Paula M. O’Shea
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Articles (10)
Year:
2023
Aims Gestational diabetes (GDM) is associated with the development of postpartum (PP) glucose intolerance. Plasma glycated CD59 (pGCD59) is an emerging biomarker for the detection of hyperglycaemia. The aim of this study was to assess the ability of PP pGCD59 to predict the development of PP GI as defined by the 2 h 75 g OGTT using the ADA criteria, in a cohort of women diagnosed with prior GDM in the index pregnancy using the 2 h 75 g OGTT at 24–28 weeks of gestation according to the World Health Organization (WHO) 2013 criteria. Methods Of the 2017 pregnant women recruited prospectively 140 women with gestational diabetes had samples for pGCD59 taken PP at the time of the OGTT. The ability of pGCD59 to predict the results of the PP OGTT was assessed using nonparametric receiver operating characteristic (ROC) curves. Results Women with PP glucose intolerance had significantly higher PP pGCD59 levels compared to women with normal glucose tolerance PP (3.8 vs. 2.7 SPU). PP pGCD59 identified women who developed glucose intolerance PP with an AUC of 0.80 (95% CI: 0.70–0.91). A PP pGCD59 cut‐off value of 1.9 SPU generated a sensitivity of 100% (95% CI: 83.9–100), specificity of 16.9% (95% CI: 9.8–26.3), positive predictive value of 22.1% (95% CI: 21.0–22.6), and negative predictive value of 100% (95% CI: 87.4–100). PP fasting plasma glucose generated an AUC of 0.96 (95% CI: 0.89–0.99) for the identification of PP glucose intolerance. Conclusion Our study found that PP pGCD9 may be a promising biomarker to identify women not requiring PP glucose intolerance screening using the traditional OGTT. While the diagnostic accuracy of pGCD59 is good, fasting plasma glucose remains a better test for the identification of PP glucose intolerance.
Year:
2023
Year:
2023
Year:
2023
Year:
2022
Year:
2022
Background Pregnancy induces physiological changes which affect biochemical and haematological parameters. As the significance of laboratory test results change throughout pregnancy, the reference interval (RI) or key result interpretive guide should be specific to pregnancy. This study sought to establish trimester-specific-RIs for routine biochemical and haematological tests in healthy white European women with singleton pregnancies with comparison to RIs for non-pregnant European adults. Methods A retrospective analysis of a prospective longitudinal single-centre study of healthy pregnant women conducted between November 2018 and December 2020 in a tertiary academic hospital with approximately 3000 births annually. Inclusion criteria: signed informed consent, age ≥18 years, white European, body mass index (BMI) <25 kg/m2, blood pressure <140/90mmHg, non-smoker, no previous pathology or gestational diabetes. Trimester defined as T1: up to 13 weeks + 6 days, T2: 14–27 weeks + 6 days and T3: ≥28–41 weeks + 6 days. Baseline demographics, anthropometric and laboratory measurements were recorded. In total, 31 biochemical and 10 haematological ISO15189:2012 accredited tests were measured using Roche Cobas® and Sysmex XN-9100™ analysers, respectively. RIs were established according to the International Federation of Clinical Chemistry (IFCC) recommended method. Results Apparently healthy pregnant women ( n = 124) with bio-banked serum samples in each trimester were recruited. At the booking visit, 49.2% ( n = 61) of participants were nulliparous, with median age of 34.4 (IQR: 31.3–37.3) years, gestational age of 89 (IQR: 84–93) days, BMI of 22.5 (IQR: 21.0–23.7) kg/m 2 and systolic and diastolic blood pressure of 116 (110–125) mmHg and 67 (61–75) mmHg, respectively. Conclusions Normative trimester-specific biological intervals for routinely requested biochemical and haematological medical laboratory tests were established. These RIs will be invaluable to result interpretation and the management of pregnant women.
Year:
2022
Year:
2022
Year:
2022
Year:
2022
Collaborators (10)
Louise Dervan
Health Service Executive
Michael C Dennedy
University of Galway
Felix Beuschlein
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Fidelma P. Dunne
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Claire Kerins
Lecturer in Evidence Based Healthcare
Ollscoil na Gaillimhe – University of Galway
Michelle Canavan
Professor of Older Adult Health
University of Galway
Conor Judge
Senior Lecturer in Applied Clinical Data Analytics
Ollscoil na Gaillimhe – University of Galway
Alberto Alvarez-Iglesias
Lecturer in Medical Biostatistics (Clinical Trials)
National University of Ireland Galway
MIGUEL ANGEL LUQUE FERNANDEZ
Université libre de Bruxelles (ULB)
Martin O'Donnell
Associate Professor of Translational Medicine
National University of Ireland Galway
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