Key result
Serum thyroid hormone levels strongly predict thyroid morphometric changes in patients with AF.
Why the study?
Developing mathematical models to evaluate structural changes in the thyroid gland based on thyroid hormone levels remains a relevant issue in patients with AF and concurrent euthyroidism or thyrotoxicosis.
Can serum thyroid hormone levels (TSH, FT4, FT3) accurately model and predict thyroid morphometric parameters using multiple linear regression in patients with paroxysmal atrial fibrillation and concurrent euthyroidism, overt thyrotoxicosis, or subclinical thyrotoxicosis?
Observational (n=84)
Can serum thyroid hormone levels (TSH, FT4, FT3) accurately model and predict thyroid morphometric parameters using multiple linear regression in patients with paroxysmal atrial fibrillation and concurrent euthyroidism, overt thyrotoxicosis, or subclinical thyrotoxicosis?
Provides non-invasive multiple linear regression equations using serum TSH, FT4, and FT3 levels to estimate thyroid cellular morphometric parameters in patients with paroxysmal atrial fibrillation across euthyroid and thyrotoxic states.
Hypothesis-generating for non-invasive thyroid structural estimation in AF that should not yet change practice; leaves open whether these regression models validate externally or improve clinical outcomes.
The development of mathematical models to evaluate structural changes in the thyroid gland in patients with atrial fibrillation (AF) and thyroid dysfunction remains a highly relevant issue in cardiology and endocrinology. Objective. The aim of the paper is to model thyroid morphometric parameters based on thyroid hormone levels in patients with AF and concurrent euthyroidism, overt, or subclinical thyrotoxicosis. Materials and Methods. The study included 33 patients with AF and euthyroidism, 24 patients with AF and overt thyrotoxicosis, and 27 subjects with AF and subclinical thyrotoxicosis. Multiple linear regression was used to evaluate prognostic models. The multiple regression equation is: Yx=a0+(b1×X1)+(b2×X2)+(b3×X3)+e, where Yx is the dependent variable, a0 is the intercept, b1, b2, and b3 are the regression coefficients, X1, X2, X3 are the independent variables, and, е is the residual error. Results. Mathematical models were developed for determining thyroid morphometric parameters in patients with AF under euthyroid, overt thyrotoxicosis, and subclinical thyrotoxicosis conditions. Conclusion. Thyroid hormone levels can be used to construct prognostic multiple linear regression models for evaluating thyroid morphometric parameters in patients with AF.
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Rakhmatullov et al. (2026) conducted an observational in Paroxysmal atrial fibrillation with concurrent euthyroidism, overt thyrotoxicosis, or subclinical thyrotoxicosis (n=84). Thyroid hormone profile (TSH, FT4, FT3) in overt and subclinical thyrotoxicosis vs. Euthyroidism (n=33) was evaluated on Thyroid morphometric parameters (thyrocyte height, number of thyrocytes per follicle, colloid area, and follicular epithelium area) evaluated via multiple linear regression models (p=<0.001). Thyroid hormone levels strongly predicted thyroid morphometric parameters via multiple linear regression in atrial fibrillation patients across thyroid states (R² 0.792–0.983, all p<0.001).
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