MétaCan
Menu
Back to cohort
Record W4280635861 · doi:10.1093/europace/euac053.283

The management of anticoagulants in patients with atrial fibrillation and history of falls or risk of falls: The Liverpool AF-Falls Project. A systematic review and meta-analysis

2022· review· en· W4280635861 on OpenAlexaboutno aff
Thibaut Galvain, Ruaraidh Hill, Sarah Donegan, P.J.G. Lisboa, G Y H Lip, Gabriela Czanner

Bibliographic record

VenueEP Europace · 2022
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtrial fibrillationStroke (engine)Meta-analysisRivaroxabanWarfarinCochrane LibraryObservational studyVitamin K antagonistRandomized controlled trialMEDLINEInternal medicineEmergency medicineIntensive care medicinePhysical therapy

Abstract

fetched live from OpenAlex

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Johnson and Johnson Medical Background Atrial fibrillation affects an estimated 33 million individuals worldwide and a major cause of stroke, heart failure, and death. Treatment with anticoagulants substantially reduces risk of stroke but is also associated with an increased risk of bleeding and especially intracranial haemorrhages which are the most feared complication. Because of that many patients do not receive anticoagulants; particularly patients at risk of falls or with history of falls. It is unclear what anticoagulant treatment these patients should be offered, and the Liverpool AF-Falls Project aims to investigate this area. Purpose This systematic review and meta-analysis aimed to determine the most appropriate anticoagulant treatment option for the management of atrial fibrillation patients at risk of falls or with a history of falls. Methods We conducted a systematic review and meta-analysis, including studies evaluating safety and efficacy of different anticoagulants (Vitamin K Antagonist-VKA- versus Non-Vitamin K Antagonist Oral Anti-Coagulants-NOAC). Outcomes were ischemic stroke, major bleeding, intracranial haemorrhage, haemorrhagic stroke and mortality. Bibliographic databases (CENTRAL, CINAHL, ClinicalTrials.gov, EMBASE, MEDLINE, Scopus and Web of Science) were searched. Two independent reviewers identified studies, extracted data, and assessed the risk of bias using the Cochrane Risk of Bias 2 tool for randomized clinical trials and with the Newcastle-Ottawa-Scale for observational studies. Pairwise meta-analysis with random and fixed effects models were conducted. Heterogeneity was assessed with the I2 statistics. Hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) were used to assess the effect of drugs on efficacy and safety. Results 823 articles were identified, 643 after removing duplicates. 95 were screened for full text and 3 articles were retained for final quantitative synthesis including 26,514 patients. Risk of bias was moderate in Rao et al. 2018 and Steffel et al. 2017, and low in Miao et al. 2019. In meta-analysis, the hazard for intracranial haemorrhage was lower with NOACs compared to VKA (hazard ratio (HR) 0.33, 95% confidence interval (CI) [0.13–0.82]; p<0,001; I²=52%). There were no difference between NOACs and VKA regarding risks in ischemic stroke (HR 0.88, 95%CI [0.70–1.10; p=0.25; I²=0%), major bleeding (HR 0.88, 95%CI [0.62–1.27]; p=0.51, I²=0%); haemorrhagic stroke (HR 0.36, 95%CI [0.11–1.13]; p=0.08; I²=0%) and all-cause mortality (HR 0.95, 95%CI [0.67–1.33]; p=0.75; I² = 0%). Conclusions NOACs were associated with less intracranial haemorrhages than VKAs. There were no statistically significant differences in other outcomes. However, limited number of studies were identified suggesting research gaps in the AF patients with increased falling risk or history of falls, requiring careful interpretation pending more evidence.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.845
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.127
GPT teacher head0.347
Teacher spread0.220 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEP EuropaceSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207