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Record W4408300669 · doi:10.1016/j.cjco.2025.03.002

Diagnosis and Management of Mixed Phenotype Hereditary Transthyretin Amyloidosis: A Case-Based, Canadian Perspective

2025· review· en· W4408300669 on OpenAlexafffundabout
Nowell M. Fine, Anique Ducharme, Geneviève Matte, Michelle M. Mezei, Vera Bril, Diego Delgado

Bibliographic record

VenueCJC Open · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health NetworkUniversity of British ColumbiaUniversity of CalgaryCentre Hospitalier de l’Université de MontréalMontreal Heart InstituteLibin Cardiovascular Institute of AlbertaUniversité de Montréal
FundersAstraZeneca Canada
KeywordsTransthyretinAmyloidosisPerspective (graphical)PhenotypeMedicineGeneticsPathologyBiologyComputer scienceArtificial intelligenceGene

Abstract

fetched live from OpenAlex

Hereditary amyloid transthyretin variant (ATTRv) amyloidosis is a rare, life-threatening disease, characterized by the deposition of aggregated transthyretin (TTR) protein in multiple organs and tissues. Diagnosis is often delayed due to its heterogeneity in presentation, which includes a wide range of cardiac and/or neurologic symptoms. Thus, awareness of ATTRv amyloidosis across multiple specialties is needed for its early diagnosis and management. This paper provides a review surrounding the diagnosis and management of mixed phenotype ATTRv amyloidosis, addressed through 3 clinical questions. This paper discusses: (i) the need for patients with ATTRv amyloidosis to be screened for mixed cardiac and neurologic phenotypes through early multidisciplinary referral; (ii) the therapeutic landscape for ATTRv amyloidosis in Canada, with emphasis on the need for prompt therapy selection and initiation, based on multidisciplinary collaboration; and (iii) how disease can be monitored pre- and post-treatment. Case studies are provided to illustrate how the available evidence impacts practice.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.326
Teacher spread0.300 · 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 designNot applicable
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

Citations1
Published2025
Admission routes3
Has abstractyes

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