Amiodarone‐induced thyrotoxicosis in heart failure with a reduced ejection fraction: A retrospective cohort study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".