相关死亡条件和定制的出生体重百分点用于死胎分类:一项回顾性队列研究
Azra Kazmi1, Devi Krishna1, Amr Abdel Aziz1
1Department of Obstetrics and Gynecology, Women's Wellness and Research Center, Hamad Medical Corporation, Doha, Qatar.
Qatar medical journal
|March 4, 2026
概括
该ReCoDe分类系统有效地分类死产 (SBs),确定胎儿生长限制 (FGR) 作为主要原因. 这种方法显著减少了无法解释的SBs,改善了围产死亡率的理解和护理.
科学领域:
- 产科和妇科 产科和妇科
- 围产儿医学 围产儿医学
- 胎儿的发育 胎儿的发育
背景情况:
- 死产 (SBs) 是围产死亡的主要原因,其中很大一部分仍然无法解释.
- 胎儿生长限制 (FGR) 是SB的一个重要因素,需要早期检测和管理.
- 相关死亡情况 (ReCoDe) 分类系统使用定制的出生体重 (CBW) 百分点来诊断FGR,旨在减少未分类的SBs.
研究的目的:
- 使用ReCoDe分类系统和定制出生体重 (CBW) 百分比来分类死产.
- 为了确定在应用ReCoDe系统后仍未分类的死产的比例.
- 确定导致死产的初级和二级诊断,重点关注FGR.
主要方法:
- 一个回顾性队列研究的死产 (SBs) 超过24周的妊娠年龄.
- 从医疗记录中提取临床,实验室和组织病理学数据.
- 根据多个母体和胎儿因素计算定制出生体重 (CBW) 百分点;FGR定义为CBW百分点<第10个百分点.
主要成果:
- 在研究的254例死胎中,胎儿生长限制 (FGR) 是最常见的诊断 (52%) 和主要诊断 (37.0%).
- 在应用ReCoDe分类后,只有7.1%的死产仍未被分类.
- 孕产妇糖尿病,胎盘断裂和胎盘缺陷是与FGR相关的常见二次诊断.
结论:
- 使用定制出生体重 (CBW) 百分位数的ReCoDe分类系统,成功分类了大多数死产 (92.9%).
- 准确的死胎分类对于了解死胎的原因,提供家庭咨询和改善产周护理至关重要.
- 通过这种分类,通过早期识别FGR,可以及时监测和干预,从而有可能降低死产率.
相关概念视频
01:29Life Histories
Constrained by limited energy and resources, organisms must compromise between offspring quantity and parental investment. This trade-off is represented by two primary reproductive strategies; K-strategists produce few offspring but provide substantial parental support, whereas r-strategists produce much progeny that receives little care. These strategies are related to an organism’s survival likelihood across its lifespan, which is represented by a survivorship curve. Three general types of...
01:52Regression Toward the Mean
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 researchers try to extrapolate results...
02:41Lethal Alleles
Agouti: A Lethal Allele
Lucien Cuénot discovered lethal alleles in 1905 while studying the inheritance of coat color in mice. The agouti gene is responsible for the color of the coat in mice. This gene codes for an agouti-signaling protein, which is responsible for melanin distribution in mammals. The wild-type allele gives rise to gray-brown coat color in mice, while the mutant allele gives rise to yellow coat color. In addition to coat color, the agouti gene is associated with the yellow...
Lucien Cuénot discovered lethal alleles in 1905 while studying the inheritance of coat color in mice. The agouti gene is responsible for the color of the coat in mice. This gene codes for an agouti-signaling protein, which is responsible for melanin distribution in mammals. The wild-type allele gives rise to gray-brown coat color in mice, while the mutant allele gives rise to yellow coat color. In addition to coat color, the agouti gene is associated with the yellow...
00:57Weighted Mean
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
01:22Life Tables
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
01:22Applications of Life Tables
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...