MétaCan
Menu
Back to cohort
Record W2802067054 · doi:10.1002/hsr2.36

Amiodarone‐induced thyrotoxicosis in heart failure with a reduced ejection fraction: A retrospective cohort study

2018· article· en· W2802067054 on OpenAlexaffabout
Jennifer M. Yamamoto, Pamela Katz, James Bras, Leigh Anne Shafer, Alexander A. C. Leung, Amir Ravandi, Francisco Córdova

Bibliographic record

VenueHealth Science Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsUniversity of ManitobaUniversity of Calgary
Fundersnot available
KeywordsEjection fractionHeart failureMedicineAmiodaroneInternal medicineCardiologyRetrospective cohort studyCohortAtrial fibrillation

Abstract

fetched live from OpenAlex

BACKGROUND: Amiodarone-induced thyrotoxicosis (AIT) is associated with significant morbidity and mortality. We aimed to describe AIT and its clinical outcomes in patients with heart failure with reduced ejection fraction (HFrEF). METHODS: We performed a retrospective chart review at a heart failure center in Winnipeg, Canada. We screened 1059 consecutive patients seen over a 12-month period (August 2011 to July 2012) for AIT in patients with HFrEF. Using descriptive and Cox proportional hazard analyses, we explored the association between AIT and mortality. RESULTS: A total of 110 patients with HFrEF who were exposed to amiodarone were included in the analysis. Of these, 13 (11.8%) were diagnosed with AIT. All AIT patients in our cohort were male. Amiodarone was discontinued in nearly half (46.2%) of patients with AIT. All patients were treated with antithyroid medications, and 5 patients (38.5%) also received prednisone. Euthyroidism was achieved in 2 patients (15.4%), hypothyroidism occurred in 6 patients (46.2%), and 5 patients remained thyrotoxic until death or time of chart review (38.5%). CONCLUSION: Thyrotoxicosis is common in patients with HFrEF on amiodarone and is challenging to treat. Due to the sample size, while no association was found in mortality for patients with HFrEF with AIT, a real association could have been missed.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.019
GPT teacher head0.340
Teacher spread0.320 · 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 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

Citations8
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueHealth Science ReportsSame topicThyroid Disorders and TreatmentsFrench-language works237,207