Anamnestic pregnancy risk assessment

Caunes, F de; Alexander, Greg R.; Berchel, C; Guengant, Jean-Pierre; Papiernik, E

doi:10.1016/0020-7292(90)90005-6

Cited by 10 publications

(11 citation statements)

References 7 publications

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“…Several other retrospective analyses attempted to associate perinatal mortality with the presence of specific risk factors. In Guadeloupe, West Indies, using data from the 1984–85 Guadeloupean Perinatal Audit, de Caunes et al [ 17 ] observed that perinatal mortality was associated with a specific combination of risk factors representing maternal demographic, socioeconomic, obstetric history and risk characteristics measurable at the first antenatal visit, leading the authors to advocate for risk assessments specific to pregnancy outcomes within specific populations [LOE: 3-] .…”

Section: Resultsmentioning

confidence: 99%

Reducing stillbirths: screening and monitoring during pregnancy and labour

Haws

Yakoob

Soomro

et al. 2009

BMC Pregnancy Childbirth

153

134

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Background: Screening and monitoring in pregnancy are strategies used by healthcare providers to identify high-risk pregnancies so that they can provide more targeted and appropriate treatment and follow-up care, and to monitor fetal well-being in both low-and high-risk pregnancies. The use of many of these techniques is controversial and their ability to detect fetal compromise often unknown. Theoretically, appropriate management of maternal and fetal risk factors and complications that are detected in pregnancy and labour could prevent a large proportion of the world's 3.2 million estimated annual stillbirths, as well as minimise maternal and neonatal morbidity and mortality.

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Section: Resultsmentioning

confidence: 99%

Reducing stillbirths: screening and monitoring during pregnancy and labour

Haws

Yakoob

Soomro

et al. 2009

BMC Pregnancy Childbirth

153

134

View full text Add to dashboard Cite

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“…Die m ü tterlichen Parameter K ö rpergr ö ß e und K ö rpergewicht haben ebenfalls einen Einfl uss auf die Fr ü hgeborenenraten [9] . Anhand fr ü herer epidemiologischer Studien gab es Versuche, Risiko-Scores zum Vorhersagewert einer Fr ü hgeburtlichkeit zu ermitteln [6,7,10,12,19,21,23,28] . Ein signifi kanter Zusammenhang zwischen Anamnese und einer erh ö hten Fr ü hgeborenenrate konnte z.…”

Section: Introductionunclassified

Evaluierung von mütterlichen Merkmalen als Risikofaktoren für Frühgeburtlichkeit (Einzel- und Kombinationswirkung)

Voigt

Briese²,

Pietzner³

et al. 2009

Z Geburtshilfe Neonatol

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“…Of the 16 studies that included model development, five studies collected data prospectively (Allouche et al, 2011; Gioan et al, 2018; Mercer et al, 1996; Misra et al, 2001; Zhu et al, 2017), 10 studies collected data retrospectively (Baer et al, 2018; de Caunes et al, 1990; Goyal et al, 2015; Hueston, 1998; Lee et al, 2020; Luo et al, 2016; Morken et al, 2014; Tan et al, 2007; Weber et al, 2018; Woolery, 1992), and one study combined prospective and retrospective designs (Takagi et al, 2012). Of the five studies that only conducted validation, three studies collected data prospectively (R. K. Creasy et al, 1980; Goodfellow et al, 2019; Holbrook et al, 1989), one study collected data retrospectively (Edenfield et al, 1995), and one study combined both designs (Wilson & Sill, 1973) (Table 2).…”

Section: Resultsmentioning

confidence: 99%

Systematic Review of Prediction Models for Preterm Birth Using CHARMS

Kim

Lee

2021

Biological Research For Nursing

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Objective: This study sought to evaluate prediction models for preterm birth (PTB) and to explore predictors frequently used in PTB prediction models. Methods: A systematic review was conducted. We selected studies according to the PRISMA, classified studies according to TRIPOD, appraised studies according to the PROBAST, and extracted and synthesized the data narratively according to the CHARMS. We classified the predictors in the models into socio-economic factors with demographic, psychosocial, biomedical, and health behavioral factors. Results: Twenty-one studies with 27 prediction models were selected for the analysis. Only 16 models (59.3%) defined PTB outcomes as 37 weeks or less, and seven models (25.9%) defined PTB as 32 weeks or less. The PTB rates varied according to whether high-risk pregnant women were included and according to the outcome definition used. The most frequently included predictors were age (among demographic factors), height, weight, body mass index, and chronic disease (among biomedical factors), and smoking (among behavioral factors). Conclusion: When using the PTB prediction model, one must pay attention to the outcome definition and inclusion criteria to select a model that fits the case. Many studies use the sub-categories of PTB; however, some of these sub-categories are not correctly indicated, and they can be misunderstood as PTB (≤ 37 weeks). To develop further PTB prediction models, it is necessary to set the target population and identify the outcomes to predict.

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Anamnestic pregnancy risk assessment

Cited by 10 publications

References 7 publications

Reducing stillbirths: screening and monitoring during pregnancy and labour

Reducing stillbirths: screening and monitoring during pregnancy and labour

Evaluierung von mütterlichen Merkmalen als Risikofaktoren für Frühgeburtlichkeit (Einzel- und Kombinationswirkung)

Systematic Review of Prediction Models for Preterm Birth Using CHARMS

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