调查约翰逊规则在估计胎儿体重时的准确性
Fariba Alidoosti1, Mahboubeh Valiani1, Masoume Pirhadi2
1Master Student of Midwifery, Faculty of Nursing and Midwifery, Isfahan University of Medical Sciences, Isfahan, Iran.
Journal of education and health promotion
|March 25, 2024
概括
约翰逊规则为估计胎儿体重提供了一种具有成本效益的方法,这对于管理分娩至关重要. 虽然对平均和大胎儿是准确的,但对小胎儿的准确性会降低.
科学领域:
- 产科和妇科 产科和妇科
- 孕产妇和胎儿医学 孕产妇和胎儿医学
- 临床生物识别技术
背景情况:
- 准确的胎儿体重估计对于降低围产死亡率和分娩管理至关重要.
- 约翰逊规则是估计胎儿体重的临床方法,但它的有效性需要研究.
研究的目的:
- 评估约翰逊规则在临床环境中估计胎儿体重的准确性和可靠性.
- 用约翰逊规则将估计的胎儿体重 (EFW) 与实际出生体重进行比较.
主要方法:
- 一项纵向研究涉及150名伊朗伊斯法罕的孕妇.
- 使用约翰逊规则估计胎儿体重,并与测量出生体重进行比较.
- 统计分析包括t配对测试,斯皮尔曼相关性和ROC曲线分析的灵敏度和特异性.
主要成果:
- 在平均出生体重 (3032.88 ± 481.11g) 和EFW (3152.15 ± 391.95g) (P < 0.001) 之间发现了显著的差异.
- 平均 (AGA) 和较大的妊娠年龄 (LGA) 胎儿 (分别为84.3%和70%) 的EFW精度高于较小的妊娠年龄 (SGA) 胎儿 (4%).
- 在SGA胎儿中,EFW的平均百分比误差在SGA胎儿中更大.
结论:
- 约翰逊法则是临床胎儿体重估计的一种易于获得和免费的方法.
- 这种方法是管理分娩的可行替代方案,特别是对AGA和LGA胎儿.
相关概念视频
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
Testing a Claim about Standard Deviation
2.4K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.4K
z Scores and Area Under the Curve
10.5K
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...
10.5K
Accuracy and Errors in Hypothesis Testing
198
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
198
Wald-Wolfowitz Runs Test II
238
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
238
Uncertainty in Measurement: Reading Instruments
38.2K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
38.2K


