Prevalence of atrial fibrillation in patients taking TSH suppression therapy for management of thyroid cancer
Bibliographic record
Abstract
BACKGROUND: Suppression of thyroid stimulating hormone (TSH) below the normal range with administration of L-thyroxine has been shown to improve survival in patients treated for thyroid cancer (TC). Although most TC patients require long-term TSH suppression therapy, the effect of this treatment on cardiac rhythm remains unknown. A cross-sectional study was conducted to determine the prevalence of atrial fibrillation (AF) in TC patients on TSH suppressive therapy. METHODS: All TC patients seen between June 2009 and March 2010 through a multidisciplinary thyroid oncology clinic, Halifax, Nova Scotia, Canada, for whom TSH suppressive therapy had previously been recommended, were recruited into the study. Each patient underwent an electrocardiogram and filled out a questionnaire relevant to causes, signs/symptoms of AF and/or its complications. The prevalence of AF in this population then was compared against the published prevalence of AF in general populations. RESULTS: A total of 351 patients were seen in the thyroid clinic of which 136 patients met the inclusion criteria for the study. The mean age was 52 years, 85% were female, and mean follow-up duration prior to recruitment was 11 years. The mean TSH was 0.17 mIU/L (Normal: 0.35 - 5.5 mIU/L). There were 14 patients found to have AF (two patients had long-standing persistent AF and 12 patients had paroxysmal AF). The mean ages of patients with and without AF were 61.6 years and 51.4 years, respectively (P = 0.01). Prevalence of AF in the study group was 10.3%; the rate of AF in the TC patients aged 60 years and over (17.5%) was higher than the rate of AF in published data in people 60 years and over (P < 0.001). AF was diagnosed after the initiation of the TSH suppression therapy in all except one patient. CONCLUSION: TSH suppression in thyroid cancer is associated with a high prevalence of AF, particularly in older individuals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".