Background/aim: Systemic sclerosis (SSc) is a chronic systemic disease characterized by vascular damage, autoimmunity, and fibrosis in the skin and internal organs. In this study, we tried to determine the causes of severe infection in patients with SSc and to reveal the factors associated with severe infection. Materials and methods: We retrospectively examined 214 SSc patients between January 2010 and August 2020. Forty-seven patients with at least one severe infection and 167 patients without severe infection were compared. Results: A total of 76 episodes of severe infections were detected in 47 (22%) patients. Common infections included pneumonia, infected digital ulcer, urinary tract infections, and osteomyelitis. Female patients had a higher frequency in the group without severe infection (91.6% vs. 80.9%, p = 0.035). Patients with severe infections had a higher frequency of digital ulcers (p < 0.001), cardiac (p = 0.002), and GIS involvement (p < 0.001). In multivariable analysis, digital ulcer presence (OR: 2.849 [1.356-5.898] (p = 0.006) and cardiac involvement (OR: 2.801 [1.248-6.285]) were associated with severe infection. Of the patients with severe infections, 34% had recurrent severe infections. There was no difference in demographic and clinical characteristics between patients with recurrent and nonrecurrent severe infections. Conclusion: The presence of digital ulcer and cardiac involvement seem to be associated with a severe infection in patients with systemic sclerosis. In patients with cardiac involvement and digital ulcers, more careful attention may be required for the development of severe infections.

Background: Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a rare au-toimmune disease usually involving small vessels and progressing with necrotizing inflammation. Treatment requires long-term use of immunosuppressive agents to inhibit disease activity. Serious infections (SIs) are a common complication in AAV. Objective: The aim of this study was to identify the risk factors for serious in-fections which required hospitalization in patients with AAV. Methods: In this retrospective cohort study., we included 84 patients admitted to the Ankara University Faculty of Medicine in the last 10 years with a diagno-sis of AAV. Results: In 42 (50%) of 84 patients followed up with the diagnosis of AAV, an infection requiring hospitalization was identified. The patients' total corticosteroid dose, use of pulse steroids, induction regimen, levels of C-reactive protein (CRP) and the presence of pulmonary and renopulmonary involvement were found to be associated with the frequency of infection (p=0.015, p=0.016, p=0.010, p=0.03, p= 0.026 and p=0.029, respectively). In multivariable analysis, it was found that renopulmonary involvement (p=0.002, HR=4.95, 95% CI= 1.804-13.605), age of over 65 (p=0.049, HR=3.37, 95% CI=1.004-11.369) and high CRP levels (p=0.043, HR=1.006, 95% CI=1.000-1.011) constituted independent predictors of serious infection risk. Conclusion: The frequency of infection is known to be increased in ANCA-associated vasculitis. Our study showed that renopul-monary involvement, age and elevated CRP levels on admission are independent risk factors of infection.

Objective: Behçet syndrome (BS) is a multisystemic chronic vasculitic disease. Among previous studies, although there are some that showed increased risk of subclinical atherosclerosis in BS, there are also others that showed the opposite. The objective of this study is to evaluate subclinical atherosclerosis in BS by using the cutoff value for intima-media thickness in the 2013 European Society of Cardiology/European Society of Hypertension guideline. Methods: We conducted a cross-sectional analysis of 100 BS patients and 30 healthy volunteers at a single center in a 4-month period. All ultrasound scans were performed in a blind manner to the clinical assessment, and they were carried out by the same researcher by a B-mode ultrasonography. Result: When we grouped the patients based on the presence of subclinical atherosclerosis, the frequency of subclinical atherosclerosis in the BS patients was found to be higher than that in the healthy controls (32% and 7%, respectively; p = 0.006). When a cutoff is used for carotid intima-media thickness, increased atherosclerosis risk is observed in BS patients with vascular involvement (p = 0.043). Conclusions: Although higher inflammation and increased atherosclerosis in vascular BS patients were expected, this situation was not supported much in previous studies. We think that this may have been caused by mere comparison of numerical data, and usage of a cutoff value could be more significant in distinguishing what is normal and what is abnormal as in several medical parameters.

Background/Objectives: The aim of this study was to classify nailfold videocapillaroscopy (NVC) images obtained from patients with systemic sclerosis (SSc) and healthy individuals using deep learning methods. Methods: Between January and June 2025, 1280 NVC images were recorded from 50 SSc and 30 healthy individuals. The images were classified by two rheumatologists as normal, early, active, and late-stage SSc patterns. After removing 191 unclassifiable and 112 low-quality images, 977 usable images remained. To ensure balanced classes, 245 normal images were excluded. The final dataset was split into training (70%), validation (20%), and test (10%) sets. Six different deep learning models (MobileNetV3Large, ResNet152V2, Xception, VGG-19, InceptionV3, and NASNetLarge) with varying levels of complexity and computational efficiency were selected to compare their performance. Accuracy, precision, recall, F1 Score, and cross-entropy loss were employed as performance metrics. These metrics are commonly used in the literature to evaluate the effectiveness of classification models. Results: Deep learning models achieved an accuracy ranging from 90.6% to 98.9%, a precision of 93.4% to 98.9%, a recall of 90.6% to 98.8%, an F1 score of 92% to 98.9%, and an ROC AUC performance between 99% and 100%. InceptionV3 demonstrated the best performance with an accuracy of 98.95%, a precision of 98.94%, a recall of 98.80%, and an F1 score of 98.88%. In terms of test loss, the lowest values were observed in the InceptionV3 and NasNetLarge models, both with a loss of 0.03. Overall, the ROC AUC values for all models ranged between 98.99% and 100%, indicating competitive performance. Conclusions: The current findings suggest that deep learning methods may be capable of classifying NVC images as accurately as experienced rheumatologists.

Purpose: The aim of this study was to determine the association of rheumatoid arthritis–related lung disease (RA-LD) and its subtypes with all-cause mortality. Materials and Methods: For the present analyses, patients with RA who underwent computed tomography of the chest (chest-CT) were evaluated. RA-LD was defined in 4 subtypes as follows: interstitial lung disease (RA-ILD), airway disease (RA-AD), rheumatoid pulmonary nodules (RA-PN), and RA-related pleural disease (RA-PD). The date of RA-LD diagnosis was considered the date of the first chest-CT detecting the pathology. To assess the factors associated with mortality, multivariable logistic regression analyses were performed with variables selected based on their causal associations with the outcome. Results: Of 576 RA patients, 253 (43.9%) had RA-LD (38.7% male; mean age at RA-LD diagnosis, 59.9 ± 9.8 years). The most common subtype was RA-AD, which was detected in 119 (47.0%) patients followed by 107 (42.3%) with RA-ILD, 70 (27.7%) with RA-PN, and 31 (12.3%) with RA-PD. Sixty-one (24.1%) patients had 2+ subtypes. After median follow-up of 10.2 years, 97 (16.8%) died. The existence of at least 1 subtype and 2+ subtypes increased the all-cause mortality, as indicated by odds ratios of 1.60 (95% confidence interval [CI], 1.03–2.48) and 2.39 (95% CI, 1.26–4.54), respectively. Among RA-LD patients, RA-ILD and RA-PD were associated with increased mortality (odds ratios were 2.20 [95% CI, 1.18–4.08] and 1.62 [95% CI, 0.70–3.75], respectively). Conclusions: In this study, RA-AD was the most common subtype, and the presence of RA-LD increased mortality. This effect was particularly pronounced in patients with RA-ILD and RA-PD or those presenting with 2+ subtypes.