Pulmonary embolism is a life-threatening condition, which can result in respiratory insufficiency and death. Blood clots occluding branches of the pulmonary artery (PA) are traditionally considered to originate from thrombi in deep veins (usually in legs). However, growing evidence suggests that occlusion of the vessels in the lungs can develop without preceding deep vein thrombosis (DVT). In this work, we used an inferior vena cava (IVC) complete ligation model of DVT in Wistar rats to explore the possibility and mechanisms of PA thrombosis under the conditions where all routes of thrombotic mass migration from peripheral veins are blocked. We demonstrate that rats both with normal and reduced neutrophil counts developed thrombi in the IVC, although, neutropenia caused a substantial decrease in thrombus size and a shift from fresh fibrin toward mature fibrin and connective tissue inside the thrombus. Massive fibrin deposition was found in the PA branches in the majority of DVT rats with normal neutrophil counts, but in none of the neutropenic animals. Neutrophil ablation also abolished macroscopic signs of lung damage. Altogether, the results demonstrate that thrombi in the lung vasculature can form in situ by mechanisms that require local neutrophil recruitment taking place in the DVT setting.

Aim. We aimed to study the histological and thrombotic changes in lung vessels in patients who died with COVID-19, to access the correlation between anticoagulation therapy (ACT) and thrombotic events (TE), treatment results, clinical and laboratory patients' characteristics.Material and Methods. We retrospectively analyzed treatment results of patients hospitalized with COVID-19 and lung vessel samples of the deceased patients. Dynamic changes and highest levels of D-dimer and fibrinogen were studied in its correlation with the disease severity according to SOFA score, computer tomographic (CT) results, lung, renal and hepatic dysfunction. The association between different doses of ACT and treatment results, laboratory indicators and thrombotic events was accessed. The histological lung vessels examination was performed using Martius Scarlet Blue (MSB)staining.Results. 313 patients were included in the study (61 patients died). The median age of hospitalized patients was 60 years (IQR 51-66 years). The frequency of the intravitallyconfirmed TE was 4,8%. The strong statistical association was revealed between D-dimer level and 3-4 points SOFA score, patients' mortality, oxygen support requirement, CT3-CT4 pneumonia, glomerular filtration rate and TE. There was no mortality in patients with D-dimer normal references, but in cases with three times elevation reached 13%, 48,5% - in cases with 3-6 times elevation and 64,6% - in cases with more than 6 times elevation. The strong statistical association was registered between fibrinogen and SOFA score, CT 3-4 pneumonia, patients' mortality. D-dimer and fibrinogen levels demonstrated weak correlation. There was no statistical correlation between prophylactic, intermediate and therapeutic ACT and D-dimer and fibrinogen levels, CT results, patients' mortality. MSBstaining was used in 36 deceased patients tissue samples. 1394 lung vessels were analyzed. Lung vessels thrombi persisted in samples of all 36 patients (100%). Vessels with the diameter 3,5-30 mm were thrombosed in 7%, with the diameter 0,034-0,84 mm - in 48%, with the diameter 0,85-3,4 mm - in 45%. The frequency of thrombi persisted 06 hours, 6-12 hours, 12-18hours, 18-24 hours and more than 24 hours was12%, 14%, 62%, 5% and 7% respectively.Conclusion. Thrombi of different ages from fresh to organized were observed in one third of lung vessels in all deceased patients. Lung vessels thrombosis plays an important role in pathogenesis and thanatogenesis of COVID-19. The D-dimer level correlates with lung, renal dysfunction, patients' mortality and doesn't show any correlation with ACT and can be accepted as a criterion of lung vessel thrombotic progression.

BACKGROUND: Bariatric surgery has proven effective as a treatment for the metabolic complications of obesity, including type 2 diabetes mellitus (T2DM). Nowadays it is important to develop a personalized approach for bariatric patients generally, and for those with T2DM.AIM: Development of a scale for preoperative prediction of remission of T2DM in obese patients Russian population undergoing bariatric surgery (sleeve gastrectomy or gastric bypass).MATERIALS AND METHODS: A retrospective multicenter cohort study was conducted. The study included 112 patients (75 women and 37 men), mean age 46.25±9.29 years, mean BMI 48.71±7.66 kg/m². A mathematical analysis of 17 preoperative clinical criteria was carried out to search for independent predictors of T2DM remission.RESULTS: A remission of T2DM was verified in 85 subjects, (75.9%), absence of remission of T2DM — in 27 subjects (24.1%). The most important prognostic factors were T2DM experience, age, HOMA-IR insulin resistance index, HbA_1c, BMI, metformin therapy, SUs, insulin intake, increased levels of liver transaminases, and total cholesterol levels. The relative importance coefficient of each parameter was calculated. A formula has been developed to predict the high or low probability of T2DM remission after bariatric treatment. An online DRAMS (Diabetes Remission After Metabolic Surgery) calculator was proposed based on this formula so it is easy to use in clinical practice.CONCLUSION: An online calculator has been developed to predict the probability of T2DM remission after bariatric surgery. The received data allow us to construct a qualitative “high risk”/“low risk” scale. A number of identified predictors require further study in larger samples of patients.

Венозные тромбоэмболические осложнения (ВТЭО) относятся к многофакторным заболеваниям со сложным патогенезом и полигенным характером наследования. ЦЕЛЬ ИССЛЕДОВАНИЯ Поиск наиболее часто встречающихся комбинаций генов, кодирующих основные плазменные факторы гемостаза, у пациентов молодого возраста с ВТЭО. МАТЕРИАЛ И МЕТОДЫ Обследованы 243 молодых пациента в возрасте 18—45 лет (средний возраст 37,4 года) с тромбозом глубоких вен нижних конечностей и/или тромбоэмболией легочной артерии: 119 (48,9%) мужчин и 124 (51,1%) женщины. В контрольную группу включили 171 здорового добровольца. В обеих группах выполняли типирование аллельного полиморфизма семи генов, кодирующих факторы плазменного звена гемостаза: FI-В -455 G/A, FII 20210 G/A, FV 1691 G/A, FXII 46 C/T, FXIII Val34Leu, PAI-1 -675 4G/5G, TPA 311 п.н. Ins/Del. Генотипирование проводили методом ПЦР с рестрикционным анализом. РЕЗУЛЬТАТЫ Самостоятельными факторами риска ВТЭО явились мутации FV 1691 G/A (ОШ 2,9; p=0,006) и FII 20210 G/A (ОШ 8,8; p=0,001). Кроме того, в группе пациентов значительно чаще наблюдались следующие комбинации генотипов: «FXIII 34Val/Leu + FI-B -455GA» (ОШ 2,3; p=0,007), «FXIII 34Val/Leu + PAI-1 4G/4G» (ОШ 2,1; p=0,013) и «FXIII 34Val/Leu + FXII 46CT» (ОШ 2,2; p=0,01). У женщин гетерозиготный вариант FXIII 34Val/Leu был независимо ассоциирован с риском ВТЭО (ОШ 2,3; p=0,002). ЗАКЛЮЧЕНИЕ Помимо мутаций в генах факторов II и V значительное влияние на риск развития ВТЭО у лиц молодого возраста оказывает полиморфизм Val34Leu фактора XIII, особенно при сочетании с носительством неблагоприятных вариантов генов FI-B, FXII, PAI-1.

Chronic venous disease (CVD) is one of the most common vascular disorders, affecting millions of people worldwide. Owing to the variability of clinical symptoms and the subjective nature of their interpretation, diagnosing CVD at an early stage is complicated, making it crucial for patients to consult a specialist. It was hypothesized that an artificial intelligence (AI) model could accurately classify CVD (C0-C2 Clinical, Etiology, Anatomy, and Pathophysiology (CEAP) clinical class) from lower limb photographs. Therefore, this study aimed to develop and validate such a model. A multicenter cross-sectional study (NCT17122021) was conducted from May 2020 to January 2024 in accordance with the Declaration of Helsinki. A dataset of 10,745 lower limb photographs was collected using smartphones and professional cameras across several Russian clinics, then standardized and anonymized before model training. CEAP clinical class was determined by consensus among three surgeons experienced in phlebology. The AI model IVENUS was developed to automatically assess lower limb photographs and classify early-stage CVD according to the CEAP clinical classification (C0-C2). The model was trained using a deep learning approach based on the Swin Transformer V2 architecture. To improve model robustness and reduce overfitting, Gaussian blurring and color jitter were applied as data augmentation methods during training. The standard performance metrics (sensitivity, recall, specificity, accuracy, and precision) were calculated. The dataset consisted of 673 lower limbs of stage C0, 4445 lower limbs of stage C1, and 5627 lower limbs of stage C2. The overall diagnostic accuracy in the external validation subset of 1622 photographs was 84.8%, with a precision of 84.3%, sensitivity of 84.3%, and specificity of 92.3%. The AI model IVENUS demonstrated high diagnostic value for early-stage CVD, sufficient for its application as a clinical decision support system. Therefore, this model may support patient self-screening and telemedicine triage and may be used by specialists for automated patient routing and tracking of treatment progress.