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Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia.

08:00 EDT 29th September 2018 | BioPortfolio

Summary of "Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia."

To quantify differences in assessing preterm delivery when calculating gestational age from last menstrual period (LMP) versus ultrasonography biometry.

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This article was published in the following journal.

Name: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
ISSN: 1879-3479
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Medical and Biotech [MESH] Definitions

The period from onset of one menstrual bleeding (MENSTRUATION) to the next in an ovulating woman or female primate. The menstrual cycle is regulated by endocrine interactions of the HYPOTHALAMUS; the PITUITARY GLAND; the ovaries; and the genital tract. The menstrual cycle is divided by OVULATION into two phases. Based on the endocrine status of the OVARY, there is a FOLLICULAR PHASE and a LUTEAL PHASE. Based on the response in the ENDOMETRIUM, the menstrual cycle is divided into a proliferative and a secretory phase.

The period in the MENSTRUAL CYCLE that is optimal for FERTILIZATION of the OVUM and yielding PREGNANCY. The duration of fertile period depends on the life span of male GAMETES within the female reproductive tract and the time of OVULATION. It usually begins a few days before ovulation and ends on the day of ovulation.

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

Adverse of favorable selection bias exhibited by insurers or enrollees resulting in disproportionate enrollment of certain groups of people.

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