Abstract

Objective.This research ismeant to study the features of the clinical course and to developanoptimal algorithm for the diagnosis of autoimmune thyroiddiseases. Material and methods.The work is based on the examination and treatment data of 481 patients with autoimmune diseases of the thyroid gland, treated in the clinic.Diagnosis and treatment results of 481 patients were analyzed to develop an optimal algorithm for diagnosingautoimmune thyroiditis.The differential diagnostic capabilities of clinical, laboratory, and morphological examination methods of patients withautoimmune thyroiddiseases have been specified.The study of long-term results of treatment was carried out on 340patients, taking into account the various methods of treatment they underwent. Results.The analysis of existing diagnostic tools and methods allowed us to develop an optimal algorithm for diagnosingautoimmune thyroiddiseases, which is a complex of clinical, laboratory, and morphological methods that can reliably verify the diagnosis of autoimmune thyroiditis. Based on the examination results, it is possible to predict the likelihood of surgical treatment and to identify a group of patients in whom autoimmune processes can progress in the thyroid residue, contributing to the development of postoperative recurrence of the disease or causing its atrophy. Conclusion. Based on the study’s results, a rational algorithm for diagnostic search has been developed. The proposed algorithm allows, in the shortest possible time, to identify the presence of a form of autoimmune thyroiddisease and to determine the optimal tactics to treat patients withautoimmune thyroiditis based on clinical, laboratory, immunological tests and instrumental examinations.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.