We report a case of infected iliac artery aneurysm concomitant with liver abscesses caused by Fusobacterium nucleatum. A 58-year-old man developed an aneurysm of the right common iliac artery and liver abscesses. The aneurysm was resected and a femoro-femoral crossover bypass with a knitted Dacron graft was performed for impending rupture. Anaerobic cultures obtained from blood and intramural thrombus were positive for Fusobacterium nucleatum. With antibiotics, the liver abscesses disappeared without drainage. Iliopsoas abscesses developed after surgery, but it was controlled with antibiotics. The patient was free of infection 1 year after the surgery. The causative bacterium was suspected to originate in the oral cavity, because the patient had a notable history of poor chronic periodontal conditions. Clinically, infected aortoiliac aneurysm complicated by Fusobacterium is extremely rare relative to the prevalence of the pathogenic bacterium. However, it is noteworthy that Fusobacterium can cause this condition.
The development of liver cancer in patients with hepatitis B is a major problem, and several models have been reported to predict the development of liver cancer. However, no predictive model involving human genetic factors has been reported to date. For the items incorporated in the prediction model reported so far, we selected items that were significant in predicting liver carcinogenesis in Japanese patients with hepatitis B and constructed a prediction model of liver carcinogenesis by the Cox proportional hazard model with the addition of Human Leukocyte Antigen (HLA) genotypes. The model, which included four items—sex, age at the time of examination, alpha-fetoprotein level (log10AFP) and presence or absence of HLA-A*33:03—revealed an area under the receiver operating characteristic curve (AUROC) of 0.862 for HCC prediction within 1 year and an AUROC of 0.863 within 3 years. A 1000 repeated validation test resulted in a C-index of 0.75 or higher, or sensitivity of 0.70 or higher, indicating that this predictive model can distinguish those at high risk of developing liver cancer within a few years with high accuracy. The prediction model constructed in this study, which can distinguish between chronic hepatitis B patients who develop hepatocellular carcinoma (HCC) early and those who develop HCC late or not, is clinically meaningful.
Patients with spinal cord injury experience changes in the cardiovascular system and a high morbidity associated with peripheral artery disease. We report a case of acute aortic occlusion in a patient with chronic paralysis due to spinal cord injury. A 65-year-old man with chronic paralysis due to spinal cord injury developed mottling of the right extremity. Because of the complete tetraplegia, the patient had no subjective symptoms. Computed tomography revealed occlusion of the infrarenal abdominal aorta. An emergency thromboembolectomy established adequate blood flow, and the postoperative course was uneventful. The loss of muscle mass might be an advantage in avoiding ischemia reperfusion syndrome. Early detection of acute aortic occlusion and immediate reperfusion are primarily important, but patients with chronic paralysis present a risk of delay in detection, diagnosis, and treatment of acute aortic occlusion because of motor or sensory deficits. Although rare, it is necessary to consider acute aortic occlusion in the case of acute limb ischemia in patients with chronic paralysis due to spinal cord injury.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.