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Use of oral anticoagulation for people with atrial fibrillation post-stroke and associations with recurrent stroke and mortality: a systematic review

2021· review· en· W3205207511 on OpenAlexaboutno aff
Mahum Shahid, Heshwin Singh, Deirdre A. Lane, Sunil Jit R. J. Logantha, Gregory Y.H. Lip, Stephanie L. Harrison

Bibliographic record

VenueEuropean Heart Journal · 2021
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Atrial fibrillationObservational studyHazard ratioCohort studyPopulationMEDLINEData extractionInternal medicineEmergency medicinePediatricsConfidence interval

Abstract

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Abstract Introduction Current guidelines recommend oral anticoagulation (OAC) to reduce recurrent stroke risk for people with atrial fibrillation (AF); however, outcomes for post-stroke AF patients receiving different types of anticoagulants and optimal timing of anticoagulation in this population remains unclear. Purpose The objective of this systematic review was to summarise observational study data reporting associations between OAC use and risk of mortality, recurrent stroke, and major bleeding within post-stroke AF populations. Methods SCOPUS and OVID Medline databases were searched from inception to 02/11/2020. Studies were limited to publications in the English language post-2012. Observational studies, including case-control and cohort studies were eligible for inclusion. The outcomes examined were all-cause mortality, recurrent stroke and major bleeding. Screening and risk of bias assessment with the Newcastle-Ottawa scale were completed independently by two reviewers. Data extraction was completed by one reviewer and checked by a second. The review was registered on PROSPERO: CRD42020221105. Results Searches identified 3803 studies; 29 studies were eligible for inclusion. Variations between studies including time of OAC initiation, types of OACs used, and length of follow-up meant a meta-analysis was not possible. Four of six studies reporting effect measures of pre-admission or post-stroke OAC use found significant associations with reduced all-cause post-stroke mortality compared to no OAC use (Figure 1A). One study reported lower recurrent stroke rates in patients with no preadmission OAC use compared to preadmission OAC use (2.9% vs. 5.3%; adjusted hazard ratio (aHR) 1.50, 95% confidence interval [CI] 1.02–2.21). A separate study found post-stroke OAC use resulted in a non-significant lower stroke recurrence rate compared to no post-stroke OAC use (3.7% vs. 4.3%; p=0.9). Eight studies examined non-vitamin K antagonist OACs (NOACs) compared to warfarin; five demonstrated significant associations between post-stroke NOAC use and improved outcomes such as post-stroke mortality (Figure 1B). Two studies examined post-stroke OAC therapy timing; both suggested OAC initiation within 4 days of the index event was associated with reduced all-cause mortality (4.5% and 0.6% vs. 8.7% and 3.1%) and recurrent stroke rates (9.4% and 0.8% vs. 10.5% and 1.6%). One study reported non-significant increased major bleeding rates for earlier OAC initiation (2.7% vs. 2.2%; aHR 1.39, 95% CI 0.42–4.60). Overall, the results were consistent with previously published randomised controlled trials. Conclusions Evidence from observational studies suggest that the overall benefit of NOACs in reducing recurrent stroke and post-stroke mortality outweighs the risk of major bleeding in post-stroke AF patients. There is a need for further studies to evaluate the optimum timing of post-stroke anticoagulation initiation and management differences in patients with AF. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): The project is supported by the MRes programme in the Institute of Life Course and Medical Sciences at The University of Liverpool. All-Cause Mortality Forest Plots

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.008
Bibliometrics0.0070.008
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.185
GPT teacher head0.398
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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