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Record W2997151245 · doi:10.4022/jafib.2183

Left Atrial Appendage Morphology as a Determinant for Stroke Risk Assessment in Atrial Fibrillation Patients: Systematic Review and Meta-Analysis

2019· article· en· W2997151245 on OpenAlexaboutno aff
Anan Abu Rmilah, Fareed Jumah, Suhaib Jaber, Rafat Roubi, M. Daana, Isam Bsisu, Tariq Muamar, Patricia J. Erwin, Alexander C. Egbe, Vaidya Vaibha, Peter A. Noseworthy, Abhishek Deshmukh

Bibliographic record

VenueJournal of Atrial Fibrillation · 2019
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAtrial fibrillationMedicineInternal medicineMeta-analysisCardiologyStroke (engine)Relative riskAtrial AppendageForest plotConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Atrial fibrillation (AF) is a leading source of emboli that precipitate cerebrovascular accident (CVA) which is correlated with left atrial appendage (LAA) morphology. We aimed to elaborate the relationship between CVA and LAA morphology in AF patients. METHODS: Medline and EMBASE databases were thoroughly searched between 2010-2018 for studies that included atrial fibrillation patients and classified them into two groups based on CVA occurrence. Four different LAA morphologies (Chicken wing CW, Cauliflower, cactus and windsock) were determined in each group by 3D TEE, MDCT or CMRI. New Castle Ottawa Scale was used to appraise the quality of included studies. The risk of CVA before cardiac ablation and/or LAA intervention in CW patients was compared to each type of non-CW morphologies. The extracted data was statistically analyzed in the form of forest plot by measuring the risk ratio (RR) using REVMAN software. P value and I square were used to assess the heterogeneity between studies. RESULTS: PRISMA diagram was illustrated showing 789 imported studies for screening. Three duplicates were removed, and the rest were arbitrated by 2 reviewers yielding 12 included studies with 3486 patients including 1551 with CW, 442 with cauliflower, 732 with cactus 765 with windsock. The risk of CVA in CW patients was reduced by 41% relative to non-CW patients (Total RR=0.59 (0.52-0.68)). Likewise, the risk of CVA in CW patients was less by 46%, 35% and 31% compared to cauliflower (Total RR =0.54(0.46-0.64)), cactus (Total RR =0.65(0.55-0.77)) and windsock (Total RR =0.69(0.58-0.83)) patients respectively. Low levels of heterogeneity were achieved in all comparisons (I square <35% and p value > 0.1). CONCLUSIONS: Patients with non-CW morphologies (cauliflower, cactus and windsock) show a higher incidence of CVA than CW patients. For that reason, LAA appendage morphology could be useful for risk stratification of CVA in AF patients.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.047
GPT teacher head0.362
Teacher spread0.315 · 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.

Study designMeta-analysis
Domainnot available
GenreEmpirical

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

Citations27
Published2019
Admission routes1
Has abstractyes

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