Reversal treatment and clinical outcomes in acute intracranial haemorrhage associated with oral anticoagulant use: protocol of a planned systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Reversal treatment is commonly used for managing oral anticoagulant (OAC)-associated intracranial haemorrhages. Its effects on mortality are still understudied, particularly in various subtypes of intracranial haemorrhages. This systematic review and meta-analysis aims to synthesise the available data to study the impact of reversal therapies on mortality following various OAC-associated acute intracranial haemorrhages. METHODS AND ANALYSIS: This protocol follows the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Protocols, and the final review will be reported in accordance with the PRISMA reporting guidelines. This systematic review and meta-analysis will include studies that assess contemporary reversal treatment in comparison to no reversal treatment, in cases of OAC-associated intracranial haemorrhage. Stratification will be performed for the types of bleeding as well as OAC at bleeding onset. Preliminary searches to determine search term inclusions were conducted in May-August 2024 in the electronic databases Embase, PubMed, Scopus and Web of Science without language and publication date restrictions. Randomised controlled studies, non-randomised controlled trials, and observational studies will be considered for the final meta-analysis. Three reviewers (MT, JOS and AB) will screen titles and abstracts, and one reviewer (MT) will subsequently conduct full-text screening.Risks of bias will be assessed by MT using tools such as Risk of Bias 2, Risk Of Bias In Non-randomised Studies - of Interventions and the Newcastle-Ottawa Scale. Heterogeneity among the study results will be assessed using the I² statistic. If appropriate, a random-effects meta-analysis model will be performed. Subgroup analyses and meta-regression (if applicable) will be performed to assess sources of heterogeneity among (1) intracranial haemorrhage types, (2) OAC drugs and (3) study types, with randomised controlled trials being the primary focus. ETHICS AND DISSEMINATION: Ethical approval is not needed as this project involves previously published data. We intend to publish the results in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42024556420.
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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 | 0.082 | 0.134 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.006 |
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".