ORCID Profile
0000-0001-5074-4954
Current Organisations
University of Queensland
,
Eberhard Karls Universitat Tübingen
,
Queensland Health
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Publisher: Wiley
Date: 17-07-2018
DOI: 10.1111/AJO.12849
Abstract: Maternal smoking is associated with a number of adverse outcomes with a dose-dependent increase in risk. The aim of this study was to evaluate the obstetric and perinatal outcomes in women who smoked during pregnancy. This was a retrospective cohort study of women who smoked during pregnancy and birthed at a major perinatal centre in Australia between January 2000 and April 2017. The study cohort was compared to a cohort of women who did not smoke in pregnancy. Smoking status was ascertained on history and included all types of smoking. Demographic characteristics and obstetric, intrapartum and perinatal outcomes were compared between the two groups. The study cohort included 20 477 (14.6%) women who smoked during pregnancy and 119 396 controls. Women who smoked tended to be younger, of higher body mass index (BMI), Caucasian and Indigenous ethnicity. Smokers were less likely to be nulliparous, but more likely to be hypertensive and have a lower socioeconomic status compared to non-smokers. Women who smoked were more likely to have a caesarean section for non-reassuring fetal status (adjusted odds ratio (aOR) 1.16, 95%CI 1.07-1.26, P < 0.001). The infants of women who smoked were more likely to be born preterm, have a lower median birth weight and birth weights <10th (aOR 1.76, 95%CI 1.66-1.86, P < 0.001) and <5th centile (aOR 2.00, 95%CI 1.86-2.16, P < 0.001). Neonatal outcomes in the smoking cohort were worse with an increase in neonatal intensive care unit admission (aOR 1.34, 95%CI 1.27-1.43, P < 0.001), severe acidosis (aOR 1.41, 95%CI 1.27-1.43, P < 0.001) and a composite of severe neonatal outcomes (18.0% vs 12.0%, aOR 1.35, 95%CI 1.28-1.43, P < 0.001). Women who smoke in pregnancy have worse obstetric and perinatal outcomes compared to controls and should be managed as high risk.
Publisher: Cold Spring Harbor Laboratory
Date: 23-03-2023
DOI: 10.1101/2023.03.21.512712
Abstract: The field of metabolic modelling at the genomescale continues to grow with more models being created and curated. This comes with an increasing demand for adopting common principles regarding transparency and versioning, in addition to standardisation efforts regarding file formats, annotation and testing. Here, we present a standardised template for git-based and GitHub-hosted genome-scale metabolic models (GEMs) supporting both new models and curated ones, following FAIR principles (findability, accessibility, interoperability, and reusability), and incorporating bestpractices. standard-GEM facilitates the reuse of GEMs across web services and platforms in the metabolic modelling field and enables automatic validation of GEMs. The use of this template for new models, and its adoption for existing ones, paves the way for increasing model quality, openness, and accessibility with minimal effort. standard-GEM is available from github.com/MetabolicAtlas/standard-GEM under the conditions of the CC BY 4.0 licence along with additional supporting material.
Location: United States of America
No related grants have been discovered for Raymond Li.