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Automatic Levothyroxine Dosing Algorithm for Patients Suffering from Hashimoto’s Thyroiditis

Authors :
Reichhartinger, Ravi Sharma
Verena Theiler-Schwetz
Christian Trummer
Stefan Pilz
Markus
Source :
Bioengineering; Volume 10; Issue 6; Pages: 724
Publication Year :
2023
Publisher :
Multidisciplinary Digital Publishing Institute, 2023.

Abstract

Hypothyroidism is a condition where the patient’s thyroid gland cannot produce sufficient thyroid hormones (mainly triiodothyronine and thyroxine). The primary cause of hypothyroidism is autoimmune-mediated destruction of the thyroid gland, referred to as Hashimoto’s thyroiditis. A patient’s desired thyroid hormone concentration is achieved by oral administration of thyroid hormone, usually levothyroxine. Establishing individual levothyroxine doses to achieve desired thyroid hormone concentrations requires several patient visits. Additionally, clear guidance for the dosing regimen is lacking, and significant inter-individual differences exist. This study aims to design a digital automatic dosing algorithm for patients suffering from Hashimoto’s thyroiditis. The dynamic behaviour of the relevant thyroid function is mathematically modelled. Methods of automatic control are exploited for the design of the proposed robust model-based levothyroxine dosing algorithm. Numerical simulations are performed to evaluate the mathematical model and the dosing algorithm. With the help of the developed controller thyroid hormone concentrations of patients, emulated using Thyrosim, have been regulated under the euthyroid state. The proposed concept demonstrates reliable responses amidst varying patient parameters. Our developed model provides a useful basis for the design of automatic levothyroxine dosing algorithms. The proposed robust feedback loop contributes to the first results for computer-assisted thyroid dosing algorithms.

Details

Language :
English
ISSN :
23065354
Database :
OpenAIRE
Journal :
Bioengineering; Volume 10; Issue 6; Pages: 724
Accession number :
edsair.multidiscipl..6ebc509f5801c2e2aa7e5b4a4c3f00a3
Full Text :
https://doi.org/10.3390/bioengineering10060724