上海的流行病学特征和90天急性肝炎E的不良结果的预后名录
Xue Mei1, Ying Zou1, Xin Zheng2
1Department of Liver Intensive Care Unit, Shanghai Public Health Clinical Centre, Fudan University, 2901 Cao Lang Road, Jinshan District, Shanghai, 201508, China.
Hepatology international
|February 12, 2026
概括
肝炎E病毒 (HEV) 感染在上海表现出季节性模式,慢性肝病 (CLD),MELD得分和中性粒细胞与淋巴细胞比率 (NLR) 预测了不良结果. 经过验证的诺基图有助于对HEV患者的早期风险分层.
科学领域:
- 肝病学和病毒性胃肠道学
- 流行病学和公共卫生.
- 临床预测建模模型
背景情况:
- 肝炎E病毒 (HEV) 是中国急性病毒性肝炎的主要原因.
- 关于HEV流行病学和不良结果预测的大规模研究是有限的.
- 了解HEV动态对于公共卫生干预至关重要.
研究的目的:
- 在上海描述HEV感染的流行病学.
- 确定住院HEV患者90天不良结果的预测因素.
- 开发和验证用于风险分层的预后编号.
主要方法:
- 816名住院的HEV患者 (2019-2024) 的回顾性队列研究.
- 多变量逻辑回归和Firth的惩罚性概率方法用于预测器识别.
- 预测名ograms (CLD-MELD-NLR和MELD-NLR) 的开发和外部验证.
主要成果:
- 在上海,HEV感染呈现出冬季-春季季节性.
- 90天不良结果的独立预测因素包括慢性肝病 (CLD),MELD得分和中性粒细胞与淋巴细胞的比率 (NLR).
- 在CLD-MELD-NLR和MELD-NLR的诺米图表显示出高精度和良好的校准风险分层.
结论:
- 上海高温病毒的明显季节性和疾病负担需要有针对性的公共卫生措施.
- 经过验证的CLD-MELD-NLR和MELD-NLR名录为早期风险分层提供了实用的工具.
- 这些名录支持在不同的临床环境中对HEV患者进行个性化管理.
相关概念视频
Characteristics of Life
262.9K
Biology is a natural science that studies life and living organisms, including their structure, function, development, interactions, evolution, distribution, and taxonomy. The field's scope is extensive and divided into several specialized disciplines, such as anatomy, physiology, ethology, genetics, and many more. All living things share a few key traits, including cellular organization, heritable genetic material and the ability to adapt/evolve, metabolism to regulate energy needs, the...
262.9K
Introduction to Epidemiology
1.9K
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.9K
Causality in Epidemiology
1.7K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.7K
Dosage Regimen Designs: Nomograms and Tabulations
203
Nomograms and tabulations are vital tools used by clinicians to design accurate and individualized dosage regimens. These instruments provide a straightforward method for adjusting dosages based on individual patient characteristics, including age, weight, and physiological condition. The foundation of a drug's nomogram is population pharmacokinetic data collected and analyzed using specific models. This data simplifies complex equations, presenting them diagrammatically or tabularly for easy...
203
Study Designs in Epidemiology
1.0K
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
1.0K
Confounding in Epidemiological Studies
858
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
858


