International Journal of Rheumatic Diseases最新文献

Aim: Artificial intelligence and machine learning have been increasingly employed in medical image diagnosis, but face the challenge of database acquisition. Hence, this study applies the You Only Look Once (YOLO) technique, a real-time object detection system, to construct the inference model, including the image preprocessing and labeling, model training, and the prediction of unknown data to detect objects.

Methods: We implement the YOLOv4 technique to classify osteoporosis and detect compression fractures. Trabecular characteristics of osteoporosis are extracted from caput femoris in X-ray images, and compression fractures are observed in lateral spine images. All the datasets are derived from the clinical practice of the collaborated teaching hospital.

Results: We construct the YOLOv4 model to classify osteoporosis and detect compression fractures with prediction accuracy of 78.1% and 68.3%, respectively. X-ray could be a screening tool to predict osteoporosis and select patients for DXA, especially in settings where the DXA facility is unavailable.

Conclusion: We find it promising to apply the developed approach to medical diagnosis with an accuracy of near 80%, and this deep learning model could preliminarily help to screen possible positives from abundant radiographs.

Objectives: Familial clustering and HLA haplotype association studies suggest that genetic factors disrupting the regulation of the immune system may predispose to risk of both neoplasms and autoimmune diseases, potentially leading to an increased frequency of cancer development in patients with primary Sjögren's disease (SjD), as well as their relatives. In this study, we aimed to assess the risk of cancer in patients with primary SjD and their close relatives.

Methods: Primary SjD patients who were actively followed-up in the rheumatology outpatient clinic at Gazi University Hospital and who met the 2016 ACR-EULAR classification criteria for primary SjD were included in the study. Data on cancer history in patients and their relatives were collected through direct face-to-face interviews and telephone surveys with the patients. The risk of developing cancer was calculated by comparing it with the general population of Turkey obtained from the Global Cancer Observatory of the World Health Organization International Agency for Research on Cancer (GLOBOCAN).

Results: A total of 323 primary SjD patients (F/M: 313/10, mean age: 56 ± 11) and their 1750 close relatives (parents, siblings, and children) were studied. Among SjD patients, 29 (9%) had a history of malignancy. Of these, 19 (5.9%) were solid organ and 10 (3.1%) were hematological malignancies. Breast cancer was the most common solid tumor. The median follow-up was 3.6 years, and the calculated standardized incidence ratio (SIR) for all cancers was 3.3 (95% CI: 2.2-4.7, p < 0.001). Leukemia or lymphoma cases had an SIR of 22.5 (95% CI: 10.8-41.4, p < 0.001). Among 313 women, seven cases of breast cancer had an SIR of 3.8 (95% CI: 1.5-7.9, p < 0.001). Risk of malignancy in patients with SjD did not differ based on age, gender, smoking history, Schirmer test result, laboratory parameters including anti-SSA, anti-SSB, ANA, complement levels, ESSDAI status, or Focus score, but it was higher in the presence of a cancer among close relatives. A total of 128 (43.3%) patients with SjD had at least one close relative with cancer (176 cancer cases in total), giving an SIR of 3.5 (95% CI: 3.0-4.1, p < 0.001). The average age of close relatives with cancer was 58 ± 10 years; 56% were male, and 7.4% were active smokers.

Conclusion: Our results suggest that not only patients with primary SjD but also their close relatives have an increased risk of developing cancer compared with the general population.

Introduction: Systemic lupus erythematosus (SLE) is a chronic multisystem autoimmune disease. Endothelial dysfunction is an early change in atherosclerosis. Endocan is a new indicator of endothelial dysfunction and is probably involved in proinflammatory processes in SLE. This study aimed to assess the serum endocan level in SLE patients and its relation to disease activity, endothelial dysfunction, and subclinical atherosclerosis.

Methods: This study included 60 SLE patients and 60 healthy controls. Demographic data were collected, and disease activity was assessed using the SLEDAI score for SLE patients. Functional assessment was done using the Health Assessment Questionnaire (HAQ). Serum endocan level was measured, and subclinical atherosclerosis was assessed using brachial artery flow-mediated dilation (FMD) and carotid intima-media thickness (cIMT).

Results: Endocan levels in the SLE group (632.2 ± 70.58 ng/L) were significantly higher than controls (125.83 ± 16.23 ng/L). cIMT was significantly higher in SLE patients (8.18 ± 1.13 mm) than in controls (6.43 ± 0.54), and the mean flow-mediated dilation value in SLE patients was 9.57 ± 2.59, whereas in the control group, it was 21.8 ± 4.27. The serum level of endocan was significantly correlated with the duration of the disease, triglycerides, and cIMT, and it had a significant negative correlation with flow-mediated dilation. cIMT and flow-mediated dilation were significantly correlated with age, disease duration, and triglycerides.

Conclusions: Elevated serum levels of endocan in SLE patients may be associated with subclinical atherosclerosis and endothelial dysfunction.