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Aim: Comparative analysis of the results of open thrombectomy and conservative therapy in patients with acute thrombosis of the lower limb arteries against the background of the XBB.1.5 ("Kraken") subvariant of Omicron Severe acute respiratory syndrome-related coronavirus-2 (Sars-cov-2). Material and methods: The present prospective, open, multicenter comparative study for the period 04/01/2022 to 12/01/2023 included 167 patients with acute thrombosis of the lower limb arteries against the background of the XBB.1.5 ("Kraken") subvariant of the XBB.1.5 ("Kraken") subvariant of Omicron Sars-cov-2.Depending on the treatment strategy, two groups were formed: group 1 - open thrombectomy (n = 136) and drug treatment with an anticoagulant (unfractionated heparin in a therapeutic dosage) and an antiplatelet (acetylsalicylic acid 125 mg once a day); group 2 - only drug therapy (n = 31). This group consisted of patients who refused surgical revascularization and were on a prophylactic dose of unfractionated heparin (5000 U 3 times a day subcutaneously). On the development of acute arterial thrombosis, 80 U/kg (maximum 5000 U) of unfractionated heparin was injected intravenously in a bolus, followed by transfer to intravenous infusion using an infusion pump with an initial rate of 18 U/kg per hour under control of activated partial thromboplastin time. Analgesic and antiplatelet therapy was also prescribed (acetylsalicylic acid 125 mg once a day). Results: No significant intergroup differences either in mortality rates (group 1: n = 58, 38.2%; group 2: n = 7, 22.6%; p = 0.09) or limb amputation (group 1: n = 63, 46.3%; group 2: n = 9, 29.0%; p = 0.07) were found. However, there was a trend towards a decrease in the incidence of these events in the drug treatment group. After open thrombectomy, rethrombosis developed in 50.7% (n = 69) cases; and thrombosis after rethrombectomy followed by amputation in 46.3% (n = 63). There were no hemorrhagic complications in both groups. Myocardial infarction and ischemic strokes were not recorded. Conclusion: Anticoagulant therapy demonstrates several advantages over aggressive surgical management. However, probably due to the small size of the studied sample, significant differences were not obtained. Further study of this issue is required with the identification of the optimal reperfusion method in this complex cohort of patients.
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OBJECTIVE: Cardiac magnetic resonance (CMR) imaging is a well-established technique for diagnosis of hypertrophic obstructive cardiomyopathy (HOCM) and evaluation of cardiac function, but the process is complicated and time consuming. Therefore, this paper proposes a cardiomyopathy recognition algorithm using a multi-task learning mechanism and a double-branch deep learning neural network. METHOD: We implemented a double-branch neural network CMR-based HOCM recognition algorithm. Compared with the traditional classification algorithms such as the ResNet, DenseNet network, contrast the accuracy of network classification of cardiomyopathy is higher by 10.11%. RESULT: The loss curve of the algorithm basically converges in 100 rounds, and the convergence speed of the algorithm is twice that of the traditional algorithm. The accuracy of this algorithm to classify cardiomyopathy is 96.79%, and the sensitivity is 95.24%, which is 10.11% higher than the conventional algorithm. CONCLUSION: The CMR imaging automatic recognition algorithm for HOCM capture static morphological and motion characteristics of the heart, and comprehensively enhances recognition accuracy when the sample size is limited.
