自身免疫性胃炎(autoimmune gastritis)又称A型胃炎,是一种主要以胃体萎缩为主要特征的CD4+ T细胞介导的自身免疫性疾病。虽然其临床表现呈现多样化及非特异性,但近些年来我国AIG的发病率并不低。为增加临床医生对自身免疫性胃炎的认识及给临床医生提出诊疗疾病的目标和对策,本文将自身免疫性胃炎的流行病学、发生机理、临床表现、症状和治疗方式做了总结。 Autoimmune gastritis (AIG), also known as type A gastritis, is a CD4+ T-cell-mediated autoimmune disease mainly characterized by atrophy of the gastric body. Although its clinical manifestations are diverse and non-specific, the incidence of AIG in China has not been low in recent years. In order to raise the attention of clinicians to autoimmune gastritis and to provide clinicians with directions and strategies for diagnosis and treatment of this disease, this paper reviews the epidemiology, pathogenesis, clinical manifestations, diagnosis, and therapeutic progress of autoimmune gastritis.
原发性胆汁性肝硬化(Primary Biliary Cholangitis, PBC)和自身免疫性肝炎(Autoimmune Hepatitis, AIH)是不同的自身免疫性慢性肝病,这2种疾病在同一患者中共存称为重叠综合征。干燥综合征(Sjögren Syndrome, SS)是自身免疫性肝病(Autoimmune Liver Disease, AILD)最常并发的肝外自身免疫病。本文报告了一例AIH-PBC重叠综合征合并SS的病例,探讨其临床表现、诊断和治疗策略。Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are two common clinical autoimmune liver diseases, and some patients have both diseases;this feature is called AIH-PBC overlap syndrome. Sjögren syndrome is one of the most common extrahepatic autoimmune diseases among patients with autoimmune liver diseases. This article presents the case report of an elderly female patient who was diagnosed with AIH-PBC overlap syndrome combined with Sjögren syndrome, and discusses its clinical presentation, diagnosis and treatment strategies.
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.
目前,国内尚无关于九价人乳头瘤病毒疫苗导致药物性肝损伤的报道,但这一问题应引起临床医师的高度重视。现报道1例中年女性患者,在接种九价HPV疫苗第二针后出现乏力、纳差、巩膜及皮肤黄染,经护肝、利胆等对症支持治疗后症状好转,但临床医生未能及时说服患者完善相关检查进一步排查药物性肝损伤,致患者继续接种第三针,出现肝损慢性化、严重化。经进一步的护肝、利胆、营养支持等对症支持治疗并随访5个月,患者肝脏功能已恢复正常。通过该病例以期提高临床对药物性肝损伤的认知及诊治水平。At present, there is no report on drug-induced liver injury caused by nine-valent human papillomavirus vaccine in China, but this problem should be highly valued by clinicians. It is reported that a middle-aged female patient suffered from fatigue, poor appetite, yellow staining of sclera and skin after the second dose of nine-valent HPV vaccine. After symptomatic support treatment such as protecting the liver and promoting gallbladder function, the symptoms improved, but the clinician failed to persuade the patient to improve the relevant examination in time to further investigate the drug-induced liver injury, resulting in the patient continuing to receive the third dose, resulting in chronic and severe liver damage. After further symptomatic support treatment such as liver protection, choleretic and nutritional support and follow-up for 5 months, the liver function of the patient has returned to normal. Through this case, we hope to improve the clinical cognition, diagnosis and treatment of drug-induced liver injury.
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