Context: The aims of the study are to compare characteristics of subacute thyroiditis (SAT) related to different etiologies, and to identify predictors of recurrence of SAT and incident hypothyroidism. Methods: This nationwide, multicenter, retrospective cohort study included 53 endocrinology centers in Turkey. The study participants were divided into either COVID-19–related SAT (Cov-SAT), SARS-CoV-2 vaccine–related SAT (Vac-SAT), or control SAT (Cont-SAT) groups. Results: Of the 811 patients, 258 (31.8%) were included in the Vac-SAT group, 98 (12.1%) in the Cov-SAT group, and 455 (56.1%) in the Cont-SAT group. No difference was found between the groups with regard to laboratory and imaging findings. SAT etiology was not an independent predictor of recurrence or hypothyroidism. In the entire cohort, steroid therapy requirement and younger age were statistically significant predictors for SAT recurrence. C-reactive protein measured during SAT onset, female sex, absence of antithyroid peroxidase (TPO) positivity, and absence of steroid therapy were statistically significant predictors of incident (early) hypothyroidism, irrespective of SAT etiology. On the other hand, probable predictors of established hypothyroidism differed from that of incident hypothyroidism. Conclusion: Since there is no difference in terms of follow-up parameters and outcomes, COVID-19– and SARS-CoV-2 vaccine–related SAT can be treated and followed up like classic SATs. Recurrence was determined by younger age and steroid therapy requirement. Steroid therapy independently predicts incident hypothyroidism that may sometimes be transient in overall SAT and is also associated with a lower risk of established hypothyroidism.

Our goal was to assess the effectiveness of fine-needle aspiration thyroglobulin (FNA-Tg) in detecting malignant lymph nodes (LNs) in patients with differentiated thyroid cancer (DTC). We also aimed to determine the factors that affect the accuracy of FNA-Tg. We conducted a retrospective cohort study using the laboratory, ultrasonographic, histopathological, FNA cytology (FNA-C), and FNA-Tg results of 176 DTC patients. We used receiver operating characteristic analysis to identify the cutoff value of FNA-Tg, and binary regression analysis to compare FNA-Tg with other diagnostic parameters. Spearman correlation was utilized to identify factors that influence FNA-Tg. Our study revealed that a cutoff value of 3.14 ng/mL for FNA-Tg had a sensitivity of 91.8% and a specificity of 96.6% in detecting malignant LNs in the entire group. In the subgroup with thyroid tissue, the optimal cutoff value for FNA-Tg was determined to be 15.5 ng/mL. Additionally, FNA-C had a sensitivity of 82.4% and a specificity of 99.4% for the entire group. The combined use of FNA-Tg and FNA-C yielded a sensitivity of 100% and a specificity of 96%, which was found to be more effective than using either test alone. Serum Tg positivity and serum thyroid-stimulating hormone were positively correlated with FNA-Tg levels in detecting malignant LNs. Our study demonstrated that FNA-Tg is a reliable method for detecting LN metastases in DTC patients, with a 3.14 ng/mL cutoff value. However, each center should take into account factors such as serum thyroid-stimulating hormone, serum Tg, and the presence of thyroid tissue when interpreting FNA-Tg results and determining the appropriate cutoff level.

Background: Cushing syndrome (CS) is a rare endocrine disorder characterized by excessive secretion of glucocorticoids, leading to a variety of clinical manifestations, comorbidities, and increased mortality despite treatment. Despite advances in imaging modalities and biochemical testing, the diagnosis and management of CS remains challenging. Several tests are used to confirm the diagnosis of CS, including urinary free cortisol measurements, dexamethasone suppression tests (1 mg, 2 mg, and 8 mg), and nocturnal salivary cortisol measurements. However, each of these tests has some limitations, making the diagnosis of CS. Methods: In this paper, we explore the potential of state-of-the-art machine learning algorithms as a clinical decision support system for analyzing and classifying CS. Our aim is to use advanced machine learning methods to analyze the accuracy rates of diagnostic tests and identify the most sensitive tests for diagnosing CS. Results: In this study, we performed binary classification based on data from 278 patients with CS (CS+) and 220 healthy patients (CS-). We developed a linear mathematical model with high predictive ability, achieving a classification accuracy of 97.03% and a Kappa value of 94.05%. The correlation graph shows that CS has strong positive relationships with 2 mg (78.8%), 1 mg (76.9%), and mc (72.1%), and moderate positive correlations with 8 mg (45%) and saliva (45.4%). In contrast, gender has almost no correlation with CS, so it was removed from the dataset. As a result, the model achieves an overall classification accuracy of 97.03%. Finally, we converted the linear model into a mobile application for use by specialist doctors in the field of endocrinology. Conclusion: Traditional diagnostic methods can be time-consuming and require specialized medical expertise. Recently, advances in machine learning and mobile technology have opened new avenues for improving diagnostic accuracy and accessibility. This study explores the integration of machine learning algorithms into a mobile application designed to assist healthcare professionals and patients in the diagnosis of CS.

Background/aim: To describe Graves’ Disease (GD) associated with COVID-19 infection (COVID) or its vaccines (VAC) and to compare the clinical presentations, laboratory parameters, and short-term clinical course of the disease among different etiology groups (COVID, VAC, and GD control). Materials and methods: Included in this multicenter matched case–control, retrospective cohort study were 239 patients with newly diagnosed (n = 196) or recurrent GD (n = 43) associated with COVID (n = 79) or VAC (n = 160). Each case was matched (1:1) with a control who had been diagnosed with GD prior to COVID. Results: The median age of the entire group was 42 years (female:male = 137:102). Both the COVID (4.6-fold) and VAC (4.1-fold) groups demonstrated higher TSH receptor antibody (TRAb) titers (p < 0.001) compared with the control group (3.5-fold), as well as a higher proportion of recurrent cases. At baseline, the COVID group had higher free triiodothyronine (fT3) levels than the other groups. Graves orbitopathy (GO) was observed in 60 patients (12.6%), with a higher frequency in classical GD (18.4%). At baseline, the variables associated with thyrotoxicosis severity (defined as fT3 levels) were younger age, higher thyroid gland volume (TGV), and etiology, with the COVID and, to a lesser extent, VAC groups presenting with higher fT3 levels. The variables associated with GO were higher TGV, TRAb titers, and smoking, while no association with etiology was identified. Conclusion: The clinical course was similar in all groups other than in some laboratory findings. Although the frequency of GO associated with COVID and VAC was lower, the proportion of cases with a Clinical Activity Score of ≥3 was higher compared to GD. This pattern suggests a potentially stronger immunologic trigger in these cases.