急性缺血性卒中伴大血管闭塞(acute ischemic stroke with large vessel occlusion,AIS-LVO)是鼻咽癌患者的少见并发症,且治疗难度较大。本文报道了2例鼻咽癌相关性AIS-LVO患者,其中1例为鼻咽癌放疗后出现颈内动脉假性动脉瘤合并出血患...
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急性缺血性卒中伴大血管闭塞(acute ischemic stroke with large vessel occlusion,AIS-LVO)是鼻咽癌患者的少见并发症,且治疗难度较大。本文报道了2例鼻咽癌相关性AIS-LVO患者,其中1例为鼻咽癌放疗后出现颈内动脉假性动脉瘤合并出血患者,覆膜支架置入术后出现急性支架内血栓闭塞,经血管内治疗后颈内动脉复通;另1例为鼻咽癌放疗后出现颈内动脉闭塞患者,经血管内治疗后颈内动脉复通。本文对这2例鼻咽癌相关性AI S-LVO患者的诊治过程进行分析和讨论,以期为临床治疗鼻咽癌合并脑动脉闭塞提供借鉴。
卒中后抑郁是一种常见的卒中并发症,对患者的康复和生活质量有着显著影响。约三分一卒中患者伴有糖尿病,而糖尿病可加剧卒中后抑郁的风险,两者之间在病理生理学上存在相互促进的关系。本文将探讨糖尿病与卒中后抑郁之间的病理生理学联系,并从药物治疗的角度进行分析,旨在为合并糖尿病的卒中后抑郁患者提供预防和诊治参考。Post-stroke depression is a common complication of stroke, significantly affecting patients’ recovery and quality of life. Approximately one-third of stroke patients are diagnosed with diabetes, and diabetes can exacerbate the risk of post-stroke depression. There is a mutually reinforcing relationship between the two in terms of pathophysiology. This article will explore the pathophysiological connection between diabetes and post-stroke depression and analyze it from the perspective of drug therapy, aiming to provide prevention and treatment references for patients with post-stroke depression who also have diabetes.
在缺血性卒中的多种风险原因中,高脂血症特别是高胆固醇血症始终占有着很关键的地位,通过降低血浆中胆固醇特别是低密度脂蛋白胆固醇的水平,可以很有效地减少缺血性卒中发生的风险,这一观点已是世界神经科专家的普遍共识。他汀类药物是缺血性卒中二级预防的基石,被广泛应用于临床,然而,他汀类药物也有其自身的局限性。首先,如果他汀类药物剂量增加一倍,其降脂效果仅增加6%,这使得许多患者仅靠他汀类药物很难达到LDL-C目标。其次,有些患者不能耐受他汀类药物,这一现象在接受大剂量他汀类药物治疗的中国患者中尤为明显。近几年新上市的新型降脂药物–前蛋白转化酶枯草溶菌素9 (proprotein convertase subtilisin/kexin type 9, PCSK9)抑制剂则为缺血性卒中的治疗提供了新的策略。Among the myriad risk factors for ischemic stroke, hyperlipidemia, particularly hypercholesterolemia, consistently holds a pivotal role. The reduction of plasma cholesterol levels, notably low-density lipoprotein cholesterol (LDL-C), has been recognized as an effective strategy to mitigate the risk of ischemic stroke. This perspective has garnered widespread acceptance among neurology experts globally. Statins, as the mainstay of secondary prevention for ischemic stroke, are extensively utilized in clinical settings. However, statins are not without their inherent limitations. Firstly, the lipid-lowering efficacy of statins plateaus with increased dosage;doubling the dose results in a mere 6% increase in cholesterol reduction, making it challenging for many patients to achieve their LDL-C targets with statin monotherapy. Secondly, statin intolerance is not uncommon, with a pronounced incidence observed among Chinese patients undergoing high-dose statin therapy. In this context, the advent of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, a novel class of lipid-lowering agents, offers a promising alternative for the management of ischemic stroke, presenting a new therapeutic horizon in the field.
缺血性卒中是一种高致残率和致死率的脑血管疾病,早期治疗以溶栓和神经保护为主。神经保护剂可改善溶栓再通引发的缺血再灌注损伤,但因存在脑靶向性不足和作用靶点单一等缺陷,在临床应用中疗效欠佳。聚多巴胺纳米颗粒是一种具有自由基清除、多功能修饰、光热转换等特性的纳米材料,在神经保护、药物靶向、多靶点治疗方面具有独特优势,为突破目前神经保护治疗的局限提供了一个多功能集合平台。本文总结了聚多巴胺纳米颗粒的抗炎抗氧化的神经保护作用,系统阐述了聚多巴胺纳米颗粒通过各种途径促进神经保护剂靶向大脑,并结合其本身的自由基清除功能发挥多靶点治疗,为疗效确切的脑保护治疗方案的开发和应用提供新的策略。Ischemic stroke is a cerebrovascular disease with a high disabling and lethal rate, and early treatment is mainly thrombolysis and neuroprotection. Neuroprotective agents can improve ischemia-reperfusion injury caused by thrombolytic recanalization, but they have poor efficacy in clinical application due to shortcomings such as insufficient brain targeting and single target. Polydopamine nanoparticles are nanomaterials with the characteristics of free radical scavenging, multifunctional modification, photothermal conversion, etc., which have unique advantages in neuroprotection, drug targeting, and multi-target therapy, and provide a multifunctional platform for breaking through the limitations of current neuroprotective therapy. In this paper, we summarize the neuroprotective effects of polydopamine nanoparticles on anti-inflammatory and antioxidant effects, and systematically elaborate that polydopamine nanoparticles promote the targeting of neuroprotective agents to the brain through various pathways, and combine their own free radical scavenging functions to exert multi-target therapy, providing a new strategy for the development and application of brain protection therapy regimens with definite efficacy.
系统性红斑狼疮(SLE)是一种影响多个器官的全身性自身免疫疾病,其特点是免疫细胞、免疫因子和免疫途径的复杂相互作用导致各种临床表现。抗中性粒细胞胞浆抗体(ANCA)相关性血管炎(AAV)是一组以中小血管坏死性炎症和外周血中出现ANCA为特征的自身免疫综合征。SLE/AAV重叠综合征(overlap syndrome, OS)一种混合表现的炎症性疾病,具有SLE和AAV的临床特征。在极少数情况下,SLE和AAV同时发病表现出更严重的临床症状。缺血性结肠炎(IC)是一组存在血管闭塞性或非闭塞性疾病的临床综合征,以结肠供血不足为特征。本文报告了1例SLE/AAV OS伴随缺血性结肠炎患者。经过血浆置换、足量激素冲击、免疫抑制剂环磷酰胺和硫酸羟氯喹、抑酸药、生长激素抑制类药物等治疗后,患者病情缓解。Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that affects multiple organs and is characterized by a complex interplay of immune cells, immune factors, and immune pathways leading to a variety of clinical manifestations. Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of autoimmune syndromes characterized by necrotizing inflammation of small and medium-sized blood vessels and the presence of ANCA in the peripheral blood. Overlap syndrome (OS) is a mixed manifestation of inflammatory disease with clinical features of SLE and AAV. In rare cases, the concurrent onset of SLE and AAV results in SLE/AAV OS, which exhibits more severe clinical symptoms. Ischemic colitis (IC) is a group of clinical syndromes in the presence of vaso-occlusive or non-occlusive disorders characterized by inadequate blood supply to the colon. In this article, we report a patient with SLE/AAV OS combined with ischemic colitis. After treatment with adequate hormonal shocks, the immunosuppressants cyclophosphamide and hydroxychloroquine sulfate, plasma exchange, acid-suppressing drugs, and anti-growth hormone analogs, the patient's condition resolved.
腹膜炎是全球重症监护病房患者败血症的第二大死亡原因,脓毒血症的早期预测对于及时干预并最终改善预后至关重要。本研究基于新型的机器学习算法,建立并验证腹膜炎患者发展为脓毒血症的预测模型,研究结果提示机器学习模型可以成为预测腹膜炎患者预测脓毒血症的可靠工具,并且,随机森林算法模型具有最佳的预测性能,这种机器学习方法可用于帮助临床医生对于高风险因素的认识并早期干预以降低死亡率。Peritonitis is the second leading cause of sepsis-related mortality in intensive care unit (ICU) patients worldwide. Early prediction of sepsis is critical for timely intervention and ultimately improving prognosis. This study established and validated a predictive model for the development of sepsis in peritonitis patients using novel machine learning algorithms. The findings suggest that machine learning models can be a reliable tool for predicting sepsis in peritonitis patients. Among them, the random forest algorithm model showed the best predictive performance. This machine learning approach can help clinicians recognize high-risk factors and intervene early to reduce mortality.
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