Antithrombotic regimens in females with symptomatic lower extremity peripheral arterial disease: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Patients with peripheral arterial disease (PAD) are at increased risk for systemic arterial thromboembolic events. Females represent a unique subset of patients with PAD, who differ from males in important ways: they have smaller diameter vessels, undergo lower extremity bypass less frequently and experience higher rates of graft occlusion, amputation and mortality than males. Females also trend towards higher rates of major coronary events and cardiovascular mortality. Current guidelines recommend monoantiplatelet therapy (MAPT) for secondary prevention in patients with symptomatic PAD. However, indications for more intensive antithrombotic therapy in this cohort-especially among females who are frequently under-represented in randomised controlled trials (RCTs)-remain unclear. As newer antithrombotic therapies emerge, some RCTs have demonstrated differential effects in females versus males. A systematic review is needed to quantify the rates of arterial thromboembolic and bleeding events with different antithrombotic regimens in females with symptomatic PAD. METHODS AND ANALYSIS: We will search MEDLINE, Embase and the Cochrane Central Register of Controlled trials for published RCTs that include females with symptomatic PAD and compare full dose anticoagulation±antiplatelet therapy, dual pathway inhibition or dual antiplatelet therapy with MAPT. Title, abstract and full-text screening will be conducted in duplicate by three reviewers. Authors will be contacted to obtain sex-stratified outcomes as needed. Risk of bias will be assessed using the Cochrane Risk of Bias tool. Data will be extracted by independent reviewers and confirmed by a second reviewer. Quantitative synthesis will be conducted using Review Manager (RevMan) V.5 for applicable outcomes data. Planned subgroup analysis by PAD severity, vascular intervention and indication for antithrombotics will be conducted where data permits. ETHICS AND DISSEMINATION: Ethics approval is waived as the study does not involve primary data collection. This review will be submitted for publication in a peer-reviewed journal and for presentation at national and international scientific meetings. TRIAL REGISTRATION NUMBER: This protocol was registered with the PROSPERO International Prospective Register of Systematic Reviews (ID# CRD42020196933).
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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 | 0.041 | 0.069 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.025 | 0.027 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.048 | 0.004 |
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".