Objective: Previous studies suggest that hyperthyroid patients remain at increased risk of cardiovascular morbidity after restoring euthyroidism. The aim of this study was to compare the rate and causes of hospitalization of hyperthyroid patients treated with radioactive iodine (RAI) with those of an age- and gender-matched reference population in a long-term follow-up study.
Patients And Measurements: A population-based cohort study with a median follow-up time of 9 years was conducted among 2611 hyperthyroid patients treated with RAI between 1969 and 2002 in Tampere University Hospital, and among 2611 reference subjects. Information on hospitalizations was obtained from the nationwide Hospital Discharge Registry. New events were analysed as the main outcome, including only the first hospitalization due to a given indication.
Results: The rate of hospitalization due to cardiovascular disease (CVD) was higher among patients with hyperthyroidism than among the control population [637.1 vs. 476.4 per 10 000 person-years, rate ratio (RR) 1.12, 95% confidence interval (CI) 1.03-1.21]. The risk remained elevated up to 35 years after the RAI treatment. Hospitalizations due to atrial fibrillation (RR 1.35), cerebrovascular disease (RR 1.31), diseases of other arteries and veins (RR 1.22), hypertension (RR 1.20) and heart failure (RR 1.48) were more frequent in the patients than controls, while no such difference was found for coronary artery disease. Hospitalizations due to cancer, infectious and gastrointestinal diseases, and fractures were also more common in patients than in controls.
Conclusions: Hyperthyroidism increases hospitalizations due to CVDs. The excess risk is sustained decades after treatment. Patients treated for hyperthyroidism constitute a high-risk group for CVD and may benefit from preventive interventions.
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http://dx.doi.org/10.1111/j.1365-2265.2007.03064.x | DOI Listing |
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Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
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