BackgroundObesity is increasingly common in the obstetric population. Maternal obesity and excess gestational weight gain (GWG) are associated with increased perinatal risk. There is limited published data demonstrating the level of pregnant women’s knowledge regarding these problems, their consequences and management strategies.We aimed to assess the level of knowledge of pregnant women regarding: (i) their own weight and body mass index (BMI) category, (ii) awareness of guidelines for GWG, (iii) concordance of women’s own expectations with guidelines, (iv) knowledge of complications associated with excess GWG, and (v) knowledge of safe weight management strategies in pregnancy.Methods364 pregnant women from a single center university hospital antenatal clinic were interviewed by an obstetric registrar. The women in this convenience sample were asked to identify their weight category, their understanding of the complications of obesity and excessive GWG in pregnancy and safe and/or effective weight management strategies in pregnancy.ResultsNearly half (47.8%) of the study population were overweight or obese. 74% of obese women underestimated their BMI category. 64% of obese women and 40% of overweight women overestimated their recommended GWG. Women’s knowledge of the specific risks associated with excess GWG or maternal obesity was poor. Women also reported many incorrect beliefs about safe weight management in pregnancy.ConclusionsMany pregnant women have poor knowledge about obesity, GWG, their consequences and management strategies. Bridging this knowledge gap is an important step towards improving perinatal outcomes for all pregnant women, especially those who enter pregnancy overweight or obese.
Objective Describe the epidemiology of obstetric patients admitted to an Intensive Care Unit (ICU). Design Registry-based cohort study. Setting One hundred and eighty-three ICUs in Australia and New Zealand. Population Women aged 15-49 years, admitted to ICU between 2008 and 2017, classified as pregnant, postpartum or with an obstetric-related diagnosis. Methods Data were extracted from the Australia and New Zealand Intensive Care Society (ANZICS) Adult Patient Database and national agencies. Main outcome measures Incidence of ICU admission, cohort characteristics, maternal outcomes and changes over time. Results The cohort comprised 16 063 patients. The annual number of obstetric ICU admissions increased, whereas their proportion of total ICU admissions (1.3%) did not change (odds ratio 1.02, 95% CI 0.99-1.04, P = 0.14). There were 10 518 (65%) with an obstetric-related ICU diagnosis, and 5545 (35%) with a nonobstetric ICU diagnosis. Mean (SD) age was 31 (6.4) years, 1463 (9.1%) were Indigenous, 2305 (14%) were transferred from another hospital, and 3008 (19%) received mechanical ventilation. Median [IQR] length of stay in hospital was 5.2 [3.1-7.9] days, which included 1.1 [0.7-1.8] days in ICU. There were 108 (0.7%) maternal deaths, most (n = 97, 90%) having a non-obstetric diagnosis. There was no change in risk-adjusted length of stay or mortality over time. Conclusions Obstetric patients account for a stable proportion of ICU admissions in Australia and New Zealand. These patients typically have a short length of ICU stay and low hospital mortality.
2020, that is, whether they encountered any problems in the year after its institution and whether any of their criteria for admission, nighttime coverage, ease of consultation with other services involved, etc., needed to be changed or modified. I have a feeling that that paper is now being written, but it probably should have been combined with the current manuscript.
BackgroundPreterm birth is a clinical event significant but difficult to predict. Biomarkers such as fetal fibronectin and cervical length are effective, but the often are used only for women with clinically suspected preterm risk. It is unknown whether routinely collected data can be used in early pregnancy to stratify preterm birth risk by identifying asymptomatic women. This paper tries to determine the value of the Victorian Perinatal Data Collection (VPDC) dataset in predicting preterm birth and screening for invasive tests.MethodsDe-identified VPDC report data from 2009 to 2013 were extracted for patients from Barwon Health in Victoria. Logistic regression models with elastic-net regularization were fitted to predict 37-week preterm, with the VPDC antenatal variables as predictors. The models were also extended with two additional variables not routinely noted in the VPDC: previous preterm birth and partner smoking status, testing the hypothesis that these two factors add prediction accuracy. Prediction performance was evaluated using a number of metrics, including Brier scores, Nagelkerke’s R2, c statistic.ResultsAlthough the predictive model utilising VPDC data had a low overall prediction performance, it had a reasonable discrimination (c statistic 0.646 [95% CI: 0.596–0.697] for 37-week preterm) and good calibration (goodness-of-fit p = 0.61). On a decision threshold of 0.2, a Positive Predictive Value (PPV) of 0.333 and a negative predictive value (NPV) of 0.941 were achieved. Data on previous preterm and partner smoking did not significantly improve prediction.ConclusionsFor multiparous women, the routine data contains information comparable to some purposely-collected data for predicting preterm risk. But for nulliparous women, the routine data contains insufficient data related to antenatal complications.
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