ArticleGalen medical journal2025
Determining the Epidemiologic Aspects and Treatment Results of Patients with Idiopathic Granulomatous Mastitis (IGM) Visiting Rheumatology and Surgery Clinics Using Fuzzy Artificial Intelligence, from 2015 to 2023 : Treatment Results of Patients with Idiopathic Granulomatous Mastitis Using Fuzzy Artificial Intelligence.
Article in Galen medical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Granulomatous mastitis (GM) is a benign inflammatory disease that affects the breasts. From a pathological perspective, GM is characterized by chronic granulomatous and necrosing lesions containing small abscesses and inflammation of lobules. A variety of cures has been listed for this condition, including follow-up without intervention, antibiotic therapy, and consumption of corticosteroids, drainage, excisions, and mastectomy, but still the best cure remains unknown. This study aims to determine the epidemiologic aspects and treatment results of patients with idiopathic GM visiting rheumatology and surgery clinics from 2015 to 2023. Materials and Methods: This retrospective cohort study analyzed 39 patients with IGM visiting rheumatology and surgery clinics from 2015 to 2023. Based on a study by Kehribar et al., granulomatous mastitis has an annual prevalence of 2.4 in 100,000 cases and an incidence rate of 0.37% [1]. The required sample size was calculated as 39 people. Data were collected using a census method, categorized into types of treatment and response to treatment and patient characteristics, with ethical approval obtained. Results: The study analyzed 39 patients with an average age of 34.48±5.47 years, ranging from 22 to 45 years. Treatment strategies varied: oral steroids (25 patients), antibiotics (9 patients), surgical treatment (9 patients), combined antibiotic and surgical treatment (4 patients), steroids and MTX (2 patients), and combined steroid and antibiotic treatment (15 patients). Disease recurrence was noted in 15.4% of patients. Recovery outcomes were no recovery in 7 patients, partial recovery in 15 patients, and complete recovery in 17 patients. Conclusion: The results found that the type of treatment has no statistically significant relationship with the patient's recovery process. Complete recovery was higher in the oral steroid and steroid plus antibiotic treatment group compared to other methods. Using AI to investigate and evaluate treatments for granulomatous mastitis can provide valuable insights into the effectiveness and safety of various therapeutic approaches. By leveraging machine learning and AI techniques, researchers and clinicians can make more informed decisions that ultimately improve patient outcomes.
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