英国成年人脑炎的临床预测因素-多中心前性观察队列研究
Sylviane Defres1,2,3,4, Kukatharmini Tharmaratnam5, Benedict D Michael1,2,6
1Department of Clinical Infection Microbiology and Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom.
PloS one
|August 23, 2023
概括
早期识别脑炎类型至关重要. 临床特征可以预测自身免疫性脑炎,使得与单纯疹病毒 (HSV) 脑炎相比,治疗更快.
科学领域:
- 神经学 神经学
- 传染性疾病 传染性疾病
- 免疫学 免疫学 免疫学
背景情况:
- 脑炎,以脑部炎症为特征,可以是感染或自身免疫反应的结果.
- 晚期诊断脑炎可能会导致严重的后果.
- 早期识别特定类型的脑炎对于及时有效治疗至关重要.
研究的目的:
- 确定不同类型脑炎的临床预测因子.
- 帮助临床医生考虑早期治疗脑炎患者.
- 为了比较不同脑炎病因的治疗开始时间.
主要方法:
- 一项多中心前性观察队列研究 (ENCEPH-UK),涉及31家英国医院.
- 对成年患者的临床特征的评估和对感染性和自身免疫性原因的调查.
- 在2012年12月至2015年12月期间,招募了341名患者,随访时间为12个月.
主要成果:
- 在233名脑炎患者中,65人患有HSV,38人患有自身免疫,87人患有未知原因.
- 治疗HSV脑炎的中位时间为14小时;对于自身免疫性脑炎,是125小时.
- 与其他类型相比,HSV脑炎患者更经常出现发烧,低,缺乏皮疹. 自身免疫性脑炎患者更有可能是女性,有异常的运动,正常的和较低的CSF白细胞计数.
结论:
- 与HSV脑炎相比,自身免疫性脑炎的治疗开始显著延迟.
- 独特的临床特征可以帮助识别患有自身免疫性脑炎的患者.
- 建议根据临床表现提前对自身免疫性脑炎进行推定治疗.
相关概念视频
01:26Factors Affecting the Risk of Infection
11.9K
The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
11.9K
01:29Bias in Epidemiological Studies
352
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
352
01:08Prevalence and Incidence
627
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
627