Abruptio Placentae

ObjectiveTo study whether pregnancies complicated by hyperemesis gravidarum in the first (DesignPopulation-based cohort study.SettingSweden.PopulationAll pregnancies in the Swedish Medical Birth Register estimated to have started on 1 January 1997 or later and ended in a single birth on 31 December 2009 or earlier (n = 1 156 050).MethodsOdds ratios with 95% confidence intervals were estimated for placental dysfunction disorders in women with an inpatient diagnosis of hyperemesis gravidarum, using women without inpatient diagnosis of hyperemesis gravidarum as reference. Risks were adjusted for maternal age, parity, body mass index, height, smoking, cohabitation with the infant's father, infant's sex, mother's country of birth, education, presence of hyperthyreosis, pregestational diabetes mellitus, chronic hypertension and year of infant birth.Main outcome measuresPlacental dysfunction disorders, i.e. pre-eclampsia, placental abruption, stillbirth and small for gestational age (SGA).ResultsWomen with hyperemesis gravidarum in the first trimester had only a slightly increased risk of pre-eclampsia. Women with hyperemesis gravidarum with first admission in the second trimester had a more than doubled risk of preterm (ConclusionsThere is an association between hyperemesis gravidarum and placental dysfunction disorders, which is especially strong for women with hyperemesis gravidarum in the second trimester.

Placental dysfunction is involved in a group of obstetrical conditions including preeclampsia, intrauterine growth restriction, and placental abruption. Their timely and accurate recognition is often a challenge since diagnostic criteria are still based on nonspecific signs and symptoms. The discovering of the role of angiogenic-related factors (sFlt-1/PlGF) in the underlying pathophysiology of placental dysfunction, taking into account that angiogenesis-related biomarkers are not specific to any particular placental insufficiency-related disease, has marked an important step for improving their early diagnosis and prognosis assessment. However, sFlt-1/PlGF has not been yet established as a part of most guidelines. We will review the current evidence on the clinical utility of sFlt-1/PlGF and propose a new protocol for its clinical integration.

BackgroundAlthough rare, placental abruption is implicated in disproportionately high rates of perinatal morbidity and mortality. Understanding geographic and temporal variations may provide insights into possible amenable factors of abruption. We examined abruption frequencies by maternal age, delivery year, and maternal birth cohorts over three decades across seven countries.MethodsWomen that delivered in the US (n = 863,879; 1979-10), Canada (4 provinces, n = 5,407,463; 1982-11), Sweden (n = 3,266,742; 1978-10), Denmark (n = 1,773,895; 1978-08), Norway (n = 1,780,271, 1978-09), Finland (n = 1,411,867; 1987-10), and Spain (n = 6,151,508; 1999-12) were analyzed. Abruption diagnosis was based on ICD coding. Rates were modeled using Poisson regression within the framework of an age-period-cohort analysis, and multi-level models to examine the contribution of smoking in four countries.ResultsAbruption rates varied across the seven countries (3-10 per 1000), Maternal age showed a consistent J-shaped pattern with increased rates at the extremes of the age distribution. In comparison to births in 2000, births after 2000 in European countries had lower abruption rates; in the US there was an increase in rate up to 2000 and a plateau thereafter. No birth cohort effects were evident. Changes in smoking prevalence partially explained the period effect in the US (P = 0.01) and Sweden (PConclusionsThere is a strong maternal age effect on abruption. While the abruption rate has plateaued since 2000 in the US, all other countries show declining rates. These findings suggest considerable variation in abruption frequencies across countries; differences in the distribution of risk factors, especially smoking, may help guide policy to reduce abruption rates.

BackgroundGenerally, studies in perinatal epidemiology restrict cohort entry to 20 weeks of gestation, but exposures and outcomes may occur earlier. This restriction may introduce left truncation bias.ObjectivesTo examine the impact of left truncation bias when estimating the causal effect of abruption on perinatal mortality in the context of abnormal placentation, with spontaneous abortion (SAB) as a censoring event.MethodsThrough 80 Monte Carlo simulation scenarios based on realistic clinical assumptions, we estimated risk differences (RD), risk ratios (RR) and bias parameters for the abruption-perinatal mortality association.ResultsCensoring by SAB ranged from 5.6% to 7.6% across simulation setups. The risk of mortality was overestimated in observable (left-truncated) data at ≥ 20 weeks compared to an unobservable cohort starting follow-up at placental implantation (conception cohort). Underestimation of risks was stronger among abruption pregnancies. RDs for the abruption-mortality association were biased by +1% to +3% among conceptions with normal implantation and by +5% to +43% among abnormal placentation. Due to the disproportionate underestimation of mortality among nonabruption pregnancies, RRs were overestimated by 1.1 to 1.2-fold for normal implantations and by 1.1 to 8.4-fold for abnormal implantations.ConclusionsThe findings of this simulation study highlight the critical importance of placentation in successful pregnancy. Abnormal placentation has profound consequences for unsuccessful pregnancies, remarkably increasing the risks of early losses, placental abruption and other obstetrical complications. This study underscores that left truncation can bias the abruption-perinatal mortality association, differentially by whether the placentation was normal or abnormal. However, defining the causal question regarding the abruption-perinatal mortality association requires consideration of the target population, which may include all conceptions. In studies of these effects, outcome follow-up capability may introduce left truncation bias. We do not prescribe one analytic approach to account for left truncation, but rather, the approach should be guided by the causal question.