基于单元和双胞胎图表的孕期年龄小的双胞胎新生儿发病率
概括
小到孕期年龄 (SGA) 双胞胎的新生儿重症监护室 (NICU) 患病率高于SGA单身双胞胎. 单子生长图表适用于监测双胞胎和单子怀孕中的胎儿生长.
科学领域:
- 新生儿科学 新生儿科学
- 孕产妇和胎儿医学 孕产妇和胎儿医学
- 周围生理学 周围生理学
背景情况:
- 怀孕年龄较小的新生儿 (SGA) 患不良后果的风险增加.
- 准确的胎儿生长评估对于识别SGA新生儿至关重要.
- 单子和双胞胎怀孕的分离生长图通常使用.
研究的目的:
- 为了比较双胞胎和单子妊娠的新生儿重症监护室 (NICU) 发病率,分类为小到妊娠年龄 (SGA).
- 评估使用单元生长图表用于双胞胎SGA分类的适当性.
主要方法:
- 1150名双胞胎和29035名单胞胎的回顾性比较,这些双胞胎在怀孕35周至36周之间进行了评估.
- 估计的胎儿体重是用哈德洛克公式从超声波测量中计算的.
- 基于SGA分类使用单元和双元参考分布的NICU入院率和停留时间的比较.
主要成果:
- 双胞胎和单胞胎的整体NICU入院率相似 (7.3%对7.4%).
- 双胞胎在新生儿重症监护室停留时间明显长 (≥7天:2.4%vs0.8%).
- 当使用单子图表时,SGA双胞胎与SGA单子相比,表现出更高的NICU发病率 (≥7天:3.7%与1.4%相比).
结论:
- 单体生长图表不会在双胞胎中过度诊断胎儿生长限制.
- SGA双胞胎显示出与生长相关的新生儿发病率比SGA单胞胎更高.
- 建议使用单子图表来监测单子和双胞胎怀孕中的胎儿生长.
关键词:
这两个双胞胎是迪科里奥尼克双胞胎.胎儿的成长 胎儿的成长胎儿生长限制 限制胎儿生长增长监测 增长监控 增长监控双胞胎是一个的双胞胎.过早分娩 过早分娩是什么单一的参考分布 单一的参考分布双胞胎怀孕 双胞胎怀孕 双胞胎怀孕双胞胎的参考分布是双胞胎的参考分布.更多相关视频
相关概念视频
Teratogenicity
2.5K
The ability of a drug to produce structural deformations and functional abnormalities in the developing embryo or the fetus is called teratogenicity, and the drug producing this effect is known as a teratogen. Teratogenic effects include stillbirth, miscarriage, intrauterine growth restriction, and neurocognitive delay. A teratogen may affect the embryo at different stages of development, which is important in determining the type and extent of the damage. During blastocyst formation, the early...
2.5K
Pathophysiology of Diabetes
971
Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia. The four categories of diabetes are type 1 diabetes, type 2 diabetes, other specific types of diabetes, and gestational diabetes.
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility,...
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility,...
971
Prevalence and Incidence
619
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...
619
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Relative Risk
208
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...
208
z Scores and Area Under the Curve
10.9K
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
10.9K


