Higher FT4 level within the normal range predicts the outcome of cryoballoon ablation in paroxysmal atrial fibrillation patients without structural heart disease

Yan, Ping; Xu, Shixin; Yang, Haotian; Ren, Zhongyuan; Meng, Weilun; Zheng, Yonglai; Guo, Rong; Li, Shuang; Zhao, Dongdong; Tang, Kai; Li, Yong

doi:10.1111/anec.12874

Cited by 2 publications

(2 citation statements)

References 45 publications

(37 reference statements)

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“…Increased thyroid hormone was associated with more cardiac brosis [26] . Pervious clinical studies have found FT4, but not TSH or FT3, was associated signi cantly with LV diastolic dysfunction [27] , LA enlargement [28] and independently predicted atrial brillation recurrence [29] , even FT4 is in the normal range [30,31] . In the current study, using ML with tree ensemble methods, we found CC, NLR/PLR, and FT4 played relatively more important roles in predicting LA remodeling.…”

Section: Routine Clinical Biomarkers Correlated With La Remodelingmentioning

confidence: 99%

Applying Machine Learning with Tree Ensemble Methods and SHAP Values based on Routine Circulating Biomarkers to Detect Left Atrial Morphological and Functional Remodeling in Hypertension

Wang,

Pan,

et al. 2023

Preprint

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Introduction: Hypertension induces left atrial (LA) dysfunction and stiffness. Machine learning (ML) has been increasingly used in clinical diagnosis and prognosis prediction. To detect LA stiffness using ML with tree ensemble methods and SHAP values based on clinical biomarkers which were routinely measured in hypertension. Methods: 351 hypertensive patients were enrolled and measured LA volume (LAV) using the biplane modified Simpson’s method and LA reservoir strain (LAS-S) using 2D speckle-tracking echocardiography. The LA stiffness index (LASI) was defined as the ratio of E/eʹ to LAS-S. Four tree-based ML algorithms, including XGBoost, GBDT, Random Forest (RF), and LightGBM were used to discriminate the increased LASI (≥0.29) and LAV index (LAVI) ( ≥ 28 mL/m2) based on the routine circulating biomarkers including 38 features. We also used the SHAP values to evaluate features importance and interactions. Results: The top 20 selected variables were used as inputs for four ML models, GBDT presented the highest AUC/ROC (0.85, 95% CI 0.70-0.94) for predicting LASI, and RF model exhibited the best AUC/ROC (0.75, CI 0.57-0.92) for predicting LAVI. SHAP summary plot was applied on GBDT or RF model to identify feature contribution to LA stiffness and LA enlargement, and SHAP also revealed the interactions between variables. Conclusions: tree-based ML models with the SHAP method combining routine circulating biomarkers predicted LA stiffness with high accuracy. ML models can be useful to screen hypertensive patients with preclinical cardiac TOD, in order to improve personalized medical care at low cost.

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Section: Routine Clinical Biomarkers Correlated With La Remodelingmentioning

confidence: 99%

Applying Machine Learning with Tree Ensemble Methods and SHAP Values based on Routine Circulating Biomarkers to Detect Left Atrial Morphological and Functional Remodeling in Hypertension

Wang,

Pan,

et al. 2023

Preprint

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“…Catheter ablation is commonly used in patients with drug-refractory AF and as first-line therapy in selected cases. In patients without a history of thyroid disease, high-normal free T3/T4 (FT3, FT4) levels have been associated with a higher rate of atrial arrhythmia recurrence after AF radiofrequency ablation (hazard ratio 3.31, 95% confidence interval 1.45–7.54; high vs. lowest FT4 quartile) or cryo-ablation (HR 1.187, 95% CI 1.093–1.290) [ 13 , 14 , 111 , 112 , 113 ]. One study found patients on thyroid hormone therapy for hypothyroidism (but with normal TSH levels) to have a higher incidence of non-pulmonary vein AF triggers, particularly right atrial sources, and lower AF-free survival after ablation (64.4% vs. 75.3% for THR vs. no THR; p = 0.04) [ 7 ].…”

Section: Current Therapy Of Af In Thyroid Diseasementioning

confidence: 99%

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

Takawale

Aguilar

Bouchrit

et al. 2022

Cells

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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.

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Higher FT4 level within the normal range predicts the outcome of cryoballoon ablation in paroxysmal atrial fibrillation patients without structural heart disease

Cited by 2 publications

References 45 publications

Applying Machine Learning with Tree Ensemble Methods and SHAP Values based on Routine Circulating Biomarkers to Detect Left Atrial Morphological and Functional Remodeling in Hypertension

Applying Machine Learning with Tree Ensemble Methods and SHAP Values based on Routine Circulating Biomarkers to Detect Left Atrial Morphological and Functional Remodeling in Hypertension

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

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