COMPARISON OF CARDIAC ARRHYTHMIA TYPES BETWEEN HYPERTHYROID PATIENTS WITH GRAVES' DISEASE AND TOXIC NODULAR GOITER

Mechanisms and Management of Thyroid Disease and Atrial Fibrillation: Impact of Atrial Electrical Remodeling and Cardiac Fibrosis

Atrial fibrillation (AF) is the most common cardiac arrhythmia associated with increased cardiovascular morbidity and mortality. The pathophysiology of AF is characterized by electrical and structural remodeling occurring in the atrial myocardium. As a source of production of various hormones such as angiotensin-2, calcitonin, and atrial natriuretic peptide, the atria are a target for endocrine regulation. Studies have shown that disorders associated with endocrine dysregulation are potential underlying causes of AF. The thyroid gland is an endocrine organ that secretes three hormones: triiodothyronine (T3), thyroxine (T4) and calcitonin. Thyroid dysregulation affects the cardiovascular system. Although there is a well-established relationship between thyroid disease (especially hyperthyroidism) and AF, the underlying biochemical mechanisms leading to atrial fibrosis and atrial arrhythmias are poorly understood in thyrotoxicosis. Various animal models and cellular studies demonstrated that thyroid hormones are involved in promoting AF substrate. This review explores the recent clinical and experimental evidence of the association between thyroid disease and AF. We highlight the current knowledge on the potential mechanisms underlying the pathophysiological impact of thyroid hormones T3 and T4 dysregulation, in the development of the atrial arrhythmogenic substrate. Finally, we review the available therapeutic strategies to treat AF in the context of thyroid disease.

Prediction model for thyrotoxic atrial fibrillation: a retrospective study

BACKGROUND

Thyrotoxic atrial fibrillation (TAF) is a recognized significant complication of hyperthyroidism. Early identification of the individuals predisposed to TAF would improve thyrotoxic patients' management. However, to our knowledge, an instrument that establishes an individual risk of the condition is unavailable. Therefore, the aim of this study is to build a TAF prediction model and rank TAF predictors in order of importance using machine learning techniques.

METHODS

In this retrospective study, we have investigated 36 demographic and clinical features for 420 patients with overt hyperthyroidism, 30% of which had TAF. At first, the association of these features with TAF was evaluated by classical statistical methods. Then, we developed several TAF prediction models with eight different machine learning classifiers and compared them by performance metrics. The models included ten features that were selected based on their clinical effectuality and importance for model output. Finally, we ranked TAF predictors, elicited from the optimal final model, by the machine learning tehniques.

RESULTS

The best performance metrics prediction model was built with the extreme gradient boosting classifier. It had the reasonable accuracy of 84% and AUROC of 0.89 on the test set. The model confirmed such well-known TAF risk factors as age, sex, hyperthyroidism duration, heart rate and some concomitant cardiovascular diseases (arterial hypertension and conjestive heart rate). We also identified premature atrial contraction and premature ventricular contraction as new TAF predictors. The top five TAF predictors, elicited from the model, included (in order of importance) PAC, PVC, hyperthyroidism duration, heart rate during hyperthyroidism and age.

CONCLUSIONS

We developed a machine learning model for TAF prediction. It seems to be the first available analytical tool for TAF risk assessment. In addition, we defined five most important TAF predictors, including premature atrial contraction and premature ventricular contraction as the new ones. These results have contributed to TAF prediction investigation and may serve as a basis for further research focused on TAF prediction improvement and facilitation of thyrotoxic patients' management.

Pro-Arrhythmic Signaling of Thyroid Hormones and Its Relevance in Subclinical Hyperthyroidism

A perennial task is to prevent the occurrence and/or recurrence of most frequent or life-threatening cardiac arrhythmias such as atrial fibrillation (AF) and ventricular fibrillation (VF). VF may be lethal in cases without an implantable cardioverter defibrillator or with failure of this device. Incidences of AF, even the asymptomatic ones, jeopardize the patient's life due to its complication, notably the high risk of embolic stroke. Therefore, there has been a growing interest in subclinical AF screening and searching for novel electrophysiological and molecular markers. Considering the worldwide increase in cases of thyroid dysfunction and diseases, including thyroid carcinoma, we aimed to explore the implication of thyroid hormones in pro-arrhythmic signaling in the pathophysiological setting. The present review provides updated information about the impact of altered thyroid status on both the occurrence and recurrence of cardiac arrhythmias, predominantly AF. Moreover, it emphasizes the importance of both thyroid status monitoring and AF screening in the general population, as well as in patients with thyroid dysfunction and malignancies. Real-world data on early AF identification in relation to thyroid function are scarce. Even though symptomatic AF is rare in patients with thyroid malignancies, who are under thyroid suppressive therapy, clinicians should be aware of potential interaction with asymptomatic AF. It may prevent adverse consequences and improve the quality of life. This issue may be challenging for an updated registry of AF in clinical practice. Thyroid hormones should be considered a biomarker for cardiac arrhythmias screening and their tailored management because of their multifaceted cellular actions.