墨西哥艾滋病毒感染者心血管风险预测分数四项比较
P F Oliva-Sánchez1,2, S Landeros-López1, M M Rosas-Dossetti3
1El Instituto Nacional de Medicina Genomica, Mexico City, Mexico.
AIDS research and human retroviruses
|April 26, 2024
概括
目前的心血管风险评分对艾滋病毒感染者 (PWH) 不够. 一项研究发现,分数之间的一致性很差,并确定了与HIV特定因素的关联,例如整合酶链转移抑制剂 (INSTI) 的使用,这强调了需要量身定制的风险评估.
科学领域:
- 心脏病学 心脏病学
- 传染性疾病 传染性疾病
- 药理学 药理学是指药理学的学科.
背景情况:
- 艾滋病毒感染者 (PWH) 由于免疫激活,并发病症和抗逆转录病毒药物 (ARV) 导致心血管事件风险升高.
- 现有的心血管风险 (CVR) 评分没有针对PWH进行优化,可能低估了他们的风险.
研究的目的:
- 在墨西哥PWH中评估不同预测CVR得分之间的协议.
- 探索CVR得分与该人口中的临床/人口统计数据之间的关系.
主要方法:
- 在墨西哥城市中心 (200 PWH) 进行了一项描述性的横截面研究 (2017-2018).
- 分析包括人口统计数据,ARV治疗,病毒载量 (VL),CD4计数和各种CVR得分.
- 使用后勤回归来确定CVR得分与临床因素之间的关联.
主要成果:
- 不同的CVR得分之间观察到的一致性很低.
- 对于硬冠状动脉心脏病的Framingham风险评分较高的值被注意到.
- 与初始VL,CD4计数和甘油三相关的CVR得分,但不是BMI或腹周.
- 使用整合酶链转移抑制剂 (INSTIs) 的治疗与较高的心血管转移率得分密切相关 (例如,ASCVD OR=7.03).
结论:
- 现有的CVR得分显示PWH的一致性很差,并且没有完全捕捉到HIV特定的风险.
- 需要PWH特定的CVR得分,包括并发症和ARV使用 (特别是INSTIs) 等因素.
- 建议对所有PWH进行定期CVR查,无论当前的得分值如何.
相关概念视频
Relative Risk
157
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
157
Comparing the Survival Analysis of Two or More Groups
178
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
178
Hazard Ratio
115
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
115
Assessment of the Cardiovascular System I: Subjective Data
322
A thorough health history and physical assessment are essential for identifying cardiovascular disease (CVD) symptoms and distinguishing them from other health issues.
Initial Enquiry
Ask the patient about their primary concern and thoroughly explore all reported symptoms.
Medical History
Investigate past illnesses affecting the cardiovascular system, such as angina, anemia, rheumatic fever, congenital heart disease, stroke, thrombophlebitis, dysrhythmias, varicosities
Inquire about symptoms...
Initial Enquiry
Ask the patient about their primary concern and thoroughly explore all reported symptoms.
Medical History
Investigate past illnesses affecting the cardiovascular system, such as angina, anemia, rheumatic fever, congenital heart disease, stroke, thrombophlebitis, dysrhythmias, varicosities
Inquire about symptoms...
322
Sensitivity, Specificity, and Predicted Value
298
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Sensitivity is the...
298
Bias in Epidemiological Studies
254
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:
254


