 0.94]; P =0.02; I 2 =0%) but higher major bleeding risk (relative risk, 2.25 [95% CI, 1.07 to 4.72]; P =0.03, I 2 =0%). The risks of death and symptomatic intracranial hemorrhage were similar between the 2 treatments. Effect sizes were larger in randomized trials. There are insufficient data on the efficacy and safety of dual antiplatelet therapy or direct oral anticoagulants. CONCLUSIONS: In this study of patients with cervical artery dissection, anticoagulation was superior to antiplatelet therapy in reducing ischemic stroke but carried a higher major bleeding risk. This argues for an individualized therapeutic approach incorporating the net clinical benefit of ischemic stroke reduction and bleeding risks. Large randomized clinical trials are required to clarify optimal antithrombotic strategies for management of cervical artery dissection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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, 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".