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1.
J Vasc Surg Cases Innov Tech ; 10(1): 101366, 2024 Feb.
Article in English | MEDLINE | ID: mdl-38130360

ABSTRACT

New-onset acute type B aortic dissection after prior endovascular aneurysm repair is extremely rare. Extension of an aortic dissection can cause destabilization of the previously implanted stent graft, thrombosis of the stent graft, and rupture of the aneurysmal sac, with high mortality without therapy. This report describes the case of a 66-year-old patient complaining of sudden abdominal pain radiating to both flanks. Computed tomography angiography of the aorta revealed acute type B aortic dissection with infrarenal rupture of the false lumen after endovascular abdominal aneurysm repair 5 years prior. The patient underwent infrarenal open surgical conversion with suprarenal aortic clamping and implantation of a bifurcated Dacron graft. Postoperatively, no serious complications resulted from the treatment, except for fascial dehiscence. In such cases, the patients can be treated in an emergency situation with open repair, despite the high risk of complications and mortality.

2.
Langenbecks Arch Surg ; 408(1): 449, 2023 Nov 30.
Article in English | MEDLINE | ID: mdl-38030864

ABSTRACT

PURPOSE: To evaluate the safety and technical success of the AndraValvulotome™ device (Andramed GmbH, Reutlingen, Germany) in patients with peripheral arterial disease (PAD) requiring bypass surgery using the great saphenous vein (GSV) as graft. METHODS: This was a multicenter, post-market observational study conducted in 2021 in 11 German centers. Safety and efficacy data were prospectively collected and analyzed. Primary endpoints were the absence of device-related serious adverse events until 30 ± 7 days follow-up, the clinical efficacy of valvulotomy, which was defined as pulsatile blood flow in the bypass and the number of insufficiently destroyed vein valves. Secondary endpoints were the number of valvulotomy passages, the primary patency rate of the venous bypass (determined by a color-duplex sonography showing a normal blood flow through the bypass and absence of stenosis or occlusion), and the primary technical success defined as the absence of product-specific (serious) adverse events and clinical efficacy. RESULTS: Fifty-nine patients were enrolled. The mean age of the patients was 71 years (46-91), and 74.6% were males. The vein material used for bypass grafting had a median length of 47.5 cm (range 20-70 cm) with a median diameter of 5.0 mm (range 3-6 mm) and 4.0 mm (range 2-6 mm) in the proximal and distal segments, respectively. The technical success rate was 96.6%. The primary patency rate was 89.9% at 30 days follow-up. The clinical efficacy was rated as very good in 81% of patients, fair in 17%, and poor in 2%. Between 1 and 5 (average 2.9) valvulotome passages were performed. One product-related serious adverse event was recorded (bypass vein dissection). CONCLUSION: The AndraValvulotome™ can be considered a safe and effective device to disrupt venous valves during in situ non-reversed bypass surgeries using GSV grafts in patients with PAD.


Subject(s)
Saphenous Vein , Vascular Surgical Procedures , Male , Humans , Middle Aged , Aged , Aged, 80 and over , Female , Saphenous Vein/transplantation , Vascular Patency , Treatment Outcome , Ultrasonography, Doppler, Duplex
3.
IEEE Trans Pattern Anal Mach Intell ; 44(10): 6196-6208, 2022 10.
Article in English | MEDLINE | ID: mdl-34125671

ABSTRACT

Action segmentation is the task of predicting the actions for each frame of a video. As obtaining the full annotation of videos for action segmentation is expensive, weakly supervised approaches that can learn only from transcripts are appealing. In this paper, we propose a novel end-to-end approach for weakly supervised action segmentation based on a two-branch neural network. The two branches of our network predict two redundant but different representations for action segmentation and we propose a novel mutual consistency (MuCon) loss that enforces the consistency of the two redundant representations. Using the MuCon loss together with a loss for transcript prediction, our proposed approach achieves the accuracy of state-of-the-art approaches while being 14 times faster to train and 20 times faster during inference. The MuCon loss proves beneficial even in the fully supervised setting.


Subject(s)
Algorithms , Supervised Machine Learning , Neural Networks, Computer
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