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Record W2157089183 · doi:10.1002/clc.20969

Can We Predict Stroke in Atrial Fibrillation?

2012· review· en· W2157089183 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueClinical Cardiology · 2012
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtrial fibrillationStroke (engine)WarfarinAntithromboticStroke riskCohortInternal medicineRisk assessmentRisk factorIntensive care medicineCardiologyIschemic stroke

Abstract

fetched live from OpenAlex

Stroke prevention with appropriate thromboprophylaxis still remains central to the management of atrial fibrillation (AF). Nonetheless, stroke risk in AF is not homogeneous, but despite stroke risk in AF being a continuum, prior stroke risk stratification schema have been used to 'artificially' categorise patients into low, moderate and high risk stroke strata, so that the patients at highest risk can be identified for warfarin therapy. Data from recent large cohort studies show that by being more inclusive, rather than exclusive, of common stroke risk factors in the assessment of the risk for stroke and thromboembolism in AF patients, we can be so much better in assessing stroke risk, and in optimising thromboprophylaxis with the resultant reduction in stroke and mortality. Thus, there has been a recent paradigm shift towards getting better at identifying the 'truly low risk' patients with AF who do not even need antithrombotic therapy, whilst those with one or more stroke risk factors can be treated with oral anticoagulation, whether as well-controlled warfarin or one or the new oral anticoagulant drugs. The new European guidelines on AF have evolved to deemphasise the artificial low/moderate/high risk strata (as they were not very predictive of thromboembolism, anyway) and stressed a risk factor based approach (within the CHA(2) DS(2)-VASc score) given that stroke risk is a continuum. Those categorised as 'low risk' using the CHA(2) DS(2)-VASc score are 'truly low risk' for thromboembolism, and the CHA(2) DS(2)-VASc score performs as good as-and possibly better--than the CHADS(2) score in predicting those at 'high risk'. Indeed, those patients with a CHA(2) DS(2)-VASc score = 0 are 'truly low risk' so that no antithrombotic therapy is preferred, whilst in those with a CHA(2) DS(2)-VASc score of 1 or more, oral anticoagulation is recommended or preferred. Given that guidelines should be applicable for >80% of the time, for >80% of the patients, this stroke risk assessment approach covers the majority of the patients we commonly seen in everyday clinical practice, and considers the common stroke risk factors seen in these patients. The European guidelines also do stress that antithrombotic therapy is necessary in all patients with AF unless they are age <65 years and truly low risk. Indeed, some patients with 'female gender' only as a single risk factor (but still CHA(2) DS(2)-VASc score of 1, due to gender) do not need anticoagulation, especially if they fulfil the criterion of "age <65 and lone AF, and very low risk". In the European and Canadian guidelines, bleeding risk assessment is also emphasised, and the simple validated HAS-BLED score is recommended. A HAS-BLED score of ≥ 3 represents a sufficiently high risk such that caution and/or regular review of a patient is needed. It also makes the clinician think of correctable common bleeding risk factors, and the availability of such a score allows an informed assessment of bleeding risk in AF patients, when antithrombotic therapy is being initiated.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.295
GPT teacher head0.483
Teacher spread0.188 · 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