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Record W4311616659 · doi:10.14740/cr1436

High Prevalence of Cardiac Amyloidosis in Clinically Significant Aortic Stenosis: A Meta-Analysis

2022· article· en· W4311616659 on OpenAlexvenueno aff
Samiullah Arshad, Ythan Goldberg, Huzefa Bhopalwala, Nakeya Dewaswala, Nicholas S. Miceli, Emma J. Birks, Gaurang Vaidya

Bibliographic record

VenueCardiology Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCardiologyCardiac amyloidosisStenosisInterventricular septumLeft bundle branch blockTransthyretinAmyloidosisConcomitantHeart failureVentricle

Abstract

fetched live from OpenAlex

Background: There is growing evidence of coexistence of aortic stenosis (AS) and transthyretin cardiac amyloidosis (CA). Not screening AS patients at the time of hospital/clinic visit for CA represents a lost opportunity. Methods: We surveyed studies that reported the prevalence of CA among AS patients. Studies that compared patients with aortic stenosis with cardiac amyloidosis (AS-CA) and AS alone were further analyzed, and meta-regression was performed. Results: We identified nine studies with 1,321 patients of AS, of which 131 patients had concomitant CA, with a prevalence of 11%. When compared to AS-alone, the patients with AS-CA were older, more likely to be males, had higher prevalence of carpal tunnel syndrome, right bundle branch block. On echocardiogram, patients with AS-CA had thicker interventricular septum, higher left ventricular mass index (LVMI), lower myocardial contraction fraction, and lower stroke volume index. Classical low-flow low-gradient (LFLG) physiology was more common among patients with AS-CA. Patients with AS-CA had higher all-cause mortality than patients with AS alone (33% vs. 22%, P = 0.02) in a follow-up period of at least 1 year. Conclusions: CA has a high prevalence in patients with AS and is associated with worse clinical, imaging, and biochemical parameters than patients with AS alone.

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)0.005
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.100
GPT teacher head0.389
Teacher spread0.289 · 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 designObservational
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

Citations12
Published2022
Admission routes1
Has abstractyes

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