Thyroid Dysfunction under Amiodarone in Patients with and without Congenital Heart Disease: Results of a Nationwide Analysis

The possible effects of chronic administration of amiodarone hydrochloride on the seminiferous tubules of adult male albino rats: histological and biochemical study

Amiodarone hydrochloride is an antiarrhythmic agent that is widely prescribed. However, it has serious side effects that approximately affect the whole body organs. In our study, we aimed to assess the possible effects of chronic administration of two different doses of amiodarone hydrochloride on the oxidative and inflammatory parameters as well as the histological morphology and ultrastructure of the seminiferous tubules of adult male albino rats. Forty rats were divided into four groups; Control group 1: each rat did not receive any drugs at all. Control group 2: each rat received 3 ml of 0.16% methylcellulose, orally and daily for 4 weeks. Low dose amiodarone group: each rat received 3 ml of 0.16% methylcellulose contained 3.6 mg amiodarone, orally and daily for 4 weeks. High dose amiodarone group: each rat received 3 ml of 0.16% methylcellulose contained 7.2 mg amiodarone, orally and daily for 4 weeks. Blood samples were collected for measuring serum levels of malondialdehyde, superoxide dismutase, interleukin-6 and tumor necrosis factor-alpha. Testes specimens were examined to assess the morphological changes and the level of expression of caspase-3 apoptotic marker. The results indicated that; amiodarone hydrochloride could induce a dose-dependent toxicity, causing oxidative stress, inflammation, cellular degeneration, deposition of collagen and enhanced apoptosis in the seminiferous tubules.

Enhanced Differentiation of Amiodarone-Induced Thyrotoxicosis Types Using Semi-Quantitative 99mTc-MIBI Uptake Analysis: A Pilot Study

BACKGROUND Technetium (99mTc)-labelled Methoxy-2-Isobutylisonitrile (MIBI) is a diagnostic lipophilic cationic radiotracer used to evaluate the cardiac, breast, thyroid, and parathyroid pathology. This study aimed to evaluate the role of MIBI combined with Tc-99m pertechnetate thyroid scintigraphy, thyroid ultrasonography, and measurement of thyrotropin, thyroid hormones, and autoantibodies to subtype amiodarone-induced thyrotoxicosis (AIT) and the contribution of semi-quantitative analysis of MIBI uptake. MATERIAL AND METHODS This cross-sectional study included 36 patients with AIT who underwent thyrotropin, thyroid hormone, and autoantibody analysis using chemiluminescent method, ultrasonography, pertechnetate, and MIBI thyroid scintigraphy with semi-quantitative uptake, including calculation of the target-to-background ratio (TBR) with 2 different background regions. The MIBI washout rate (WR) was analyzed in all groups. Statistical analysis was performed using descriptive statistics, correlations, and the receiver operating characteristic curve - area under the curve (ROC-AUC). The results were compared with the control group. RESULTS Based on visual and semi-quantitative analyses, patients were successfully categorized into AIT groups (AIT-1, AIT-2 and AIT-3) but the latter method enabled better differentiation of MIBI uptake between all groups. Additionally, ROC-AUC analysis determined cutoff values which enabled discerning between AIT-1 and AIT-2 groups, and AIT-1 and AIT-3 groups. WR showed no significant difference between all AIT groups and controls (P>0.05). CONCLUSIONS Visual MIBI analysis enabled differentiation between AIT-1 and 2 groups, but the method was substantially improved with semi-quantitative analysis, especially in defining AIT-3 group. However, multicenter collaboration with larger studies is needed to standardize the method and obtain more accurate and consistent results.

Amiodarone-induced thyrotoxicosis: Should surgery be considered?

Amiodarone is the most widely prescribed antiarrhythmic drug worldwide, but induces thyrotoxicosis or hypothyroidism in 15 to 20% of patients. Hyperthyroidism is less frequent than hypothyroidism, and two types of thyrotoxicosis are distinguished according to presence of underlying thyroid disease. Diagnosis is made in case of low TSH and high levels of T3 and T4. Initial treatment is based on anti-thyroid drugs and/or glucocorticoids. Some patients do not respond to medication, which increases the time spent with hyperthyroidism. A long interval between diagnosis and euthyroidism and low left ventricular ejection fraction (LVEF) are predictive of major adverse cardiovascular events. Here, after describing the current state of knowledge of amiodarone-induced thyrotoxicosis, we analyze the literature on the impact of surgery. We suggest that early surgery should be the first option in case of ineffective medical treatment or LVEF<40%. In expert centers, surgical morbidity is no longer different than in other indications for thyroidectomy.

[Type 2 amiodarone-induced thyrotoxicosis: prevalence, time and predictors of development]

BACKGROUND

Amiodarone takes a leading position in arrhythmological practice in the prevention and relief of various cardiac arrhythmias. Type 2 amiodarone-induced thyrotoxicosis is a frequent side effect of the drug. It is the most complex type of thyroid dysfunction both in terms of the severity of clinical manifestations, and in terms of understanding the mechanisms of pathogenesis, possibility of differential diagnosis and providing effective treatment. Due to the increasing life expectancy of the population, corresponding increase in the frequency of cardiac arrhythmias, the problem does not lose its relevance. Identification of predictors, assessment and prediction of the individual risk of developing this thyroid pathology is a necessity in daily clinical practice for making a reasonable decision when prescribing the drug, determining the algorithm for further dynamic monitoring of the patient.

AIM

To evaluate the structure of amiodarone-induced thyroid dysfunction, prevalence, time and predictors of development type 2 amiodarone-induced thyrotoxicosis in a prospective cohort study. MATERIALS AND METHODS: The study involved 124 patients without thyroid dysfunction who received amiodarone therapy for the first time. Evaluation of the functional state of the thyroid gland was performed initially, after prescribing the drug for the first 3 months 1 time per month, in the future - every 3 months. The follow-up period averaged 12-24 months. The end of the observation occurred with the development of amiodaron-induced thyroid dysfunction or patient's refusal to further participate in the study. For the differential diagnosis of the type of amiodarone-induced thyrotoxicosis, the level of anti-TSH receptor antibodies and thyroid scintigraphy with technetium pertechnetate were determined. The type and frequency of thyroid dysfunction, time and predictors of development type 2 amiodarone-induced thyrotoxicosis were evaluated.

RESULTS

The structure of amiodarone-induced thyroid dysfunction was represented by hypothyroidism in 19,3% (n=24), type 1 thyrotoxicosis in 1,6% (n=2), type 2 thyrotoxicosis in 23,4% (n=29). The median time of its development was 92,0 [69,0;116,0] weeks; the average period of common survival - 150,2±12,6 weeks (95% CI: 125,5-175,0), median - 144±21,7 weeks (95% CI: 101,4-186,6). The main predictors of type 2 amiodarone-induced thyrotoxicosis were: age (OR=0,931; 95% CI: 0,895-0,968; p<0.001), BMI (OR=0,859; 95% CI: 0,762-0,967; p=0,012), time from the start of amiodarone therapy (OR=1,023; 95% CI: 1,008-1,038; p=0,003). Age ≤60 years was associated with increased risk of the dysfunction by 2.4 times (OR=2,352; 95% CI: 1,053-5,253; p=0,037), BMI≤26,6 kg/m2 - 2,3 times (OR=2,301; 95% CI: 1,025-5,165; p=0,043). CONCLUSION: The results allow to personalized estimate the risk of type 2 amiodarone-induced thyrotoxicosis and determine the patient's management tactic.

Amiodarone-Induced Myxedema Coma in Elderly Patients: A Systematic Review of Case Reports

This systematic review aimed to explore whether elderly patients administered amiodarone were susceptible to developing myxedema coma. Utilizing the Cochrane guidelines, a comprehensive review of databases such as Medline (PubMed), Science Direct, CINAHL Cochrane, and Google Scholar was undertaken to examine case reports on amiodarone-induced myxedema coma. Following stringent criteria for inclusion, 12 pertinent case reports were identified. These findings suggested a high probability of myxedema coma development in patients who had been administered amiodarone. Specifically, patients who received an oral dosage of 100-200 mg of amiodarone were reported to have developed bradycardia and hypothermia alongside elevated thyroid-stimulating hormone (TSH) levels. Upon diagnosis, the majority of patients were treated with a regimen of levothyroxine and hydrocortisone medication. Despite the myriad potential causes of myxedema coma complicating the diagnosis, it was found that through a combination of clinical symptoms and serum TSH measurements, a confirmed diagnosis could be reached. Furthermore, it was observed that amiodarone-induced myxedema coma responded favorably to treatment with levothyroxine and glucocorticoids.

Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation

BACKGROUND

Machine learning offers new solutions for predicting life-threatening, unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches for adverse-effect prediction without time-series consideration of features have yielded suboptimal predictions. Machine learning algorithms with multiple data sets at different time points may generate better performance in predicting adverse effects.

OBJECTIVE

We aimed to develop and validate machine learning models for forecasting individualized amiodarone-induced thyroid dysfunction risk and to optimize a machine learning-based risk stratification scheme with a resampling method and readjustment of the clinically derived decision thresholds.

METHODS

This study developed machine learning models using multicenter, delinked electronic health records. It included patients receiving amiodarone from January 2013 to December 2017. The training set was composed of data from Taipei Medical University Hospital and Wan Fang Hospital, while data from Taipei Medical University Shuang Ho Hospital were used as the external test set. The study collected stationary features at baseline and dynamic features at the first, second, third, sixth, ninth, 12th, 15th, 18th, and 21st months after amiodarone initiation. We used 16 machine learning models, including extreme gradient boosting, adaptive boosting, k-nearest neighbor, and logistic regression models, along with an original resampling method and 3 other resampling methods, including oversampling with the borderline-synthesized minority oversampling technique, undersampling-edited nearest neighbor, and over- and undersampling hybrid methods. The model performance was compared based on accuracy; Precision, recall, F₁-score, geometric mean, area under the curve of the receiver operating characteristic curve (AUROC), and the area under the precision-recall curve (AUPRC). Feature importance was determined by the best model. The decision threshold was readjusted to identify the best cutoff value and a Kaplan-Meier survival analysis was performed.

RESULTS

The training set contained 4075 patients from Taipei Medical University Hospital and Wan Fang Hospital, of whom 583 (14.3%) developed amiodarone-induced thyroid dysfunction, while the external test set included 2422 patients from Taipei Medical University Shuang Ho Hospital, of whom 275 (11.4%) developed amiodarone-induced thyroid dysfunction. The extreme gradient boosting oversampling machine learning model demonstrated the best predictive outcomes among all 16 models. The accuracy; Precision, recall, F₁-score, G-mean, AUPRC, and AUROC were 0.923, 0.632, 0.756, 0.688, 0.845, 0.751, and 0.934, respectively. After readjusting the cutoff, the best value was 0.627, and the F₁-score reached 0.699. The best threshold was able to classify 286 of 2422 patients (11.8%) as high-risk subjects, among which 275 were true-positive patients in the testing set. A shorter treatment duration; higher levels of thyroid-stimulating hormone and high-density lipoprotein cholesterol; and lower levels of free thyroxin, alkaline phosphatase, and low-density lipoprotein were the most important features.

CONCLUSIONS

Machine learning models combined with resampling methods can predict amiodarone-induced thyroid dysfunction and serve as a support tool for individualized risk prediction and clinical decision support.